A systematic review of the biomarkers associated with cognition and mood state in bipolar disorder

A systematic review of the biomarkers associated with cognition and mood state in bipolar disorder | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report A systematic review of the biomarkers associated with cognition and mood state in bipolar disorder Perez-Ramos Anaid, Romero-Lopez-Alberca Cristina, HIdalgo-Figueroa Maria, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4020734/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Bipolar disorder (BD) is a severe psychiatric disorder characterized by changes in mood that alternate between (hypo) mania or depression and mixed states, often associated with functional impairment and cognitive dysfunction. But little is known about biomarkers that contribute to the development and sustainment of cognitive deficits. The aim of this study was to review the association between neurocognition and biomarkers across different mood states. Method Search databases were Web of Science, Scopus and PudMed. A systematic review was carried out following the PRISMA guidelines. Risk of bias was assessed with the Newcastle-Ottawa Scale. Studies were selected that focused on the correlation between neuroimaging, physiological, genetic or peripheral biomarkers and cognition in at least two phases of BD: depression, (hypo)mania, euthymia or mixed. PROSPERO Registration No.: CRD42023410782 Results A total of 1824 references were screened, identifying 1023 published articles, of which 336 were considered eligible. Only 16 provided information on the association between biomarkers and cognition in the different affective states of BD. We mainly found two types of biomarkers examining this association across BD mood states. Regarding peripheral biomarkers, although literature suggests an association with cognition, our review did not reveal such an association. Differences in levels of total cholesterol and C-reactive protein were observed depending on mood state. Neuroimaging biomarkers highlighted hypoactivation of frontal areas stands out for the acute states of BD and a deactivation failure has been reported in the ventromedial prefrontal cortex (vmPFC), potentially serving as a trait marker of BD. Conclusion Only a few recent articles have investigated biomarker-cognition associations in BD mood phases. Our findings underline that there appear to be central regions involved in BD that are observed in all mood states. However, there appear to be underlying mechanisms of cognitive dysfunction that may vary across different mood states in bipolar disorder. This review highlights the importance of standardizing the data and the assessment of cognition, as well as the need for biomarkers to help prevent acute symptomatic phases of the disease, and the associated functional and cognitive impairment. Biomarker Bipolar Disorder Cognition Mood state Psychiatry Figures Figure 1 1. Background Bipolar disorder (BD) is a chronic psychiatry disease characterized by the recurrence of acute mood episodes with euphoric, depressive or mixed clinical features (Carvalho et al. 2020 ). Cognitive alterations negatively affect the disease course, the functional outcome and work capacity in mood disorders, particularly in BD (Burdick et al. 2010 ; Mora et al. 2013 ; Torrent et al. 2012 ). Previous literature shows that BD patients present impairment in most cognitive domains (psychomotor delay and impairment of declarative memory, executive function and attention) compared to healthy controls (HCs) (Li et al. 2020; Sanches et al. 2015 ). Despite this cognitive impairment being also present during remission phases (Bourne et al. 2013 ; Chen et al. 2023 ), there is considerable heterogeneity among patients with BD. This heterogeneity ranges from patients with intact cognition and performance comparable to HCs, to patients with significant global cognitive impairment (Burdick et al. 2014 ; Ehrlich et al. 2022), suggesting that there are different subgroups in function of cognitive performance. Studies examining the prevalence of cognitive impairment in BD report inconsistent results. A recent study examines the prevalence of cognitive impairment in a cohort of euthymic patients and estimates that 35% of patients experienced clinically significant cognitive deficits (Tsapekos et al. 2021 ). Cognition can also be affected by various factors, such as symptoms, age of onset, the incidence of psychosis and pharmacological treatments (Uluyol et al. 2020 ). The effect of medications on cognition has been the subject of debate. On the one hand, some studies report cognitive deficits in domains such as attention and memory during prolonged lithium treatment (Wingo et al. 2009 ), and other suggest that lithium treatment does not significantly affect cognitive performance (Burdick et al. 2020 ). The use of antipsychotic medication has also been linked to poorer cognitive performance (Cullen et al., 2016 ). Additionally, a higher estimated Intelligence Quotient (IQ) before the onset of the illness is associated with a slower cognitive decline as people age (Tsapekos et al. 2021 ). Similarly, the risk of developing BD has been associated with cognitive performance, so better cognitive performance in late adolescence was associated with a lower risk of BD (Hiyoshi et al. 2017 ). On the other hand, BD has a high prevalence of psychiatric comorbidities, with more than half of adult patients diagnosed with at least one comorbid condition in their lifetime (Loftus et al., 2020 ). A recent systematic review reinforces that individuals with BD and substance use disorder (SUD) comorbidity may have greater cognitive impairment compared to individuals with BD without SUD comorbidity (Gogia et al. 2022 ). In recent years, most studies focus on patients in a euthymic state while few compare cognitive functioning across the acute and euthymic phases of BD. Executive dysfunction seems to arise in the early stages of BD, and it tends to be exacerbated during depression and after manic episodes, suggesting it may be considered as a marker of the disease state (Elshahawi et al. 2011 ; López-Jaramillo et al. 2010 ). In a recent study, the cognitive performance of BD patients over 60 years of age was worse than age-matched HCs and those with depression had worse working memory than those in a state of hypomania (Schouws et al. 2020 ). Although cognitive abnormalities were detected in all phases of the disease, they were most notable during acute episodes (Kurtz and Gerraty, 2009 ). Patients with a manic episode appear to show greater cognitive impairment in verbal and working memory, executive function/reasoning, and problem solving, compared to the depressed, mixed, and euthymic subgroup (Vrabie et al., 2015 ). Therefore, the acute clinical state could modify the pattern or magnitude of neurocognitive impairment in patients with BD (Kurtz and Gerraty, 2009 ). However, a study that compared patients in a depressive (BDD), manic (BDM) and euthymic state (BDE) failed to find cognitive differences between the different BD groups (Martínez-Arán et al. 2004 ). Therefore, the acute clinical state could modify the pattern or magnitude of neurocognitive impairment in patients with BD, but it is still under discussion (Kurtz and Gerraty, 2009 ). Furthermore, our understanding of the physiological or biological mechanisms underlying cognitive impairment in BD remains limited (Strawbridge et al. 2021 ). It is of great importance to understand and delve into the mechanisms underlying cognitive impairment for a better understanding of the role that cognition plays in pathology and to design more effective treatment approaches. Identification of markers has become a promising tool to guide diagnosis, predict clinical status, and help understand the pathophysiology of mental disorders. Hence, associations with biomarkers could clarify the cognitive models underlying each mood state and create adapted remediation tasks to achieve better cognitive and functional performance and to find markers of specific states that can prevent relapse. Current diagnostic criteria for mental disorders are based solely on clinical features and behavioral observations, with no substantial biological validation (Brückl et al. 2020 ). Recent years have seen an increase in the number of studies focusing on the neural correlates of BD (Muneer 2020 ), however few studies have addressed whether there is an association between biological mechanisms and cognitive dysfunction in the different affective states of BD. An inflammatory state measured by CRP and cytokine levels in peripheral blood could be an important contributor to the cognitive impairment observed in patients with schizophrenia and BD (Misiak et al. 2018 ; Uluyol et al. 2020 ). Furthermore, patients with first-episode BD exhibited worse EFs and higher TNFR1 levels than healthy controls (Chen et al. 2020 ). Hence, there appears to be an association between inflammatory processes and executive dysfunction. Frey et al. ( 2013 ) summarized BD-related biomarkers from genetic, peripheral, and neuroimaging biomarkers. In addition, ‘omics' technologies, including genomics, proteomics, transcriptomics, metabolomics, and epigenetics, have contributed to the rapid discovery of many potential biomarkers (García-Guitierrez et al. 2020). Current advances in this field have focused on the need for more precise neuroimaging biomarkers (Janiri and Frangou, 2022 ) and including them in cognitive trials to investigate the neural correlates of potential procognitive efficacy in candidate treatments (Miskowiak et al. 2017 ). A longitudinal neuroimaging study demonstrated changes in prefrontal regions across mood states in subjects with BD. BDM patients exhibited increased connectivity with the right middle frontal gyrus compared to HCs, whereas in depressed BD subject’s connectivity was increase with the right medial frontal gyrus and left middle frontal gyrus (Cerullo et al. 2012 ). An interesting study also showed different brain activity patterns depending on cognitive impairment, those with poorer cognitive performance exhibit lower activity in regions associated with cognitive control and higher activity in the default mode network, whereas cognitively normal patients show minimal hypoactivity compared to HCs (Petersen et al. 2022). Accordingly, one of the main objectives in the management of psychiatric disorders would be to prevent or limit any cognitive deterioration by studying the factors involved in neurocognitive performance (Martínez-Aran and Vieta, 2015). Furthermore, there are no clinically available treatments with direct pro-cognitive efficacy in mood disorders (Miskowiak et al. 2017 ) and there is little understanding of the reasons why some patients with BD develop significant cognitive deficits, while others remain cognitively intact during the different affective phases of the illness. In fact, cognitive function is a complex construct, and a combination of instruments that allow us to evaluate different aspects could greatly contribute to knowledge about the nature and extent of cognitive dysfunctions in BD. The aim of this systematic review was to synthesize studies in the literature that evaluated the association between biomarkers and cognition in patients with bipolar disorder according to affective state, since, to date, no study has systematically included these three factors. 2. Methods 2.1. Systematic Search Strategy The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) on 30th March, 2023 (Registration No.: CRD42023410782). Following the PRISMA guidelines (Preferred Reporting Items for Systematic reviews and Meta-analyses; Page et al. 2021 ), a systematic review was carried out of studies investigating biomarkers and cognition in the different mood states of BD (see Supplementary Material Appendix 1 for PRISMA Checklist). Searches of PubMed, SCOPUS and the Web of Science (WOS) were carried out for the past 10 years (from 2013), and we included studies of patients with BD in which data from at least two different mood states were compared. We started the search in August 2022 and concluded it in December 2022. To update the systematic review, a final search has been done to include those studies that could have been done during 2023. Figure 1 provides the methodological procedure followed was based on the PRISMA guidelines (Moher et al. 2009 ). The syntax search [‘bipolar disorder’] AND [mood] AND [biomarker] AND [cogni*] in PubMed and its equivalents in the other databases were used. For the second search, studies from January 2023 to December 2023 have been included. Note that the general term biomarker was used to include neuroimaging, physiological, genetic or peripheral markers. 2.2. Eligibility Eligility criteria were: (a) the study was carried out on adult patients (≥ 18 years of age); (b) they were diagnosed with BD according to the criteria of the International Classification of Diseases (CIE-10) or the DSM (DSM-IV to DSM-5); (c) the study included a comparison of at least two phases of BD (mania, depression, mixed state or euthymia); (d) that includes a neurocognitive assessment and its association with a biomarker; (e) published from 2013 to December 2023 (e) longitudinal or cross-sectional studies and (f) it was written in English, Spanish or French. The exclusion criteria were: (a) if the patients had a history of psychosis; (b) if the article was a family study, systematic review, book chapter, case report or a meta-analysis; (c) non-access articles. 2.3. Data extraction Two authors (CRLA and APR) performed the review independently using the Covidence program and any disagreements on study selection were resolved by a third person (JPR). Covidence is a web-based collaboration software platform that streamlines the production of systematic and other literature reviews (Babineau 2014 ). 2.4. Data synthesis The following characteristics were extracted from the table (Table 1 ): Reference; Type of study; Population; Biomarker; Neuropsychological assessment; Results depending on the mood state; Association between biomarker and cognition; Criteria to establish the mood state. 2.5. Quality assessment A quality assessment was carried out by APR and MHF using the Newcastle-Ottawa Quality Assessment Scale (Wells et al. 2013), rating each study in Table S2 (see Supplementary Material Appendix 2). From : Babineau, 2014 . Product Review: Covidence (Systematic Review Software) 3. Results A total of 1824 articles were recovered for screening, of which 803 duplicates were removed and 687 were excluded as they did not deal with BD, while 4 articles were included as a result of the Snowballing effect (Wohlin 2014 ). Subsequent to review of titles and abstracts, 687 records were discarded and the full manuscripts of 336 studies were examined in detail. Of the articles included, only 16 explored an association between biomarkers and cognition in different affective states, most of which demonstrated a correlation between the cognitive functions evaluated and the different alterations during the mood phases of the disorder. Table 1 Data extraction from studies describing the characteristics of the studies included correlating biomarkers to cognitive variables Author/ year Subject (n) Biomarker Sample size (n) Sex (m/f) Cognitive assessment Criteria to establish mood state Association biomarker and cognition Main Findings 1. Idemoto et al., 2021 BDD (58) BDE (58) BDM (7) BDX (19) Serum GDNF BD: 143 HC: 158 MDD: 166 BD: 61/82 HC: 80/58 MDD: 80/78 Premorbid IQ with JART BDD: HAMD ≥ 8 and YMRS ≤ 7 BDE: HAMD ≤ 7 YMRS ≤ 7 BDM: HAMD ≤ 7 YMRS ≥ 8 BDX: HAMD ≥ 8 YMRS ≥ 8 No correlation between serum GDNF levels and cognition Serum GDNF levels in BDD < HC IQ < HC 2. Guidara et al., 2021 BDD (6) BDM (27) Tchol, triglycerides, HDL-C, hs-CRP, LDL-C BD: 33 HC: 40 BD: 33/0 HC: 40/0 MoCA BDM moderate: MAS ≤ 21 BD No correlation between the biological markers and cognition Tchol < BDD 24-OHC < BDD CRP 21 and YMRS < 7 BDE: HDRS < 8 and YMRS < 7 at least 6 months NAA/Cr ratio in left basal ganglia in the acute-episode was correlated with WCST and TMT-B uptake Worse cognitive performance in BD group and NAA/Cr ratio in bilateral lenticular nucleus < HC 4. Nishimura et al., 2015 BDD (16) BDH (11) NIRS BD: 27 HC: 12 BD: 18/9 HC:4/8 IQ VFT The cutoff point for the YMRS was 4 Correlation between left DLPFC function and hypomanic symptoms ↓ DLPFC left (CH49) in BDD < BDM/HC ↓ VLPFC left in BD groups (were absent symptoms) 5. Pomarol- Clotet et al., 2015 BDD (38) BDE (38) BDM (38) fMRI BD:114 HC: 38 BD: 52/62 HC: 18/20 n-back WAIS-II TAP BDD: HDRS ≥ 15 BDE: HDRS ≤ 8 and YMRS ≤ 6 at least 3 months BDM: YMRS ≥ 18 Reduced activation in the dorsal parietal cortex in both mania and depression during cognitive task ↓ Dorsal parietal cortesx in BDD and BDM < BDE ↓ DLPFC in BDM < BDE Failure of de-activation in the medial frontal cortex 6. Rive et al., 2016 BDD (9) BDE (23) fMRI BD: 32 HC: 35 MDD: 40 BD: 13/19 HC: 10/25 MDD: 12/28 IQ ToL N/A Task was associated with activity in parieto-temporal and lateral/medial frontal regions, in precuneus, insula, caudate nucleus and pallidum ↑ DLPFC in BDD > BDE 7. Estudillo-Guerra et al., 2020 BDE (6) BDM(10) SPECT BD: 10 HC: 10 BD: 2/8 HC: N/A SCIP-S BDE: MADRS < 6 and YMRS < 2 BDM: MADRS 20 Manic : positive correlation SCIP-S score and brain perfusion in the right TP. Negative correlation with right OFC and right sACC. Follow-up : Brain perfusion was not correlated with SCIP-S ↑ Left DLFPC and left FPC in BDM > BDE 8. Alonso-Lana et al, 2019 BDE (26) BDM (26) fMRI BD: 26 HC: 26 BD: 15/11 HC: 15/11 n-back TAP BDE: YMRS and HDRS ≤ 8 BDM: YMRS ≥ 15 at least 2 months Recovery from mania is associated with increase in activation in the left DLPFC/precentral cortex and the bilateral parietal cortex during n-back task 1-back and 2-back in BDM < BE Failure de-activation vmPFC in BD < HC ↓ Left DLPFC, PFC superior PaC in BDM < HC/BDE 9. Magioncalda et al., 2016 BDD (20) BDE (20) BDM (21) DTI BD: 61 HC: 42 BD: 18/43 HC: 15/27 CPT Verbal Fluency BDD and BDM: HAM-D 17 ≥ 18 and/or YMRS ≥ 13 BDE: HAM-D < 8 and YMRS < 8 WM alterations were associated with cognitive deficits. CPT total hits correlate with the mean FA and with the mean MD and RD values. Fluency prompted by letter showed a correlation with the mean FA, MD and RD values Worse performance in CPT and Fluency in BDD and BDM < HC ↓ FA in BDD and BDM HC 10. Magioncalda et al., 2015 BDD (11) BDE (11) BDM (11) BDX (7) fMRI BD: 40 HC: 42 BD: 18/43 HC: 15/27 CPT Verbal Fluency BDD, BDM and BDX: HAM-D 17 ≥ 18 and/or YMRS ≥ 13 BDE: HAM-D < 8 and YMRS < 8 Fluency letter showed correlation with PACC-SACC FCo CPT associated with PACC-OFC L FCo and with PACC‐TPJ L FC Worse cognitive performance in BD group ↓ FCo in Slow-5 from PACC in BD < HC 11. Velasques et al, 2013 BDD (10) BDM (10) EEG BD: 20 HC: 12 BD: 14/6 HC: 3/9 Saccadic attention task N/A Clinical Global Impression-Bipolar Version (CGI-BP) During a saccadic attention task, gamma coherence varies according to the group and the area of the cortex observed ↓ Saccade latency in BDM < BDD and HC ↓ Frontal eye field Fz/F4 in BDM HC 12. Martino et al., 2016 BDD (20) BDE (20) BDM (21) Rs-fMRI DTI BD: 61 HC: 42 BD: N/A HC: N/A CPT BDD and BDM: HAMD ≥ 18 and/or score YMRS ≥ 13 HAM-D Cognitive scores correlated with the measures of cingulum SC BDD and BDM more omissions errors in CPT ↓ PACC-PCC functional connectivity in BDM < BDD and HC ↓ FA in BDM < BDE ↓ SC of the cingulum in BDM 7 and YMRS < 10 BDE: HAM-D ≤ 7 and YMRS BDD ↓ Left temporal regions in BDE < HC 14. Yang et al., 2020 BDD (32) BDE (25) BDM (15) MRI BD: 72 HC: 71 BD: 32/40 HC: 33/38 n-back BDD: HAMD ≥ 17 and YMRS < 12 BDE: HAMD score < 17 and YMRS < 12 BDM: HAMD < 17 and YMRS ≥ 12 Increase in small-worldness was associated with decreased working memory accuracy Worse working menory in BDD and BDM ↓ sigma and gamma in BDM < BDD ↓ Cingulo-opercular network in BDM and BDE < BDD 15. Gao et al., 2023 BDE (28) BDM (38) Rf-fMRI BD: 66 HC: 60 BD: 36/30 HC: 38/22 PDQ N/A No correlation was found ↓ right IPL in BDM < BDD 16. Kopf et al., 2023 BDD (32) BDE (15) fNIRS BD: 32 HC: 31 BD: 29/22 HC: 10/20 n-back N/A Right DLPFC activation during n-back task No difference in DLPFC and vlPFC activation between BDD and BDE ↑, increased; ↓, decreased; >, higher; <, lower; N/A, not applicable; HAMD, Hamilton Depression Rating Scale; HDRS, Hamilton Depression Scale; MAS, Bech and Rafaelsen Mania Scale; YMRS, Young Mania Rating Scale; MADRS, Montgomery-Asberg Depression Rating Scale; BDM, bipolar mania; BDD, bipolar depression; BDE, bipolar euthymic; BDH, bipolar hypomania; BDX, bipolar mixed state; MDD, major depressive disorder; HC, healthy control; FCr, right frontal cortex; PaC, Parietal cortex; PCr, parietal cortex right; DLPFC, dorsolateral prefrontal cortex; OFC, orbitofrontal cortex; SACC, supragenual anterior cingulate cortex; TPJ L, temporal parietal junction left; TP, temporal polar cortex; IPL, inferior parietal lobe; PACC, perigenual anterior cingulate cortex; PCC, posterior cingulate cortex; vlPFC, ventrolateral prefrontal cortex; MD, mean diffusivity; RD, radial diffusivity; FA, DTI-derived fractional anisotropy; FCo, functional connectivity; SPECT, brain perfusion single-photon emission computed tomography; SC, structural connectivity; WM, White matter; NAA/Cr, N-acetylaspartate/creatine; GDNF, Glial cell line-derived neurotrophic factor; Tchol, Total cholesterol; HDL-C, high-density lipoprotein cholesterol; hs-CRP, high sensitivity C reactive protein; LDL-C, low-density lipoprotein-cholesterol; OCH-24/27, cholesterol 24/27 hydroxycholesterol; oxy-Hb, Relative concentration changes of oxygenated; deoxy-Hb, concentration changes of deoxygenated; rs-fMRI, resting-state functional magnetic resonance imaging; MRI, Magnetic Resonance Imaging; NIRS, near infrared spectroscopy; fNIRS, functional near-infrared spectroscopy; EEG, electroencephalography; DTI, probabilistic tractographic diffusion tensor imaging; MoCA, Montreal Cognitive Assessment; TAP, Word Accentuation Test; VFT, Verbal Fluency Test; WAIS, Wechsler Adult Intelligence Scale; IQ, intelligence quotient; JART, Japanese Adult Reading Test; CPT, Continuous performance test; SCIP-S, Screen for Cognitive Impairment in Psychiatry Scale; ToL, Tower of London; WCST, Wisconsin card sorting test; TMT-B, Trail making test part B; PDQ, Perceived Deficits Questionnaire. 3.1. Cognitive and biomarkers findings across affective state Studies included markers from serum or plasma and neuroimaging. The studies were grouped into the following cognitive domains according to the tasks used or the fMRI paradigms used: "attention", "executive functions", "memory (working memory and verbal memory)", "IQ" “Self-reported cognitive” and "Cognitive Screening Test ". Fourteen studies used a combination of neuroimaging and neurocognitive assessments to investigate the affective states in BD (Alonso-Lana et al. 2019 ; Estudillo-Guerra et al. 2020 ; Gao et al. 2023 ; Kopf et al. 2023 ; Lai et al. 2018 ; Magioncalda et al. 2016 ; Magioncalda et al. 2015 ; Martino et al., 2016 ; Mikawa et al. 2015 ; Nishimura et al. 2015 ; Pomarol-Clotet et al. 2015 ; Rive et al. 2016 ; Velasques et al. 2013 ; Yang et al. 2020 ). We find different neuroimaging modalities (e.g., structural magnetic resonance imaging (MRI), fMRI, diffusion tensor imaging, resting-state, brain perfusion, proton magnetic resonance spectroscopy). Two studies used peripheral markers (Guidara et al. 2021 ; Idemoto et al. 2021 ). Four studies used a longitudinal design (Alonso-Lana et al. 2019 ; Estudillo-Guerra et al. 2020 ; Kopf et al. 2023 ; Nishimura et al. 2015 ) and twelve were cross-sectional studies (Gao et al. 2023 ; Guidara et al. 2021 ; Idemoto et al. 2021 ; Lai et al. 2018 ; Magioncalda et al. 2016 ; Magioncalda et al. 2015 ; Martino et al., 2016 ; Mikawa et al. 2015 ; Pomarol-Clotet et al. 2015 ; Rive et al. 2016 ; Velasques et al. 2013 ; Yang et al. 2020 ). Attention Four studies carry out a neurocognitive evaluation of attention (Magioncalda et al. 2015 ; Magioncalda et al. 2016 ; Martino et al. 2016 ; Velasques et al. 2013 ). Three of them evaluate sustained attention with the continuous performance test (CPT; Magiocalda et al. 2016; Martino et al. 2016 ), where we find that BD patients showed lower number of total hits and higher number of total omission errors. On the one hand, BDM patients showed that structural changes in the cingulum were related to the deficits found at the attentional level. Furthermore, it was found that the perigenual anterior cingulate cortex (PACC) and posterior cingulate cortex (PCC) functional connectivity was decreased in manic patients when compared to both HCs and BDD patients and the SC of the cingulum, especially its anterior part, was decreased in manic patients when compared to HC (Martino et al. 2016 ). When microstructural abnormalities in the white matter (WM) were investigated, subgroups of BD patients showed different spatial patterns of WM alterations (Magioncalda et al. 2016 ). The BDE patients had minor and localized WM alterations in the midline structures, whereas the WM alterations were more diffuse in the BDM patients, affecting both midline and lateral structures, and there were stronger and more widespread WM alterations in BDD patients. In addition, these WM alterations were associated with attention deficits. Similarly, in another study these authors found differences in functional connectivity from the PACC to other regions in the posterior default mode network (DMN) between patients in manic or depressed episode and HCs, but no differences between the BD patient subgroups (Magioncalda et al. 2015 ). In Velasques et al. ( 2013 ), BDM patients showed lower saccade latency than BDD patients or the HCs. In a prosaccadic attention task the BDM patients showed stronger gamma coherence in the frontal cortex than in the other groups (BDD and HCs). Processing speed Only one study evaluates processing speed (Estudillo-Guerra et al. 2020 ). Six months after an acute episode of mania, patients in euthymic state do not show differences in this cognitive sphere. At follow-up, a decrease in perfusion was observed in the right middle temporal gyrus (MTG) and the right superior temporal gyrus (STG). Executive functions Seven studies explored EFs (Estudillo-Guerra et al. 2020 ; Lai et al. 2018 ; Magioncalda et al. 2016 ; Magioncalda et al. 2015 ; Mikawa et al. 2015 ; Nishimura et al. 2015 ; Rive et al. 2016 ). Three of them found no differences in performance between the groups (BD in different states and HCs) in the cognitive task (Mikawa et al. 2015 ; Nishimura et al. 2015 ; Rive et al. 2016 ). Estudillo-Guerra et al. 2020 explored cognitive deficits in acute BDM patients and their subsequent evaluation after 6 months (euthymic state). This study evaluates cognitive functions using the Spanish version of the Screen for Cognitive Impairment in Psychiatry Scale (SCIP-S). A subtest contains the Verbal Fluency Test (VFT) to evaluate executive functions. A negative correlation between Brodmann area (BA) 25 and positive with BA 38 and 21 was found during a manic episode. At follow up Cognitive impairment in VFT correlated with changes increased perfusion in the bilateral Anterior cingulate cortex (ACC). Fluency prompted by letter showed a correlation with PACC-SACC (Magioncalda et al., 2015 ). By contrast, in another study, there was increased activation in the dorsolateral prefrontal cortex (DLPFC) of BDD patients, and in the parietal cortex (PC) compared to the BDE patients (Rive et al., 2016 ). However, hypoactivation of the left DLPFC and of the left ventrolateral prefrontal cortex (VLPFC) during a verbal fluency task was found in patients with hypomanic symptoms, while this activation was less prominent in the DLPFC of BDD patients (Nishimura et al. 2015 ). In addition, this study followed hypomanic patients who showed significantly greater concentration changes of oxygenated hemoglobin (oxy-Hb) in the left DLPFC and frontopolar prefrontal cortex (FPPFC) when experiencing hypomanic symptoms compared to when they were absent (8 patients). Similarly, the oxy-Hb levels induced by executive tasks were significantly lower in BDD than BDE patients (Mikawa et al. 2015 ). Finally, another study failed to find differences between the BD groups (Lai et al. 2018 ), showing a decrease in the N-acetylaspartate to creatine ratio (NAA/Cr) in the bilateral basal ganglia compared to the HCs. Nevertheless, the decrease in NAA/Cr ratios was negatively correlated with total errors and TMT-B uptake, but there was no correlation between the NAA/Cr and Cho/Cr in the right basal ganglia and the scores of WCST and TMT-B in acute-episode BD patients. Memory Working memory Regarding working memory, four studies used an n-back paradigm (Alonso-Lana et al. 2019 ; Kopf et al. 2023 ; Pomarol-Clotet et al. 2015 ; Yang et al. 2020 ) and one used the SCIP-S subtest (Estudillo-Guerra et al. 2020 ). We found worse performance in the manic or depressed state compared to HC and BDE patients. In a first study, the BDM group obtained worse results in the two versions of the task compared to the BDD patients and HC individuals (Pomarol-Clotet et al. 2015 ). However, when the cognitive load was increased (2-back version), the BDD patients also differed from the HCs. Surprisingly, the BDE patients did not differ from the HCs. There was reduced activation in the left and right dorsal PC and precuneus in BDM patients, and failure to de-activate the medial frontal cortex was evident in all BD groups. In a longitudinal study, patients were assessed during a manic episode and later, in a state of euthymia after about 12 months (Alonso-Lana et al. 2019 ). Similar to previous findings, BDM patients performed worse than HCs and BDE patients. Activation during the cognitive task showed weaker activation in the left DLPFC, PC, and bilateral superior precuneus in BDM patients, while the BDE group continued to exhibit failure in vmPFC deactivation. During the working memory test of SCIP-S, manic episodes were associated with limited perfusion in the right OFC, whereas no significant differences were observed during euthymia (Estudillo-Guerra et al. 2020 ). Finally, functional neuroimaging data was used to provide an intuitive method to study fMRI-inferred neural efficiency in the whole brain, allowing interindividual differences related to the task to be predicted (connectome; Yang et al. 2020 ). An overall increase of the functional connectome was detected and there was a more homogeneous distribution in BDD patients. Interestingly, the maladaptive modulation of the functional connectome was associated with worse performance in working memory. Verbal memory Only one study assessed verbal memory (Estudillo-Guerra et al. 2020 ), with immediate verbal learning correlated to the temporal polar cortex. No significant correlation of manic episodes with delayed verbal learning was detected, although a significant correlation was seen in euthymic states. Intellectual Quotient (IQ) Concerning the IQ, HCs had a higher mean current IQ than the BDD and BDM patients but not the BDE patients (Pomarol-Clotet et al. 2015 ). When the relationship between neurotrophic factors and cognition was studied in different mood phases of BD (Idemoto et al. 2021 ), no differences in plasma GDNF levels were evident between the affective states. Furthermore, no correlation was performed to see if there was an association between IQ and serum GDNF levels. However, after controlling for factors such as sex, age, BMI, estimated IQ, and diagnosis, serum GDNF levels in TB patients were lower in remission and depression states than control subjects (this did not occur in patients in a manic or mixed state). Cognitive Screening Test Differences in the levels of oxysterols and CRP were analyzed in the distinct groups of bipolar patients, with lower cholesterol levels (Tchol, 24-OCH) reported in BDM patients relative to BDD patients and in patients with severe manic episode compared to those with moderate manic episode for 24-OCH levels (Guidara et al. 2021 ). By contrast, CRP levels were higher in BDM patients and in patients with severe manic episode compared to those with moderate manic episode. No correlations with the cognitive scale (MoCA) were found. Self-reported cognitive A study utilizes a self-report measure to assess cognitive dysfunction with the Perceived Deficits Questionnaire (PDQ) (Gao et al. 2023 ). Despite finding differences in activation between patients in acute state and their remission state in the follow-up (BDM patients showed reduced network homogeneity compared to BDE), no association with cognition was found. 4. Discussion This systematic review represents an effort to synthesize the reliable evidence available on the associations between biomarkers and cognition in different phases of BD. When we look at these associations, we found a total of 14 articles that have addressed this issue. Acute mood episodes Neuroimaging biomarker Neuroimaging research has highlighted the importance of modular and hierarchical brain networks for the functional integration of neural operations related to cognitive function (Park and Friston, 2015). Cognitive control and executive functions are associated with activity in the prefrontal cortex (PFC; Menon and D’Esposito 2022). Activation of the DLPFC, superior frontal gyrus, superior parietal lobule and precuneus are common neural correlates of working memory, EFs and attention (Friedman and Robbins, 2022 ; Saldarini et al. 2022 ). Data from the n -back paradigm and neuroimaging studies suggest that there is a mood-state dependent hypoactivation in DLPFC and PC. In the included studies, during states of mania or depression there appears to be hypoactivation in the prefrontal and parietal cortex within the framework of a task that requires executive functions or working memory (Bi et al. 2022 ; Brooks et al. 2015 ; Fleck et al. 2010; Penfold et al. 2015 ; Rodríguez-Cano et al. 2017 ; Takizawa et al. 2014 ). Although we found this hypoactivation also in the euthymic group (Saldarini et al. 2022 ), there could be less activation in frontal regions during the acute states of BD (Schumer et al. 2023 ). In fact, we found that moving from mania to euthymia was associated with an increase in activation in these areas (Estudillo-Guerra et al. 2020 ; Strakowski et al. 2016 ). Interestingly, Peterson and colleagues (2021), found this hypoactivation in patients with poor cognitive performance, but after covarying for subsyndromal mood symptoms, it does not remain in DLPFC cluster in cognitively normal patients, which would imply that brain activity in the DLPFC region would be associated with cognitive performance, independently of sub-syndromic mood symptoms. However, a resting-state study observed reduced network homogeneity in the right inferior parietal lobe in patients with BDM compared to BDE (Gao et al. 2023 ). While this may serve as a potential biomarker for predicting mania remission status according to the authors, no correlations with cognitive tasks were found. This could be attributed to the nature of the task, as this region has been associated with language, social cognition, and other functions (Numssen et al. 2021). WM abnormalities have also been seen during all affective states of bipolar disorder (Hu et al., 2020 ), being more prevalent in active phases of the disease. Thus, it seems that an acute mood state may be associated with acute state-dependent microstructural WM changes (Zanneti et al., 2009). BDD patients have the largest overall cluster size of WM alterations relative to BDE or BDM patients. Although no association between fractional anisotropy (FA) and antidepressants was evident in a meta-analysis (Favre et al. 2019 ), this could explain the difference between the alterations in the acute state, as other studies have found an association with treatment (de Diego-Adeliño et al. 2014 ). Nevertheless, longitudinal studies would be better suited to identify and predict the effect of age, illness duration/severity and medication on WM microstructure in patients with BD (Favre et al. 2019 ). Different studies report conflicting results for the NAA/Cr ratio. Both an increase (Zhong et al. 2018 ) or a decrease in the NAA/Cr ratio was detected in the bilateral lenticular nucleus of BDD and BDM patients relative to the HCs (Frye et al. 2007 ). However, a correlation was found between the NAA/Cr ratio in the left BG in acute-episode BD patients and those with better EFs (Zhong et al. 2018 ). Similarly, other patterns of impaired functional connectivity have been proposed within dorsal attention networks that could differentiate mood states in BD, such as weaker connectivity in BDE patients and hyper-connectivity in BDM patients (Brady et al. 2017 ; Cerullo et al. 2012 ). A study using VFT found that BDD patients had weaker activation in both the right and left PFC than controls (Fu et al. 2018 ). In addition, patients show weaker activation for a second cognitive task (Tower of London test) in the bilateral DLPFC (Fu et al. 2018 ), although an increase in activity was described in the frontostriatal areas (Rive et al. 2016 ). In this regard, an increase in the small world (functional connectome) was described in BDD patients, associated with worse performance in working memory (Yang et al. 2020 ). These results might reflect a compensatory effect to control excessive rumination in the DMN (Claeys et al. 2022 ) or compensatory activity required by patients in a more severe state of BD, as observed in other disorders (Xing et al. 2017). Neuropsychological data support the differences found between patients in an acute state, who present worse cognitive performance (Ryan et al. 2012 ). Therefore, verbal memory, attention and EF seem to be affected in manic states (Bourne et al. 2013 ; Kurtz and Gerraty, 2009 ; Vrabie et al. 2015 ) and these deficits correlate with brain alterations (Benabarre et al. 2005 ; Pattanayak et al. 2012 ; Yamada et al. 2015 ). In contrast, deficits in working memory processing have also been consistently reported in euthymic patients (Thompson et al. 2007 ; Daglas et al. 2015 ) and no main effect of mood is found (Manelis et al. 2022 ). Therefore, differences have been seen in EFs and working memory in mania (Volkert et al. 2016 ), however finding differences between mania and euthymia may be due to a higher number of past manic episodes that were associated with poorer cognitive performance (Martinez-Arán et al. 2004) or the history of psychosis (Allen et al. 2010 ; Simonsen et al. 2011 ), which we have tried to consider in this review. Peripheral biomarkers Regarding peripheral biomarkers, we see that lower cholesterol levels (Fusar-Poli et al. 2020 ) were reported in BDM patients relative to BDD patients, as well as higher CRP levels (Ekinci and Ekinci; Tsai et al. 2017 ). However, other studies failed to find differences between the depressive and manic state (Sundaresh et al. 2018 ). Some studies have pointed towards an inflammatory component in BD, and it was suggested that elevated CRP levels might rather be a state than a marker in this condition (Evers et al. 2019 ; Fernandes et al. 2016 ). Although we found no correlations between cognitive variables and markers of inflammation here, serum CRP expression was negatively correlated with performance scores of immediate memory, language and attention in BD patients when the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was used (Bauer et al. 2014 ). Finally, only two studies assessed cognition and performed a search for biomarkers in the mixed state (Idemoto et al. 2021 ; Mangiocalda et al. 2015). The serum GDNF levels in BD patients in a mixed state showed no significant difference from those in HCs. Although altered levels of GDNF were only found in BDD patients, an increase in serum GDNF relative to the activity of the immune system occurred in BDM and BDD patients (Tunca et al., 2014 ), and there was no difference between BDE patients and HCs (Rosa et al. 2006 ). Moreover, the estimated IQ values, verbal memory and EFs of the BD mixed group were significantly lower than those of HCs (Vreeker et al. 2016 ). We have seen that GDNF levels in BDD patients decrease relative to those of the HCs (Takebayashi et al. 2006 ; Zhang et al. 2010 ), whereas those levels in BD patients in a mixed or manic state were comparable to those of the HCs. Conversely, GDNF plasma levels were higher in BDE patients relative to BDM patients and HCs (Barbosa et al. 2011 ). Similarly, serum GDNF increases in bipolar patients during acute manic and depressive episodes (Rosa et al. 2006 ). There is no clear relationship between GDNF and mood states, although GDNF mRNA expression may be increased by antidepressants or lithium (De-Paula et al. 2016 ; de Sousa et al. 2011 ). An association between peripheral levels of GDNF and cognitive function was found in patients with major depressive disorder (MDD; Liu et al. 2022 ; Zhang et al. 2014 ), which could suggest that GDNF is a biomarker for both BD and MDD in depressive states (Zinchuk et al. 2022 ). Euthymic/remission states Neuroimaging biomarker A meta-analysis consistently found trait-related deficits in EFs and verbal memory in patients with BD (Bourne et al. 2013 ). Executive dysfunction was also evident in BDE patients in our systematic review and hence, EFs deficits in BD may persist across different mood states, both in acute episodes and the euthymic state (Bourne et al. 2013 ; Rosa et al. 2010 ; Volkert et al. 2016 ). However, we found here studies where the performance of euthymic patients is comparable to that of HCs, which could be due to the subtype of BD type I or II (Dittmann et al., 2008 ) or to cognitive heterogeneity within the sample. This highlights the need to differentiate subgroups by cognitive performance (Burdick et al., 2014 ). In neuroimaging studies, de-activation failure has been reported in the vmPFC in BDD and BDM patients, persisting in remission (Fernández-Corcuera et al. 2013 ; Tian et al. 2020 ; Verdolini et al. 2023 ). This de-activation failure finding unique to BD may be core to the illness and akin to a trait mechanism not impacted by mood states. In euthymic state there seems to be parietal hypoactivation (Hajek et al. 2013 ) and normalization of DLPFC activation, which is mainly altered during manic episodes (Van der Schot et al. 2010 ). Hypoactivation of the PFC in verbal fluency tasks has also been found (Yoshimura et al. 2014 ). Moreover, during the euthymic state the NAA/Cr ratio in the bilateral lenticular nucleus was lower than in HCs (Kraguljac et al. 2012 ), although they did not exhibit changes in the NAA/Cr ratio in the temporal or parietal cortex (Brambilla et al. 2005 ). Regarding working memory, there are deficiencies in the manic or depressed state but not in euthymia. Indeed, most fMRI studies using an n -back paradigm suggested there were no significant differences in accuracy or reaction times between BDE patients and HCs (Cremaschi et al. 2013 ). However, elsewhere such deficits seem to persist during disease remission (Oh et al. 2019 ; Srivastava et al. 2019 ; Volkert et al. 2016 ). Regarding differences in cognitive performance, it is observed that BDE patients also achieve lower performance than controls, and these differences seem to increase with task complexity (Volkert et al., 2016 ). Furthermore, despite dysfunction in brain circuits related to working memory in patients with BD, other intact systems may help overcome this deficiency (Cremaschi et al. 2013 ). Peripheral biomarkers Unlike what was found in the study included here, where the differences GDNF levels for patients in the euthymic state were only found after correction (Rosa et al. 2006 ), Barbosa et al. ( 2011 ) found higher GDNF levels in BDE compared to BDM patients. Other studies do not find differences in GDNF levels between euthymia and HCs (Tunca et al. 2014 ). The inconsistency of results could be due to type II error, and larger sample sized studies are needed. With growing evidence that inflammation contributes to cognitive impairment in several medical conditions, it is crucial to investigate this aspect in bipolar disorder. However, until now, the relationship between inflammatory markers and affective symptoms is not completely (Strawbridge et al. 2021 ). 5. Conclusions Our findings highlight core regions involved in BD that are not only mood-specific, but also observed across mood states. Although individuals are clinically in remission, they still show abnormalities in brain connectivity, but a state-dependent topology appears to exist in BD and there appear to be underlying mechanisms of cognitive dysfunction that may be different in the different mood states of bipolar disorder. Consequently, this systematic review highlights the need for greater consistency in the use of staging models in BD research to standardize the results and identify biomarkers. Monitoring patients and verifying the most significant biomarkers could prevent the onset of acute episodes, and the functional and cognitive deterioration this entails. Similarly, it could allow a more precise differential diagnosis and improve the patient’s quality of life. As such, it is important to create a framework incorporating genetics, neuroimaging and cognitive sciences in order to refine the classification of mental disorders where the cognitive system is one of the potential higher order domains (Cuthbert 2014 ). A multidimensional approach combining peripheral and neuroimaging biomarkers may provide a more comprehensive understanding of cognitive endophenotypes across affective states in bipolar disorder. The results obtained in this review demonstrate the importance of considering BD with its different characteristics and shows the need for further longitudinal studies, as there are insufficient studies on hypo/mania, mixed states and clinical comparisons. Examining individuals in different affective states is crucial to identify mechanisms dependent on traits or the current state of symptoms (state), allowing the study of disease mechanisms to develop improved methods of diagnosis and treatment. 6. Limitations This systematic review has several limitations. Firstly, the sample of patients that we found in most studies is small and this may be due to the difficulty of evaluating these patients in acute states. Due to the heterogeneity in BD, we sought to be rigorous with the inclusion and exclusion criteria. For instance, as the impact of psychotic symptoms on cognition remains unclear, we excluded studies indicating patients had psychosis symptoms or if a history of psychosis was not included as a covariate. Conversely, most of the included studies do not seem to control this factor, potentially confounding the results. Methodological heterogeneity within and between studies is an important limitation of the articles included in this review, as different modalities are used in neuroimaging studies. The absence of consensus for defining euthymia and the definition of clinically significant impairment also imposes difficulties in both clinical practice and research. Although the duration of clinical remission has been associated with a significant improvement of residual symptoms, in this review, the range of duration to establish a euthymic state is from 2 to 6 months. The effects of medication or comorbidities are another factor to consider in the search for biomarkers and in neuropsychological assessments. An important limitation is also the cross-sectional nature of the studies available, along with the small samples. Furthermore, the longitudinal studies analyzed here experience significant loss of patients to follow-up, complicating interpretation. 7. Future directions The following systematic review could serve to create interventions that combine cognitive rehabilitation with biological treatments. It would be interesting to consider subsyndromal conditions and the presence of residual mood symptoms, since they could have a negative impact on certain cognitive spheres and the cognitive deficit in the euthymic state could change after controlling for these factors (Tsitsipa et al., 2015). More powerful longitudinal studies that follow patients across mood cycles will be crucial to clarify the relationship between neurocognitive impairment and mood. Additionally, neuroimaging studies reveal problem areas such as DLPFC in patients with mental disorders. To improve cognition, we could use non-drug techniques such as transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS) targeting those target areas (Hyde et al. 2022 ). Third, research is underway on how patients with bipolar disorder who have experienced psychosis and those who have not differ in their neurocognitive functioning (Glahn et al. 2007 ). It is important to clearly define different mood states in studies of bipolar disorder. Abbreviations BD Bipolar disorder BDE patients with bipolar disorder in a euthymic state BDD patients with bipolar disorder in a depressed state BDM patients with bipolar disorder in a manic state HCs Healthy subjects EFs Executive functions IL-6 Interleukin-6 TNRF1 Tumor Necrosis Factor Receptor 1 BDNF Brain-derived neuorotrophic factor WM White matter PACC Perigenual Anterior Cingulate Cortex PCC Posterior Cingulate Cortex CPT Continuous Performance Test MD Mean Diffusivity RD Radial Diffusivity FA Fractional Anisotropy fMRI Functional Magnetic Resonance Imaging DMN Default Mode Network DLPFC Dorsolateral Prefrontal Cortex FPPFC Frontopolar Prefrontal Cortex PC Parietal Cortex VLPFC Ventrolateral Prefrontal Cortex vmPFC Ventromedial Prefrontal Cortex OFC Orbitofrontal Cortex SACC Supragenual Anterior Cingulate Cortex NAA/CR N-acetylaspartate to creatine ratio Oxy-Hb Oxyhemoglobin CRP C-reactive Protein BG Basal Ganglia IQ Intellectual Quotient Tchol Total cholesterol 24-OCH 24-Hydroxycholesterol GDNF Glial Cell-Derived Neurotrophic Factor Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials All data generated during this study are included in this published article (supplementary information files). Disclosure statement The authors have no conflicts of interest to declare. Funding This work was supported by the General Secretariat of Research, Development and Innovation of the Andalusian Ministry of Health and Families. Project reference: PEMP-0008-2020. Author contributions CRLA and APR performed the systematic literature search, the screening and the data extraction, and wrote the manuscript. MHF and APR carried out the quality assessment. CRLA, EB and JIRR critically reviewed the content of the manuscript and approved the final version. Acknowledgements Not applicable. References Allen DN, Randall C, Bello D, Armstrong C, Frantom L, Cross C, Kinney J. Are working memory deficits in bipolar disorder markers for psychosis? Neuropsychology. 2010;24(2):244–54. 10.1037/a0018159 . Alonso-Lana S, Moro N, McKenna PJ, Sarró S, Romaguera A, Monté GC, Maristany T, Goikolea JM, Vieta E, Salvador R, Pomarol-Clotet E. Longitudinal brain functional changes between mania and euthymia in bipolar disorder. Bipolar Disord. 2019;5449–57. 10.1111/bdi.12767 . Babineau J. Product Review: Covidence (Systematic Review Software). Journal of the Canadian Health Libraries Association /. J de l'Association des bibliothèques de la santé du Can. 2014;35(2):68–71. 10.5596/c14-016 . Barbosa IG, Huguet RB, Sousa LP, Abreu MN, Rocha NP, Bauer ME, Carvalho LA, Teixeira AL. Circulating levels of GDNF in bipolar disorder. Neurosci Lett. 2011;502(2):103–6. 10.1016/j.neulet.2011.07.031 . Bauer IE, Pascoe MC, Wollenhaupt-Aguiar B, Kapczinski F, Soares JC. Inflammatory mediators of cognitive impairment in bipolar disorder. J Psychiatr Res. 2014;56:18–27. 10.1016/j.jpsychires.2014.04.017 . Benabarre A, Vieta E, Martínez-Arán A, Garcia-Garcia M, Martín F, Lomeña F, Torrent C, Sánchez-Moreno J, Colom F, Reinares M, Brugue E, Valdés M. Neuropsychological disturbances and cerebral blood flow in bipolar disorder. Aust N Z J Psychiatry. 2005;39(4):227–34. 10.1080/j.1440-1614.2004.01558.x . Bi B, Che D, Bai Y. Neural network of bipolar disorder: Toward integration of neuroimaging and neurocircuit-based treatment strategies. Transl Psychiatry. 2022;12:143. 10.1038/s41398-022-01917-x . Bourne C, Aydemir Ö, Balanzá-Martínez V, Bora E, Brissos S, Cavanagh JT, et al. Neuropsychological testing of cognitive impairment in euthymic bipolar disorder: an individual patient data meta-analysis. Acta Psychiatr Scand. 2013;128(3):149–62. https://doi.org/10.1111/acps.12133 . Brady RO Jr, Tandon N, Masters GA, Margolis A, Cohen BM, Keshavan M, Öngür D. Differential brain network activity across mood states in bipolar disorder. J Affect Disord. 2017;207:367–76. 10.1016/j.jad.2016.09.041 . Brambilla P, Stanley JA, Nicoletti MA, Sassi RB, Mallinger AG, Frank E, Kupfer D, Keshavan MS, Soares JC. 1H magnetic resonance spectroscopy investigation of the dorsolateral prefrontal cortex in bipolar disorder patients. J Affect Disord. 2005;86(1):61–7. 10.1016/j.jad.2004.12.008 . Brooks JO 3rd, Vizueta N, Penfold C, Townsend JD, Bookheimer SY, Altshuler LL. Prefrontal hypoactivation during working memory in bipolar II depression. Psychol Med. 2015;45(8):1731–40. 10.1017/S0033291714002852 . Brückl TM, Spoormaker VI, Sämann PG, Brem AK, Henco L, Czamara D, Elbau I, Grandi NC, Jollans L, Kühnel A, Leuchs L, Pöhlchen D, Schneider M, Tontsch A, Keck ME, Schilbach L, Czisch M, Lucae S, Erhardt A, Binder EB. The biological classification of mental disorders (BeCOME) study: a protocol for an observational deep-phenotyping study for the identification of biological subtypes. BMC Psychiatry. 2020;20(1):213. 10.1186/s12888-020-02541-z . Burdick KE, Goldberg JF, Harrow M. Neurocognitive dysfunction and psychosocial outcome in patients with bipolar I disorder at 15-year follow-up. Acta Psychiatr Scand. 2010;122(6):499–506. 10.1111/j.1600-0447.2010.01590.x . Burdick KE, Millett CE, Russo M, Alda M, Alliey-Rodriguez N, Anand A, Balaraman Y, Berrettini W, Bertram H, Calabrese JR, Calkin C, Conroy C, Coryell W, DeModena A, Feeder S, Fisher C, Frazier N, Frye M, Gao K, Garnham J, Gershon ES, Glazer K, Goes FS, Goto T, Harrington GJ, Jakobsen P, Kamali M, Kelly M, Leckband S, Løberg EM, Lohoff FW, Maihofer AX, McCarthy MJ, McInnis M, Morken G, Nievergelt CM, Nurnberger J, Oedegaard KJ, Ortiz A, Ritchey M, Ryan K, Schinagle M, Schwebel C, Shaw M, Shilling P, Slaney C, Stapp E, Tarwater B, Zandi P, Kelsoe JR. The association between lithium use and neurocognitive performance in patients with bipolar disorder. Neuropsychopharmacology. 2020;45(10):1743–9. 10.1038/s41386-020-0683-2 . Burdick KE, Russo M, Frangou S, Mahon K, Braga RJ, Shanahan M, Malhotra AK. Empirical evidence for discrete neurocognitive subgroups in bipolar disorder: clinical implications. Psychol Med. 2014;44(14):3083–96. 10.1017/S0033291714000439 . Carvalho AF, Firth J, Vieta E, Bipolar Disorder. N Engl J Med. 2020;383(1):58–66. 10.1056/NEJMra1906193 . Cerullo MA, Fleck DE, Eliassen JC, Smith MS, DelBello MP, Adler CM, Strakowski SM. A longitudinal functional connectivity analysis of the amygdala in bipolar I disorder across mood states. Bipolar Disord. 2012;14(2):175–84. 10.1111/j.1399-5618.2012.01002.x . Chen MH, Kao ZK, Chang WC, Tu PC, Hsu JW, Huang KL, Su TP, Li CT, Lin WC, Tsai SJ, Bai YM. Increased Proinflammatory Cytokines, Executive Dysfunction, and Reduced Gray Matter Volumes In First-Episode Bipolar Disorder and Major Depressive Disorder. J Affect Disord. 2020;274:825–31. 10.1016/j.jad.2020.05.158 . Chen MH, Wang L, Li H, Song H, Zhang X, Wang D. Altered intrinsic brain activity and cognitive impairment in euthymic, unmedicated individuals with bipolar disorder. Asian J Psychiatr. 2023;80:103386. 10.1016/j.ajp.2022.103386 . Claeys EHI, Mantingh T, Morrens M, Yalin N, Stokes PRA. Resting-state fMRI in depressive and (hypo)manic mood states in bipolar disorders: A systematic review. Prog Neuropsychopharmacol Biol Psychiatry. 2022;113:110465. 10.1016/j.pnpbp.2021.110465 . Cremaschi L, Penzo B, Palazzo M, Dobrea C, Cristoffanini M, Dell'Osso B, Altamura AC. Assessing working memory via N-back task in euthymic bipolar I disorder patients: a review of functional magnetic resonance imaging studies. Neuropsychobiology. 2013;68(2):63–70. 10.1159/000352011 . Cullen B, Ward J, Graham NA, Deary IJ, Pell JP, Smith DJ, Evans JJ. Prevalence and correlates of cognitive impairment in euthymic adults with bipolar disorder: A systematic review. J Affect Disord. 2016;205:165–181. 10.1016/j.jad.2016.06.063 . Epub 2016 Jul 5. PMID: 27449549. Cuthbert BN. The RDoC framework: facilitating transition from ICD/DSM to dimensional approaches that integrate neuroscience and psychopathology. World Psychiatry. 2014;13(1):28–35. 10.1002/wps.20087 . Daglas R, Yücel M, Cotton S, Allott K, Hetrick S, Berk M. Cognitive impairment in first-episode mania: a systematic review of the evidence in the acute and remission phases of the illness. Int J Bipolar Disord. 2015;3:9. 10.1186/s40345-015-0024-2 . De-Paula VJ, Gattaz WF, Forlenza OV. Long-term lithium treatment increases intracellular and extracellular brain-derived neurotrophic factor (BDNF) in cortical and hippocampal neurons at subtherapeutic concentrations. Bipolar Disord. 2016;18(8):692–5. 10.1111/bdi.12449 . de Diego-Adeliño J, Pires P, Gómez-Ansón B, Serra-Blasco M, Vives-Gilabert Y, Puigdemont D, Martín-Blanco A, Alvarez E, Pérez V, Portella MJ. Microstructural white-matter abnormalities associated with treatment resistance, severity and duration of illness in major depression. Psychol Med. 2014;44(6):1171–82. 10.1017/S003329171300158X . de Sousa RT, van de Bilt MT, Diniz BS, Ladeira RB, Portela LV, Souza DO, Forlenza OV, Gattaz WF, Machado-Vieira R. Lithium increases plasma brain-derived neurotrophic factor in acute bipolar mania: a preliminary 4-week study. Neurosci Lett. 2011;494(1):54–6. 10.1016/j.neulet.2011.02.054 . Dittmann S, Hennig-Fast K, Gerber S, Seemüller F, Riedel M, Emanuel Severus W, Langosch J, Engel RR, Möller HJ, Grunze HC. Cognitive functioning in euthymic bipolar I and bipolar II patients. Bipolar Disord. 2008;10(8):877–87. 10.1111/j.1399-5618.2008.00640.x . Ehrlich TJ, Ryan KA, Burdick KE, Langenecker SA, McInnis MG, Marshall DF. Cognitive subgroups and their longitudinal trajectories in bipolar disorder. Acta Psychiatr Scand., Ekinci A. Inflammatory parameters and blood lipid values across the different mood states in patients with bipolar disorder. Klinik Psikiyatri Dergisi. 2020;23. https://doi.org/10.5505/kpd.2020.98216 . Elshahawi HH, Essawi H, Rabie MA, Mansour M, Beshry ZA, Mansour AN. Cognitive functions among euthymic bipolar I patients after a single manic episode versus recurrent episodes. J Affect Disord. 2011;130(1–2):180–91. 10.1016/j.jad.2010.10.027 . Estudillo-Guerra MA, Pacheco-Barrios K, Cardenas-Rojas A, Adame-Ocampo G, Camprodon JA, Morales-Quezada L, Gutiérrez-Mora D, Flores-Ramos M. Brain perfusion during manic episode and at 6-month follow-up period in bipolar disorder patients: Correlation with cognitive functions. Brain Behav. 2020;10(6):e01615. 10.1002/brb3.1615 . Evers AK, Veeh J, McNeill R, Reif A, Kittel-Schneider S. C-reactive protein concentration in bipolar disorder: association with genetic variants. Int J Bipolar Disord. 2019;7(1):26. 10.1186/s40345-019-0162-z . Favre P, Pauling M, Stout J, Hozer F, Sarrazin S, Abé C, et al. Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals. Neuropsychopharmacology. 2019;44(13):2285–93. https://doi.org/10.1038/s41386-019-0485-6 . Fernandes BS, Steiner J, Molendijk ML, Dodd S, Nardin P, Gonçalves CA, Jacka F, Köhler CA, Karmakar C, Carvalho AF, Berk M. C-reactive protein concentrations across the mood spectrum in bipolar disorder: a systematic review and meta-analysis. Lancet Psychiatry. 2016;3(12):1147–56. 10.1016/S2215-0366(16)30370-4 . Fernández-Corcuera P, Salvador R, Monté GC, Salvador Sarró S, Goikolea JM, Amann B, et al. Bipolar depressed patients show both failure to activate and failure to de-activate during performance of a working memory task. J Affect Disord. 2013;148(2–3):170–8. Fleck DE, Eliassen JC, Durling M, Lamy M, Adler CM, DelBello MP, Shear PK, Cerullo MA, Lee JH, Strakowski SM. Functional MRI of sustained attention in bipolar mania. Mol Psychiatry. 2012;17(3):325–36. 10.1038/mp.2010.108 . Frey BN, Andreazza AC, Houenou J, Jamain S, Goldstein BI, Frye MA, Leboyer M, Berk M, Malhi GS, Lopez-Jaramillo C, Taylor VH, Dodd S, Frangou S, Hall GB, Fernandes BS, Kauer-Sant'Anna M, Yatham LN, Kapczinski F, Young LT. Biomarkers in bipolar disorder: a positional paper from the International Society for Bipolar Disorders Biomarkers Task Force. Aust N Z J Psychiatry. 2013;47(4):321–32. 10.1177/0004867413478217 . Friedman NP, Robbins TW. The role of prefrontal cortex in cognitive control and executive function. Neuropsychopharmacology. 2022;47(1):72–89. 10.1038/s41386-021-01132-0 . Frye MA, Thomas MA, Yue K, Binesh N, Davanzo P, Ventura J, O'Neill J, Guze B, Curran JG, Mintz J. Reduced concentrations of N-acetylaspartate (NAA) and the NAA-creatine ratio in the basal ganglia in bipolar disorder: a study using 3-Tesla proton magnetic resonance spectroscopy. Psychiatry Res. 2007;154(3):259–65. 10.1016/j.pscychresns.2006.11.003 . Fu L, Xiang D, Xiao J, Yao L, Wang Y, Xiao L, Wang H, Wang G, Liu Z. Reduced Prefrontal Activation During the Tower of London and Verbal Fluency Task in Patients With Bipolar Depression: A Multi-Channel NIRS Study. Front Psychiatry. 2018;9:214. 10.3389/fpsyt.2018.00214 . Fusar-Poli L, Amerio A, Cimpoesu P, Natale A, Salvi V, Zappa G, Serafini G, Amore M, Aguglia E, Aguglia A. Lipid and Glycemic Profiles in Patients with Bipolar Disorder: Cholesterol Levels Are Reduced in Mania. Med (Kaunas). 2020;57(1):28. 10.3390/medicina57010028 . Gao Y, Guo X, Wang S, Huang Z, Zhang B, Hong J, Zhong Y, Weng C, Wang H, Zha Y, Sun J, Lu L, Wang G. Frontoparietal network homogeneity as a biomarker for mania and remitted bipolar disorder and a predictor of early treatment response in bipolar mania patient. J Affect Disord. 2023;339:486–94. 10.1016/j.jad.2023.07.033 . García-Gutiérrez MS, Navarrete F, Sala F, Gasparyan A, Austrich-Olivares A, Manzanares J. Biomarkers in Psychiatry: Concept, Definition, Types and Relevance to the Clinical Reality. Front Psychiatry. 2020;11:432. 10.3389/fpsyt.2020.00432 . Glahn DC, Bearden CE, Barguil M, Barrett J, Reichenberg A, Bowden CL, Soares JC, Velligan DI. The neurocognitive signature of psychotic bipolar disorder. Biol Psychiatry. 2007;62(8):910-6. 10.1016/j.biopsych.2007.02.001 . Epub 2007 Jun 1. PMID: 17543288. Gogia M, Shah AQ, Kapczinski F, de Azevedo Cardoso T. The impact of substance use disorder comorbidity on cognition of individuals with bipolar disorder: A systematic review. Psychiatry Res. 2022;311:114525. 10.1016/j.psychres.2022.114525 . Epub 2022 Mar 23. PMID: 35364335. Guidara W, Messedi M, Maalej M, Naifar M, Khrouf W, Grayaa S, Maalej M, Bonnefont-Rousselot D, Lamari F, Ayadi F. Plasma oxysterols: Altered level of plasma 24-hydroxycholesterol in patients with bipolar disorder. J Steroid Biochem Mol Biol. 2021;211:105902. 10.1016/j.jsbmb.2021.105902 . Hajek T, Alda M, Hajek E, Ivanoff J. Functional neuroanatomy of response inhibition in bipolar disorders–combined voxel based and cognitive performance meta-analysis. J Psychiatr Res. 2013;47(12):1955–66. 10.1016/j.jpsychires.2013.08.015 . Hyde J, Carr H, Kelley N, Seneviratne R, Reed C, Parlatini V, Garner M, Solmi M, Rosson S, Cortese S, Brandt V. Efficacy of neurostimulation across mental disorders: systematic review and meta-analysis of 208 randomized controlled trials. Mol Psychiatry. 2022;27(6):2709–19. 10.1038/s41380-022-01524-8 . Epub 2022 Apr 1. PMID: 35365806; PMCID: PMC8973679. Hiyoshi A, Sabet JA, Sjöqvist H, Melinder C, Brummer RJ, Montgomery S. Precursors in adolescence of adult-onset bipolar disorder. J Affect Disord. 2017;218:353–8. 10.1016/j.jad.2017.04.071 . Hu R, Stavish C, Leibenluft E, Linke JO. White Matter Microstructure in Individuals With and At Risk for Bipolar Disorder: Evidence for an Endophenotype From a Voxel-Based Meta-analysis. Biol Psychiatry Cogn Neurosci Neuroimaging. 2020;12:1104–13. 10.1016/j.bpsc.2020.06.007 . Idemoto K, Niitsu T, Hata T, Ishima T, Yoshida S, Hattori K, et al. Serum levels of glial cell line-derived neurotrophic factor as a biomarker for mood disorders and lithium response. Psychiatry Res. 2021;301:113967. 10.1016/j.psychres.2021.113967 . Janiri D, Frangou S. Precision neuroimaging biomarkers for bipolar disorder. Int Rev Psychiatry. 2022;34(7–8):727–35. 10.1080/09540261.2022.2106121 . Kopf J, Glöckner S, Althen H, Cevada T, Schecklmann M, Dresler T, Kittel-Schneider S, Reif A. Neural Responses to a Working Memory Task in Acute Depressed and Remitted Phases in Bipolar Patients. Brain Sci. 2023;13(5):744. 10.3390/brainsci13050744 . Kraguljac NV, Reid M, White D, Jones R, den Hollander J, Lowman D, Lahti AC. Neurometabolites in schizophrenia and bipolar disorder - a systematic review and meta-analysis. Psychiatry Res. 2012;203(2–3):111–25. 10.1016/j.pscychresns.2012.02.003 . Kurtz MM, Gerraty RT. A meta-analytic investigation of neurocognitive deficits in bipolar illness: profile and effects of clinical state. Neuropsychology. 2009;23(5):551–62. 10.1037/a0016277 . Lai S, Zhong S, Liao X, Wang Y, Huang J, Zhang S, Sun Y, Zhao H, Jia Y. Biochemical abnormalities in basal ganglia and executive dysfunction in acute- and euthymic-episode patients with bipolar disorder: A proton magnetic resonance spectroscopy study. J Affect Disord. 2018;225:108–16. 10.1016/j.jad.2017.07.036 . Li W, Zhou FC, Zhang L, Ng CH, Ungvari GS, Li J, Xiang YT. Comparison of cognitive dysfunction between schizophrenia and bipolar disorder patients: A meta-analysis of comparative studies. J Affect Disord 20201; 274:652–61. 10.1016/j.jad.2020.04.051 . Liu X, Li P, Ma X, Zhang J, Sun X, Luo X, Zhang Y. Association between plasma levels of BDNF and GDNF and the diagnosis, treatment response in first-episode MDD. J Affect Disord. 2022;315:190–7. 10.1016/j.jad.2022.07.041 . Loftus J, Scott J, Vorspan F, Icick R, Henry C, Gard S, Kahn JP, Leboyer M, Bellivier F, Etain B. Psychiatric comorbidities in bipolar disorders: An examination of the prevalence and chronology of onset according to sex and bipolar subtype. J Affect Disord. 2020;267:258–63. 10.1016/j.jad.2020.02.035 . López-Jaramillo C, Lopera-Vásquez J, Gallo A, Ospina-Duque J, Bell V, Torrent C, Martínez-Arán A, Vieta E. Effects of recurrence on the cognitive performance of patients with bipolar I disorder: implications for relapse prevention and treatment adherence. Bipolar Disord. 2010;12(5):557–67. 10.1111/j.1399-5618.2010.00835.x . Magioncalda P, Martino M, Conio B, Escelsior A, Piaggio N, Presta A, Marozzi V, Rocchi G, Anastasio L, Vassallo L, Ferri F, Huang Z, Roccatagliata L, Pardini M, Northoff G, Amore M. Functional connectivity and neuronal variability of resting state activity in bipolar disorder–reduction and decoupling in anterior cortical midline structures. Hum Brain Mapp. 2015;36(2):666–82. 10.1002/hbm.22655 . Magioncalda P, Martino M, Conio B, Piaggio N, Teodorescu R, Escelsior A, Marozzi V, Rocchi G, Roccatagliata L, Northoff G, Inglese M, Amore M. Patterns of microstructural white matter abnormalities and their impact on cognitive dysfunction in the various phases of type I bipolar disorder. J Affect Disord. 2016;193:39–50. 10.1016/j.jad.2015.12.050 . Manelis A, Halchenko YO, Bonar L, et al. Working memory updating in individuals with bipolar and unipolar depression: fMRI study. Transl Psychiatry. 2022;12:441. 10.1038/s41398-022-02211-6 . Martinez-Arán A, Vieta E. Cognition as a target in schizophrenia, bipolar disorder and depression. Eur Neuropsychopharmacol. 2015;25(2):151–7. 10.1016/j.euroneuro.2015.01.007 . Martínez-Arán A, Vieta E, Reinares M, Colom F, Torrent C, Sánchez-Moreno J, Benabarre A, Goikolea JM, Comes M, Salamero M. Cognitive function across manic or hypomanic, depressed, and euthymic states in bipolar disorder. Am J Psychiatry. 2004;161(2):262–70. 10.1176/appi.ajp.161.2.262 . Martino M, Magioncalda P, Saiote C, Conio B, Escelsior A, Rocchi G, Piaggio N, Marozzi V, Huang Z, Ferri F, Amore M, Inglese M, Northoff G. Abnormal functional-structural cingulum connectivity in mania: combined functional magnetic resonance imaging-diffusion tensor imaging investigation in different phases of bipolar disorder. Acta Psychiatr Scand. 2016;134(4):339–49. 10.1111/acps.12596 . Menon V, D'Esposito M. The role of PFC networks in cognitive control and executive function. Neuropsychopharmacology. 2022;47(1):90–103. 10.1038/s41386-021-01152-w . Mikawa W, Tsujii N, Akashi H, Adachi T, Kirime E, Shirakawa O. Left temporal activation associated with depression severity during a verbal fluency task in patients with bipolar disorder: a multichannel near-infrared spectroscopy study. J Affect Disord. 2015;173:193–200. 10.1016/j.jad.2014.10.051 . Misiak B, Stańczykiewicz B, Kotowicz K, Rybakowski JK, Samochowiec J, Frydecka D. Cytokines and C-reactive protein alterations with respect to cognitive impairment in schizophrenia and bipolar disorder: A systematic review. Schizophr Res. 2018;192:16–29. 10.1016/j.schres.2017.04.015 . Miskowiak KW, Burdick KE, Martinez-Aran A, Bonnin CM, Bowie CR, Carvalho AF, Gallagher P, Lafer B, López-Jaramillo C, Sumiyoshi T, McIntyre RS, Schaffer A, Porter RJ, Torres IJ, Yatham LN, Young AH, Kessing LV, Vieta E. Methodological recommendations for cognition trials in bipolar disorder by the International Society for Bipolar Disorders Targeting Cognition Task Force. Bipolar Disord. 2017;19(8):614–26. 10.1111/bdi.12534 . Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097. 10.1371/journal.pmed.1000097 . Mora E, Portella MJ, Forcada I, Vieta E, Mur M. Persistence of cognitive impairment and its negative impact on psychosocial functioning in lithium-treated, euthymic bipolar patients: a 6-year follow-up study. Psychol Med. 2013;43(6):1187–96. 10.1017/S0033291712001948 . Muneer A. The Discovery of Clinically Applicable Biomarkers for Bipolar Disorder: A Review of Candidate and Proteomic Approaches. Chonnam Med J. 2020;56(3):166–79. 10.4068/cmj.2020.56.3.166 . Nishimura Y, Takahashi K, Ohtani T, Ikeda-Sugita R, Kasai K, Okazaki Y. Dorsolateral prefrontal hemodynamic responses during a verbal fluency task in hypomanic bipolar disorder. Bipolar Disord. 2015;17(2):172–83. 10.1111/bdi.12252 . Oh DH, Lee S, Kim SH, Ryu V, Cho HS. Low working memory capacity in euthymic bipolar I disorder: No relation to reappraisal on emotion regulation. J Affect Disord. 2019;252:174–81. 10.1016/j.jad.2019.04.042 . Page MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 2021;372:n160. 10.1136/bmj.n160 . Park HJ, Friston K. Structural and functional brain networks: from connections to cognition. Science. 2013;342:1238411. Pattanayak RD, Sagar R, Mehta M. Neuropsychological performance in euthymic Indian patients with bipolar disorder type I: correlation between quality of life and global functioning. Psychiatry Clin Neurosci. 2012;66(7):553–63. 10.1111/j.1440-1819.2012.02400.x . Penfold C, Vizueta N, Townsend JD, Bookheimer SY, Altshuler LL. Frontal lobe hypoactivation in medication-free adults with bipolar II depression during response inhibition. Psychiatry Res. 2015;231(3):202–9. 10.1016/j.pscychresns.2014.11.005 . Pomarol-Clotet E, Alonso-Lana S, Moro N, Sarró S, Bonnin MC, Goikolea JM, Fernández-Corcuera P, Amann BL, Romaguera A, Vieta E, Blanch J, McKenna PJ, Salvador R. Brain functional changes across the different phases of bipolar disorder. Br J Psychiatry. 2015;206(2):136–44. 10.1192/bjp.bp.114.152033 . Rive MM, Koeter MW, Veltman DJ, Schene AH, Ruhé HG. Visuospatial planning in unmedicated major depressive disorder and bipolar disorder: distinct and common neural correlates. Psychol Med. 2016;46(11):2313–28. 10.1017/S0033291716000933 . Rodríguez-Cano E, Alonso-Lana S, Sarró S, Fernández-Corcuera P, Goikolea JM, Vieta E, Maristany T, Salvador R, McKenna PJ, Pomarol-Clotet E. Differential failure to deactivate the default mode network in unipolar and bipolar depression. Bipolar Disord. 2017;19(5):386–95. 10.1111/bdi.12517 . Rosa AR, Frey BN, Andreazza AC, Ceresér KM, Cunha AB, Quevedo J, Santin A, Gottfried C, Gonçalves CA, Vieta E, Kapczinski F. Increased serum glial cell line-derived neurotrophic factor immunocontent during manic and depressive episodes in individuals with bipolar disorder. Neurosci Lett. 2006;407(2):146–50. 10.1016/j.neulet.2006.08.026 . Rosa AR, Reinares M, Michalak EE, Bonnin CM, Sole B, Franco C, Comes M, Torrent C, Kapczinski F, Vieta E. Functional impairment and disability across mood states in bipolar disorder. Value Health. 2010;13(8):984–8. 10.1111/j.1524-4733.2010.00768.x . Ryan KA, Vederman AC, McFadden EM, Weldon AL, Kamali M, Langenecker SA, McInnis MG. Differential executive functioning performance by phase of bipolar disorder. Bipolar Disord. 2012;14:527–36. Saldarini F, Gottlieb N, Stokes PRA. Neural correlates of working memory function in euthymic people with bipolar disorder compared to healthy controls: A systematic review and meta-analysis. J Affect Disord. 2022;297:610–22. 10.1016/j.jad.2021.10.084 . Sanches M, Bauer IE, Galvez JF, Zunta-Soares GB, Soares JC. The management of cognitive impairment in bipolar disorder: current status and perspectives. Am J Ther. 2015;22(6):477–86. 10.1097/MJT.0000000000000120 . Schouws SNTM, Korten N, Beekman ATF, Stek ML, Dols A. Does cognitive function in older bipolar patients depend on recurrent or current mood symptoms? Int J Geriatr Psychiatry. 2020;35(10):1163–70. 10.1002/gps.5352 . Schumer MC, Chase HW, Rozovsky R, Eickhoff SB, Phillips ML. Prefrontal, parietal, and limbic condition-dependent differences in bipolar disorder: a large-scale meta-analysis of functional neuroimaging studies. Mol Psychiatry. 2023;28(7):2826–38. 10.1038/s41380-023-01974-8 . Simonsen C, Sundet K, Vaskinn A, Birkenaes AB, Engh JA, Faerden A, Jónsdóttir H, Ringen PA, Opjordsmoen S, Melle I, Friis S, Andreassen OA. Neurocognitive dysfunction in bipolar and schizophrenia spectrum disorders depends on history of psychosis rather than diagnostic group. Schizophr Bull. 2011;37(1):73–83. 10.1093/schbul/sbp034 . Srivastava C, Bhardwaj A, Sharma M, Kumar S. Cognitive Deficits in Euthymic Patients With Bipolar Disorder: State or Trait Marker? J Nerv Ment Dis. 2019;207(2):100–5. 10.1097/NMD.0000000000000920 . Strakowski SM, Fleck DE, Welge J, Eliassen JC, Norris M, Durling M, Komoroski RA, Chu WJ, Weber W, Dudley JA, Blom TJ, Stover A, Klein C, Strawn JR, DelBello MP, Lee JH, Adler CM. fMRI brain activation changes following treatment of a first bipolar manic episode. Bipolar Disord. 2016;18(6):490–501. 10.1111/bdi.12426 . Strawbridge R, Carter R, Saldarini F, Tsapekos D, Young AH. Inflammatory biomarkers and cognitive functioning in individuals with euthymic bipolar disorder: exploratory study. BJPsych Open. 2021;7(4):e126. 10.1192/bjo.2021.966 . Sundaresh A, Rajkumar R, Krishnamoorthy R, Leboyer M, Negi V, Tamouza RC. -Reactive Protein in Bipolar Disorder in an Indian Clinical Setting. J Clin Diagn Res. 2018;12. 10.7860/jcdr/2018/37177.12014 . Takebayashi M, Hisaoka K, Nishida A, Tsuchioka M, Miyoshi I, Kozuru T, Hikasa S, Okamoto Y, Shinno H, Morinobu S, Yamawaki S. Decreased levels of whole blood glial cell line-derived neurotrophic factor (GDNF) in remitted patients with mood disorders. Int J Neuropsychopharmacol. 2006;9(5):607–12. 10.1017/S1461145705006085 . Takizawa R, Fukuda M, Kawasaki S, Kasai K, Mimura M, Pu S, Noda T, Niwa S, Okazaki Y. Joint Project for Psychiatric Application of Near-Infrared Spectroscopy (JPSY-NIRS) Group. Neuroimaging-aided differential diagnosis of the depressive state. NeuroImage. 2014;85(Pt):498–507. 10.1016/j.neuroimage.2013.05.126 . Thompson JM, Gray JM, Hughes JH, Watson S, Young AH, Ferrier IN. Impaired working memory monitoring in euthymic bipolar patients. Bipolar Disord. 2007;9(5):478–89. 10.1111/j.1399-5618.2007.00470.x . Tian F, Diao W, Yang X, Wang X, Roberts N, Feng C, Jia Z. Failure of activation of striatum during the performance of executive function tasks in adult patients with bipolar disorder. Psychol Med. 2020;50(4):653–65. 10.1017/S0033291719000473 . Torrent C, Martinez-Arán A, del Mar Bonnin C, Reinares M, Daban C, Solé B, Rosa AR, Tabarés-Seisdedos R, Popovic D, Salamero M, Vieta E. Long-term outcome of cognitive impairment in bipolar disorder. J Clin Psychiatry. 2012;73(7):e899–905. 10.4088/JCP.11m07471 . Tunca Z, Ozerdem A, Ceylan D, Yalçın Y, Can G, Resmi H, Akan P, Ergör G, Aydemir O, Cengisiz C, Kerim D. Alterations in BDNF (brain derived neurotrophic factor) and GDNF (glial cell line-derived neurotrophic factor) serum levels in bipolar disorder: The role of lithium. J Affect Disord. 2014;166:193–200. 10.1016/j.jad.2014.05.012 . Tsai SY, Chung KH, Chen PH. Levels of interleukin-6 and high-sensitivity C-reactive protein reflecting mania severity in bipolar disorder. Bipolar Disord. 2017;19(8):708–9. 10.1111/bdi.12570 . Tsapekos D, Strawbridge R, Cella M, Wykes T, Young AH. Cognitive impairment in euthymic patients with bipolar disorder: Prevalence estimation and model selection for predictors of cognitive performance. J Affect Disord. 2021;294:497–504. 10.1016/j.jad.2021.07.036 . Tsitsipa E, Fountoulakis KN. The neurocognitive functioning in bipolar disorder: a systematic review of data. Ann Gen Psychiatry. 2015;14:42. 10.1186/s12991-015-0081-z . Uluyol OB, Onur OS, Ekinci A, Guclu O. Relationship Between Serum Uric Acid Levels and Cognitive Functions in Bipolar Disorder. Psychiatry Clin Psychopharmacol. 2020;30(2):165–74. 10.5455/pcp.20200321090156 . Van der Schot A, Kahn R, Ramsey N, Nolen W, Vink M. Trait and state dependent functional impairments in bipolar disorder. Psychiatry Res. 2010;184(3):135–42. 10.1016/j.pscychresns.2010.07.009 . Velasques B, Bittencourt J, Diniz C, Teixeira S, Basile LF, Inácio Salles J, et al. Changes in saccadic eye movement (SEM) and quantitative EEG parameter in bipolar patients. J Affect Disord. 2013;145(3):378–85. 10.1016/j.jad.2012.04.049 . Verdolini N, Moreno-Ortega M, Salgado-Pineda P, Monté G, de Aragón AM, Dompablo M, McKenna PJ, Salvador R, Palomo T, Pomarol-Clotet E, Rodriguez-Jimenez R. Failure of deactivation in bipolar disorder during performance of an fMRI adapted version of the Stroop task. J Affect Disord. 2023;329:307–14. 10.1016/j.jad.2023.02.132 . Volkert J, Schiele MA, Kazmaier J, Glaser F, Zierhut KC, Kopf J, Kittel-Schneider S, Reif A. Cognitive deficits in bipolar disorder: from acute episode to remission. Eur Arch Psychiatry Clin Neurosci. 2016;266(3):225–37. 10.1007/s00406-015-0657-2 . Vrabie M, Marinescu V, Talaşman A, Tăutu O, Drima E, Micluţia I. Cognitive impairment in manic bipolar patients: important, understated, significant aspects. Ann Gen Psychiatry. 2015;14:41. 10.1186/s12991-015-0080-0 . Vreeker A, Boks MP, Abramovic L, Verkooijen S, van Bergen AH, Hillegers MH, et al. High educational performance is a distinctive feature of bipolar disorder: a study on cognition in bipolar disorder, schizophrenia patients, relatives and controls. Psychol Med. 2016;46(4):807–18. 10.1017/s0033291715002299 . Wells G, Shea B, O'Connell D, Peterson J, Welch V, Losos M, Tugwell P. The Newcastle–Ottawa Scale (NOS) for Assessing the Quality of Non-Randomized Studies in Meta-Analysis. 2000. Available from: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp . Wingo AP, Wingo TS, Harvey PD, Baldessarini RJ. Effects of lithium on cognitive performance: a meta-analysis. J Clin Psychiatry. 2009;70(11):1588-97. 10.4088/JCP.08r04972 . Epub 2009 Aug 11. PMID: 19689922. Wohlin C. Guidelines for snowballing in systematic literature studies and a replication in software engineering. ACM International Conference Proceeding Series. 2014. 10.1145/2601248.2601268 . Xing M, Tadayonnejad R, MacNamara A, Ajilore O, DiGangi J, Phan KL, Leow A, Klumpp H. Resting-state theta band connectivity and graph analysis in generalized social anxiety disorder. Neuroimage Clin. 2016;13:24–32. PMID: 27920976; PMCID: PMC5126152. Yamada S, Takahashi S, Ukai S, Tsuji T, Iwatani J, Tsuda K, et al. Microstructural abnormalities in anterior callosal fibers and their relationship with cognitive function in major depressive disorder and bipolar disorder: a tract-specific analysis study. J Affect Disord. 2015;174:542–8. 10.1016/j.jad.2014.12.022 . Yang J, Ouyang X, Tao H, Pu W, Fan Z, Zeng C, Huang X, Chen X, Liu J, Liu Z, Palaniyappan L. Connectomic signatures of working memory deficits in depression, mania, and euthymic states of bipolar disorder. J Affect Disord. 2020;274:190–8. 10.1016/j.jad.2020.05.058 . Yoshimura Y, Okamoto Y, Onoda K, Okada G, Toki S, Yoshino A, Yamashita H, Yamawaki S. Psychosocial functioning is correlated with activation in the anterior cingulate cortex and left lateral prefrontal cortex during a verbal fluency task in euthymic bipolar disorder: a preliminary fMRI study. Psychiatry Clin Neurosci. 2014;68(3):188–96. 10.1111/pcn.12115 . Zarp Petersen J, Varo C, Skovsen CF, Ott CV, Kjaerstad HL, Vieta E, Harmer CJ, Knudsen GM, Kessing LV, Macoveanu J, Miskowiak KW. Neuronal underpinnings of cognitive impairment in bipolar disorder: A large data-driven functional magnetic resonance imaging study. Bipolar Disord. 2022;24(1):69–81. 10.1111/bdi.13100 . Zanetti MV, Jackowski MP, Versace A, Almeida JR, Hassel S, Duran FL, Busatto GF, Kupfer DJ, Phillips ML. State-dependent microstructural white matter changes in bipolar I depression. Eur Arch Psychiatry Clin Neurosci. 2009;259(6):316–28. 10.1007/s00406-009-0002-8 . Zhang X, Ru B, Sha W, Xin W, Zhou H, Zhang Y. Performance on the Wisconsin card-sorting test and serum levels of glial cell line-derived neurotrophic factor in patients with major depressive disorder. Asia Pac Psychiatry. 2014;6(3):302–7. 10.1111/appy.12120 . Zhang X, Zhang Z, Sha W, Xie C, Xi G, Zhou H, Zhang Y. Effect of treatment on serum glial cell line-derived neurotrophic factor in bipolar patients. J Affect Disord. 2010;126(1–2):326–9. 10.1016/j.jad.2010.03.003 . Zhong S, Wang Y, Lai S, Liu T, Liao X, Chen G, Jia Y. Associations between executive function impairment and biochemical abnormalities in bipolar disorder with suicidal ideation. J Affect Disord. 2018;241:282–90. 10.1016/j.jad.2018.08.031 . Zinchuk MS, Guekht AB, Druzhkova TA, Gulyaeva NV, Shpak AA. Glial cell line-derived neurotrophic factor (GDNF) in blood serum and lacrimal fluid of patients with a current depressive episode. J Affect Disord. 2022;318:409–13. 10.1016/j.jad.2022.09.025 . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4020734","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":282026109,"identity":"be13cd28-7f53-44e6-abc4-e3b69ca28b38","order_by":0,"name":"Perez-Ramos Anaid","email":"","orcid":"","institution":"University of Cádiz","correspondingAuthor":false,"prefix":"","firstName":"Perez-Ramos","middleName":"","lastName":"Anaid","suffix":""},{"id":282026110,"identity":"cc2fa6df-a42c-41d2-aa0d-47c65d566965","order_by":1,"name":"Romero-Lopez-Alberca Cristina","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYFACxgYGBgMEV444LQeQtBgTZ9EBJHZiAyHV/LMPN3/+UHBHnkH68NENH/fYpG84fvgBw4c/uLVInEtskzhg8MywgS8t7eaMZ2m5G86kGTDObMOtxYCHsQ3ol8OMDTw8Zrd5DhzO3XCDwYCZF4/zgFqaPwC12IO1/DlwON3gBvsH5j94HAbU0gB02OFEsBaGA4cTDG7wGDAzsOHxyxnGNokzBoeT23jY0m72HEgznHkmp+BgLx6/8PewP/5Q8eewbT8P87EbPw7YyPMdP77xwQ88DoMDFJccIELDKBgFo2AUjAI8AAAarVWCuTw6vAAAAABJRU5ErkJggg==","orcid":"","institution":"University of Cádiz","correspondingAuthor":true,"prefix":"","firstName":"Romero-Lopez-Alberca","middleName":"","lastName":"Cristina","suffix":""},{"id":282026111,"identity":"ccdc3283-6302-4bfd-9c3a-b9ce99ac6814","order_by":2,"name":"HIdalgo-Figueroa Maria","email":"","orcid":"","institution":"University of Cádiz","correspondingAuthor":false,"prefix":"","firstName":"HIdalgo-Figueroa","middleName":"","lastName":"Maria","suffix":""},{"id":282026112,"identity":"7c27d2af-a6bd-4807-9766-663767bf074d","order_by":3,"name":"Berrocoso Esther","email":"","orcid":"","institution":"University of Cádiz","correspondingAuthor":false,"prefix":"","firstName":"Berrocoso","middleName":"","lastName":"Esther","suffix":""},{"id":282026113,"identity":"899c4c12-e6ba-4b5a-b695-9d6d0b534683","order_by":4,"name":"Perez-Revuelta Jose Ildefonso","email":"","orcid":"","institution":"University of Cádiz","correspondingAuthor":false,"prefix":"","firstName":"Perez-Revuelta","middleName":"Jose","lastName":"Ildefonso","suffix":""}],"badges":[],"createdAt":"2024-03-06 11:48:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4020734/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4020734/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53359715,"identity":"56d202a0-a756-46ef-b8d6-d5231dac7d99","added_by":"auto","created_at":"2024-03-25 04:27:57","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":349071,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA Flow Diagram of the literature search and study selection\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFrom: \u003c/em\u003eBabineau, 2014. Product Review: Covidence (Systematic Review Software)\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4020734/v1/3ed8276e7dcab3d44bcba7a1.jpeg"},{"id":53360371,"identity":"1c373928-716f-4b38-a4b9-25dcada892bc","added_by":"auto","created_at":"2024-03-25 04:35:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":606523,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4020734/v1/cbb9f712-ca26-46e9-8b16-baaa8ccc9524.pdf"},{"id":53359714,"identity":"f5d812c5-1a11-4275-9f33-7e13476ea9b0","added_by":"auto","created_at":"2024-03-25 04:27:57","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":35650,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix13.docx","url":"https://assets-eu.researchsquare.com/files/rs-4020734/v1/4df2751f3bfdff5cb6af9e86.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A systematic review of the biomarkers associated with cognition and mood state in bipolar disorder","fulltext":[{"header":"1. Background","content":"\u003cp\u003eBipolar disorder (BD) is a chronic psychiatry disease characterized by the recurrence of acute mood episodes with euphoric, depressive or mixed clinical features (Carvalho et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Cognitive alterations negatively affect the disease course, the functional outcome and work capacity in mood disorders, particularly in BD (Burdick et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Mora et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Torrent et al. \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Previous literature shows that BD patients present impairment in most cognitive domains (psychomotor delay and impairment of declarative memory, executive function and attention) compared to healthy controls (HCs) (Li et al. 2020; Sanches et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Despite this cognitive impairment being also present during remission phases (Bourne et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Chen et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), there is considerable heterogeneity among patients with BD. This heterogeneity ranges from patients with intact cognition and performance comparable to HCs, to patients with significant global cognitive impairment (Burdick et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Ehrlich et al. 2022), suggesting that there are different subgroups in function of cognitive performance. Studies examining the prevalence of cognitive impairment in BD report inconsistent results. A recent study examines the prevalence of cognitive impairment in a cohort of euthymic patients and estimates that 35% of patients experienced clinically significant cognitive deficits (Tsapekos et al. \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCognition can also be affected by various factors, such as symptoms, age of onset, the incidence of psychosis and pharmacological treatments (Uluyol et al. \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The effect of medications on cognition has been the subject of debate. On the one hand, some studies report cognitive deficits in domains such as attention and memory during prolonged lithium treatment (Wingo et al. \u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), and other suggest that lithium treatment does not significantly affect cognitive performance (Burdick et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The use of antipsychotic medication has also been linked to poorer cognitive performance (Cullen et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Additionally, a higher estimated Intelligence Quotient (IQ) before the onset of the illness is associated with a slower cognitive decline as people age (Tsapekos et al. \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Similarly, the risk of developing BD has been associated with cognitive performance, so better cognitive performance in late adolescence was associated with a lower risk of BD (Hiyoshi et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). On the other hand, BD has a high prevalence of psychiatric comorbidities, with more than half of adult patients diagnosed with at least one comorbid condition in their lifetime (Loftus et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). A recent systematic review reinforces that individuals with BD and substance use disorder (SUD) comorbidity may have greater cognitive impairment compared to individuals with BD without SUD comorbidity (Gogia et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn recent years, most studies focus on patients in a euthymic state while few compare cognitive functioning across the acute and euthymic phases of BD. Executive dysfunction seems to arise in the early stages of BD, and it tends to be exacerbated during depression and after manic episodes, suggesting it may be considered as a marker of the disease state (Elshahawi et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; L\u0026oacute;pez-Jaramillo et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In a recent study, the cognitive performance of BD patients over 60 years of age was worse than age-matched HCs and those with depression had worse working memory than those in a state of hypomania (Schouws et al. \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Although cognitive abnormalities were detected in all phases of the disease, they were most notable during acute episodes (Kurtz and Gerraty, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Patients with a manic episode appear to show greater cognitive impairment in verbal and working memory, executive function/reasoning, and problem solving, compared to the depressed, mixed, and euthymic subgroup (Vrabie et al., \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Therefore, the acute clinical state could modify the pattern or magnitude of neurocognitive impairment in patients with BD (Kurtz and Gerraty, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). However, a study that compared patients in a depressive (BDD), manic (BDM) and euthymic state (BDE) failed to find cognitive differences between the different BD groups (Mart\u0026iacute;nez-Ar\u0026aacute;n et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Therefore, the acute clinical state could modify the pattern or magnitude of neurocognitive impairment in patients with BD, but it is still under discussion (Kurtz and Gerraty, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, our understanding of the physiological or biological mechanisms underlying cognitive impairment in BD remains limited (Strawbridge et al. \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It is of great importance to understand and delve into the mechanisms underlying cognitive impairment for a better understanding of the role that cognition plays in pathology and to design more effective treatment approaches. Identification of markers has become a promising tool to guide diagnosis, predict clinical status, and help understand the pathophysiology of mental disorders. Hence, associations with biomarkers could clarify the cognitive models underlying each mood state and create adapted remediation tasks to achieve better cognitive and functional performance and to find markers of specific states that can prevent relapse.\u003c/p\u003e \u003cp\u003eCurrent diagnostic criteria for mental disorders are based solely on clinical features and behavioral observations, with no substantial biological validation (Br\u0026uuml;ckl et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Recent years have seen an increase in the number of studies focusing on the neural correlates of BD (Muneer \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), however few studies have addressed whether there is an association between biological mechanisms and cognitive dysfunction in the different affective states of BD. An inflammatory state measured by CRP and cytokine levels in peripheral blood could be an important contributor to the cognitive impairment observed in patients with schizophrenia and BD (Misiak et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Uluyol et al. \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, patients with first-episode BD exhibited worse EFs and higher TNFR1 levels than healthy controls (Chen et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Hence, there appears to be an association between inflammatory processes and executive dysfunction. Frey et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) summarized BD-related biomarkers from genetic, peripheral, and neuroimaging biomarkers. In addition, \u0026lsquo;omics' technologies, including genomics, proteomics, transcriptomics, metabolomics, and epigenetics, have contributed to the rapid discovery of many potential biomarkers (Garc\u0026iacute;a-Guitierrez et al. 2020). Current advances in this field have focused on the need for more precise neuroimaging biomarkers (Janiri and Frangou, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and including them in cognitive trials to investigate the neural correlates of potential procognitive efficacy in candidate treatments (Miskowiak et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). A longitudinal neuroimaging study demonstrated changes in prefrontal regions across mood states in subjects with BD. BDM patients exhibited increased connectivity with the right middle frontal gyrus compared to HCs, whereas in depressed BD subject\u0026rsquo;s connectivity was increase with the right medial frontal gyrus and left middle frontal gyrus (Cerullo et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). An interesting study also showed different brain activity patterns depending on cognitive impairment, those with poorer cognitive performance exhibit lower activity in regions associated with cognitive control and higher activity in the default mode network, whereas cognitively normal patients show minimal hypoactivity compared to HCs (Petersen et al. 2022).\u003c/p\u003e \u003cp\u003eAccordingly, one of the main objectives in the management of psychiatric disorders would be to prevent or limit any cognitive deterioration by studying the factors involved in neurocognitive performance (Mart\u0026iacute;nez-Aran and Vieta, 2015). Furthermore, there are no clinically available treatments with direct pro-cognitive efficacy in mood disorders (Miskowiak et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and there is little understanding of the reasons why some patients with BD develop significant cognitive deficits, while others remain cognitively intact during the different affective phases of the illness. In fact, cognitive function is a complex construct, and a combination of instruments that allow us to evaluate different aspects could greatly contribute to knowledge about the nature and extent of cognitive dysfunctions in BD.\u003c/p\u003e \u003cp\u003eThe aim of this systematic review was to synthesize studies in the literature that evaluated the association between biomarkers and cognition in patients with bipolar disorder according to affective state, since, to date, no study has systematically included these three factors.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Systematic Search Strategy\u003c/h2\u003e \u003cp\u003eThe study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) on 30th March, 2023 (Registration No.: CRD42023410782). Following the PRISMA guidelines (Preferred Reporting Items for Systematic reviews and Meta-analyses; Page et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), a systematic review was carried out of studies investigating biomarkers and cognition in the different mood states of BD (see Supplementary Material Appendix 1 for PRISMA Checklist). Searches of PubMed, SCOPUS and the Web of Science (WOS) were carried out for the past 10 years (from 2013), and we included studies of patients with BD in which data from at least two different mood states were compared. We started the search in August 2022 and concluded it in December 2022. To update the systematic review, a final search has been done to include those studies that could have been done during 2023. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides the methodological procedure followed was based on the PRISMA guidelines (Moher et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe syntax search [\u0026lsquo;bipolar disorder\u0026rsquo;] AND [mood] AND [biomarker] AND [cogni*] in PubMed and its equivalents in the other databases were used. For the second search, studies from January 2023 to December 2023 have been included.\u003c/p\u003e \u003cp\u003eNote that the general term biomarker was used to include neuroimaging, physiological, genetic or peripheral markers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Eligibility\u003c/h2\u003e \u003cp\u003eEligility criteria were: (a) the study was carried out on adult patients (\u0026ge;\u0026thinsp;18 years of age); (b) they were diagnosed with BD according to the criteria of the International Classification of Diseases (CIE-10) or the DSM (DSM-IV to DSM-5); (c) the study included a comparison of at least two phases of BD (mania, depression, mixed state or euthymia); (d) that includes a neurocognitive assessment and its association with a biomarker; (e) published from 2013 to December 2023 (e) longitudinal or cross-sectional studies and (f) it was written in English, Spanish or French.\u003c/p\u003e \u003cp\u003eThe exclusion criteria were: (a) if the patients had a history of psychosis; (b) if the article was a family study, systematic review, book chapter, case report or a meta-analysis; (c) non-access articles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Data extraction\u003c/h2\u003e \u003cp\u003eTwo authors (CRLA and APR) performed the review independently using the Covidence program and any disagreements on study selection were resolved by a third person (JPR). Covidence is a web-based collaboration software platform that streamlines the production of systematic and other literature reviews (Babineau \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Data synthesis\u003c/h2\u003e \u003cp\u003eThe following characteristics were extracted from the table (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e): Reference; Type of study; Population; Biomarker; Neuropsychological assessment; Results depending on the mood state; Association between biomarker and cognition; Criteria to establish the mood state.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Quality assessment\u003c/h2\u003e \u003cp\u003eA quality assessment was carried out by APR and MHF using the Newcastle-Ottawa Quality Assessment Scale (Wells et al. 2013), rating each study in Table S2 (see Supplementary Material Appendix 2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003cem\u003eFrom\u003c/em\u003e: Babineau, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e. Product Review: Covidence (Systematic Review Software)\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eA total of 1824 articles were recovered for screening, of which 803 duplicates were removed and 687 were excluded as they did not deal with BD, while 4 articles were included as a result of the Snowballing effect (Wohlin \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Subsequent to review of titles and abstracts, 687 records were discarded and the full manuscripts of 336 studies were examined in detail. Of the articles included, only 16 explored an association between biomarkers and cognition in different affective states, most of which demonstrated a correlation between the cognitive functions evaluated and the different alterations during the mood phases of the disorder.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eData extraction from studies describing the characteristics of the studies included correlating biomarkers to cognitive variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor/ year\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubject (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBiomarker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample size (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSex (m/f)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCognitive assessment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCriteria to establish mood state\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAssociation biomarker and cognition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMain Findings\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Idemoto et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (58)\u003c/p\u003e \u003cp\u003eBDE (58)\u003c/p\u003e \u003cp\u003eBDM (7)\u003c/p\u003e \u003cp\u003eBDX (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSerum GDNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 143\u003c/p\u003e \u003cp\u003eHC: 158\u003c/p\u003e \u003cp\u003eMDD: 166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 61/82\u003c/p\u003e \u003cp\u003eHC: 80/58\u003c/p\u003e \u003cp\u003eMDD: 80/78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePremorbid IQ with JART\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBDD: HAMD\u0026thinsp;\u0026ge;\u0026thinsp;8 and YMRS\u0026thinsp;\u0026le;\u0026thinsp;7\u003c/p\u003e \u003cp\u003eBDE: HAMD\u0026thinsp;\u0026le;\u0026thinsp;7 YMRS\u0026thinsp;\u0026le;\u0026thinsp;7\u003c/p\u003e \u003cp\u003eBDM: HAMD\u0026thinsp;\u0026le;\u0026thinsp;7 YMRS\u0026thinsp;\u0026ge;\u0026thinsp;8\u003c/p\u003e \u003cp\u003eBDX: HAMD\u0026thinsp;\u0026ge;\u0026thinsp;8 YMRS\u0026thinsp;\u0026ge;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo correlation between serum GDNF levels and cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSerum GDNF levels in BDD\u0026thinsp;\u0026lt;\u0026thinsp;HC\u003c/p\u003e \u003cp\u003eIQ\u0026thinsp;\u0026lt;\u0026thinsp;HC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Guidara et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (6)\u003c/p\u003e \u003cp\u003eBDM (27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTchol, triglycerides, HDL-C, hs-CRP, LDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 33\u003c/p\u003e \u003cp\u003eHC: 40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 33/0\u003c/p\u003e \u003cp\u003eHC: 40/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMoCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBDM moderate: MAS\u0026thinsp;\u0026le;\u0026thinsp;21\u003c/p\u003e \u003cp\u003eBD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo correlation between the biological markers and cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTchol\u0026thinsp;\u0026lt;\u0026thinsp;BDD\u003c/p\u003e \u003cp\u003e24-OHC\u0026thinsp;\u0026lt;\u0026thinsp;BDD\u003c/p\u003e \u003cp\u003eCRP\u0026thinsp;\u0026lt;\u0026thinsp;BM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Lai et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (30)\u003c/p\u003e \u003cp\u003eBDE (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 52\u003c/p\u003e \u003cp\u003eHC: 31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 26/26\u003c/p\u003e \u003cp\u003eHC: 15/16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTMT-B\u003c/p\u003e \u003cp\u003eWCST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBDD: HDRS\u0026thinsp;\u0026gt;\u0026thinsp;21 and YMRS\u0026thinsp;\u0026lt;\u0026thinsp;7\u003c/p\u003e \u003cp\u003eBDE: HDRS\u0026thinsp;\u0026lt;\u0026thinsp;8 and YMRS\u0026thinsp;\u0026lt;\u0026thinsp;7 at least 6 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNAA/Cr ratio in left basal ganglia in the acute-episode was correlated with WCST and TMT-B uptake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWorse cognitive performance in BD group and\u003c/p\u003e \u003cp\u003eNAA/Cr ratio in bilateral lenticular nucleus\u0026thinsp;\u0026lt;\u0026thinsp;HC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Nishimura et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2015\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (16)\u003c/p\u003e \u003cp\u003eBDH (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNIRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 27\u003c/p\u003e \u003cp\u003eHC: 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 18/9\u003c/p\u003e \u003cp\u003eHC:4/8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIQ\u003c/p\u003e \u003cp\u003eVFT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eThe cutoff point for the YMRS was 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCorrelation between left DLPFC function and hypomanic symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026darr; DLPFC left (CH49) in BDD\u0026thinsp;\u0026lt;\u0026thinsp;BDM/HC\u003c/p\u003e \u003cp\u003e\u0026darr; VLPFC left in BD groups\u0026thinsp;\u0026lt;\u0026thinsp;HC\u003c/p\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eLongitudinal\u003c/span\u003e:\u003c/p\u003e \u003cp\u003eLeft DLPFC/temporal regions/ FPC (symptoms were present) \u0026gt; (were absent symptoms)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. Pomarol- Clotet et al., 2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (38)\u003c/p\u003e \u003cp\u003eBDE (38)\u003c/p\u003e \u003cp\u003eBDM (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003efMRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD:114\u003c/p\u003e \u003cp\u003eHC: 38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 52/62\u003c/p\u003e \u003cp\u003eHC: 18/20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en-back\u003c/p\u003e \u003cp\u003eWAIS-II\u003c/p\u003e \u003cp\u003eTAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBDD: HDRS\u0026thinsp;\u0026ge;\u0026thinsp;15\u003c/p\u003e \u003cp\u003eBDE: HDRS\u0026thinsp;\u0026le;\u0026thinsp;8 and YMRS\u0026thinsp;\u0026le;\u0026thinsp;6 at least 3 months\u003c/p\u003e \u003cp\u003eBDM: YMRS\u0026nbsp;\u0026ge; 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReduced activation in the dorsal parietal cortex in both mania and depression during cognitive task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026darr; Dorsal parietal cortesx in BDD and BDM\u0026thinsp;\u0026lt;\u0026thinsp;BDE\u003c/p\u003e \u003cp\u003e\u0026darr; DLPFC in BDM\u0026thinsp;\u0026lt;\u0026thinsp;BDE\u003c/p\u003e \u003cp\u003eFailure of de-activation in the medial frontal cortex\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6. Rive et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2016\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (9)\u003c/p\u003e \u003cp\u003eBDE (23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003efMRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 32\u003c/p\u003e \u003cp\u003eHC: 35\u003c/p\u003e \u003cp\u003eMDD: 40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 13/19\u003c/p\u003e \u003cp\u003eHC: 10/25\u003c/p\u003e \u003cp\u003eMDD: 12/28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIQ\u003c/p\u003e \u003cp\u003eToL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTask was associated with activity in parieto-temporal and lateral/medial frontal regions, in precuneus, insula, caudate nucleus and pallidum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026uarr; DLPFC in BDD\u0026thinsp;\u0026gt;\u0026thinsp;BDE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7. Estudillo-Guerra et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDE (6)\u003c/p\u003e \u003cp\u003eBDM(10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSPECT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 10\u003c/p\u003e \u003cp\u003eHC: 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 2/8\u003c/p\u003e \u003cp\u003eHC: N/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSCIP-S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBDE: MADRS\u0026thinsp;\u0026lt;\u0026thinsp;6 and YMRS\u0026thinsp;\u0026lt;\u0026thinsp;2\u003c/p\u003e \u003cp\u003eBDM: MADRS\u0026thinsp;\u0026lt;\u0026thinsp;19 and YMRS\u0026thinsp;\u0026gt;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eManic\u003c/span\u003e: positive correlation SCIP-S score and brain perfusion in the right TP. Negative correlation with right OFC and right sACC.\u003c/p\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eFollow-up\u003c/span\u003e:\u003c/p\u003e \u003cp\u003eBrain perfusion was not correlated with SCIP-S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026uarr; Left DLFPC and left FPC in BDM\u0026thinsp;\u0026gt;\u0026thinsp;BDE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8. Alonso-Lana et al, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDE (26)\u003c/p\u003e \u003cp\u003eBDM (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003efMRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 26\u003c/p\u003e \u003cp\u003eHC: 26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 15/11\u003c/p\u003e \u003cp\u003eHC: 15/11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en-back\u003c/p\u003e \u003cp\u003eTAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBDE: YMRS and HDRS\u0026thinsp;\u0026le;\u0026thinsp;8\u003c/p\u003e \u003cp\u003eBDM: YMRS\u0026thinsp;\u0026ge;\u0026thinsp;15 at least 2 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRecovery from mania is associated with increase in activation in the left DLPFC/precentral cortex and the bilateral parietal cortex during n-back task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1-back and 2-back in BDM\u0026thinsp;\u0026lt;\u0026thinsp;BE\u003c/p\u003e \u003cp\u003eFailure de-activation vmPFC in BD\u0026thinsp;\u0026lt;\u0026thinsp;HC\u003c/p\u003e \u003cp\u003e\u0026darr; Left DLPFC, PFC superior PaC in BDM\u0026thinsp;\u0026lt;\u0026thinsp;HC/BDE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9. Magioncalda et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2016\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (20)\u003c/p\u003e \u003cp\u003eBDE (20)\u003c/p\u003e \u003cp\u003eBDM (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 61\u003c/p\u003e \u003cp\u003eHC: 42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 18/43\u003c/p\u003e \u003cp\u003eHC: 15/27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCPT\u003c/p\u003e \u003cp\u003eVerbal Fluency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBDD and BDM: HAM-D 17\u0026thinsp;\u0026ge;\u0026thinsp;18 and/or YMRS\u0026thinsp;\u0026ge;\u0026thinsp;13\u003c/p\u003e \u003cp\u003eBDE: HAM-D\u0026thinsp;\u0026lt;\u0026thinsp;8 and YMRS\u0026thinsp;\u0026lt;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eWM alterations were associated with cognitive deficits. CPT total hits correlate with the mean FA and with the mean MD and RD values. Fluency prompted by letter showed a correlation with the mean FA, MD and RD values\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWorse performance in CPT and Fluency in BDD and BDM\u0026thinsp;\u0026lt;\u0026thinsp;HC\u003c/p\u003e \u003cp\u003e\u0026darr; FA in BDD and BDM\u0026thinsp;\u0026lt;\u0026thinsp;HC\u003c/p\u003e \u003cp\u003e\u0026uarr; MD, RD in BDD\u0026thinsp;\u0026gt;\u0026thinsp;HC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10. Magioncalda et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (11)\u003c/p\u003e \u003cp\u003eBDE (11)\u003c/p\u003e \u003cp\u003eBDM (11)\u003c/p\u003e \u003cp\u003eBDX (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003efMRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 40\u003c/p\u003e \u003cp\u003eHC: 42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 18/43\u003c/p\u003e \u003cp\u003eHC: 15/27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCPT\u003c/p\u003e \u003cp\u003eVerbal Fluency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBDD, BDM and BDX: HAM-D 17\u0026thinsp;\u0026ge;\u0026thinsp;18 and/or YMRS\u0026thinsp;\u0026ge;\u0026thinsp;13\u003c/p\u003e \u003cp\u003eBDE: HAM-D\u0026thinsp;\u0026lt;\u0026thinsp;8 and YMRS\u0026thinsp;\u0026lt;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFluency letter showed correlation with PACC-SACC FCo\u003c/p\u003e \u003cp\u003eCPT associated with PACC-OFC L FCo and with PACC‐TPJ L FC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWorse cognitive performance in BD group\u003c/p\u003e \u003cp\u003e\u0026darr; FCo in Slow-5 from PACC in BD\u0026thinsp;\u0026lt;\u0026thinsp;HC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11. Velasques et al, \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2013\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (10)\u003c/p\u003e \u003cp\u003eBDM (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEEG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 20\u003c/p\u003e \u003cp\u003eHC: 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 14/6\u003c/p\u003e \u003cp\u003eHC: 3/9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSaccadic attention task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003cp\u003eClinical Global Impression-Bipolar Version (CGI-BP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDuring a saccadic attention task, gamma coherence varies according to the group and the area of the cortex observed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026darr; Saccade latency in BDM\u0026thinsp;\u0026lt;\u0026thinsp;BDD and HC\u003c/p\u003e \u003cp\u003e\u0026darr; Frontal eye field Fz/F4 in BDM\u0026thinsp;\u0026lt;\u0026thinsp;BDD and HC\u003c/p\u003e \u003cp\u003e\u0026uarr; FCr gamma coherence Fz/F8 in BDD\u0026thinsp;\u0026gt;\u0026thinsp;HC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12. Martino et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (20)\u003c/p\u003e \u003cp\u003eBDE (20)\u003c/p\u003e \u003cp\u003eBDM (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRs-fMRI\u003c/p\u003e \u003cp\u003eDTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 61\u003c/p\u003e \u003cp\u003eHC: 42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: N/A\u003c/p\u003e \u003cp\u003eHC: N/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBDD and BDM: HAMD\u0026thinsp;\u0026ge;\u0026thinsp;18 and/or score YMRS\u0026thinsp;\u0026ge;\u0026thinsp;13 HAM-D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCognitive scores correlated with the measures of cingulum SC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eBDD and BDM more omissions errors in CPT\u003c/p\u003e \u003cp\u003e\u0026darr; PACC-PCC functional connectivity in BDM\u0026thinsp;\u0026lt;\u0026thinsp;BDD and HC\u003c/p\u003e \u003cp\u003e\u0026darr; FA in BDM\u0026thinsp;\u0026lt;\u0026thinsp;BDE\u003c/p\u003e \u003cp\u003e\u0026darr; SC of the cingulum in BDM\u0026thinsp;\u0026lt;\u0026thinsp;HC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13. Mikawa et al, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2015\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (30)\u003c/p\u003e \u003cp\u003eBDE (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNIRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 47\u003c/p\u003e \u003cp\u003eHC: 28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 20/27\u003c/p\u003e \u003cp\u003eHC: 11/17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVFT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBDD: HAM-D\u0026thinsp;\u0026gt;\u0026thinsp;7 and YMRS\u0026thinsp;\u0026lt;\u0026thinsp;10\u003c/p\u003e \u003cp\u003eBDE: HAM-D\u0026thinsp;\u0026le;\u0026thinsp;7 and YMRS\u0026thinsp;\u0026lt;\u0026thinsp;10 at least 2 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNegative correlations between the increase in mean oxy-Hb levels induced by the VFT in the left temporal regions (channels 51\u0026ndash;52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026uarr; Left temporal regions in BDE\u0026thinsp;\u0026gt;\u0026thinsp;BDD\u003c/p\u003e \u003cp\u003e\u0026darr; Left temporal regions in BDE\u0026thinsp;\u0026lt;\u0026thinsp;HC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14. Yang et al., \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2020\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (32)\u003c/p\u003e \u003cp\u003eBDE (25)\u003c/p\u003e \u003cp\u003eBDM (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 72\u003c/p\u003e \u003cp\u003eHC: 71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 32/40\u003c/p\u003e \u003cp\u003eHC: 33/38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en-back\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBDD: HAMD\u0026thinsp;\u0026ge;\u0026thinsp;17 and YMRS\u0026thinsp;\u0026lt;\u0026thinsp;12\u003c/p\u003e \u003cp\u003eBDE: HAMD score\u0026thinsp;\u0026lt;\u0026thinsp;17 and YMRS\u0026thinsp;\u0026lt;\u0026thinsp;12\u003c/p\u003e \u003cp\u003eBDM: HAMD\u0026thinsp;\u0026lt;\u0026thinsp;17 and YMRS\u0026thinsp;\u0026ge;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIncrease in small-worldness was associated with decreased working memory accuracy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWorse working menory in BDD and BDM\u003c/p\u003e \u003cp\u003e\u0026darr; sigma and gamma in BDM\u0026thinsp;\u0026lt;\u0026thinsp;BDD\u003c/p\u003e \u003cp\u003e\u0026darr; Cingulo-opercular network in BDM and BDE\u0026thinsp;\u0026lt;\u0026thinsp;BDD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15. Gao et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDE (28)\u003c/p\u003e \u003cp\u003eBDM (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRf-fMRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 66\u003c/p\u003e \u003cp\u003eHC: 60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 36/30\u003c/p\u003e \u003cp\u003eHC: 38/22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePDQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo correlation was found\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026darr; right IPL in BDM\u0026thinsp;\u0026lt;\u0026thinsp;BDD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16. Kopf et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBDD (32)\u003c/p\u003e \u003cp\u003eBDE (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003efNIRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBD: 32\u003c/p\u003e \u003cp\u003eHC: 31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD: 29/22\u003c/p\u003e \u003cp\u003eHC: 10/20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en-back\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRight DLPFC activation during n-back task\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo difference in DLPFC and vlPFC activation between BDD and BDE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e\u0026uarr;, increased; \u0026darr;, decreased; \u0026gt;, higher; \u0026lt;, lower; N/A, not applicable; HAMD, Hamilton Depression Rating Scale; HDRS, Hamilton Depression Scale; MAS, Bech and Rafaelsen Mania Scale; YMRS, Young Mania Rating Scale; MADRS, Montgomery-Asberg Depression Rating Scale; BDM, bipolar mania; BDD, bipolar depression; BDE, bipolar euthymic; BDH, bipolar hypomania; BDX, bipolar mixed state; MDD, major depressive disorder; HC, healthy control; FCr, right frontal cortex; PaC, Parietal cortex; PCr, parietal cortex right; DLPFC, dorsolateral prefrontal cortex; OFC, orbitofrontal cortex; SACC, supragenual anterior cingulate cortex; TPJ L, temporal parietal junction left; TP, temporal polar cortex; IPL, inferior parietal lobe; PACC, perigenual anterior cingulate cortex; PCC, posterior cingulate cortex; vlPFC, ventrolateral prefrontal cortex; MD, mean diffusivity; RD, radial diffusivity; FA, DTI-derived fractional anisotropy; FCo, functional connectivity; SPECT, brain perfusion single-photon emission computed tomography; SC, structural connectivity; WM, White matter; NAA/Cr, N-acetylaspartate/creatine; GDNF, Glial cell line-derived neurotrophic factor; Tchol, Total cholesterol; HDL-C, high-density lipoprotein cholesterol; hs-CRP, high sensitivity C reactive protein; LDL-C, low-density lipoprotein-cholesterol; OCH-24/27, cholesterol 24/27 hydroxycholesterol; oxy-Hb, Relative concentration changes of oxygenated; deoxy-Hb, concentration changes of deoxygenated; rs-fMRI, resting-state functional magnetic resonance imaging; MRI, Magnetic Resonance Imaging; NIRS, near infrared spectroscopy; fNIRS, functional near-infrared spectroscopy; EEG, electroencephalography; DTI, probabilistic tractographic diffusion tensor imaging; MoCA, Montreal Cognitive Assessment; TAP, Word Accentuation Test; VFT, Verbal Fluency Test; WAIS, Wechsler Adult Intelligence Scale; IQ, intelligence quotient; JART, Japanese Adult Reading Test; CPT, Continuous performance test; SCIP-S, Screen for Cognitive Impairment in Psychiatry Scale; ToL, Tower of London; WCST, Wisconsin card sorting test; TMT-B, Trail making test part B; PDQ, Perceived Deficits Questionnaire.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Cognitive and biomarkers findings across affective state\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eStudies included markers from serum or plasma and neuroimaging. The studies were grouped into the following cognitive domains according to the tasks used or the fMRI paradigms used: \"attention\", \"executive functions\", \"memory (working memory and verbal memory)\", \"IQ\" \u0026ldquo;Self-reported cognitive\u0026rdquo; and \"Cognitive Screening Test \".\u003c/p\u003e \u003cp\u003eFourteen studies used a combination of neuroimaging and neurocognitive assessments to investigate the affective states in BD (Alonso-Lana et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Estudillo-Guerra et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Gao et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kopf et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lai et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Magioncalda et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Magioncalda et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Martino et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Mikawa et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Nishimura et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Pomarol-Clotet et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Rive et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Velasques et al. \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). We find different neuroimaging modalities (e.g., structural magnetic resonance imaging (MRI), fMRI, diffusion tensor imaging, resting-state, brain perfusion, proton magnetic resonance spectroscopy). Two studies used peripheral markers (Guidara et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Idemoto et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFour studies used a longitudinal design (Alonso-Lana et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Estudillo-Guerra et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kopf et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Nishimura et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and twelve were cross-sectional studies (Gao et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Guidara et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Idemoto et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Lai et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Magioncalda et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Magioncalda et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Martino et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Mikawa et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Pomarol-Clotet et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Rive et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Velasques et al. \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eAttention\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFour studies carry out a neurocognitive evaluation of attention (Magioncalda et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Magioncalda et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Martino et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Velasques et al. \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThree of them evaluate sustained attention with the continuous performance test (CPT; Magiocalda et al. 2016; Martino et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), where we find that BD patients showed lower number of total hits and higher number of total omission errors.\u003c/p\u003e \u003cp\u003eOn the one hand, BDM patients showed that structural changes in the cingulum were related to the deficits found at the attentional level. Furthermore, it was found that the perigenual anterior cingulate cortex (PACC) and posterior cingulate cortex (PCC) functional connectivity was decreased in manic patients when compared to both HCs and BDD patients and the SC of the cingulum, especially its anterior part, was decreased in manic patients when compared to HC (Martino et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen microstructural abnormalities in the white matter (WM) were investigated, subgroups of BD patients showed different spatial patterns of WM alterations (Magioncalda et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The BDE patients had minor and localized WM alterations in the midline structures, whereas the WM alterations were more diffuse in the BDM patients, affecting both midline and lateral structures, and there were stronger and more widespread WM alterations in BDD patients. In addition, these WM alterations were associated with attention deficits. Similarly, in another study these authors found differences in functional connectivity from the PACC to other regions in the posterior default mode network (DMN) between patients in manic or depressed episode and HCs, but no differences between the BD patient subgroups (Magioncalda et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Velasques et al. (\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), BDM patients showed lower saccade latency than BDD patients or the HCs. In a prosaccadic attention task the BDM patients showed stronger gamma coherence in the frontal cortex than in the other groups (BDD and HCs).\u003c/p\u003e \u003cp\u003e \u003cb\u003eProcessing speed\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOnly one study evaluates processing speed (Estudillo-Guerra et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Six months after an acute episode of mania, patients in euthymic state do not show differences in this cognitive sphere. At follow-up, a decrease in perfusion was observed in the right middle temporal gyrus (MTG) and the right superior temporal gyrus (STG).\u003c/p\u003e \u003cp\u003e \u003cb\u003eExecutive functions\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSeven studies explored EFs (Estudillo-Guerra et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lai et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Magioncalda et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Magioncalda et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Mikawa et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Nishimura et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Rive et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Three of them found no differences in performance between the groups (BD in different states and HCs) in the cognitive task (Mikawa et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Nishimura et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Rive et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEstudillo-Guerra et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e explored cognitive deficits in acute BDM patients and their subsequent evaluation after 6 months (euthymic state). This study evaluates cognitive functions using the Spanish version of the Screen for Cognitive Impairment in Psychiatry Scale (SCIP-S). A subtest contains the Verbal Fluency Test (VFT) to evaluate executive functions. A negative correlation between Brodmann area (BA) 25 and positive with BA 38 and 21 was found during a manic episode. At follow up Cognitive impairment in VFT correlated with changes increased perfusion in the bilateral Anterior cingulate cortex (ACC). Fluency prompted by letter showed a correlation with PACC-SACC (Magioncalda et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBy contrast, in another study, there was increased activation in the dorsolateral prefrontal cortex (DLPFC) of BDD patients, and in the parietal cortex (PC) compared to the BDE patients (Rive et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, hypoactivation of the left DLPFC and of the left ventrolateral prefrontal cortex (VLPFC) during a verbal fluency task was found in patients with hypomanic symptoms, while this activation was less prominent in the DLPFC of BDD patients (Nishimura et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In addition, this study followed hypomanic patients who showed significantly greater concentration changes of oxygenated hemoglobin (oxy-Hb) in the left DLPFC and frontopolar prefrontal cortex (FPPFC) when experiencing hypomanic symptoms compared to when they were absent (8 patients). Similarly, the oxy-Hb levels induced by executive tasks were significantly lower in BDD than BDE patients (Mikawa et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Finally, another study failed to find differences between the BD groups (Lai et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), showing a decrease in the N-acetylaspartate to creatine ratio (NAA/Cr) in the bilateral basal ganglia compared to the HCs. Nevertheless, the decrease in NAA/Cr ratios was negatively correlated with total errors and TMT-B uptake, but there was no correlation between the NAA/Cr and Cho/Cr in the right basal ganglia and the scores of WCST and TMT-B in acute-episode BD patients.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMemory\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eWorking memory\u003c/em\u003e \u003c/p\u003e \u003cp\u003eRegarding working memory, four studies used an n-back paradigm (Alonso-Lana et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kopf et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Pomarol-Clotet et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and one used the SCIP-S subtest (Estudillo-Guerra et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). We found worse performance in the manic or depressed state compared to HC and BDE patients.\u003c/p\u003e \u003cp\u003eIn a first study, the BDM group obtained worse results in the two versions of the task compared to the BDD patients and HC individuals (Pomarol-Clotet et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, when the cognitive load was increased (2-back version), the BDD patients also differed from the HCs. Surprisingly, the BDE patients did not differ from the HCs. There was reduced activation in the left and right dorsal PC and precuneus in BDM patients, and failure to de-activate the medial frontal cortex was evident in all BD groups.\u003c/p\u003e \u003cp\u003eIn a longitudinal study, patients were assessed during a manic episode and later, in a state of euthymia after about 12 months (Alonso-Lana et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Similar to previous findings, BDM patients performed worse than HCs and BDE patients. Activation during the cognitive task showed weaker activation in the left DLPFC, PC, and bilateral superior precuneus in BDM patients, while the BDE group continued to exhibit failure in vmPFC deactivation. During the working memory test of SCIP-S, manic episodes were associated with limited perfusion in the right OFC, whereas no significant differences were observed during euthymia (Estudillo-Guerra et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinally, functional neuroimaging data was used to provide an intuitive method to study fMRI-inferred neural efficiency in the whole brain, allowing interindividual differences related to the task to be predicted (connectome; Yang et al. \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). An overall increase of the functional connectome was detected and there was a more homogeneous distribution in BDD patients. Interestingly, the maladaptive modulation of the functional connectome was associated with worse performance in working memory.\u003c/p\u003e \u003cp\u003e \u003cem\u003eVerbal memory\u003c/em\u003e \u003c/p\u003e \u003cp\u003e Only one study assessed verbal memory (Estudillo-Guerra et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), with immediate verbal learning correlated to the temporal polar cortex. No significant correlation of manic episodes with delayed verbal learning was detected, although a significant correlation was seen in euthymic states.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIntellectual Quotient (IQ)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eConcerning the IQ, HCs had a higher mean current IQ than the BDD and BDM patients but not the BDE patients (Pomarol-Clotet et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen the relationship between neurotrophic factors and cognition was studied in different mood phases of BD (Idemoto et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), no differences in plasma GDNF levels were evident between the affective states. Furthermore, no correlation was performed to see if there was an association between IQ and serum GDNF levels. However, after controlling for factors such as sex, age, BMI, estimated IQ, and diagnosis, serum GDNF levels in TB patients were lower in remission and depression states than control subjects (this did not occur in patients in a manic or mixed state).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCognitive Screening Test\u003c/b\u003e \u003c/p\u003e \u003cp\u003eDifferences in the levels of oxysterols and CRP were analyzed in the distinct groups of bipolar patients, with lower cholesterol levels (Tchol, 24-OCH) reported in BDM patients relative to BDD patients and in patients with severe manic episode compared to those with moderate manic episode for 24-OCH levels (Guidara et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). By contrast, CRP levels were higher in BDM patients and in patients with severe manic episode compared to those with moderate manic episode. No correlations with the cognitive scale (MoCA) were found.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSelf-reported cognitive\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA study utilizes a self-report measure to assess cognitive dysfunction with the Perceived Deficits Questionnaire (PDQ) (Gao et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Despite finding differences in activation between patients in acute state and their remission state in the follow-up (BDM patients showed reduced network homogeneity compared to BDE), no association with cognition was found.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis systematic review represents an effort to synthesize the reliable evidence available on the associations between biomarkers and cognition in different phases of BD. When we look at these associations, we found a total of 14 articles that have addressed this issue.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAcute mood episodes\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eNeuroimaging biomarker\u003c/em\u003e \u003c/p\u003e \u003cp\u003eNeuroimaging research has highlighted the importance of modular and hierarchical brain networks for the functional integration of neural operations related to cognitive function (Park and Friston, 2015). Cognitive control and executive functions are associated with activity in the prefrontal cortex (PFC; Menon and D\u0026rsquo;Esposito 2022). Activation of the DLPFC, superior frontal gyrus, superior parietal lobule and precuneus are common neural correlates of working memory, EFs and attention (Friedman and Robbins, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Saldarini et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Data from the \u003cem\u003en\u003c/em\u003e-back paradigm and neuroimaging studies suggest that there is a mood-state dependent hypoactivation in DLPFC and PC. In the included studies, during states of mania or depression there appears to be hypoactivation in the prefrontal and parietal cortex within the framework of a task that requires executive functions or working memory (Bi et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Brooks et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Fleck et al. 2010; Penfold et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Rodr\u0026iacute;guez-Cano et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Takizawa et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Although we found this hypoactivation also in the euthymic group (Saldarini et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), there could be less activation in frontal regions during the acute states of BD (Schumer et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In fact, we found that moving from mania to euthymia was associated with an increase in activation in these areas (Estudillo-Guerra et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Strakowski et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Interestingly, Peterson and colleagues (2021), found this hypoactivation in patients with poor cognitive performance, but after covarying for subsyndromal mood symptoms, it does not remain in DLPFC cluster in cognitively normal patients, which would imply that brain activity in the DLPFC region would be associated with cognitive performance, independently of sub-syndromic mood symptoms.\u003c/p\u003e \u003cp\u003eHowever, a resting-state study observed reduced network homogeneity in the right inferior parietal lobe in patients with BDM compared to BDE (Gao et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). While this may serve as a potential biomarker for predicting mania remission status according to the authors, no correlations with cognitive tasks were found. This could be attributed to the nature of the task, as this region has been associated with language, social cognition, and other functions (Numssen et al. 2021).\u003c/p\u003e \u003cp\u003eWM abnormalities have also been seen during all affective states of bipolar disorder (Hu et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), being more prevalent in active phases of the disease. Thus, it seems that an acute mood state may be associated with acute state-dependent microstructural WM changes (Zanneti et al., 2009). BDD patients have the largest overall cluster size of WM alterations relative to BDE or BDM patients. Although no association between fractional anisotropy (FA) and antidepressants was evident in a meta-analysis (Favre et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), this could explain the difference between the alterations in the acute state, as other studies have found an association with treatment (de Diego-Adeli\u0026ntilde;o et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Nevertheless, longitudinal studies would be better suited to identify and predict the effect of age, illness duration/severity and medication on WM microstructure in patients with BD (Favre et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDifferent studies report conflicting results for the NAA/Cr ratio. Both an increase (Zhong et al. \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) or a decrease in the NAA/Cr ratio was detected in the bilateral lenticular nucleus of BDD and BDM patients relative to the HCs (Frye et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). However, a correlation was found between the NAA/Cr ratio in the left BG in acute-episode BD patients and those with better EFs (Zhong et al. \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Similarly, other patterns of impaired functional connectivity have been proposed within dorsal attention networks that could differentiate mood states in BD, such as weaker connectivity in BDE patients and hyper-connectivity in BDM patients (Brady et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Cerullo et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). A study using VFT found that BDD patients had weaker activation in both the right and left PFC than controls (Fu et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In addition, patients show weaker activation for a second cognitive task (Tower of London test) in the bilateral DLPFC (Fu et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), although an increase in activity was described in the frontostriatal areas (Rive et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In this regard, an increase in the small world (functional connectome) was described in BDD patients, associated with worse performance in working memory (Yang et al. \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These results might reflect a compensatory effect to control excessive rumination in the DMN (Claeys et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) or compensatory activity required by patients in a more severe state of BD, as observed in other disorders (Xing et al. 2017).\u003c/p\u003e \u003cp\u003eNeuropsychological data support the differences found between patients in an acute state, who present worse cognitive performance (Ryan et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Therefore, verbal memory, attention and EF seem to be affected in manic states (Bourne et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Kurtz and Gerraty, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Vrabie et al. \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and these deficits correlate with brain alterations (Benabarre et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Pattanayak et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Yamada et al. \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In contrast, deficits in working memory processing have also been consistently reported in euthymic patients (Thompson et al. \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Daglas et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and no main effect of mood is found (Manelis et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, differences have been seen in EFs and working memory in mania (Volkert et al. \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), however finding differences between mania and euthymia may be due to a higher number of past manic episodes that were associated with poorer cognitive performance (Martinez-Ar\u0026aacute;n et al. 2004) or the history of psychosis (Allen et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Simonsen et al. \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), which we have tried to consider in this review.\u003c/p\u003e \u003cp\u003e \u003cem\u003ePeripheral biomarkers\u003c/em\u003e \u003c/p\u003e \u003cp\u003eRegarding peripheral biomarkers, we see that lower cholesterol levels (Fusar-Poli et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) were reported in BDM patients relative to BDD patients, as well as higher CRP levels (Ekinci and Ekinci; Tsai et al. \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, other studies failed to find differences between the depressive and manic state (Sundaresh et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Some studies have pointed towards an inflammatory component in BD, and it was suggested that elevated CRP levels might rather be a state than a marker in this condition (Evers et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Fernandes et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Although we found no correlations between cognitive variables and markers of inflammation here, serum CRP expression was negatively correlated with performance scores of immediate memory, language and attention in BD patients when the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was used (Bauer et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinally, only two studies assessed cognition and performed a search for biomarkers in the mixed state (Idemoto et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mangiocalda et al. 2015). The serum GDNF levels in BD patients in a mixed state showed no significant difference from those in HCs. Although altered levels of GDNF were only found in BDD patients, an increase in serum GDNF relative to the activity of the immune system occurred in BDM and BDD patients (Tunca et al., \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and there was no difference between BDE patients and HCs (Rosa et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Moreover, the estimated IQ values, verbal memory and EFs of the BD mixed group were significantly lower than those of HCs (Vreeker et al. \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). We have seen that GDNF levels in BDD patients decrease relative to those of the HCs (Takebayashi et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), whereas those levels in BD patients in a mixed or manic state were comparable to those of the HCs. Conversely, GDNF plasma levels were higher in BDE patients relative to BDM patients and HCs (Barbosa et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Similarly, serum GDNF increases in bipolar patients during acute manic and depressive episodes (Rosa et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). There is no clear relationship between GDNF and mood states, although GDNF mRNA expression may be increased by antidepressants or lithium (De-Paula et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; de Sousa et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). An association between peripheral levels of GDNF and cognitive function was found in patients with major depressive disorder (MDD; Liu et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), which could suggest that GDNF is a biomarker for both BD and MDD in depressive states (Zinchuk et al. \u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eEuthymic/remission states\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eNeuroimaging biomarker\u003c/em\u003e \u003c/p\u003e \u003cp\u003eA meta-analysis consistently found trait-related deficits in EFs and verbal memory in patients with BD (Bourne et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Executive dysfunction was also evident in BDE patients in our systematic review and hence, EFs deficits in BD may persist across different mood states, both in acute episodes and the euthymic state (Bourne et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Rosa et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Volkert et al. \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, we found here studies where the performance of euthymic patients is comparable to that of HCs, which could be due to the subtype of BD type I or II (Dittmann et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) or to cognitive heterogeneity within the sample. This highlights the need to differentiate subgroups by cognitive performance (Burdick et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn neuroimaging studies, de-activation failure has been reported in the vmPFC in BDD and BDM patients, persisting in remission (Fern\u0026aacute;ndez-Corcuera et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Tian et al. \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Verdolini et al. \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This de-activation failure finding unique to BD may be core to the illness and akin to a trait mechanism not impacted by mood states.\u003c/p\u003e \u003cp\u003eIn euthymic state there seems to be parietal hypoactivation (Hajek et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and normalization of DLPFC activation, which is mainly altered during manic episodes (Van der Schot et al. \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Hypoactivation of the PFC in verbal fluency tasks has also been found (Yoshimura et al. \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Moreover, during the euthymic state the NAA/Cr ratio in the bilateral lenticular nucleus was lower than in HCs (Kraguljac et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), although they did not exhibit changes in the NAA/Cr ratio in the temporal or parietal cortex (Brambilla et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Regarding working memory, there are deficiencies in the manic or depressed state but not in euthymia. Indeed, most fMRI studies using an \u003cem\u003en\u003c/em\u003e-back paradigm suggested there were no significant differences in accuracy or reaction times between BDE patients and HCs (Cremaschi et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, elsewhere such deficits seem to persist during disease remission (Oh et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Srivastava et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Volkert et al. \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding differences in cognitive performance, it is observed that BDE patients also achieve lower performance than controls, and these differences seem to increase with task complexity (Volkert et al., \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Furthermore, despite dysfunction in brain circuits related to working memory in patients with BD, other intact systems may help overcome this deficiency (Cremaschi et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003ePeripheral biomarkers\u003c/em\u003e \u003c/p\u003e \u003cp\u003eUnlike what was found in the study included here, where the differences GDNF levels for patients in the euthymic state were only found after correction (Rosa et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), Barbosa et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) found higher GDNF levels in BDE compared to BDM patients. Other studies do not find differences in GDNF levels between euthymia and HCs (Tunca et al. \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe inconsistency of results could be due to type II error, and larger sample sized studies are needed. With growing evidence that inflammation contributes to cognitive impairment in several medical conditions, it is crucial to investigate this aspect in bipolar disorder. However, until now, the relationship between inflammatory markers and affective symptoms is not completely (Strawbridge et al. \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eOur findings highlight core regions involved in BD that are not only mood-specific, but also observed across mood states. Although individuals are clinically in remission, they still show abnormalities in brain connectivity, but a state-dependent topology appears to exist in BD and there appear to be underlying mechanisms of cognitive dysfunction that may be different in the different mood states of bipolar disorder.\u003c/p\u003e \u003cp\u003eConsequently, this systematic review highlights the need for greater consistency in the use of staging models in BD research to standardize the results and identify biomarkers. Monitoring patients and verifying the most significant biomarkers could prevent the onset of acute episodes, and the functional and cognitive deterioration this entails. Similarly, it could allow a more precise differential diagnosis and improve the patient\u0026rsquo;s quality of life. As such, it is important to create a framework incorporating genetics, neuroimaging and cognitive sciences in order to refine the classification of mental disorders where the cognitive system is one of the potential higher order domains (Cuthbert \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). A multidimensional approach combining peripheral and neuroimaging biomarkers may provide a more comprehensive understanding of cognitive endophenotypes across affective states in bipolar disorder.\u003c/p\u003e \u003cp\u003eThe results obtained in this review demonstrate the importance of considering BD with its different characteristics and shows the need for further longitudinal studies, as there are insufficient studies on hypo/mania, mixed states and clinical comparisons. Examining individuals in different affective states is crucial to identify mechanisms dependent on traits or the current state of symptoms (state), allowing the study of disease mechanisms to develop improved methods of diagnosis and treatment.\u003c/p\u003e"},{"header":"6. Limitations","content":"\u003cp\u003eThis systematic review has several limitations. Firstly, the sample of patients that we found in most studies is small and this may be due to the difficulty of evaluating these patients in acute states.\u003c/p\u003e \u003cp\u003eDue to the heterogeneity in BD, we sought to be rigorous with the inclusion and exclusion criteria. For instance, as the impact of psychotic symptoms on cognition remains unclear, we excluded studies indicating patients had psychosis symptoms or if a history of psychosis was not included as a covariate. Conversely, most of the included studies do not seem to control this factor, potentially confounding the results.\u003c/p\u003e \u003cp\u003eMethodological heterogeneity within and between studies is an important limitation of the articles included in this review, as different modalities are used in neuroimaging studies.\u003c/p\u003e \u003cp\u003eThe absence of consensus for defining euthymia and the definition of clinically significant impairment also imposes difficulties in both clinical practice and research. Although the duration of clinical remission has been associated with a significant improvement of residual symptoms, in this review, the range of duration to establish a euthymic state is from 2 to 6 months.\u003c/p\u003e \u003cp\u003eThe effects of medication or comorbidities are another factor to consider in the search for biomarkers and in neuropsychological assessments. An important limitation is also the cross-sectional nature of the studies available, along with the small samples. Furthermore, the longitudinal studies analyzed here experience significant loss of patients to follow-up, complicating interpretation.\u003c/p\u003e"},{"header":"7. Future directions","content":"\u003cp\u003eThe following systematic review could serve to create interventions that combine cognitive rehabilitation with biological treatments. It would be interesting to consider subsyndromal conditions and the presence of residual mood symptoms, since they could have a negative impact on certain cognitive spheres and the cognitive deficit in the euthymic state could change after controlling for these factors (Tsitsipa et al., 2015). More powerful longitudinal studies that follow patients across mood cycles will be crucial to clarify the relationship between neurocognitive impairment and mood. Additionally, neuroimaging studies reveal problem areas such as DLPFC in patients with mental disorders. To improve cognition, we could use non-drug techniques such as transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS) targeting those target areas (Hyde et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThird, research is underway on how patients with bipolar disorder who have experienced psychosis and those who have not differ in their neurocognitive functioning (Glahn et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). It is important to clearly define different mood states in studies of bipolar disorder.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBipolar disorder\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBDE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epatients with bipolar disorder in a euthymic state\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBDD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epatients with bipolar disorder in a depressed state\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBDM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epatients with bipolar disorder in a manic state\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealthy subjects\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEFs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExecutive functions\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIL-6\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterleukin-6\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNRF1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTumor Necrosis Factor Receptor 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBDNF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBrain-derived neuorotrophic factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWhite matter\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePACC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePerigenual Anterior Cingulate Cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePosterior Cingulate Cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCPT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eContinuous Performance Test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMean Diffusivity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRadial Diffusivity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFractional Anisotropy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003efMRI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFunctional Magnetic Resonance Imaging\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDMN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDefault Mode Network\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDLPFC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDorsolateral Prefrontal Cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFPPFC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFrontopolar Prefrontal Cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eParietal Cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVLPFC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVentrolateral Prefrontal Cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003evmPFC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVentromedial Prefrontal Cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOFC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOrbitofrontal Cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSACC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSupragenual Anterior Cingulate Cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNAA/CR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eN-acetylaspartate to creatine ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOxy-Hb\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOxyhemoglobin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eC-reactive Protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBasal Ganglia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntellectual Quotient\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTchol\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTotal cholesterol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e24-OCH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e24-Hydroxycholesterol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGDNF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlial Cell-Derived Neurotrophic Factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated during this study are included in this published article (supplementary information files).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the General Secretariat of Research, Development and Innovation of the Andalusian Ministry of Health and Families. Project reference: PEMP-0008-2020.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCRLA and APR performed the systematic literature search, the screening and the data extraction, and wrote the manuscript. MHF and APR carried out the quality assessment. CRLA, EB and JIRR critically reviewed the content of the manuscript and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAllen DN, Randall C, Bello D, Armstrong C, Frantom L, Cross C, Kinney J. Are working memory deficits in bipolar disorder markers for psychosis? Neuropsychology. 2010;24(2):244\u0026ndash;54. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/a0018159\u003c/span\u003e\u003cspan address=\"10.1037/a0018159\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlonso-Lana S, Moro N, McKenna PJ, Sarr\u0026oacute; S, Romaguera A, Mont\u0026eacute; GC, Maristany T, Goikolea JM, Vieta E, Salvador R, Pomarol-Clotet E. Longitudinal brain functional changes between mania and euthymia in bipolar disorder. Bipolar Disord. 2019;5449\u0026ndash;57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/bdi.12767\u003c/span\u003e\u003cspan address=\"10.1111/bdi.12767\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBabineau J. Product Review: Covidence (Systematic Review Software). Journal of the Canadian Health Libraries Association /. J de l'Association des biblioth\u0026egrave;ques de la sant\u0026eacute; du Can. 2014;35(2):68\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5596/c14-016\u003c/span\u003e\u003cspan address=\"10.5596/c14-016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarbosa IG, Huguet RB, Sousa LP, Abreu MN, Rocha NP, Bauer ME, Carvalho LA, Teixeira AL. Circulating levels of GDNF in bipolar disorder. Neurosci Lett. 2011;502(2):103\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neulet.2011.07.031\u003c/span\u003e\u003cspan address=\"10.1016/j.neulet.2011.07.031\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBauer IE, Pascoe MC, Wollenhaupt-Aguiar B, Kapczinski F, Soares JC. Inflammatory mediators of cognitive impairment in bipolar disorder. J Psychiatr Res. 2014;56:18\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jpsychires.2014.04.017\u003c/span\u003e\u003cspan address=\"10.1016/j.jpsychires.2014.04.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenabarre A, Vieta E, Mart\u0026iacute;nez-Ar\u0026aacute;n A, Garcia-Garcia M, Mart\u0026iacute;n F, Lome\u0026ntilde;a F, Torrent C, S\u0026aacute;nchez-Moreno J, Colom F, Reinares M, Brugue E, Vald\u0026eacute;s M. Neuropsychological disturbances and cerebral blood flow in bipolar disorder. Aust N Z J Psychiatry. 2005;39(4):227\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/j.1440-1614.2004.01558.x\u003c/span\u003e\u003cspan address=\"10.1080/j.1440-1614.2004.01558.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBi B, Che D, Bai Y. Neural network of bipolar disorder: Toward integration of neuroimaging and neurocircuit-based treatment strategies. Transl Psychiatry. 2022;12:143. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41398-022-01917-x\u003c/span\u003e\u003cspan address=\"10.1038/s41398-022-01917-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBourne C, Aydemir \u0026Ouml;, Balanz\u0026aacute;-Mart\u0026iacute;nez V, Bora E, Brissos S, Cavanagh JT, et al. Neuropsychological testing of cognitive impairment in euthymic bipolar disorder: an individual patient data meta-analysis. Acta Psychiatr Scand. 2013;128(3):149\u0026ndash;62. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/acps.12133\u003c/span\u003e\u003cspan address=\"10.1111/acps.12133\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrady RO Jr, Tandon N, Masters GA, Margolis A, Cohen BM, Keshavan M, \u0026Ouml;ng\u0026uuml;r D. Differential brain network activity across mood states in bipolar disorder. J Affect Disord. 2017;207:367\u0026ndash;76. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2016.09.041\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2016.09.041\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrambilla P, Stanley JA, Nicoletti MA, Sassi RB, Mallinger AG, Frank E, Kupfer D, Keshavan MS, Soares JC. 1H magnetic resonance spectroscopy investigation of the dorsolateral prefrontal cortex in bipolar disorder patients. J Affect Disord. 2005;86(1):61\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2004.12.008\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2004.12.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrooks JO 3rd, Vizueta N, Penfold C, Townsend JD, Bookheimer SY, Altshuler LL. Prefrontal hypoactivation during working memory in bipolar II depression. Psychol Med. 2015;45(8):1731\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0033291714002852\u003c/span\u003e\u003cspan address=\"10.1017/S0033291714002852\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBr\u0026uuml;ckl TM, Spoormaker VI, S\u0026auml;mann PG, Brem AK, Henco L, Czamara D, Elbau I, Grandi NC, Jollans L, K\u0026uuml;hnel A, Leuchs L, P\u0026ouml;hlchen D, Schneider M, Tontsch A, Keck ME, Schilbach L, Czisch M, Lucae S, Erhardt A, Binder EB. The biological classification of mental disorders (BeCOME) study: a protocol for an observational deep-phenotyping study for the identification of biological subtypes. BMC Psychiatry. 2020;20(1):213. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12888-020-02541-z\u003c/span\u003e\u003cspan address=\"10.1186/s12888-020-02541-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurdick KE, Goldberg JF, Harrow M. Neurocognitive dysfunction and psychosocial outcome in patients with bipolar I disorder at 15-year follow-up. Acta Psychiatr Scand. 2010;122(6):499\u0026ndash;506. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1600-0447.2010.01590.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1600-0447.2010.01590.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurdick KE, Millett CE, Russo M, Alda M, Alliey-Rodriguez N, Anand A, Balaraman Y, Berrettini W, Bertram H, Calabrese JR, Calkin C, Conroy C, Coryell W, DeModena A, Feeder S, Fisher C, Frazier N, Frye M, Gao K, Garnham J, Gershon ES, Glazer K, Goes FS, Goto T, Harrington GJ, Jakobsen P, Kamali M, Kelly M, Leckband S, L\u0026oslash;berg EM, Lohoff FW, Maihofer AX, McCarthy MJ, McInnis M, Morken G, Nievergelt CM, Nurnberger J, Oedegaard KJ, Ortiz A, Ritchey M, Ryan K, Schinagle M, Schwebel C, Shaw M, Shilling P, Slaney C, Stapp E, Tarwater B, Zandi P, Kelsoe JR. The association between lithium use and neurocognitive performance in patients with bipolar disorder. Neuropsychopharmacology. 2020;45(10):1743\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41386-020-0683-2\u003c/span\u003e\u003cspan address=\"10.1038/s41386-020-0683-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurdick KE, Russo M, Frangou S, Mahon K, Braga RJ, Shanahan M, Malhotra AK. Empirical evidence for discrete neurocognitive subgroups in bipolar disorder: clinical implications. Psychol Med. 2014;44(14):3083\u0026ndash;96. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0033291714000439\u003c/span\u003e\u003cspan address=\"10.1017/S0033291714000439\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarvalho AF, Firth J, Vieta E, Bipolar Disorder. N Engl J Med. 2020;383(1):58\u0026ndash;66. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1056/NEJMra1906193\u003c/span\u003e\u003cspan address=\"10.1056/NEJMra1906193\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCerullo MA, Fleck DE, Eliassen JC, Smith MS, DelBello MP, Adler CM, Strakowski SM. A longitudinal functional connectivity analysis of the amygdala in bipolar I disorder across mood states. Bipolar Disord. 2012;14(2):175\u0026ndash;84. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1399-5618.2012.01002.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1399-5618.2012.01002.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen MH, Kao ZK, Chang WC, Tu PC, Hsu JW, Huang KL, Su TP, Li CT, Lin WC, Tsai SJ, Bai YM. Increased Proinflammatory Cytokines, Executive Dysfunction, and Reduced Gray Matter Volumes In First-Episode Bipolar Disorder and Major Depressive Disorder. J Affect Disord. 2020;274:825\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2020.05.158\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2020.05.158\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen MH, Wang L, Li H, Song H, Zhang X, Wang D. Altered intrinsic brain activity and cognitive impairment in euthymic, unmedicated individuals with bipolar disorder. Asian J Psychiatr. 2023;80:103386. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ajp.2022.103386\u003c/span\u003e\u003cspan address=\"10.1016/j.ajp.2022.103386\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClaeys EHI, Mantingh T, Morrens M, Yalin N, Stokes PRA. Resting-state fMRI in depressive and (hypo)manic mood states in bipolar disorders: A systematic review. Prog Neuropsychopharmacol Biol Psychiatry. 2022;113:110465. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.pnpbp.2021.110465\u003c/span\u003e\u003cspan address=\"10.1016/j.pnpbp.2021.110465\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCremaschi L, Penzo B, Palazzo M, Dobrea C, Cristoffanini M, Dell'Osso B, Altamura AC. Assessing working memory via N-back task in euthymic bipolar I disorder patients: a review of functional magnetic resonance imaging studies. Neuropsychobiology. 2013;68(2):63\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1159/000352011\u003c/span\u003e\u003cspan address=\"10.1159/000352011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCullen B, Ward J, Graham NA, Deary IJ, Pell JP, Smith DJ, Evans JJ. Prevalence and correlates of cognitive impairment in euthymic adults with bipolar disorder: A systematic review. J Affect Disord. 2016;205:165\u0026ndash;181. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2016.06.063\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2016.06.063\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2016 Jul 5. PMID: 27449549.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCuthbert BN. The RDoC framework: facilitating transition from ICD/DSM to dimensional approaches that integrate neuroscience and psychopathology. World Psychiatry. 2014;13(1):28\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/wps.20087\u003c/span\u003e\u003cspan address=\"10.1002/wps.20087\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDaglas R, Y\u0026uuml;cel M, Cotton S, Allott K, Hetrick S, Berk M. Cognitive impairment in first-episode mania: a systematic review of the evidence in the acute and remission phases of the illness. Int J Bipolar Disord. 2015;3:9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40345-015-0024-2\u003c/span\u003e\u003cspan address=\"10.1186/s40345-015-0024-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe-Paula VJ, Gattaz WF, Forlenza OV. Long-term lithium treatment increases intracellular and extracellular brain-derived neurotrophic factor (BDNF) in cortical and hippocampal neurons at subtherapeutic concentrations. Bipolar Disord. 2016;18(8):692\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/bdi.12449\u003c/span\u003e\u003cspan address=\"10.1111/bdi.12449\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Diego-Adeli\u0026ntilde;o J, Pires P, G\u0026oacute;mez-Ans\u0026oacute;n B, Serra-Blasco M, Vives-Gilabert Y, Puigdemont D, Mart\u0026iacute;n-Blanco A, Alvarez E, P\u0026eacute;rez V, Portella MJ. Microstructural white-matter abnormalities associated with treatment resistance, severity and duration of illness in major depression. Psychol Med. 2014;44(6):1171\u0026ndash;82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S003329171300158X\u003c/span\u003e\u003cspan address=\"10.1017/S003329171300158X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Sousa RT, van de Bilt MT, Diniz BS, Ladeira RB, Portela LV, Souza DO, Forlenza OV, Gattaz WF, Machado-Vieira R. Lithium increases plasma brain-derived neurotrophic factor in acute bipolar mania: a preliminary 4-week study. Neurosci Lett. 2011;494(1):54\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neulet.2011.02.054\u003c/span\u003e\u003cspan address=\"10.1016/j.neulet.2011.02.054\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDittmann S, Hennig-Fast K, Gerber S, Seem\u0026uuml;ller F, Riedel M, Emanuel Severus W, Langosch J, Engel RR, M\u0026ouml;ller HJ, Grunze HC. Cognitive functioning in euthymic bipolar I and bipolar II patients. Bipolar Disord. 2008;10(8):877\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1399-5618.2008.00640.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1399-5618.2008.00640.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEhrlich TJ, Ryan KA, Burdick KE, Langenecker SA, McInnis MG, Marshall DF. Cognitive subgroups and their longitudinal trajectories in bipolar disorder. Acta Psychiatr Scand., Ekinci A. Inflammatory parameters and blood lipid values across the different mood states in patients with bipolar disorder. Klinik Psikiyatri Dergisi. 2020;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5505/kpd.2020.98216\u003c/span\u003e\u003cspan address=\"10.5505/kpd.2020.98216\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElshahawi HH, Essawi H, Rabie MA, Mansour M, Beshry ZA, Mansour AN. Cognitive functions among euthymic bipolar I patients after a single manic episode versus recurrent episodes. J Affect Disord. 2011;130(1\u0026ndash;2):180\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2010.10.027\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2010.10.027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEstudillo-Guerra MA, Pacheco-Barrios K, Cardenas-Rojas A, Adame-Ocampo G, Camprodon JA, Morales-Quezada L, Guti\u0026eacute;rrez-Mora D, Flores-Ramos M. Brain perfusion during manic episode and at 6-month follow-up period in bipolar disorder patients: Correlation with cognitive functions. Brain Behav. 2020;10(6):e01615. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/brb3.1615\u003c/span\u003e\u003cspan address=\"10.1002/brb3.1615\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEvers AK, Veeh J, McNeill R, Reif A, Kittel-Schneider S. C-reactive protein concentration in bipolar disorder: association with genetic variants. Int J Bipolar Disord. 2019;7(1):26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40345-019-0162-z\u003c/span\u003e\u003cspan address=\"10.1186/s40345-019-0162-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFavre P, Pauling M, Stout J, Hozer F, Sarrazin S, Ab\u0026eacute; C, et al. Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals. Neuropsychopharmacology. 2019;44(13):2285\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41386-019-0485-6\u003c/span\u003e\u003cspan address=\"10.1038/s41386-019-0485-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFernandes BS, Steiner J, Molendijk ML, Dodd S, Nardin P, Gon\u0026ccedil;alves CA, Jacka F, K\u0026ouml;hler CA, Karmakar C, Carvalho AF, Berk M. C-reactive protein concentrations across the mood spectrum in bipolar disorder: a systematic review and meta-analysis. Lancet Psychiatry. 2016;3(12):1147\u0026ndash;56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S2215-0366(16)30370-4\u003c/span\u003e\u003cspan address=\"10.1016/S2215-0366(16)30370-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFern\u0026aacute;ndez-Corcuera P, Salvador R, Mont\u0026eacute; GC, Salvador Sarr\u0026oacute; S, Goikolea JM, Amann B, et al. Bipolar depressed patients show both failure to activate and failure to de-activate during performance of a working memory task. J Affect Disord. 2013;148(2\u0026ndash;3):170\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFleck DE, Eliassen JC, Durling M, Lamy M, Adler CM, DelBello MP, Shear PK, Cerullo MA, Lee JH, Strakowski SM. Functional MRI of sustained attention in bipolar mania. Mol Psychiatry. 2012;17(3):325\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/mp.2010.108\u003c/span\u003e\u003cspan address=\"10.1038/mp.2010.108\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrey BN, Andreazza AC, Houenou J, Jamain S, Goldstein BI, Frye MA, Leboyer M, Berk M, Malhi GS, Lopez-Jaramillo C, Taylor VH, Dodd S, Frangou S, Hall GB, Fernandes BS, Kauer-Sant'Anna M, Yatham LN, Kapczinski F, Young LT. Biomarkers in bipolar disorder: a positional paper from the International Society for Bipolar Disorders Biomarkers Task Force. Aust N Z J Psychiatry. 2013;47(4):321\u0026ndash;32. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/0004867413478217\u003c/span\u003e\u003cspan address=\"10.1177/0004867413478217\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFriedman NP, Robbins TW. The role of prefrontal cortex in cognitive control and executive function. Neuropsychopharmacology. 2022;47(1):72\u0026ndash;89. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41386-021-01132-0\u003c/span\u003e\u003cspan address=\"10.1038/s41386-021-01132-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrye MA, Thomas MA, Yue K, Binesh N, Davanzo P, Ventura J, O'Neill J, Guze B, Curran JG, Mintz J. Reduced concentrations of N-acetylaspartate (NAA) and the NAA-creatine ratio in the basal ganglia in bipolar disorder: a study using 3-Tesla proton magnetic resonance spectroscopy. Psychiatry Res. 2007;154(3):259\u0026ndash;65. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.pscychresns.2006.11.003\u003c/span\u003e\u003cspan address=\"10.1016/j.pscychresns.2006.11.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFu L, Xiang D, Xiao J, Yao L, Wang Y, Xiao L, Wang H, Wang G, Liu Z. Reduced Prefrontal Activation During the Tower of London and Verbal Fluency Task in Patients With Bipolar Depression: A Multi-Channel NIRS Study. Front Psychiatry. 2018;9:214. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpsyt.2018.00214\u003c/span\u003e\u003cspan address=\"10.3389/fpsyt.2018.00214\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFusar-Poli L, Amerio A, Cimpoesu P, Natale A, Salvi V, Zappa G, Serafini G, Amore M, Aguglia E, Aguglia A. Lipid and Glycemic Profiles in Patients with Bipolar Disorder: Cholesterol Levels Are Reduced in Mania. Med (Kaunas). 2020;57(1):28. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/medicina57010028\u003c/span\u003e\u003cspan address=\"10.3390/medicina57010028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao Y, Guo X, Wang S, Huang Z, Zhang B, Hong J, Zhong Y, Weng C, Wang H, Zha Y, Sun J, Lu L, Wang G. Frontoparietal network homogeneity as a biomarker for mania and remitted bipolar disorder and a predictor of early treatment response in bipolar mania patient. J Affect Disord. 2023;339:486\u0026ndash;94. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2023.07.033\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2023.07.033\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarc\u0026iacute;a-Guti\u0026eacute;rrez MS, Navarrete F, Sala F, Gasparyan A, Austrich-Olivares A, Manzanares J. Biomarkers in Psychiatry: Concept, Definition, Types and Relevance to the Clinical Reality. Front Psychiatry. 2020;11:432. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpsyt.2020.00432\u003c/span\u003e\u003cspan address=\"10.3389/fpsyt.2020.00432\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlahn DC, Bearden CE, Barguil M, Barrett J, Reichenberg A, Bowden CL, Soares JC, Velligan DI. The neurocognitive signature of psychotic bipolar disorder. Biol Psychiatry. 2007;62(8):910-6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.biopsych.2007.02.001\u003c/span\u003e\u003cspan address=\"10.1016/j.biopsych.2007.02.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2007 Jun 1. PMID: 17543288.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGogia M, Shah AQ, Kapczinski F, de Azevedo Cardoso T. The impact of substance use disorder comorbidity on cognition of individuals with bipolar disorder: A systematic review. Psychiatry Res. 2022;311:114525. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.psychres.2022.114525\u003c/span\u003e\u003cspan address=\"10.1016/j.psychres.2022.114525\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2022 Mar 23. PMID: 35364335.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuidara W, Messedi M, Maalej M, Naifar M, Khrouf W, Grayaa S, Maalej M, Bonnefont-Rousselot D, Lamari F, Ayadi F. Plasma oxysterols: Altered level of plasma 24-hydroxycholesterol in patients with bipolar disorder. J Steroid Biochem Mol Biol. 2021;211:105902. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jsbmb.2021.105902\u003c/span\u003e\u003cspan address=\"10.1016/j.jsbmb.2021.105902\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHajek T, Alda M, Hajek E, Ivanoff J. Functional neuroanatomy of response inhibition in bipolar disorders\u0026ndash;combined voxel based and cognitive performance meta-analysis. J Psychiatr Res. 2013;47(12):1955\u0026ndash;66. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jpsychires.2013.08.015\u003c/span\u003e\u003cspan address=\"10.1016/j.jpsychires.2013.08.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHyde J, Carr H, Kelley N, Seneviratne R, Reed C, Parlatini V, Garner M, Solmi M, Rosson S, Cortese S, Brandt V. Efficacy of neurostimulation across mental disorders: systematic review and meta-analysis of 208 randomized controlled trials. Mol Psychiatry. 2022;27(6):2709\u0026ndash;19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41380-022-01524-8\u003c/span\u003e\u003cspan address=\"10.1038/s41380-022-01524-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2022 Apr 1. PMID: 35365806; PMCID: PMC8973679.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiyoshi A, Sabet JA, Sj\u0026ouml;qvist H, Melinder C, Brummer RJ, Montgomery S. Precursors in adolescence of adult-onset bipolar disorder. J Affect Disord. 2017;218:353\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2017.04.071\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2017.04.071\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu R, Stavish C, Leibenluft E, Linke JO. White Matter Microstructure in Individuals With and At Risk for Bipolar Disorder: Evidence for an Endophenotype From a Voxel-Based Meta-analysis. Biol Psychiatry Cogn Neurosci Neuroimaging. 2020;12:1104\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.bpsc.2020.06.007\u003c/span\u003e\u003cspan address=\"10.1016/j.bpsc.2020.06.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIdemoto K, Niitsu T, Hata T, Ishima T, Yoshida S, Hattori K, et al. Serum levels of glial cell line-derived neurotrophic factor as a biomarker for mood disorders and lithium response. Psychiatry Res. 2021;301:113967. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.psychres.2021.113967\u003c/span\u003e\u003cspan address=\"10.1016/j.psychres.2021.113967\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJaniri D, Frangou S. Precision neuroimaging biomarkers for bipolar disorder. Int Rev Psychiatry. 2022;34(7\u0026ndash;8):727\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/09540261.2022.2106121\u003c/span\u003e\u003cspan address=\"10.1080/09540261.2022.2106121\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKopf J, Gl\u0026ouml;ckner S, Althen H, Cevada T, Schecklmann M, Dresler T, Kittel-Schneider S, Reif A. Neural Responses to a Working Memory Task in Acute Depressed and Remitted Phases in Bipolar Patients. Brain Sci. 2023;13(5):744. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/brainsci13050744\u003c/span\u003e\u003cspan address=\"10.3390/brainsci13050744\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKraguljac NV, Reid M, White D, Jones R, den Hollander J, Lowman D, Lahti AC. Neurometabolites in schizophrenia and bipolar disorder - a systematic review and meta-analysis. Psychiatry Res. 2012;203(2\u0026ndash;3):111\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.pscychresns.2012.02.003\u003c/span\u003e\u003cspan address=\"10.1016/j.pscychresns.2012.02.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKurtz MM, Gerraty RT. A meta-analytic investigation of neurocognitive deficits in bipolar illness: profile and effects of clinical state. Neuropsychology. 2009;23(5):551\u0026ndash;62. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/a0016277\u003c/span\u003e\u003cspan address=\"10.1037/a0016277\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLai S, Zhong S, Liao X, Wang Y, Huang J, Zhang S, Sun Y, Zhao H, Jia Y. Biochemical abnormalities in basal ganglia and executive dysfunction in acute- and euthymic-episode patients with bipolar disorder: A proton magnetic resonance spectroscopy study. J Affect Disord. 2018;225:108\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2017.07.036\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2017.07.036\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi W, Zhou FC, Zhang L, Ng CH, Ungvari GS, Li J, Xiang YT. Comparison of cognitive dysfunction between schizophrenia and bipolar disorder patients: A meta-analysis of comparative studies. J Affect Disord 20201; 274:652\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2020.04.051\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2020.04.051\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu X, Li P, Ma X, Zhang J, Sun X, Luo X, Zhang Y. Association between plasma levels of BDNF and GDNF and the diagnosis, treatment response in first-episode MDD. J Affect Disord. 2022;315:190\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2022.07.041\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2022.07.041\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLoftus J, Scott J, Vorspan F, Icick R, Henry C, Gard S, Kahn JP, Leboyer M, Bellivier F, Etain B. Psychiatric comorbidities in bipolar disorders: An examination of the prevalence and chronology of onset according to sex and bipolar subtype. J Affect Disord. 2020;267:258\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2020.02.035\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2020.02.035\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL\u0026oacute;pez-Jaramillo C, Lopera-V\u0026aacute;squez J, Gallo A, Ospina-Duque J, Bell V, Torrent C, Mart\u0026iacute;nez-Ar\u0026aacute;n A, Vieta E. Effects of recurrence on the cognitive performance of patients with bipolar I disorder: implications for relapse prevention and treatment adherence. Bipolar Disord. 2010;12(5):557\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1399-5618.2010.00835.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1399-5618.2010.00835.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMagioncalda P, Martino M, Conio B, Escelsior A, Piaggio N, Presta A, Marozzi V, Rocchi G, Anastasio L, Vassallo L, Ferri F, Huang Z, Roccatagliata L, Pardini M, Northoff G, Amore M. Functional connectivity and neuronal variability of resting state activity in bipolar disorder\u0026ndash;reduction and decoupling in anterior cortical midline structures. Hum Brain Mapp. 2015;36(2):666\u0026ndash;82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/hbm.22655\u003c/span\u003e\u003cspan address=\"10.1002/hbm.22655\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMagioncalda P, Martino M, Conio B, Piaggio N, Teodorescu R, Escelsior A, Marozzi V, Rocchi G, Roccatagliata L, Northoff G, Inglese M, Amore M. Patterns of microstructural white matter abnormalities and their impact on cognitive dysfunction in the various phases of type I bipolar disorder. J Affect Disord. 2016;193:39\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2015.12.050\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2015.12.050\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManelis A, Halchenko YO, Bonar L, et al. Working memory updating in individuals with bipolar and unipolar depression: fMRI study. Transl Psychiatry. 2022;12:441. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41398-022-02211-6\u003c/span\u003e\u003cspan address=\"10.1038/s41398-022-02211-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartinez-Ar\u0026aacute;n A, Vieta E. Cognition as a target in schizophrenia, bipolar disorder and depression. Eur Neuropsychopharmacol. 2015;25(2):151\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.euroneuro.2015.01.007\u003c/span\u003e\u003cspan address=\"10.1016/j.euroneuro.2015.01.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMart\u0026iacute;nez-Ar\u0026aacute;n A, Vieta E, Reinares M, Colom F, Torrent C, S\u0026aacute;nchez-Moreno J, Benabarre A, Goikolea JM, Comes M, Salamero M. Cognitive function across manic or hypomanic, depressed, and euthymic states in bipolar disorder. Am J Psychiatry. 2004;161(2):262\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1176/appi.ajp.161.2.262\u003c/span\u003e\u003cspan address=\"10.1176/appi.ajp.161.2.262\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartino M, Magioncalda P, Saiote C, Conio B, Escelsior A, Rocchi G, Piaggio N, Marozzi V, Huang Z, Ferri F, Amore M, Inglese M, Northoff G. Abnormal functional-structural cingulum connectivity in mania: combined functional magnetic resonance imaging-diffusion tensor imaging investigation in different phases of bipolar disorder. Acta Psychiatr Scand. 2016;134(4):339\u0026ndash;49. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/acps.12596\u003c/span\u003e\u003cspan address=\"10.1111/acps.12596\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMenon V, D'Esposito M. The role of PFC networks in cognitive control and executive function. Neuropsychopharmacology. 2022;47(1):90\u0026ndash;103. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41386-021-01152-w\u003c/span\u003e\u003cspan address=\"10.1038/s41386-021-01152-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMikawa W, Tsujii N, Akashi H, Adachi T, Kirime E, Shirakawa O. Left temporal activation associated with depression severity during a verbal fluency task in patients with bipolar disorder: a multichannel near-infrared spectroscopy study. J Affect Disord. 2015;173:193\u0026ndash;200. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2014.10.051\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2014.10.051\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMisiak B, Stańczykiewicz B, Kotowicz K, Rybakowski JK, Samochowiec J, Frydecka D. Cytokines and C-reactive protein alterations with respect to cognitive impairment in schizophrenia and bipolar disorder: A systematic review. Schizophr Res. 2018;192:16\u0026ndash;29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.schres.2017.04.015\u003c/span\u003e\u003cspan address=\"10.1016/j.schres.2017.04.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiskowiak KW, Burdick KE, Martinez-Aran A, Bonnin CM, Bowie CR, Carvalho AF, Gallagher P, Lafer B, L\u0026oacute;pez-Jaramillo C, Sumiyoshi T, McIntyre RS, Schaffer A, Porter RJ, Torres IJ, Yatham LN, Young AH, Kessing LV, Vieta E. Methodological recommendations for cognition trials in bipolar disorder by the International Society for Bipolar Disorders Targeting Cognition Task Force. Bipolar Disord. 2017;19(8):614\u0026ndash;26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/bdi.12534\u003c/span\u003e\u003cspan address=\"10.1111/bdi.12534\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pmed.1000097\u003c/span\u003e\u003cspan address=\"10.1371/journal.pmed.1000097\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMora E, Portella MJ, Forcada I, Vieta E, Mur M. Persistence of cognitive impairment and its negative impact on psychosocial functioning in lithium-treated, euthymic bipolar patients: a 6-year follow-up study. Psychol Med. 2013;43(6):1187\u0026ndash;96. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0033291712001948\u003c/span\u003e\u003cspan address=\"10.1017/S0033291712001948\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuneer A. The Discovery of Clinically Applicable Biomarkers for Bipolar Disorder: A Review of Candidate and Proteomic Approaches. Chonnam Med J. 2020;56(3):166\u0026ndash;79. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4068/cmj.2020.56.3.166\u003c/span\u003e\u003cspan address=\"10.4068/cmj.2020.56.3.166\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNishimura Y, Takahashi K, Ohtani T, Ikeda-Sugita R, Kasai K, Okazaki Y. Dorsolateral prefrontal hemodynamic responses during a verbal fluency task in hypomanic bipolar disorder. Bipolar Disord. 2015;17(2):172\u0026ndash;83. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/bdi.12252\u003c/span\u003e\u003cspan address=\"10.1111/bdi.12252\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOh DH, Lee S, Kim SH, Ryu V, Cho HS. Low working memory capacity in euthymic bipolar I disorder: No relation to reappraisal on emotion regulation. J Affect Disord. 2019;252:174\u0026ndash;81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2019.04.042\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2019.04.042\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePage MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 2021;372:n160. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmj.n160\u003c/span\u003e\u003cspan address=\"10.1136/bmj.n160\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark HJ, Friston K. Structural and functional brain networks: from connections to cognition. Science. 2013;342:1238411.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePattanayak RD, Sagar R, Mehta M. Neuropsychological performance in euthymic Indian patients with bipolar disorder type I: correlation between quality of life and global functioning. Psychiatry Clin Neurosci. 2012;66(7):553\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1440-1819.2012.02400.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1440-1819.2012.02400.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePenfold C, Vizueta N, Townsend JD, Bookheimer SY, Altshuler LL. Frontal lobe hypoactivation in medication-free adults with bipolar II depression during response inhibition. Psychiatry Res. 2015;231(3):202\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.pscychresns.2014.11.005\u003c/span\u003e\u003cspan address=\"10.1016/j.pscychresns.2014.11.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePomarol-Clotet E, Alonso-Lana S, Moro N, Sarr\u0026oacute; S, Bonnin MC, Goikolea JM, Fern\u0026aacute;ndez-Corcuera P, Amann BL, Romaguera A, Vieta E, Blanch J, McKenna PJ, Salvador R. Brain functional changes across the different phases of bipolar disorder. Br J Psychiatry. 2015;206(2):136\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1192/bjp.bp.114.152033\u003c/span\u003e\u003cspan address=\"10.1192/bjp.bp.114.152033\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRive MM, Koeter MW, Veltman DJ, Schene AH, Ruh\u0026eacute; HG. Visuospatial planning in unmedicated major depressive disorder and bipolar disorder: distinct and common neural correlates. Psychol Med. 2016;46(11):2313\u0026ndash;28. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0033291716000933\u003c/span\u003e\u003cspan address=\"10.1017/S0033291716000933\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodr\u0026iacute;guez-Cano E, Alonso-Lana S, Sarr\u0026oacute; S, Fern\u0026aacute;ndez-Corcuera P, Goikolea JM, Vieta E, Maristany T, Salvador R, McKenna PJ, Pomarol-Clotet E. Differential failure to deactivate the default mode network in unipolar and bipolar depression. Bipolar Disord. 2017;19(5):386\u0026ndash;95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/bdi.12517\u003c/span\u003e\u003cspan address=\"10.1111/bdi.12517\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosa AR, Frey BN, Andreazza AC, Ceres\u0026eacute;r KM, Cunha AB, Quevedo J, Santin A, Gottfried C, Gon\u0026ccedil;alves CA, Vieta E, Kapczinski F. Increased serum glial cell line-derived neurotrophic factor immunocontent during manic and depressive episodes in individuals with bipolar disorder. Neurosci Lett. 2006;407(2):146\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neulet.2006.08.026\u003c/span\u003e\u003cspan address=\"10.1016/j.neulet.2006.08.026\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosa AR, Reinares M, Michalak EE, Bonnin CM, Sole B, Franco C, Comes M, Torrent C, Kapczinski F, Vieta E. Functional impairment and disability across mood states in bipolar disorder. Value Health. 2010;13(8):984\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1524-4733.2010.00768.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1524-4733.2010.00768.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRyan KA, Vederman AC, McFadden EM, Weldon AL, Kamali M, Langenecker SA, McInnis MG. Differential executive functioning performance by phase of bipolar disorder. Bipolar Disord. 2012;14:527\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaldarini F, Gottlieb N, Stokes PRA. Neural correlates of working memory function in euthymic people with bipolar disorder compared to healthy controls: A systematic review and meta-analysis. J Affect Disord. 2022;297:610\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2021.10.084\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2021.10.084\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSanches M, Bauer IE, Galvez JF, Zunta-Soares GB, Soares JC. The management of cognitive impairment in bipolar disorder: current status and perspectives. Am J Ther. 2015;22(6):477\u0026ndash;86. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/MJT.0000000000000120\u003c/span\u003e\u003cspan address=\"10.1097/MJT.0000000000000120\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchouws SNTM, Korten N, Beekman ATF, Stek ML, Dols A. Does cognitive function in older bipolar patients depend on recurrent or current mood symptoms? Int J Geriatr Psychiatry. 2020;35(10):1163\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/gps.5352\u003c/span\u003e\u003cspan address=\"10.1002/gps.5352\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchumer MC, Chase HW, Rozovsky R, Eickhoff SB, Phillips ML. Prefrontal, parietal, and limbic condition-dependent differences in bipolar disorder: a large-scale meta-analysis of functional neuroimaging studies. Mol Psychiatry. 2023;28(7):2826\u0026ndash;38. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41380-023-01974-8\u003c/span\u003e\u003cspan address=\"10.1038/s41380-023-01974-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSimonsen C, Sundet K, Vaskinn A, Birkenaes AB, Engh JA, Faerden A, J\u0026oacute;nsd\u0026oacute;ttir H, Ringen PA, Opjordsmoen S, Melle I, Friis S, Andreassen OA. Neurocognitive dysfunction in bipolar and schizophrenia spectrum disorders depends on history of psychosis rather than diagnostic group. Schizophr Bull. 2011;37(1):73\u0026ndash;83. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/schbul/sbp034\u003c/span\u003e\u003cspan address=\"10.1093/schbul/sbp034\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSrivastava C, Bhardwaj A, Sharma M, Kumar S. Cognitive Deficits in Euthymic Patients With Bipolar Disorder: State or Trait Marker? J Nerv Ment Dis. 2019;207(2):100\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/NMD.0000000000000920\u003c/span\u003e\u003cspan address=\"10.1097/NMD.0000000000000920\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStrakowski SM, Fleck DE, Welge J, Eliassen JC, Norris M, Durling M, Komoroski RA, Chu WJ, Weber W, Dudley JA, Blom TJ, Stover A, Klein C, Strawn JR, DelBello MP, Lee JH, Adler CM. fMRI brain activation changes following treatment of a first bipolar manic episode. Bipolar Disord. 2016;18(6):490\u0026ndash;501. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/bdi.12426\u003c/span\u003e\u003cspan address=\"10.1111/bdi.12426\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStrawbridge R, Carter R, Saldarini F, Tsapekos D, Young AH. Inflammatory biomarkers and cognitive functioning in individuals with euthymic bipolar disorder: exploratory study. BJPsych Open. 2021;7(4):e126. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1192/bjo.2021.966\u003c/span\u003e\u003cspan address=\"10.1192/bjo.2021.966\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSundaresh A, Rajkumar R, Krishnamoorthy R, Leboyer M, Negi V, Tamouza RC. -Reactive Protein in Bipolar Disorder in an Indian Clinical Setting. J Clin Diagn Res. 2018;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7860/jcdr/2018/37177.12014\u003c/span\u003e\u003cspan address=\"10.7860/jcdr/2018/37177.12014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakebayashi M, Hisaoka K, Nishida A, Tsuchioka M, Miyoshi I, Kozuru T, Hikasa S, Okamoto Y, Shinno H, Morinobu S, Yamawaki S. Decreased levels of whole blood glial cell line-derived neurotrophic factor (GDNF) in remitted patients with mood disorders. Int J Neuropsychopharmacol. 2006;9(5):607\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S1461145705006085\u003c/span\u003e\u003cspan address=\"10.1017/S1461145705006085\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakizawa R, Fukuda M, Kawasaki S, Kasai K, Mimura M, Pu S, Noda T, Niwa S, Okazaki Y. Joint Project for Psychiatric Application of Near-Infrared Spectroscopy (JPSY-NIRS) Group. Neuroimaging-aided differential diagnosis of the depressive state. NeuroImage. 2014;85(Pt):498\u0026ndash;507. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neuroimage.2013.05.126\u003c/span\u003e\u003cspan address=\"10.1016/j.neuroimage.2013.05.126\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThompson JM, Gray JM, Hughes JH, Watson S, Young AH, Ferrier IN. Impaired working memory monitoring in euthymic bipolar patients. Bipolar Disord. 2007;9(5):478\u0026ndash;89. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1399-5618.2007.00470.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1399-5618.2007.00470.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian F, Diao W, Yang X, Wang X, Roberts N, Feng C, Jia Z. Failure of activation of striatum during the performance of executive function tasks in adult patients with bipolar disorder. Psychol Med. 2020;50(4):653\u0026ndash;65. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0033291719000473\u003c/span\u003e\u003cspan address=\"10.1017/S0033291719000473\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTorrent C, Martinez-Ar\u0026aacute;n A, del Mar Bonnin C, Reinares M, Daban C, Sol\u0026eacute; B, Rosa AR, Tabar\u0026eacute;s-Seisdedos R, Popovic D, Salamero M, Vieta E. Long-term outcome of cognitive impairment in bipolar disorder. J Clin Psychiatry. 2012;73(7):e899\u0026ndash;905. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4088/JCP.11m07471\u003c/span\u003e\u003cspan address=\"10.4088/JCP.11m07471\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTunca Z, Ozerdem A, Ceylan D, Yal\u0026ccedil;ın Y, Can G, Resmi H, Akan P, Erg\u0026ouml;r G, Aydemir O, Cengisiz C, Kerim D. Alterations in BDNF (brain derived neurotrophic factor) and GDNF (glial cell line-derived neurotrophic factor) serum levels in bipolar disorder: The role of lithium. J Affect Disord. 2014;166:193\u0026ndash;200. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2014.05.012\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2014.05.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsai SY, Chung KH, Chen PH. Levels of interleukin-6 and high-sensitivity C-reactive protein reflecting mania severity in bipolar disorder. Bipolar Disord. 2017;19(8):708\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/bdi.12570\u003c/span\u003e\u003cspan address=\"10.1111/bdi.12570\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsapekos D, Strawbridge R, Cella M, Wykes T, Young AH. Cognitive impairment in euthymic patients with bipolar disorder: Prevalence estimation and model selection for predictors of cognitive performance. J Affect Disord. 2021;294:497\u0026ndash;504. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2021.07.036\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2021.07.036\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsitsipa E, Fountoulakis KN. The neurocognitive functioning in bipolar disorder: a systematic review of data. Ann Gen Psychiatry. 2015;14:42. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12991-015-0081-z\u003c/span\u003e\u003cspan address=\"10.1186/s12991-015-0081-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUluyol OB, Onur OS, Ekinci A, Guclu O. Relationship Between Serum Uric Acid Levels and Cognitive Functions in Bipolar Disorder. Psychiatry Clin Psychopharmacol. 2020;30(2):165\u0026ndash;74. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5455/pcp.20200321090156\u003c/span\u003e\u003cspan address=\"10.5455/pcp.20200321090156\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan der Schot A, Kahn R, Ramsey N, Nolen W, Vink M. Trait and state dependent functional impairments in bipolar disorder. Psychiatry Res. 2010;184(3):135\u0026ndash;42. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.pscychresns.2010.07.009\u003c/span\u003e\u003cspan address=\"10.1016/j.pscychresns.2010.07.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVelasques B, Bittencourt J, Diniz C, Teixeira S, Basile LF, In\u0026aacute;cio Salles J, et al. Changes in saccadic eye movement (SEM) and quantitative EEG parameter in bipolar patients. J Affect Disord. 2013;145(3):378\u0026ndash;85. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2012.04.049\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2012.04.049\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerdolini N, Moreno-Ortega M, Salgado-Pineda P, Mont\u0026eacute; G, de Arag\u0026oacute;n AM, Dompablo M, McKenna PJ, Salvador R, Palomo T, Pomarol-Clotet E, Rodriguez-Jimenez R. Failure of deactivation in bipolar disorder during performance of an fMRI adapted version of the Stroop task. J Affect Disord. 2023;329:307\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2023.02.132\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2023.02.132\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVolkert J, Schiele MA, Kazmaier J, Glaser F, Zierhut KC, Kopf J, Kittel-Schneider S, Reif A. Cognitive deficits in bipolar disorder: from acute episode to remission. Eur Arch Psychiatry Clin Neurosci. 2016;266(3):225\u0026ndash;37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00406-015-0657-2\u003c/span\u003e\u003cspan address=\"10.1007/s00406-015-0657-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVrabie M, Marinescu V, Talaşman A, Tăutu O, Drima E, Micluţia I. Cognitive impairment in manic bipolar patients: important, understated, significant aspects. Ann Gen Psychiatry. 2015;14:41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12991-015-0080-0\u003c/span\u003e\u003cspan address=\"10.1186/s12991-015-0080-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVreeker A, Boks MP, Abramovic L, Verkooijen S, van Bergen AH, Hillegers MH, et al. High educational performance is a distinctive feature of bipolar disorder: a study on cognition in bipolar disorder, schizophrenia patients, relatives and controls. Psychol Med. 2016;46(4):807\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/s0033291715002299\u003c/span\u003e\u003cspan address=\"10.1017/s0033291715002299\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWells G, Shea B, O'Connell D, Peterson J, Welch V, Losos M, Tugwell P. The Newcastle\u0026ndash;Ottawa Scale (NOS) for Assessing the Quality of Non-Randomized Studies in Meta-Analysis. 2000. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ohri.ca/programs/clinical_epidemiology/oxford.asp\u003c/span\u003e\u003cspan address=\"http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWingo AP, Wingo TS, Harvey PD, Baldessarini RJ. Effects of lithium on cognitive performance: a meta-analysis. J Clin Psychiatry. 2009;70(11):1588-97. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4088/JCP.08r04972\u003c/span\u003e\u003cspan address=\"10.4088/JCP.08r04972\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2009 Aug 11. PMID: 19689922.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWohlin C. Guidelines for snowballing in systematic literature studies and a replication in software engineering. ACM International Conference Proceeding Series. 2014. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1145/2601248.2601268\u003c/span\u003e\u003cspan address=\"10.1145/2601248.2601268\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXing M, Tadayonnejad R, MacNamara A, Ajilore O, DiGangi J, Phan KL, Leow A, Klumpp H. Resting-state theta band connectivity and graph analysis in generalized social anxiety disorder. Neuroimage Clin. 2016;13:24\u0026ndash;32. PMID: 27920976; PMCID: PMC5126152.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamada S, Takahashi S, Ukai S, Tsuji T, Iwatani J, Tsuda K, et al. Microstructural abnormalities in anterior callosal fibers and their relationship with cognitive function in major depressive disorder and bipolar disorder: a tract-specific analysis study. J Affect Disord. 2015;174:542\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2014.12.022\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2014.12.022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang J, Ouyang X, Tao H, Pu W, Fan Z, Zeng C, Huang X, Chen X, Liu J, Liu Z, Palaniyappan L. Connectomic signatures of working memory deficits in depression, mania, and euthymic states of bipolar disorder. J Affect Disord. 2020;274:190\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2020.05.058\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2020.05.058\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoshimura Y, Okamoto Y, Onoda K, Okada G, Toki S, Yoshino A, Yamashita H, Yamawaki S. Psychosocial functioning is correlated with activation in the anterior cingulate cortex and left lateral prefrontal cortex during a verbal fluency task in euthymic bipolar disorder: a preliminary fMRI study. Psychiatry Clin Neurosci. 2014;68(3):188\u0026ndash;96. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/pcn.12115\u003c/span\u003e\u003cspan address=\"10.1111/pcn.12115\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZarp Petersen J, Varo C, Skovsen CF, Ott CV, Kjaerstad HL, Vieta E, Harmer CJ, Knudsen GM, Kessing LV, Macoveanu J, Miskowiak KW. Neuronal underpinnings of cognitive impairment in bipolar disorder: A large data-driven functional magnetic resonance imaging study. Bipolar Disord. 2022;24(1):69\u0026ndash;81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/bdi.13100\u003c/span\u003e\u003cspan address=\"10.1111/bdi.13100\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZanetti MV, Jackowski MP, Versace A, Almeida JR, Hassel S, Duran FL, Busatto GF, Kupfer DJ, Phillips ML. State-dependent microstructural white matter changes in bipolar I depression. Eur Arch Psychiatry Clin Neurosci. 2009;259(6):316\u0026ndash;28. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00406-009-0002-8\u003c/span\u003e\u003cspan address=\"10.1007/s00406-009-0002-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang X, Ru B, Sha W, Xin W, Zhou H, Zhang Y. Performance on the Wisconsin card-sorting test and serum levels of glial cell line-derived neurotrophic factor in patients with major depressive disorder. Asia Pac Psychiatry. 2014;6(3):302\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/appy.12120\u003c/span\u003e\u003cspan address=\"10.1111/appy.12120\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang X, Zhang Z, Sha W, Xie C, Xi G, Zhou H, Zhang Y. Effect of treatment on serum glial cell line-derived neurotrophic factor in bipolar patients. J Affect Disord. 2010;126(1\u0026ndash;2):326\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2010.03.003\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2010.03.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhong S, Wang Y, Lai S, Liu T, Liao X, Chen G, Jia Y. Associations between executive function impairment and biochemical abnormalities in bipolar disorder with suicidal ideation. J Affect Disord. 2018;241:282\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2018.08.031\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2018.08.031\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZinchuk MS, Guekht AB, Druzhkova TA, Gulyaeva NV, Shpak AA. Glial cell line-derived neurotrophic factor (GDNF) in blood serum and lacrimal fluid of patients with a current depressive episode. J Affect Disord. 2022;318:409\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2022.09.025\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2022.09.025\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-bipolar-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijbd","sideBox":"Learn more about [International Journal of Bipolar Disorders](http://journalbipolardisorders.springeropen.com/)","snPcode":"40345","submissionUrl":"https://submission.nature.com/new-submission/40345/3","title":"International Journal of Bipolar Disorders","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Biomarker, Bipolar Disorder, Cognition, Mood state, Psychiatry","lastPublishedDoi":"10.21203/rs.3.rs-4020734/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4020734/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eBipolar disorder (BD) is a severe psychiatric disorder characterized by changes in mood that alternate between (hypo) mania or depression and mixed states, often associated with functional impairment and cognitive dysfunction. But little is known about biomarkers that contribute to the development and sustainment of cognitive deficits. The aim of this study was to review the association between neurocognition and biomarkers across different mood states.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eSearch databases were Web of Science, Scopus and PudMed. A systematic review was carried out following the PRISMA guidelines. Risk of bias was assessed with the Newcastle-Ottawa Scale. Studies were selected that focused on the correlation between neuroimaging, physiological, genetic or peripheral biomarkers and cognition in at least two phases of BD: depression, (hypo)mania, euthymia or mixed. PROSPERO Registration No.: CRD42023410782\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 1824 references were screened, identifying 1023 published articles, of which 336 were considered eligible. Only 16 provided information on the association between biomarkers and cognition in the different affective states of BD. We mainly found two types of biomarkers examining this association across BD mood states. Regarding peripheral biomarkers, although literature suggests an association with cognition, our review did not reveal such an association. Differences in levels of total cholesterol and C-reactive protein were observed depending on mood state. Neuroimaging biomarkers highlighted hypoactivation of frontal areas stands out for the acute states of BD and a deactivation failure has been reported in the ventromedial prefrontal cortex (vmPFC), potentially serving as a trait marker of BD.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOnly a few recent articles have investigated biomarker-cognition associations in BD mood phases. Our findings underline that there appear to be central regions involved in BD that are observed in all mood states. However, there appear to be underlying mechanisms of cognitive dysfunction that may vary across different mood states in bipolar disorder. This review highlights the importance of standardizing the data and the assessment of cognition, as well as the need for biomarkers to help prevent acute symptomatic phases of the disease, and the associated functional and cognitive impairment.\u003c/p\u003e","manuscriptTitle":"A systematic review of the biomarkers associated with cognition and mood state in bipolar disorder","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-25 04:27:53","doi":"10.21203/rs.3.rs-4020734/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-15T08:36:26+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-13T05:27:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-10T22:59:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"88d3159e-62fd-4578-9b13-6bb2f0a20696","date":"2024-04-06T05:09:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"e0ff2a4b-c193-4db8-8d1b-31fea8884ea8","date":"2024-04-02T11:36:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-02T11:30:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-21T00:34:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-21T00:34:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Bipolar Disorders","date":"2024-03-06T11:04:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-bipolar-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijbd","sideBox":"Learn more about [International Journal of Bipolar Disorders](http://journalbipolardisorders.springeropen.com/)","snPcode":"40345","submissionUrl":"https://submission.nature.com/new-submission/40345/3","title":"International Journal of Bipolar Disorders","twitterHandle":"@SpringerOpen","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c9d079cd-a7ee-42f3-a963-92d0bf1cb5a1","owner":[],"postedDate":"March 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-05-02T14:07:26+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-25 04:27:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4020734","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4020734","identity":"rs-4020734","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}