The Role of the Choroid Plexus in Cognitive Impairment Across Neurological Disorders: A Systematic Review

The Role of the Choroid Plexus in Cognitive Impairment Across Neurological Disorders: A Systematic Review | 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 Systematic Review The Role of the Choroid Plexus in Cognitive Impairment Across Neurological Disorders: A Systematic Review Shahab Lotfinia, Maryam Moghbel Baerz, Mahrooz Roozneh, Mehrdad Roozbeh, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8854166/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: Choroid plexus volume (CPV), a structural marker linked to CSF regulation and neuroimmune activity, has emerged as a potential indicator of cognitive vulnerability across neurological disorders. This systematic review synthesizes evidence on CPV–cognition relationships in Alzheimer’s disease, mild cognitive impairment, Parkinson’s disease, multiple sclerosis, and related conditions. Methods Following PRISMA guidelines and a PROSPERO-registered protocol, five databases (PubMed, Scopus, Web of Science, Embase, PsycINFO) were searched through October 2025. Eligible human studies used structural MRI to quantify CPV and reported cognitive outcomes. Two independent reviewers conducted screening, data extraction, and quality assessment using the Newcastle–Ottawa Scale. Results 15 studies met inclusion criteria. Across the Alzheimer continuum CP enlargement consistently correlated with poorer global cognition, executive dysfunction, and episodic memory impairment. Longitudinal studies showed that greater CPV predicted faster cognitive decline and stronger amyloid-related pathology. In Parkinson disease, reduced CPV in de novo patients and CP enlargement in later stages were both associated with worse cognition and increased risk of dementia. In multiple sclerosis and white matter hyperintensities -related vascular aging, larger CPV was linked to deficits in processing speed, executive functioning, global cognition, and fatigue. Mechanistic evidence highlighted impaired CSF and glymphatic clearance, amyloid and α-synuclein accumulation, neuroinflammation, and microstructural CP changes as mediators of CPV-related cognitive decline. Conclusion Across conditions, CPV reliably reflects cognitive status and predicts cognitive deterioration. CP alterations signify disturbances in CSF dynamics, neuroinflammatory activity, and protein clearance, positioning CPV as a promising transdiagnostic biomarker. Future longitudinal and multimodal studies are needed to clarify causal mechanisms and evaluate its clinical utility in diagnosis, prognosis, and therapeutic monitoring. Choroid plexus volume Neurodegeneration Alzheimer’s disease Parkinson’s disease Multiple sclerosis Figures Figure 1 1. Introduction The choroid plexus (CP) is a veil-like, sheet-like structure derived from the leptomeninges and ependymal epithelium, located within the ventricular system and composed of epithelial layers, blood vessels, fibroblasts, and immune cells ( 1 ). It produces approximately 60–80% of cerebrospinal fluid (CSF), forms the blood–CSF barrier, and plays a central role in maintaining central nervous system (CNS) homeostasis by regulating immune cell trafficking, inflammatory responses, circadian rhythms, gut–brain communication, and cognitive processes ( 2 – 4 ). Beyond CSF secretion, the CP contributes to the clearance of neurotoxic waste products, and alterations in choroid plexus volume (CPV) have been increasingly implicated in neurodegenerative disease mechanisms, including Parkinson’s disease (PD) ( 5 – 8 ). CP dysfunction may exacerbate the accumulation of pathological proteins such as α-synuclein (α-syn), amyloid beta (Aβ), and hyperphosphorylated Tau, molecules strongly associated with PD-related cognitive decline ( 9 ). Furthermore, CP enlargement has been linked to higher relapse rates, chronic lesion expansion, inflammation, accelerated brain atrophy, and progression of disability in neuroinflammatory disorders, with mounting evidence associating CP enlargement with multiple sclerosis (MS)-related cognitive dysfunction ( 10 – 13 ). Beyond these disease-specific associations, recent research has increasingly focused on CP volume as an indicator of cognitive function. With the advancement of structural magnetic resonance imaging (MRI), choroid plexus volume has gained attention as a potential marker of cognitive function ( 14 ). Larger CP volumes are generally associated with greater cognitive impairment, including mild cognitive impairment (MCI) and progression toward Alzheimer’s disease (AD) ( 15 , 16 ). CP enlargement has also been reported in cognitively unimpaired adults, where age-related increases in CP volume appear to correlate with lower global cognitive performance ( 17 , 18 ). Longitudinal studies further demonstrate that greater CP volume in older adults predicts faster cognitive decline, suggesting its potential as an early biomarker of age-related cognitive vulnerability ( 19 ). Across neurological disorders, this relationship extends beyond healthy aging, as numerous studies have indicated associations between CP volume and various cognitive domains. In MS, increased CP volume has been linked to both cognitive impairment and fatigue ( 13 ). In AD, CP volume is associated with executive dysfunction and elevated dementia risk. Similarly, in early-stage PD, CP volume shows negative correlations with cognitive performance ( 20 ). A negative association between CP volume and cognitive test scores has also been observed in first-degree relatives of individuals with schizophrenia, suggesting potential relevance beyond classical neurodegenerative disorders ( 21 ). Despite these emerging findings, a comprehensive synthesis of CP volume–cognition associations across neurological disorders is lacking. The primary aim of this study is to systematically review and synthesize the existing evidence on the relationship between choroid plexus volume and cognitive function across neurological disorders. Specifically, we evaluate how variations in CP volume relate to cognitive impairment in conditions such as PD, MS, and AD, as well as in cognitively unimpaired adults. Additionally, we compare CP cognition associations across different patient populations and assess the potential of CP volume as an early biomarker of cognitive decline. By addressing these objectives, this review seeks to clarify the contribution of CP alterations to cognitive dysfunction and provide insights for future clinical and neuroimaging research. 2. Method 2.2. Protocol Registration This systematic review was designed and reported in accordance with the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines. The study protocol was prospectively registered in the International Prospective Register of Systematic Reviews (PROSPERO) (Registration ID:). Ethical approval for this study was obtained from the Shahid Beheshti University of Medical Sciences Ethics Committee (Approval Code:). Flow diagram of study summarized in Fig. 1 . 2.3. Eligibility criteria Eligible studies included original human research that employed structural magnetic resonance imaging (MRI) to assess CPV or morphology. The population of interest consisted of individuals diagnosed with neurological disorders such as AD, MS, PD, traumatic brain injury, or stroke, with comparisons made to healthy controls or other clinical groups. To be included, studies were required to report CPV or structural alterations in association with cognitive performance measures such as the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), or domain-specific assessments of memory, attention, or executive function. Only articles published in English were considered eligible. Exclusion criteria included case reports, conference abstracts lacking full text, review articles, and editorials. Studies involving animal or in vitro models, those failing to report CP volume or providing insufficient data for extraction, as well as duplicate publications or overlapping datasets, were excluded. 2.4. Search Strategy A systematic search was conducted in PubMed, Scopus, Web of Science, Embase, and PsycINFO up to November 2025. The search strategy combined Medical Subject Headings (MeSH) and free-text terms related to “choroid plexus” OR “CSF barrier,” “volume” OR “morphology” OR “atrophy” OR “enlargement,” “cognitive impairment” OR “memory” OR “attention” OR “executive function,” and “neurological disorders” along with disorder-specific terms such as Alzheimer’s disease, schizophrenia, multiple sclerosis, Parkinson’s disease, and depression. The search strategy was adapted for each database. In addition, reference lists of eligible articles and relevant reviews were manually screened to identify additional studies. 2.5. Data Extraction Two independent reviewers extracted data using a standardized extraction form. Extracted information included study characteristics (first author, year, country), study design, and sample size, as well as population characteristics such as diagnosis, age, sex, and disease severity. Only studies employing structural MRI for CPV assessment were included. Outcomes of interest comprised CPV metrics, cognitive performance measures, and reported associations between CP volume and cognition. Discrepancies between reviewers were resolved through discussion or consultation with a third reviewer when necessary. 2.6. Quality Assessment The methodological quality of the included studies was evaluated using the Newcastle-Ottawa Scale (NOS) for observational research. This tool assesses studies across three domains: ( 1 ) selection of study groups, ( 2 ) comparability of groups, and ( 3 ) outcome assessment. Each study was classified as low, moderate, or high quality based on its NOS score. When sufficient studies were available, publication bias was assessed using funnel plots and Egger's regression test. 3. Result 3.1. Study Selection The initial database search across PubMed, Web of Science, and Scopus identified 412 records. After removing 102 duplicates, 310 articles remained for title and abstract screening. Of these, 256 records were excluded for not meeting the eligibility criteria, including studies unrelated to choroid plexus volume, absence of cognitive assessments, use of animal or in vitro models, review papers, conference abstracts without full text, or articles lacking relevant neuroimaging data. A total of 54 full-text articles were retrieved for detailed evaluation. Following full-text assessment, 39 studies were excluded due to insufficient quantitative data, absence of structural MRI–based CP volume measurements, irrelevant outcomes, or non-original study design. Ultimately, 15 studies met the inclusion criteria and were included in the final systematic review. 3.2. Study Characteristics A total of 17 studies met the inclusion criteria (Table 1 ) and were incorporated into this review. These studies encompassed a broad range of populations, including individuals with cognitive impairment, neurodegenerative or neuroinflammatory disorders, and healthy controls. Sample sizes varied considerably across investigations from small single-center cohorts ( 20 ) to large multicenter datasets exceeding 1,000 participants ( 15 , 18 ). Participant ages similarly ranged widely, from mid-30s in MS cohorts ( 13 , 22 ) to over 77 years in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) samples ( 18 ). The included studies represented a diverse spectrum of clinical populations, such as AD ( 8 , 14 , 23 – 25 ), mild cognitive impairment ( 15 , 16 , 18 ), subjective cognitive decline ( 14 , 23 ), PD ( 8 , 26 ), MS ( 13 , 22 ), and individuals with varying burdens of white matter hyperintensities ( 27 ). Most studies also included healthy control groups to facilitate comparative analyses. Neuropsychological assessments varied substantially across studies. The Mini-Mental State Examination (MMSE) was the most frequently reported cognitive screening instrument ( 8 , 10 , 14 , 15 , 18 , 23 – 25 , 27 ). Other commonly used measures included the Montreal Cognitive Assessment (MoCA) ( 20 , 24 , 26 ) and the Brief Repeatable Battery of Neuropsychological Tests (BRB-N) in MS populations ( 13 , 22 ). 3.3. Risk of Bias / Quality Assessment The methodological quality of the included studies was assessed using the Newcastle–Ottawa Scale (NOS) for observational research. Overall study quality ranged from moderate to high. Of the 17 included studies, 11 were rated as high quality (NOS ≥ 7), while 4 were rated as moderate quality (NOS 5–6). No study received a low-quality rating. Most investigations demonstrated adequate representativeness of the study population and appropriate comparability between groups, particularly in studies that included both clinical populations and healthy controls. Selection bias was minimized in the majority of studies through the use of standardized diagnostic criteria for AD, mild cognitive impairment, PD, MS, and subjective cognitive decline. Nonetheless, a subset of studies provided limited information on recruitment procedures, which may restrict the generalizability of their findings. Regarding comparability, most studies adjusted or stratified analyses for key demographic confounders such as age and sex. Cognitive function was measured using validated instruments, including the MMSE, MoCA, BRB-N, and various comprehensive neuropsychological batteries, thereby reducing the likelihood of measurement bias. However, substantial variability in the type, depth, and scope of cognitive assessments across studies introduces a potential source of heterogeneity in the reported findings. Table 1 Characteristics of included studies Study Participants (male) Age Cognitive test Xia et al 2025 AD = 248 (139) MCI = 761 (420) SCD = 344 (131) AD = 74.36 ± 8.19 MCI = 71.82 ± 7.56 SCD = 70.69 ± 6.75 MMSE Wang et al 2025 MS = 77 ( 17 ) HC = 44 ( 14 ) MS = 31 (m) HC = 28 (m) BRB-N Xu 2024 et al Severe WMHs = 28 ( 16 ) Moderate WMHs = 62 ( 30 ) Mild WMHs = 116 ( 39 ) HC = 43 ( 13 ) Severe WMHs = 69.4 ± 7.4 Moderate WMHs = 71.9 ± 7.3 Mild WMHs = 66.2 ± 7.3 HC = 61.6 ± 7.8 MMSE neuropsychological battery Preziosa et al 2024 MS = 129 (56) HC = 73 ( 30 ) MS = 43.3 (11.1) HC = 41 (12.4) BRB-N Pearson et al 2024 pMCI = 115 (62) sMCI = 338 (200) pMCI = 73.76 (7.62) sMCI = 72.70 (7.55) RAVLT-I Jiang et al 2024 AD = 228 (95) MCI = 269 (101) HC = 110 (48) AD = 70.04 (8.96) MCI = 64.83 (7.61) HC = 60.44 (7.13) MMSE MoCA NPI ADL Hidaka et al 2024 MCI = 226 (108) nonMCI = 1144 (417) MCI = 77.9 (6.4) nonMCI = 73.1 ( 6 ) MMSE Choi et al 2022 AD = 147 ( 42 ) Late MCI = 149 ( 42 ) Early MCI = 158 ( 39 ) SCI = 78 ( 21 ) AD = 76 ( 8 ) Late MCI = 73 ( 8 ) Early MCI = 70 ( 9 ) SCI = 69 ( 8 ) MMSE Jeong et al 2023 PD = 240 (119) HC = 80 ( 36 ) PD = 67.89 (7.88) HC = 66.64 (9.41) K-BNT RCFT SVLT COWAT MMSE Yang et al 2025 PD = 236 HC = 47 PD= HC= MoCA LNS SDMT HVLT Umemura et al 2024 MCI = 218 (120) HC = 1904 (703) MCI = 72 (69–76) HC = 69 (66–73) MMSE He et al 2024 Lowest tertile group = 32 ( 17 ) Middle tertile group = 31 ( 19 ) Upper tertile group = 32 ( 27 ) Lowest tertile group = 54.4 (8.2) Middle tertile group = 59.9 (7.2) Upper tertile group = 65.8 ( 9 ) MoCA LNS SDMT SFT HVLT JLO Bouhrara et al 2024 108 (57) 55.7 (20.4) MMSE Jeong et al 2025 AD-D = 77 ( 24 ) AD-nD = 126 (53) HC = 82 ( 38 ) AD-D = 76.31 (6.74) AD-nD = 74.94 (7.23) HC = 66.46 (9.36) MMSE Martinkova et al 2023 CN = 188 (83) MCI = 239 (131) AD = 88 (50) Convert = 98 (54) CN = 72.62 (6.57) MCI = 71.88 (7.39) AD = 74.09 (8.03) Convert = 73.53 (7.27) MMSE AD = Alzheimer’s disease; MCI = Mild cognitive impairment; SCD = Subjective cognitive decline; MS = Multiple sclerosis; HC = Healthy controls; WMHs = White matter hyperintensities; pMCI = Progressive MCI; sMCI = Stable MCI; SCI = Subjective cognitive impairment; PD = Parkinson’s disease; CN = Cognitively normal; Convert = MCI converters to AD; AD-D = AD with dementia; AD-nD = AD without dementia. Cognitive Tests: MMSE = Mini-Mental State Examination; MoCA = Montreal Cognitive Assessment; ACE-R = Addenbrooke’s Cognitive Examination–Revised; BRB-N = Brief Repeatable Battery of Neuropsychological Tests; RAVLT-I = Rey Auditory Verbal Learning Test–Immediate recall; NPI = Neuropsychiatric Inventory; ADL = Activities of Daily Living; K-BNT = Korean version of the Boston Naming Test; RCFT = Rey Complex Figure Test; SVLT = Seoul Verbal Learning Test; COWAT = Controlled Oral Word Association Test; LNS = Letter–Number Sequencing; SDMT = Symbol Digit Modalities Test; HVLT = Hopkins Verbal Learning Test; SFT = Semantic Fluency Test; JLO = Judgment of Line Orientation. 3.4. Details of study’s findings Yang et al. showed that CPV is a meaningful structural correlate of both motor and cognitive deficits in newly diagnosed, untreated PD. CPV was significantly reduced in PD patients compared to matched controls, and lower CPV was strongly associated with more severe motor impairment (higher MDS-UPDRS scores) and poorer global cognition (lower MoCA scores). Longitudinal follow-up demonstrated that smaller CPV predicted faster decline in working memory and processing speed (LNS and SDMT). Mediation analyses further indicated that Tau protein levels partly explained the link between CPV reduction and cognitive deterioration ( 26 ). Wang et al. showed in relapsing–remitting MS (RRMS), glymphatic dysfunction indexed by enlarged CPV and reduced DTI-ALPS values. Patients with cognitive impairment showed greater CPV and lower DTI-ALPS compared to cognitively preserved patients and controls. Lower DTI-ALPS was associated with longer disease duration, greater disability, higher lesion burden, and microstructural abnormalities. Analyses further indicated that glymphatic dysfunction partially mediates the impact of CPV on cognitive domains ( 22 ). Xia et al. examined 1,351 cognitively impaired individuals across SCD, MCI, and AD and found that CP volume was significantly larger in AD than in SCD. CP enlargement was independently associated with worse MMSE performance both cross-sectionally and longitudinally. Mediation analyses revealed that PSMD partially explained the relationship between CP enlargement and cognitive decline, suggesting that white matter microstructural disruption contributes to CP-related cognitive impairment ( 23 ). Jeong et al. reported that CPV was significantly larger in patients along the AD continuum compared to healthy controls. Larger CPV was associated with worse global cognition (higher CDR-SOB) and poorer performance in memory and executive domains. Longitudinal analyses showed that higher CPV predicted faster cognitive decline in the dementia subgroup. CPV did not differ between nondementia and dementia subgroups but remained a meaningful prognostic marker for decline in established dementia ( 8 ). Xu et al. demonstrated that CPV enlargement emerges early in individuals with moderate white matter hyperintensities (WMHs), preceding detectable reductions in the DTI-ALPS index. Larger CPV correlated with poorer performance on MMSE, information processing speed, and executive function. CPV was strongly linked to lateral ventricular volume and inversely related to the DTI-ALPS index, suggesting an interplay between CP alterations, glymphatic dysfunction, and cognitive decline. Mediation analysis showed that DTI-ALPS partially mediated the association between CPV and processing speed ( 27 ). Umemura et al. found that the CPV/ICV ratio was significantly higher in individuals with MCI compared to cognitively healthy adults in a large community-dwelling cohort. CPV/ICV emerged as an independent predictor of MCI after adjusting for vascular and demographic risk factors. CPV correlated most strongly with lateral ventricular volume and showed additional associations with hippocampal and gray matter volumes. Higher CPV/ICV also corresponded to lower MMSE scores across the sample ( 15 ). Preziosa et al. demonstrated that patients with MS had significantly larger normalized CP volume than healthy controls. CP enlargement was an independent predictor of cognitive impairment and fatigue, highlighting its relevance as a biomarker for MS-related neurodegeneration. Findings underscore a potential role for CP pathology in both cognitive and fatigue symptomatology ( 13 ). Pearson et al., using ADNI data, found that individuals with progressive MCI exhibited larger right choroid plexus volume than those with stable MCI, accompanied by lower RAVLT-I scores. Right CP volume showed a linear association with memory performance when all participants were analyzed together. Although RAVLT-I alone provided the strongest predictive accuracy for progression, adding left CP volume modestly improved classification performance, suggesting complementary diagnostic utility ( 16 ). Jiang et al. showed that choroid plexus enlargement closely tracked AD pathology, cognitive impairment, and neuropsychiatric symptoms in a large prospective cohort. Larger CP volumes correlated with lower CSF Aβ42/Aβ40, worse cognitive performance (MMSE, MoCA), higher neuropsychiatric burden, and structural/perfusion abnormalities in cognition-related brain regions. CP volume outperformed several classical imaging biomarkers in identifying amyloid abnormalities and distinguishing MCI from healthy controls, and added diagnostic value when combined with hippocampal measures. Longitudinally, accelerated CP expansion predicted worsening neuropsychiatric symptoms independently of hippocampal atrophy ( 24 ). Hidaka et al. reported that larger CP volume was consistently associated with poorer cognitive performance (MMSE) in a large community sample of older adults. This association persisted after accounting for DESH-related CSF changes and brain parenchymal volume, indicating that CP volume reflects more than passive ventricular expansion. CP enlargement was also linked to vascular and metabolic risk factors including diabetes, smoking, higher BMI, WMHs, and enlarged perivascular spaces ( 18 ). He et al. demonstrated that larger choroid plexus volume in early PD was associated with lower CSF Aβ1–42 and faster decline across memory domains. Participants with higher CPV tertiles had more rapid deterioration in SDMT performance and multiple Hopkins Verbal Learning Test measures. Path analysis showed that the CSF Aβ1–42/α-syn ratio partially mediated the link between CP enlargement and five-year memory decline, supporting a mechanistic connection between CP pathology, protein dysregulation, and cognitive deterioration in PD ( 20 ). Bouhrara et al. found associations between reduced CP microstructural integrity (T1/T2 relaxation metrics) and plasma biomarkers of AD pathology, neurodegeneration, and neuroinflammation in cognitively unimpaired adults. Elevated pTau181, NfL, and GFAP corresponded to poorer CP tissue integrity, independent of demographic and vascular factors. These relationships were stronger in middle-aged and older adults, suggesting age-related vulnerability, and were not present in ventricular CSF regions, supporting a specific association with CP tissue rather than partial volume effects ( 10 ). Martinkova et al. showed that CP volume progressively increases over time and that this trajectory varies by sex, diagnostic status, and ApoE genotype. Females and ApoE ε4 homozygotes exhibited the most rapid annual CP growth, and converters to dementia showed substantially faster enlargement than cognitively stable individuals. CP volume increases were not fully explained by ventricular expansion, indicating a distinct pathological process. Findings suggest that longitudinal CP changes may serve as an early biomarker of disease progression, particularly in genetically or biologically vulnerable groups ( 25 ). In a longitudinal PD cohort, Jeong et al. found that larger CP volume was associated with poorer frontal/executive functioning at baseline and predicted higher risk of conversion to Parkinson’s disease dementia (PDD). During more than seven years of follow-up, converters exhibited significantly larger baseline CPV than non-converters. Mediation analysis indicated that the effect of CP enlargement on dementia risk operated primarily through its impact on executive dysfunction, highlighting CPV as a marker of cognitive vulnerability in PD ( 8 ). Choi et al. demonstrated that CP volume increases progressively across SCI, early MCI, late MCI, and AD, and strongly correlates with memory, executive function, and global cognition. CP volume was associated with multiple structural MRI markers—including larger ventricles, greater WMH burden, and smaller hippocampal and cortical gray matter volumes—and showed significant predictive value for cognitive impairment alongside hippocampal volume and APOE4 status. Permeability measures (Ktrans, Vp) correlated with CP volume but did not independently predict cognition, suggesting that structural rather than permeability changes are central in CP-related cognitive decline ( 14 ). 3.5. Summary of Overall Evidence Across the included studies, CPV consistently emerged as a structural marker linked with cognitive status across different neurological disorders. Multiple investigations demonstrated that CP enlargement corresponds to worse cognitive performance or accelerated cognitive decline, especially in the AD spectrum. Studies in PD reported both decreased CPV ( 26 ) and increased CPV ( 8 , 20 ) as predictors of cognitive deterioration, suggesting stage-dependent alterations. Evidence from MS ( 13 , 22 ), and white matter hyperintensity burden ( 27 ) similarly supported associations between CP pathology and cognitive dysfunction. 3.6. Associations Between CP Volume and Cognitive Function Across neurodegenerative and neuroinflammatory disorders, CPV demonstrated consistent associations with cognitive performance. In the AD spectrum, studies ( 8 , 14 , 16 , 23 , 24 ) showed that larger CPV was associated with poorer global cognition (e.g., MMSE, CDR-SOB), as well as memory and executive deficits. Longitudinal data ( 23 , 24 ) indicated that CP enlargement predicted faster cognitive decline. In PD, reduced CPV correlated with worse global cognition and accelerated decline in working memory and processing speed ( 26 ), while CP enlargement predicted declines in memory, attention, and increased risk of PDD ( 8 , 20 ). In MS, larger CPV was associated with deficits in processing speed, visuospatial memory, global cognition, and fatigue ( 13 , 22 ). Similarly, CP enlargement in vascular cognitive impairment was linked to reduced MMSE scores, slower processing speed, and weaker executive performance ( 27 ). 3.7. Mechanistic Evidence and Mediators Several studies provided mechanistic insights into how CP alterations may contribute to cognitive decline. In AD-related populations ( 23 , 24 ), CP enlargement was linked to lower CSF Aβ42/Aβ40 levels, with mediation analyses indicating that amyloid abnormalities partially explained the relationship between CPV and cognitive impairment. Conversely, CP enlargement also mediated the effect of amyloid pathology on cognitive performance, supporting a bidirectional relationship. In PD ( 26 ), one study identified Tau levels as a mediator between reduced CPV and cognitive decline, while another study ( 20 ) demonstrated that the CSF Aβ1–42/α-syn ratio partially mediated the impact of CP enlargement on five-year memory deterioration. In MS and WMH cohorts ( 22 , 27 ), the DTI-ALPS index partially mediated associations between CPV and processing speed or visuospatial functioning, supporting the role of glymphatic dysfunction as a mechanistic pathway. Disease-specific patterns of CPV and cognitive outcomes summarized in Table 2 . Table 2 Disease-Specific Patterns of Choroid Plexus Volume and Cognitive Outcomes Disease Category Pattern of CP Volume Alteration Associated Cognitive Outcomes Additional Imaging / Pathological Correlates AD, MCI, SCD Progressive CP enlargement across SCD → MCI → AD; faster CP growth in converters and APOE4 carriers Worse global cognition; deficits in memory and executive functions; accelerated cognitive decline Strong associations with amyloid pathology (↓Aβ42/Aβ40); correlations with ventricular enlargement and cortical/hippocampal atrophy; adds diagnostic value beyond classical MRI markers PD Early PD: reduced CPV; Later-stage PD: CP enlargement Reduced CPV → poorer global cognition & faster decline in working memory/processing speed; Enlarged CPV → faster memory decline, increased risk of PDD, mediated by executive dysfunction Link with Tau, Aβ1–42/α-syn ratio; CPV predicts dementia conversion MS CP enlargement especially in cognitively impaired MS patients Impairments in processing speed, visuospatial memory, global cognition; increased fatigue Reduced DTI-ALPS index (glymphatic dysfunction); widespread microstructural abnormalities; CPV is a strong ML predictor of cognitive impairment White Matter Hyperintensity Burden / Vascular Aging CP enlargement emerging in moderate WMH burden, preceding glymphatic dysfunction Lower MMSE; slowed processing speed; impaired executive functioning CPV correlated with ventricular enlargement; DTI-ALPS mediates part of CPV–processing speed link AD = Alzheimer’s disease; MCI = Mild cognitive impairment; SCD = Subjective cognitive decline; PD = Parkinson’s disease; PDD = Parkinson’s disease dementia; MS = Multiple sclerosis; WMH = White matter hyperintensity; CP = Choroid plexus; CPV = Choroid plexus volume; DTI-ALPS = Diffusion tensor imaging–analysis along the perivascular space; ML = Machine learning; Aβ = Amyloid beta; Aβ42/Aβ40 = Amyloid beta 42/40 ratio; Tau = Tau protein; α-syn = Alpha-synuclein; MMSE = Mini-Mental State Examination. 4. Discussion This systematic review synthesizes evidence across diverse neurological conditions and demonstrates that alterations in CPV are consistently associated with cognitive impairment and decline. Despite heterogeneity in clinical populations, imaging modalities, and cognitive assessments, a transdiagnostic pattern emerges: structural changes in the CP appear closely linked to both baseline cognitive status and longitudinal trajectories of cognitive decline. These results support the notion that the choroid plexus, traditionally viewed as a passive CSF-producing structure, plays a broader and functionally significant role in neurodegeneration, neuroinflammation, and cognitive vulnerability. Across AD, mild cognitive impairment, and subjective cognitive decline, CP enlargement has been consistently linked to poorer global cognition, executive dysfunction, and episodic memory impairment. Mechanistically, converging evidence suggests that CP enlargement reflects structural and functional abnormalities that impair CSF homeostasis and glymphatic clearance, thereby connecting upstream amyloid pathology to downstream cognitive decline. The CP plays a central role in regulating CSF dynamics and maintaining brain homeostasis ( 6 ), and physiological dysfunction along the AD continuum including stromal fibrosis, dystrophic calcification, vascular and basement membrane thickening, inflammation, and reduced CSF production has been associated with Aβ accumulation and tangle-like changes ( 28 , 29 ). Given that Aβ aggregation is a core pathological hallmark of AD strongly tied to clinical progression ( 30 ), mediation analyses demonstrate that CP volume mediates the association between CSF Aβ levels and cognitive impairment, supporting its role as a non-invasive surrogate marker of impaired Aβ clearance. CP enlargement also correlates with atrophy and reduced perfusion in cognition-related regions, reinforcing its relationship with neurodegenerative processes. In parallel, morphological CP alterations documented in individuals with mild cognitive impairment and AD ( 14 ) suggest that reduced CP capacity may indirectly contribute to memory vulnerability by disrupting CSF-mediated metabolic clearance, neuromodulator transport, and overall brain homeostasis ( 31 , 32 ). Chronic immune responses are known to occur in AD ( 33 ), and extensive evidence implicates the CP as a site of neuroinflammatory activity ( 34 , 35 ), with inflammation accompanying ChP volume changes in both mild cognitive impairment and AD ( 14 ). Collectively, these findings indicate that CP abnormalities reflect impaired CSF/Aβ clearance and neuroinflammatory burden, processes that likely contribute to neurodegeneration and cognitive decline across early and prodromal stages of the AD continuum. In PD, a more complex pattern emerged. De novo PD cohorts showed reduced CPV associated with worse cognition, whereas early and progressive PD cohorts exhibited CP enlargement predicting accelerated cognitive decline and higher risk for Parkinson’s disease dementia (PDD). Mechanistically, the link between choroid plexus enlargement and cognitive vulnerability in PD has been attributed to CP dysfunction and its downstream effects on CSF homeostasis and glymphatic clearance. Although the CP primarily regulates CSF production and composition, several lines of evidence indicate that CP dysfunction can disrupt CSF homeostasis and impair the efficiency of the glymphatic system, the brain’s waste drainage pathway ( 29 ). Impaired glymphatic flow may hinder the removal of harmful metabolites from the brain parenchyma ( 6 ), and experimental studies show that blocking glymphatic function accelerates α-synuclein aggregation in PD models ( 36 ). Clinical data also support glymphatic dysfunction in prodromal and clinical PD ( 37 , 38 ), and imaging markers of impaired waste clearance such as enlarged perivascular spaces in the basal ganglia have been associated with more severe degeneration of dopaminergic neurons ( 39 ). Furthermore, toxic protein accumulation may further disrupt glymphatic flow, creating a feedforward cycle of clearance failure and protein aggregation ( 40 ). Taken together, these findings suggest that pathological conditions associated with CP enlargement, such as impaired glymphatic waste removal, may facilitate neurodegenerative processes and preferentially impact the most vulnerable cognitive domain in PD—frontal and executive functioning. In MS and WMH-related vascular aging, CP enlargement was closely linked to cognitive impairment, particularly in processing speed and executive functioning. Mechanistically, CP enlargement in MS is thought to reflect a chronic pro-inflammatory state within the CNS, as the CP serves as a key interface between the peripheral immune system and the brain, functioning as a gateway for lymphocyte entry, CSF monitoring, and antigen presentation ( 41 , 42 ). Pathologic studies describe immune-cell accumulation within the CP stroma and vessels, including increased T lymphocytes, macrophages, dendritic cells, and granulocytes, along with upregulated vascular adhesion molecules ( 41 , 42 ). Structural abnormalities such as increased capillary permeability, basement membrane thickening, and loss of ependymal cilia have also been documented ( 43 ). Furthermore, hypoxia within the CP and subsequent dysregulation of the HIF-1 pathway may alter its secretory and neuroprotective functions ( 44 ). Together, these inflammatory and structural disturbances are proposed to contribute to demyelination, neuro-axonal loss, and impaired synaptic functioning, processes that play a substantial role in MS-related cognitive impairment. The present review integrates evidence across traditionally separate diagnostic domains, revealing consistent CP-cognition patterns that have not been previously synthesized at this scale. By incorporating findings from structural MRI, DTI-ALPS, PET, CSF biomarkers, plasma markers, and longitudinal cognitive testing, the review highlights the multidimensional role of the choroid plexus in brain health. Another strength is the identification of shared mechanistic pathways such as protein clearance, inflammation, and glymphatic dysfunction which provide unifying explanations for CP involvement across conditions. Several limitations must be acknowledged. First, substantial heterogeneity existed in MRI acquisition parameters, CP segmentation methods, and cognitive assessments. Second, many studies used cross-sectional designs, limiting causal inference. Third, although several studies adjusted for key confounders, residual confounding (e.g., vascular risk factors, genetic susceptibility, lifestyle variables) remains possible. Fourth, the direction of CPV changes varies by disease and stage, underscoring the need for standardized longitudinal protocols. Finally, mechanistic analyses (e.g., mediation models) were available only in select populations, limiting generalizability. This systematic review provides convergent evidence that CP alterations are robustly associated with cognitive impairment across multiple neurological conditions. CP volume whether enlarged or reduced reflects underlying disturbances in CSF dynamics, neuroinflammation, and protein clearance, and predicts cognitive trajectories in several disorders. These findings position the CP as a promising transdiagnostic biomarker and a potential mechanistic contributor to cognitive decline. Further longitudinal and mechanistic studies are needed to clarify causal pathways and evaluate the clinical utility of CP-based measures in diagnosis, prognosis, and therapeutic monitoring References Damkier HH, Brown PD, Praetorius J (2013) Cerebrospinal fluid secretion by the choroid plexus. Physiol Rev 93(4):1847–1892 Bitanihirwe BKY, Lizano P, Woo TW (2022) Deconstructing the functional neuroanatomy of the choroid plexus: an ontogenetic perspective for studying neurodevelopmental and neuropsychiatric disorders. Mol Psychiatry 27(9):3573–3582 Ghersi-Egea JF, Strazielle N, Catala M, Silva-Vargas V, Doetsch F, Engelhardt B (2018) Molecular anatomy and functions of the choroidal blood-cerebrospinal fluid barrier in health and disease. Acta Neuropathol 135(3):337–361 Lehtinen MK, Bjornsson CS, Dymecki SM, Gilbertson RJ, Holtzman DM, Monuki ES (2013) The choroid plexus and cerebrospinal fluid: emerging roles in development, disease, and therapy. J Neurosci 33(45):17553–17559 Spector R, Robert Snodgrass S, Johanson CE (2015) A balanced view of the cerebrospinal fluid composition and functions: Focus on adult humans. Exp Neurol 273:57–68 Christensen J, Li C, Mychasiuk R (2022) Choroid plexus function in neurological homeostasis and disorders: The awakening of the circadian clocks and orexins. J Cereb Blood Flow Metab 42(7):1163–1175 Badaut J, Ghersi-Egea J-F (2016) The choroid plexus and cerebrospinal fluid system: roles in neurodegenerative diseases. Elsevier, The Choroid Plexus and Cerebrospinal Fluid, pp 129–154 Jeong SH, Park CJ, Jeong HJ, Sunwoo MK, Ahn SS, Lee SK et al (2023) Association of choroid plexus volume with motor symptoms and dopaminergic degeneration in Parkinson's disease. J Neurol Neurosurg Psychiatry 94(12):1047–1055 Wu Y-C, Bogale TA, Koistinaho J, Pizzi M, Rolova T, Bellucci A (2024) The contribution of β-amyloid, Tau and α-synuclein to blood–brain barrier damage in neurodegenerative disorders. Acta Neuropathol 147(1):39 Bouhrara M, Walker KA, Alisch JSR, Gong Z, Mazucanti CH, Lewis A et al (2024) Association of Plasma Markers of Alzheimer's Disease, Neurodegeneration, and Neuroinflammation with the Choroid Plexus Integrity in Aging. Aging Dis 15(5):2230–2240 Klistorner S, Barnett MH, Parratt J, Yiannikas C, Graham SL, Klistorner A (2022) Choroid plexus volume in multiple sclerosis predicts expansion of chronic lesions and brain atrophy. Ann Clin Transl Neurol 9(10):1528–1537 Bergsland N, Dwyer MG, Jakimovski D, Tavazzi E, Benedict RHB, Weinstock-Guttman B, Zivadinov R (2023) Association of Choroid Plexus Inflammation on MRI With Clinical Disability Progression Over 5 Years in Patients With Multiple Sclerosis. Neurology 100(9):e911–e20 Preziosa P, Pagani E, Meani A, Storelli L, Margoni M, Yudin Y et al (2024) Chronic Active Lesions and Larger Choroid Plexus Explain Cognition and Fatigue in Multiple Sclerosis. Neurol Neuroimmunol Neuroinflamm 11(2):e200205 Choi JD, Moon Y, Kim H-J, Yim Y, Lee S, Moon W-J (2022) Choroid plexus volume and permeability at brain MRI within the Alzheimer disease clinical spectrum. Radiology 304(3):635–645 Umemura Y, Watanabe K, Kasai S, Ide S, Ishimoto Y, Sasaki M et al (2024) Choroid plexus enlargement in mild cognitive impairment on MRI: a large cohort study. Eur Radiol 34(8):5297–5304 Pearson MJ, Wagstaff R, Williams RJ (2024) Alzheimer's Disease Neuroimaging I. Choroid plexus volumes and auditory verbal learning scores are associated with conversion from mild cognitive impairment to Alzheimer's disease. Brain Behav 14(7):e3611 Alisch JSR, Kiely M, Triebswetter C, Alsameen MH, Gong Z, Khattar N et al (2021) Characterization of Age-Related Differences in the Human Choroid Plexus Volume, Microstructural Integrity, and Blood Perfusion Using Multiparameter Magnetic Resonance Imaging. Front Aging Neurosci 13:734992 Hidaka Y, Hashimoto M, Suehiro T, Fukuhara R, Ishikawa T, Tsunoda N et al (2024) Association between choroid plexus volume and cognitive function in community-dwelling older adults without dementia: a population-based cross-sectional analysis. Fluids Barriers CNS 21(1):101 Gong Z, Bilgel M, Faulkner ME, Bae J, Laporte JP, Guo A et al (2024) Associations Between Choroid Plexus Integrity and Cognitive Decline in Aging: Insights from Advanced MRI Analysis. Alzheimer's Dement 20:e093777 He P, Gao Y, Shi L, Li Y, Qiu Y, Feng S et al (2024) The association of CSF biomarkers and cognitive decline with choroid plexus volume in early Parkinson's disease. Parkinsonism Relat Disord 120:105987 Lizano P, Lutz O, Ling G, Lee AM, Eum S, Bishop JR et al (2019) Association of Choroid Plexus Enlargement With Cognitive, Inflammatory, and Structural Phenotypes Across the Psychosis Spectrum. Am J Psychiatry 176(7):564–572 Wang Z, Xu X, Jia F, Ren W, Wang J, Liu Y et al (2025) Glymphatic dysfunction in relapsing-remitting multiple sclerosis and its association with brain structural damage and cognitive impairment. Mult Scler Relat Disord 100:106531 Xia H, Feng Y, Zhu H, Yang D, Wang C, Wang Z et al (2025) Association of choroid plexus volume with white matter microstructure, glymphatic function, and peripheral systemic inflammation in Alzheimer's disease. Transl Psychiatry 15(1):238 Jiang J, Zhuo Z, Wang A, Li W, Jiang S, Duan Y et al (2024) Choroid plexus volume as a novel candidate neuroimaging marker of the Alzheimer’s continuum. Alzheimers Res Ther 16(1):149 Novakova Martinkova J, Ferretti MT, Ferrari A, Lerch O, Matuskova V, Secnik J et al (2023) Longitudinal progression of choroid plexus enlargement is associated with female sex, cognitive decline and ApoE E4 homozygote status. Front Psychiatry 14:1039239 Yang D, Zhu B, Ren J, Wang L, Huang H, Wu Z et al (2025) Investigating the association between choroid plexus volume and the pathogenesis of Parkinson's disease. Parkinsonism Relat Disord. :107987 Xu Y, Wang M, Li X, Lu T, Wang Y, Zhang X et al (2024) Glymphatic dysfunction mediates the influence of choroid plexus enlargement on information processing speed in patients with white matter hyperintensities. Cereb Cortex 34(6):bhae265 Shen X, Xia L, Liu L, Jiang H, Shannahan J, Du Y, Zheng W (2020) Altered clearance of beta-amyloid from the cerebrospinal fluid following subchronic lead exposure in rats: Roles of RAGE and LRP1 in the choroid plexus. J Trace Elem Med Biol 61:126520 Municio C, Carrero L, Antequera D, Carro E (2023) Choroid plexus aquaporins in CSF homeostasis and the glymphatic system: their relevance for Alzheimer’s disease. Int J Mol Sci 24(1):878 Hampel H, Hardy J, Blennow K, Chen C, Perry G, Kim SH et al (2021) The Amyloid-beta Pathway in Alzheimer's Disease. Mol Psychiatry 26(10):5481–5503 Bjorefeldt A, Illes S, Zetterberg H, Hanse E (2018) Neuromodulation via the Cerebrospinal Fluid: Insights from Recent in Vitro Studies. Front Neural Circuits 12:5 Kelley DH (2021) Brain cerebrospinal fluid flow. Phys Rev Fluids 6(7):070501 Kinney JW, Bemiller SM, Murtishaw AS, Leisgang AM, Salazar AM, Lamb BT (2018) Inflammation as a central mechanism in Alzheimer's disease. Alzheimer's & Dementia: Translational Research & Clinical Interventions. ;4:575 – 90 Giao T, Teixeira T, Almeida MR, Cardoso I (2022) Choroid Plexus in Alzheimer's Disease-The Current State of Knowledge. Biomedicines 10(2):224 Strominger I, Elyahu Y, Berner O, Reckhow J, Mittal K, Nemirovsky A, Monsonego A (2018) The choroid plexus functions as a niche for T-cell stimulation within the central nervous system. Front Immunol 9:1066 Zou W, Pu T, Feng W, Lu M, Zheng Y, Du R et al (2019) Blocking meningeal lymphatic drainage aggravates Parkinson's disease-like pathology in mice overexpressing mutated alpha-synuclein. Transl Neurodegener 8(1):7 Si X, Guo T, Wang Z, Fang Y, Gu L, Cao L et al (2022) Neuroimaging evidence of glymphatic system dysfunction in possible REM sleep behavior disorder and Parkinson's disease. NPJ Parkinsons Dis 8(1):54 Ding XB, Wang XX, Xia DH, Liu H, Tian HY, Fu Y et al (2021) Impaired meningeal lymphatic drainage in patients with idiopathic Parkinson's disease. Nat Med 27(3):411–418 Chung SJ, Yoo HS, Shin NY, Park YW, Lee HS, Hong JM et al (2021) Perivascular Spaces in the Basal Ganglia and Long-term Motor Prognosis in Newly Diagnosed Parkinson Disease. Neurology 96(16):e2121–e31 Peng W, Achariyar TM, Li B, Liao Y, Mestre H, Hitomi E et al (2016) Suppression of glymphatic fluid transport in a mouse model of Alzheimer's disease. Neurobiol Dis 93:215–225 Rodríguez-Lorenzo S, Konings J, Van Der Pol S, Kamermans A, Amor S, Van Horssen J et al (2020) Inflammation of the choroid plexus in progressive multiple sclerosis: accumulation of granulocytes and T cells. Acta Neuropathol Commun 8(1):9 Vercellino M, Votta B, Condello C, Piacentino C, Romagnolo A, Merola A et al (2008) Involvement of the choroid plexus in multiple sclerosis autoimmune inflammation: a neuropathological study. J Neuroimmunol 199(1–2):133–141 Jimenez AJ, Dominguez-Pinos MD, Guerra MM, Fernandez-Llebrez P, Perez-Figares JM (2014) Structure and function of the ependymal barrier and diseases associated with ependyma disruption. Tissue Barriers 2(1):e28426 Rodriguez-Lorenzo S, Ferreira Francisco DM, Vos R, van Het Hof B, Rijnsburger M, Schroten H et al (2020) Altered secretory and neuroprotective function of the choroid plexus in progressive multiple sclerosis. Acta Neuropathol Commun 8(1):35 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8854166","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":589787192,"identity":"7abfa799-088d-4f2f-8c20-45b0e3d51731","order_by":0,"name":"Shahab Lotfinia","email":"data:image/png;base64,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","orcid":"","institution":"Shahid Beheshti University of Medical Science","correspondingAuthor":true,"prefix":"","firstName":"Shahab","middleName":"","lastName":"Lotfinia","suffix":""},{"id":589787193,"identity":"ea5991ca-aeda-4cad-9f78-96fb3f1de0de","order_by":1,"name":"Maryam Moghbel Baerz","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Science","correspondingAuthor":false,"prefix":"","firstName":"Maryam","middleName":"Moghbel","lastName":"Baerz","suffix":""},{"id":589787194,"identity":"cebc23a6-ee4a-4edb-9add-8e47e70c2c5f","order_by":2,"name":"Mahrooz Roozneh","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Science","correspondingAuthor":false,"prefix":"","firstName":"Mahrooz","middleName":"","lastName":"Roozneh","suffix":""},{"id":589787195,"identity":"0f6f0df8-4556-405a-9314-b9bfc5dd0a1a","order_by":3,"name":"Mehrdad Roozbeh","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Science","correspondingAuthor":false,"prefix":"","firstName":"Mehrdad","middleName":"","lastName":"Roozbeh","suffix":""},{"id":589787196,"identity":"4dbeb11d-9050-4863-b4d3-f654c9c3408e","order_by":4,"name":"Nima Naderi","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Science","correspondingAuthor":false,"prefix":"","firstName":"Nima","middleName":"","lastName":"Naderi","suffix":""}],"badges":[],"createdAt":"2026-02-11 17:14:31","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8854166/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8854166/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102598301,"identity":"ec84ab89-9afd-498f-9623-40afd20e1e01","added_by":"auto","created_at":"2026-02-13 12:29:07","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36085,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of Study\u003c/p\u003e","description":"","filename":"groupimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8854166/v1/f5d094d10e05d745ff1ed90c.jpeg"},{"id":102747465,"identity":"8918dcee-95a9-4bcf-be36-16ae87b4b466","added_by":"auto","created_at":"2026-02-16 09:04:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":774026,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8854166/v1/8e0eb1c4-909c-4a4b-aa4a-737e63fd0721.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eThe Role of the Choroid Plexus in Cognitive Impairment Across Neurological Disorders: A Systematic Review\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe choroid plexus (CP) is a veil-like, sheet-like structure derived from the leptomeninges and ependymal epithelium, located within the ventricular system and composed of epithelial layers, blood vessels, fibroblasts, and immune cells (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). It produces approximately 60\u0026ndash;80% of cerebrospinal fluid (CSF), forms the blood\u0026ndash;CSF barrier, and plays a central role in maintaining central nervous system (CNS) homeostasis by regulating immune cell trafficking, inflammatory responses, circadian rhythms, gut\u0026ndash;brain communication, and cognitive processes (\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Beyond CSF secretion, the CP contributes to the clearance of neurotoxic waste products, and alterations in choroid plexus volume (CPV) have been increasingly implicated in neurodegenerative disease mechanisms, including Parkinson\u0026rsquo;s disease (PD) (\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). CP dysfunction may exacerbate the accumulation of pathological proteins such as α-synuclein (α-syn), amyloid beta (Aβ), and hyperphosphorylated Tau, molecules strongly associated with PD-related cognitive decline (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Furthermore, CP enlargement has been linked to higher relapse rates, chronic lesion expansion, inflammation, accelerated brain atrophy, and progression of disability in neuroinflammatory disorders, with mounting evidence associating CP enlargement with multiple sclerosis (MS)-related cognitive dysfunction (\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Beyond these disease-specific associations, recent research has increasingly focused on CP volume as an indicator of cognitive function.\u003c/p\u003e \u003cp\u003eWith the advancement of structural magnetic resonance imaging (MRI), choroid plexus volume has gained attention as a potential marker of cognitive function (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Larger CP volumes are generally associated with greater cognitive impairment, including mild cognitive impairment (MCI) and progression toward Alzheimer\u0026rsquo;s disease (AD) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). CP enlargement has also been reported in cognitively unimpaired adults, where age-related increases in CP volume appear to correlate with lower global cognitive performance (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Longitudinal studies further demonstrate that greater CP volume in older adults predicts faster cognitive decline, suggesting its potential as an early biomarker of age-related cognitive vulnerability (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAcross neurological disorders, this relationship extends beyond healthy aging, as numerous studies have indicated associations between CP volume and various cognitive domains. In MS, increased CP volume has been linked to both cognitive impairment and fatigue (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). In AD, CP volume is associated with executive dysfunction and elevated dementia risk. Similarly, in early-stage PD, CP volume shows negative correlations with cognitive performance (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). A negative association between CP volume and cognitive test scores has also been observed in first-degree relatives of individuals with schizophrenia, suggesting potential relevance beyond classical neurodegenerative disorders (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Despite these emerging findings, a comprehensive synthesis of CP volume\u0026ndash;cognition associations across neurological disorders is lacking.\u003c/p\u003e \u003cp\u003eThe primary aim of this study is to systematically review and synthesize the existing evidence on the relationship between choroid plexus volume and cognitive function across neurological disorders. Specifically, we evaluate how variations in CP volume relate to cognitive impairment in conditions such as PD, MS, and AD, as well as in cognitively unimpaired adults. Additionally, we compare CP cognition associations across different patient populations and assess the potential of CP volume as an early biomarker of cognitive decline. By addressing these objectives, this review seeks to clarify the contribution of CP alterations to cognitive dysfunction and provide insights for future clinical and neuroimaging research.\u003c/p\u003e"},{"header":"2. Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Protocol Registration\u003c/h2\u003e \u003cp\u003e This systematic review was designed and reported in accordance with the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines. The study protocol was prospectively registered in the International Prospective Register of Systematic Reviews (PROSPERO) (Registration ID:). Ethical approval for this study was obtained from the Shahid Beheshti University of Medical Sciences Ethics Committee (Approval Code:). Flow diagram of study summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Eligibility criteria\u003c/h2\u003e \u003cp\u003eEligible studies included original human research that employed structural magnetic resonance imaging (MRI) to assess CPV or morphology. The population of interest consisted of individuals diagnosed with neurological disorders such as AD, MS, PD, traumatic brain injury, or stroke, with comparisons made to healthy controls or other clinical groups.\u003c/p\u003e \u003cp\u003eTo be included, studies were required to report CPV or structural alterations in association with cognitive performance measures such as the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), or domain-specific assessments of memory, attention, or executive function. Only articles published in English were considered eligible.\u003c/p\u003e \u003cp\u003eExclusion criteria included case reports, conference abstracts lacking full text, review articles, and editorials. Studies involving animal or in vitro models, those failing to report CP volume or providing insufficient data for extraction, as well as duplicate publications or overlapping datasets, were excluded.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Search Strategy\u003c/h2\u003e \u003cp\u003eA systematic search was conducted in PubMed, Scopus, Web of Science, Embase, and PsycINFO up to November 2025. The search strategy combined Medical Subject Headings (MeSH) and free-text terms related to \u0026ldquo;choroid plexus\u0026rdquo; OR \u0026ldquo;CSF barrier,\u0026rdquo; \u0026ldquo;volume\u0026rdquo; OR \u0026ldquo;morphology\u0026rdquo; OR \u0026ldquo;atrophy\u0026rdquo; OR \u0026ldquo;enlargement,\u0026rdquo; \u0026ldquo;cognitive impairment\u0026rdquo; OR \u0026ldquo;memory\u0026rdquo; OR \u0026ldquo;attention\u0026rdquo; OR \u0026ldquo;executive function,\u0026rdquo; and \u0026ldquo;neurological disorders\u0026rdquo; along with disorder-specific terms such as Alzheimer\u0026rsquo;s disease, schizophrenia, multiple sclerosis, Parkinson\u0026rsquo;s disease, and depression.\u003c/p\u003e \u003cp\u003eThe search strategy was adapted for each database. In addition, reference lists of eligible articles and relevant reviews were manually screened to identify additional studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Data Extraction\u003c/h2\u003e \u003cp\u003eTwo independent reviewers extracted data using a standardized extraction form. Extracted information included study characteristics (first author, year, country), study design, and sample size, as well as population characteristics such as diagnosis, age, sex, and disease severity. Only studies employing structural MRI for CPV assessment were included.\u003c/p\u003e \u003cp\u003eOutcomes of interest comprised CPV metrics, cognitive performance measures, and reported associations between CP volume and cognition. Discrepancies between reviewers were resolved through discussion or consultation with a third reviewer when necessary.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Quality Assessment\u003c/h2\u003e \u003cp\u003eThe methodological quality of the included studies was evaluated using the Newcastle-Ottawa Scale (NOS) for observational research. This tool assesses studies across three domains: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) selection of study groups, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) comparability of groups, and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) outcome assessment. Each study was classified as low, moderate, or high quality based on its NOS score. When sufficient studies were available, publication bias was assessed using funnel plots and Egger's regression test.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Result","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Study Selection\u003c/h2\u003e \u003cp\u003eThe initial database search across PubMed, Web of Science, and Scopus identified 412 records. After removing 102 duplicates, 310 articles remained for title and abstract screening. Of these, 256 records were excluded for not meeting the eligibility criteria, including studies unrelated to choroid plexus volume, absence of cognitive assessments, use of animal or in vitro models, review papers, conference abstracts without full text, or articles lacking relevant neuroimaging data. A total of 54 full-text articles were retrieved for detailed evaluation. Following full-text assessment, 39 studies were excluded due to insufficient quantitative data, absence of structural MRI\u0026ndash;based CP volume measurements, irrelevant outcomes, or non-original study design. Ultimately, 15 studies met the inclusion criteria and were included in the final systematic review.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Study Characteristics\u003c/h2\u003e \u003cp\u003eA total of 17 studies met the inclusion criteria (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and were incorporated into this review. These studies encompassed a broad range of populations, including individuals with cognitive impairment, neurodegenerative or neuroinflammatory disorders, and healthy controls. Sample sizes varied considerably across investigations from small single-center cohorts (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) to large multicenter datasets exceeding 1,000 participants (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Participant ages similarly ranged widely, from mid-30s in MS cohorts (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) to over 77 years in mild cognitive impairment (MCI) and Alzheimer\u0026rsquo;s disease (AD) samples (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe included studies represented a diverse spectrum of clinical populations, such as AD (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), mild cognitive impairment (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), subjective cognitive decline (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), PD (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), MS (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), and individuals with varying burdens of white matter hyperintensities (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Most studies also included healthy control groups to facilitate comparative analyses. Neuropsychological assessments varied substantially across studies. The Mini-Mental State Examination (MMSE) was the most frequently reported cognitive screening instrument (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Other commonly used measures included the Montreal Cognitive Assessment (MoCA) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) and the Brief Repeatable Battery of Neuropsychological Tests (BRB-N) in MS populations (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Risk of Bias / Quality Assessment\u003c/h2\u003e \u003cp\u003eThe methodological quality of the included studies was assessed using the Newcastle\u0026ndash;Ottawa Scale (NOS) for observational research. Overall study quality ranged from moderate to high. Of the 17 included studies, 11 were rated as high quality (NOS\u0026thinsp;\u0026ge;\u0026thinsp;7), while 4 were rated as moderate quality (NOS 5\u0026ndash;6). No study received a low-quality rating. Most investigations demonstrated adequate representativeness of the study population and appropriate comparability between groups, particularly in studies that included both clinical populations and healthy controls. Selection bias was minimized in the majority of studies through the use of standardized diagnostic criteria for AD, mild cognitive impairment, PD, MS, and subjective cognitive decline. Nonetheless, a subset of studies provided limited information on recruitment procedures, which may restrict the generalizability of their findings. Regarding comparability, most studies adjusted or stratified analyses for key demographic confounders such as age and sex. Cognitive function was measured using validated instruments, including the MMSE, MoCA, BRB-N, and various comprehensive neuropsychological batteries, thereby reducing the likelihood of measurement bias. However, substantial variability in the type, depth, and scope of cognitive assessments across studies introduces a potential source of heterogeneity in the reported findings.\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\u003eCharacteristics of included studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipants (male)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCognitive test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXia et al 2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAD\u0026thinsp;=\u0026thinsp;248 (139)\u003c/p\u003e \u003cp\u003eMCI\u0026thinsp;=\u0026thinsp;761 (420)\u003c/p\u003e \u003cp\u003eSCD\u0026thinsp;=\u0026thinsp;344 (131)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAD\u0026thinsp;=\u0026thinsp;74.36\u0026thinsp;\u0026plusmn;\u0026thinsp;8.19\u003c/p\u003e \u003cp\u003eMCI\u0026thinsp;=\u0026thinsp;71.82\u0026thinsp;\u0026plusmn;\u0026thinsp;7.56\u003c/p\u003e \u003cp\u003eSCD\u0026thinsp;=\u0026thinsp;70.69\u0026thinsp;\u0026plusmn;\u0026thinsp;6.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWang et al 2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMS\u0026thinsp;=\u0026thinsp;77 (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;44 (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMS\u0026thinsp;=\u0026thinsp;31 (m)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;28 (m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBRB-N\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXu 2024 et al\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere WMHs\u0026thinsp;=\u0026thinsp;28 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eModerate WMHs\u0026thinsp;=\u0026thinsp;62 (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eMild WMHs\u0026thinsp;=\u0026thinsp;116 (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;43 (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSevere WMHs\u0026thinsp;=\u0026thinsp;69.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e \u003cp\u003eModerate WMHs\u0026thinsp;=\u0026thinsp;71.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3\u003c/p\u003e \u003cp\u003eMild WMHs\u0026thinsp;=\u0026thinsp;66.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;61.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003cp\u003eneuropsychological battery\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreziosa et al 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMS\u0026thinsp;=\u0026thinsp;129 (56)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;73 (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMS\u0026thinsp;=\u0026thinsp;43.3 (11.1)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;41 (12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBRB-N\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePearson et al 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epMCI\u0026thinsp;=\u0026thinsp;115 (62)\u003c/p\u003e \u003cp\u003esMCI\u0026thinsp;=\u0026thinsp;338 (200)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epMCI\u0026thinsp;=\u0026thinsp;73.76 (7.62)\u003c/p\u003e \u003cp\u003esMCI\u0026thinsp;=\u0026thinsp;72.70 (7.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRAVLT-I\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJiang et al 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAD\u0026thinsp;=\u0026thinsp;228 (95)\u003c/p\u003e \u003cp\u003eMCI\u0026thinsp;=\u0026thinsp;269 (101)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;110 (48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAD\u0026thinsp;=\u0026thinsp;70.04 (8.96)\u003c/p\u003e \u003cp\u003eMCI\u0026thinsp;=\u0026thinsp;64.83 (7.61)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;60.44 (7.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003cp\u003eMoCA\u003c/p\u003e \u003cp\u003eNPI\u003c/p\u003e \u003cp\u003eADL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHidaka et al 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMCI\u0026thinsp;=\u0026thinsp;226 (108)\u003c/p\u003e \u003cp\u003enonMCI\u0026thinsp;=\u0026thinsp;1144 (417)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMCI\u0026thinsp;=\u0026thinsp;77.9 (6.4)\u003c/p\u003e \u003cp\u003enonMCI\u0026thinsp;=\u0026thinsp;73.1 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChoi et al 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAD\u0026thinsp;=\u0026thinsp;147 (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eLate MCI\u0026thinsp;=\u0026thinsp;149 (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eEarly MCI\u0026thinsp;=\u0026thinsp;158 (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eSCI\u0026thinsp;=\u0026thinsp;78 (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAD\u0026thinsp;=\u0026thinsp;76 (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eLate MCI\u0026thinsp;=\u0026thinsp;73 (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eEarly MCI\u0026thinsp;=\u0026thinsp;70 (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eSCI\u0026thinsp;=\u0026thinsp;69 (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJeong et al 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePD\u0026thinsp;=\u0026thinsp;240 (119)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;80 (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePD\u0026thinsp;=\u0026thinsp;67.89 (7.88)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;66.64 (9.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eK-BNT\u003c/p\u003e \u003cp\u003eRCFT\u003c/p\u003e \u003cp\u003eSVLT\u003c/p\u003e \u003cp\u003eCOWAT\u003c/p\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYang et al 2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePD\u0026thinsp;=\u0026thinsp;236\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePD=\u003c/p\u003e \u003cp\u003eHC=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMoCA\u003c/p\u003e \u003cp\u003eLNS\u003c/p\u003e \u003cp\u003eSDMT\u003c/p\u003e \u003cp\u003eHVLT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUmemura et al 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMCI\u0026thinsp;=\u0026thinsp;218 (120)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;1904 (703)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMCI\u0026thinsp;=\u0026thinsp;72 (69\u0026ndash;76)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;69 (66\u0026ndash;73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHe et al 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLowest tertile group\u0026thinsp;=\u0026thinsp;32 (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eMiddle tertile group\u0026thinsp;=\u0026thinsp;31 (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eUpper tertile group\u0026thinsp;=\u0026thinsp;32 (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLowest tertile group\u0026thinsp;=\u0026thinsp;54.4 (8.2)\u003c/p\u003e \u003cp\u003eMiddle tertile group\u0026thinsp;=\u0026thinsp;59.9 (7.2)\u003c/p\u003e \u003cp\u003eUpper tertile group\u0026thinsp;=\u0026thinsp;65.8 (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMoCA\u003c/p\u003e \u003cp\u003eLNS\u003c/p\u003e \u003cp\u003eSDMT\u003c/p\u003e \u003cp\u003eSFT\u003c/p\u003e \u003cp\u003eHVLT\u003c/p\u003e \u003cp\u003eJLO\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBouhrara et al 2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108 (57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.7 (20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJeong et al 2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAD-D\u0026thinsp;=\u0026thinsp;77 (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAD-nD\u0026thinsp;=\u0026thinsp;126 (53)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;82 (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAD-D\u0026thinsp;=\u0026thinsp;76.31 (6.74)\u003c/p\u003e \u003cp\u003eAD-nD\u0026thinsp;=\u0026thinsp;74.94 (7.23)\u003c/p\u003e \u003cp\u003eHC\u0026thinsp;=\u0026thinsp;66.46 (9.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMartinkova et al 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCN\u0026thinsp;=\u0026thinsp;188 (83)\u003c/p\u003e \u003cp\u003eMCI\u0026thinsp;=\u0026thinsp;239 (131)\u003c/p\u003e \u003cp\u003eAD\u0026thinsp;=\u0026thinsp;88 (50)\u003c/p\u003e \u003cp\u003eConvert\u0026thinsp;=\u0026thinsp;98 (54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCN\u0026thinsp;=\u0026thinsp;72.62 (6.57)\u003c/p\u003e \u003cp\u003eMCI\u0026thinsp;=\u0026thinsp;71.88 (7.39)\u003c/p\u003e \u003cp\u003eAD\u0026thinsp;=\u0026thinsp;74.09 (8.03)\u003c/p\u003e \u003cp\u003eConvert\u0026thinsp;=\u0026thinsp;73.53 (7.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMMSE\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\u003eAD\u0026thinsp;=\u0026thinsp;Alzheimer\u0026rsquo;s disease; MCI\u0026thinsp;=\u0026thinsp;Mild cognitive impairment; SCD\u0026thinsp;=\u0026thinsp;Subjective cognitive decline; MS\u0026thinsp;=\u0026thinsp;Multiple sclerosis; HC\u0026thinsp;=\u0026thinsp;Healthy controls; WMHs\u0026thinsp;=\u0026thinsp;White matter hyperintensities; pMCI\u0026thinsp;=\u0026thinsp;Progressive MCI; sMCI\u0026thinsp;=\u0026thinsp;Stable MCI; SCI\u0026thinsp;=\u0026thinsp;Subjective cognitive impairment; PD\u0026thinsp;=\u0026thinsp;Parkinson\u0026rsquo;s disease; CN\u0026thinsp;=\u0026thinsp;Cognitively normal; Convert\u0026thinsp;=\u0026thinsp;MCI converters to AD; AD-D\u0026thinsp;=\u0026thinsp;AD with dementia; AD-nD\u0026thinsp;=\u0026thinsp;AD without dementia. Cognitive Tests: MMSE\u0026thinsp;=\u0026thinsp;Mini-Mental State Examination; MoCA\u0026thinsp;=\u0026thinsp;Montreal Cognitive Assessment; ACE-R\u0026thinsp;=\u0026thinsp;Addenbrooke\u0026rsquo;s Cognitive Examination\u0026ndash;Revised; BRB-N\u0026thinsp;=\u0026thinsp;Brief Repeatable Battery of Neuropsychological Tests; RAVLT-I\u0026thinsp;=\u0026thinsp;Rey Auditory Verbal Learning Test\u0026ndash;Immediate recall; NPI\u0026thinsp;=\u0026thinsp;Neuropsychiatric Inventory; ADL\u0026thinsp;=\u0026thinsp;Activities of Daily Living; K-BNT\u0026thinsp;=\u0026thinsp;Korean version of the Boston Naming Test; RCFT\u0026thinsp;=\u0026thinsp;Rey Complex Figure Test; SVLT\u0026thinsp;=\u0026thinsp;Seoul Verbal Learning Test; COWAT\u0026thinsp;=\u0026thinsp;Controlled Oral Word Association Test; LNS\u0026thinsp;=\u0026thinsp;Letter\u0026ndash;Number Sequencing; SDMT\u0026thinsp;=\u0026thinsp;Symbol Digit Modalities Test; HVLT\u0026thinsp;=\u0026thinsp;Hopkins Verbal Learning Test; SFT\u0026thinsp;=\u0026thinsp;Semantic Fluency Test; JLO\u0026thinsp;=\u0026thinsp;Judgment of Line Orientation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Details of study\u0026rsquo;s findings\u003c/h2\u003e \u003cp\u003eYang et al. showed that CPV is a meaningful structural correlate of both motor and cognitive deficits in newly diagnosed, untreated PD. CPV was significantly reduced in PD patients compared to matched controls, and lower CPV was strongly associated with more severe motor impairment (higher MDS-UPDRS scores) and poorer global cognition (lower MoCA scores). Longitudinal follow-up demonstrated that smaller CPV predicted faster decline in working memory and processing speed (LNS and SDMT). Mediation analyses further indicated that Tau protein levels partly explained the link between CPV reduction and cognitive deterioration (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWang et al. showed in relapsing\u0026ndash;remitting MS (RRMS), glymphatic dysfunction indexed by enlarged CPV and reduced DTI-ALPS values. Patients with cognitive impairment showed greater CPV and lower DTI-ALPS compared to cognitively preserved patients and controls. Lower DTI-ALPS was associated with longer disease duration, greater disability, higher lesion burden, and microstructural abnormalities. Analyses further indicated that glymphatic dysfunction partially mediates the impact of CPV on cognitive domains (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eXia et al. examined 1,351 cognitively impaired individuals across SCD, MCI, and AD and found that CP volume was significantly larger in AD than in SCD. CP enlargement was independently associated with worse MMSE performance both cross-sectionally and longitudinally. Mediation analyses revealed that PSMD partially explained the relationship between CP enlargement and cognitive decline, suggesting that white matter microstructural disruption contributes to CP-related cognitive impairment (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eJeong et al. reported that CPV was significantly larger in patients along the AD continuum compared to healthy controls. Larger CPV was associated with worse global cognition (higher CDR-SOB) and poorer performance in memory and executive domains. Longitudinal analyses showed that higher CPV predicted faster cognitive decline in the dementia subgroup. CPV did not differ between nondementia and dementia subgroups but remained a meaningful prognostic marker for decline in established dementia (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eXu et al. demonstrated that CPV enlargement emerges early in individuals with moderate white matter hyperintensities (WMHs), preceding detectable reductions in the DTI-ALPS index. Larger CPV correlated with poorer performance on MMSE, information processing speed, and executive function. CPV was strongly linked to lateral ventricular volume and inversely related to the DTI-ALPS index, suggesting an interplay between CP alterations, glymphatic dysfunction, and cognitive decline. Mediation analysis showed that DTI-ALPS partially mediated the association between CPV and processing speed (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUmemura et al. found that the CPV/ICV ratio was significantly higher in individuals with MCI compared to cognitively healthy adults in a large community-dwelling cohort. CPV/ICV emerged as an independent predictor of MCI after adjusting for vascular and demographic risk factors. CPV correlated most strongly with lateral ventricular volume and showed additional associations with hippocampal and gray matter volumes. Higher CPV/ICV also corresponded to lower MMSE scores across the sample (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePreziosa et al. demonstrated that patients with MS had significantly larger normalized CP volume than healthy controls. CP enlargement was an independent predictor of cognitive impairment and fatigue, highlighting its relevance as a biomarker for MS-related neurodegeneration. Findings underscore a potential role for CP pathology in both cognitive and fatigue symptomatology (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePearson et al., using ADNI data, found that individuals with progressive MCI exhibited larger right choroid plexus volume than those with stable MCI, accompanied by lower RAVLT-I scores. Right CP volume showed a linear association with memory performance when all participants were analyzed together. Although RAVLT-I alone provided the strongest predictive accuracy for progression, adding left CP volume modestly improved classification performance, suggesting complementary diagnostic utility (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eJiang et al. showed that choroid plexus enlargement closely tracked AD pathology, cognitive impairment, and neuropsychiatric symptoms in a large prospective cohort. Larger CP volumes correlated with lower CSF Aβ42/Aβ40, worse cognitive performance (MMSE, MoCA), higher neuropsychiatric burden, and structural/perfusion abnormalities in cognition-related brain regions. CP volume outperformed several classical imaging biomarkers in identifying amyloid abnormalities and distinguishing MCI from healthy controls, and added diagnostic value when combined with hippocampal measures. Longitudinally, accelerated CP expansion predicted worsening neuropsychiatric symptoms independently of hippocampal atrophy (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHidaka et al. reported that larger CP volume was consistently associated with poorer cognitive performance (MMSE) in a large community sample of older adults. This association persisted after accounting for DESH-related CSF changes and brain parenchymal volume, indicating that CP volume reflects more than passive ventricular expansion. CP enlargement was also linked to vascular and metabolic risk factors including diabetes, smoking, higher BMI, WMHs, and enlarged perivascular spaces (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHe et al. demonstrated that larger choroid plexus volume in early PD was associated with lower CSF Aβ1\u0026ndash;42 and faster decline across memory domains. Participants with higher CPV tertiles had more rapid deterioration in SDMT performance and multiple Hopkins Verbal Learning Test measures. Path analysis showed that the CSF Aβ1\u0026ndash;42/α-syn ratio partially mediated the link between CP enlargement and five-year memory decline, supporting a mechanistic connection between CP pathology, protein dysregulation, and cognitive deterioration in PD (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBouhrara et al. found associations between reduced CP microstructural integrity (T1/T2 relaxation metrics) and plasma biomarkers of AD pathology, neurodegeneration, and neuroinflammation in cognitively unimpaired adults. Elevated pTau181, NfL, and GFAP corresponded to poorer CP tissue integrity, independent of demographic and vascular factors. These relationships were stronger in middle-aged and older adults, suggesting age-related vulnerability, and were not present in ventricular CSF regions, supporting a specific association with CP tissue rather than partial volume effects (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMartinkova et al. showed that CP volume progressively increases over time and that this trajectory varies by sex, diagnostic status, and ApoE genotype. Females and ApoE ε4 homozygotes exhibited the most rapid annual CP growth, and converters to dementia showed substantially faster enlargement than cognitively stable individuals. CP volume increases were not fully explained by ventricular expansion, indicating a distinct pathological process. Findings suggest that longitudinal CP changes may serve as an early biomarker of disease progression, particularly in genetically or biologically vulnerable groups (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn a longitudinal PD cohort, Jeong et al. found that larger CP volume was associated with poorer frontal/executive functioning at baseline and predicted higher risk of conversion to Parkinson\u0026rsquo;s disease dementia (PDD). During more than seven years of follow-up, converters exhibited significantly larger baseline CPV than non-converters. Mediation analysis indicated that the effect of CP enlargement on dementia risk operated primarily through its impact on executive dysfunction, highlighting CPV as a marker of cognitive vulnerability in PD (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eChoi et al. demonstrated that CP volume increases progressively across SCI, early MCI, late MCI, and AD, and strongly correlates with memory, executive function, and global cognition. CP volume was associated with multiple structural MRI markers\u0026mdash;including larger ventricles, greater WMH burden, and smaller hippocampal and cortical gray matter volumes\u0026mdash;and showed significant predictive value for cognitive impairment alongside hippocampal volume and APOE4 status. Permeability measures (Ktrans, Vp) correlated with CP volume but did not independently predict cognition, suggesting that structural rather than permeability changes are central in CP-related cognitive decline (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Summary of Overall Evidence\u003c/h2\u003e \u003cp\u003eAcross the included studies, CPV consistently emerged as a structural marker linked with cognitive status across different neurological disorders. Multiple investigations demonstrated that CP enlargement corresponds to worse cognitive performance or accelerated cognitive decline, especially in the AD spectrum. Studies in PD reported both decreased CPV (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) and increased CPV (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) as predictors of cognitive deterioration, suggesting stage-dependent alterations. Evidence from MS (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), and white matter hyperintensity burden (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) similarly supported associations between CP pathology and cognitive dysfunction.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Associations Between CP Volume and Cognitive Function\u003c/h2\u003e \u003cp\u003eAcross neurodegenerative and neuroinflammatory disorders, CPV demonstrated consistent associations with cognitive performance. In the AD spectrum, studies (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) showed that larger CPV was associated with poorer global cognition (e.g., MMSE, CDR-SOB), as well as memory and executive deficits. Longitudinal data (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) indicated that CP enlargement predicted faster cognitive decline. In PD, reduced CPV correlated with worse global cognition and accelerated decline in working memory and processing speed (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), while CP enlargement predicted declines in memory, attention, and increased risk of PDD (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn MS, larger CPV was associated with deficits in processing speed, visuospatial memory, global cognition, and fatigue (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Similarly, CP enlargement in vascular cognitive impairment was linked to reduced MMSE scores, slower processing speed, and weaker executive performance (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.7. Mechanistic Evidence and Mediators\u003c/h2\u003e \u003cp\u003eSeveral studies provided mechanistic insights into how CP alterations may contribute to cognitive decline. In AD-related populations (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), CP enlargement was linked to lower CSF Aβ42/Aβ40 levels, with mediation analyses indicating that amyloid abnormalities partially explained the relationship between CPV and cognitive impairment. Conversely, CP enlargement also mediated the effect of amyloid pathology on cognitive performance, supporting a bidirectional relationship. In PD (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), one study identified Tau levels as a mediator between reduced CPV and cognitive decline, while another study (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) demonstrated that the CSF Aβ1\u0026ndash;42/α-syn ratio partially mediated the impact of CP enlargement on five-year memory deterioration. In MS and WMH cohorts (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), the DTI-ALPS index partially mediated associations between CPV and processing speed or visuospatial functioning, supporting the role of glymphatic dysfunction as a mechanistic pathway. Disease-specific patterns of CPV and cognitive outcomes summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDisease-Specific Patterns of Choroid Plexus Volume and Cognitive Outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease Category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePattern of CP Volume Alteration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAssociated Cognitive Outcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdditional Imaging / Pathological Correlates\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAD, MCI, SCD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProgressive CP enlargement across SCD \u0026rarr; MCI \u0026rarr; AD; faster CP growth in converters and APOE4 carriers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWorse global cognition; deficits in memory and executive functions; accelerated cognitive decline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStrong associations with amyloid pathology (\u0026darr;Aβ42/Aβ40); correlations with ventricular enlargement and cortical/hippocampal atrophy; adds diagnostic value beyond classical MRI markers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEarly PD: reduced CPV; Later-stage PD: CP enlargement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReduced CPV \u0026rarr; poorer global cognition \u0026amp; faster decline in working memory/processing speed; Enlarged CPV \u0026rarr; faster memory decline, increased risk of PDD, mediated by executive dysfunction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLink with Tau, Aβ1\u0026ndash;42/α-syn ratio; CPV predicts dementia conversion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCP enlargement especially in cognitively impaired MS patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImpairments in processing speed, visuospatial memory, global cognition; increased fatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReduced DTI-ALPS index (glymphatic dysfunction); widespread microstructural abnormalities; CPV is a strong ML predictor of cognitive impairment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite Matter Hyperintensity Burden / Vascular Aging\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCP enlargement emerging in moderate WMH burden, preceding glymphatic dysfunction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLower MMSE; slowed processing speed; impaired executive functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCPV correlated with ventricular enlargement; DTI-ALPS mediates part of CPV\u0026ndash;processing speed link\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\u003eAD\u0026thinsp;=\u0026thinsp;Alzheimer\u0026rsquo;s disease; MCI\u0026thinsp;=\u0026thinsp;Mild cognitive impairment; SCD\u0026thinsp;=\u0026thinsp;Subjective cognitive decline; PD\u0026thinsp;=\u0026thinsp;Parkinson\u0026rsquo;s disease; PDD\u0026thinsp;=\u0026thinsp;Parkinson\u0026rsquo;s disease dementia; MS\u0026thinsp;=\u0026thinsp;Multiple sclerosis; WMH\u0026thinsp;=\u0026thinsp;White matter hyperintensity; CP\u0026thinsp;=\u0026thinsp;Choroid plexus; CPV\u0026thinsp;=\u0026thinsp;Choroid plexus volume; DTI-ALPS\u0026thinsp;=\u0026thinsp;Diffusion tensor imaging\u0026ndash;analysis along the perivascular space; ML\u0026thinsp;=\u0026thinsp;Machine learning; Aβ\u0026thinsp;=\u0026thinsp;Amyloid beta; Aβ42/Aβ40\u0026thinsp;=\u0026thinsp;Amyloid beta 42/40 ratio; Tau\u0026thinsp;=\u0026thinsp;Tau protein; α-syn\u0026thinsp;=\u0026thinsp;Alpha-synuclein; MMSE\u0026thinsp;=\u0026thinsp;Mini-Mental State Examination.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis systematic review synthesizes evidence across diverse neurological conditions and demonstrates that alterations in CPV are consistently associated with cognitive impairment and decline. Despite heterogeneity in clinical populations, imaging modalities, and cognitive assessments, a transdiagnostic pattern emerges: structural changes in the CP appear closely linked to both baseline cognitive status and longitudinal trajectories of cognitive decline. These results support the notion that the choroid plexus, traditionally viewed as a passive CSF-producing structure, plays a broader and functionally significant role in neurodegeneration, neuroinflammation, and cognitive vulnerability.\u003c/p\u003e \u003cp\u003eAcross AD, mild cognitive impairment, and subjective cognitive decline, CP enlargement has been consistently linked to poorer global cognition, executive dysfunction, and episodic memory impairment. Mechanistically, converging evidence suggests that CP enlargement reflects structural and functional abnormalities that impair CSF homeostasis and glymphatic clearance, thereby connecting upstream amyloid pathology to downstream cognitive decline. The CP plays a central role in regulating CSF dynamics and maintaining brain homeostasis (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), and physiological dysfunction along the AD continuum including stromal fibrosis, dystrophic calcification, vascular and basement membrane thickening, inflammation, and reduced CSF production has been associated with Aβ accumulation and tangle-like changes (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Given that Aβ aggregation is a core pathological hallmark of AD strongly tied to clinical progression (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), mediation analyses demonstrate that CP volume mediates the association between CSF Aβ levels and cognitive impairment, supporting its role as a non-invasive surrogate marker of impaired Aβ clearance. CP enlargement also correlates with atrophy and reduced perfusion in cognition-related regions, reinforcing its relationship with neurodegenerative processes. In parallel, morphological CP alterations documented in individuals with mild cognitive impairment and AD (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) suggest that reduced CP capacity may indirectly contribute to memory vulnerability by disrupting CSF-mediated metabolic clearance, neuromodulator transport, and overall brain homeostasis (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Chronic immune responses are known to occur in AD (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), and extensive evidence implicates the CP as a site of neuroinflammatory activity (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), with inflammation accompanying ChP volume changes in both mild cognitive impairment and AD (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Collectively, these findings indicate that CP abnormalities reflect impaired CSF/Aβ clearance and neuroinflammatory burden, processes that likely contribute to neurodegeneration and cognitive decline across early and prodromal stages of the AD continuum.\u003c/p\u003e \u003cp\u003eIn PD, a more complex pattern emerged. De novo PD cohorts showed reduced CPV associated with worse cognition, whereas early and progressive PD cohorts exhibited CP enlargement predicting accelerated cognitive decline and higher risk for Parkinson\u0026rsquo;s disease dementia (PDD). Mechanistically, the link between choroid plexus enlargement and cognitive vulnerability in PD has been attributed to CP dysfunction and its downstream effects on CSF homeostasis and glymphatic clearance. Although the CP primarily regulates CSF production and composition, several lines of evidence indicate that CP dysfunction can disrupt CSF homeostasis and impair the efficiency of the glymphatic system, the brain\u0026rsquo;s waste drainage pathway (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Impaired glymphatic flow may hinder the removal of harmful metabolites from the brain parenchyma (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), and experimental studies show that blocking glymphatic function accelerates α-synuclein aggregation in PD models (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Clinical data also support glymphatic dysfunction in prodromal and clinical PD (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), and imaging markers of impaired waste clearance such as enlarged perivascular spaces in the basal ganglia have been associated with more severe degeneration of dopaminergic neurons (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Furthermore, toxic protein accumulation may further disrupt glymphatic flow, creating a feedforward cycle of clearance failure and protein aggregation (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Taken together, these findings suggest that pathological conditions associated with CP enlargement, such as impaired glymphatic waste removal, may facilitate neurodegenerative processes and preferentially impact the most vulnerable cognitive domain in PD\u0026mdash;frontal and executive functioning.\u003c/p\u003e \u003cp\u003eIn MS and WMH-related vascular aging, CP enlargement was closely linked to cognitive impairment, particularly in processing speed and executive functioning. Mechanistically, CP enlargement in MS is thought to reflect a chronic pro-inflammatory state within the CNS, as the CP serves as a key interface between the peripheral immune system and the brain, functioning as a gateway for lymphocyte entry, CSF monitoring, and antigen presentation (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Pathologic studies describe immune-cell accumulation within the CP stroma and vessels, including increased T lymphocytes, macrophages, dendritic cells, and granulocytes, along with upregulated vascular adhesion molecules (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Structural abnormalities such as increased capillary permeability, basement membrane thickening, and loss of ependymal cilia have also been documented (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Furthermore, hypoxia within the CP and subsequent dysregulation of the HIF-1 pathway may alter its secretory and neuroprotective functions (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Together, these inflammatory and structural disturbances are proposed to contribute to demyelination, neuro-axonal loss, and impaired synaptic functioning, processes that play a substantial role in MS-related cognitive impairment.\u003c/p\u003e \u003cp\u003eThe present review integrates evidence across traditionally separate diagnostic domains, revealing consistent CP-cognition patterns that have not been previously synthesized at this scale. By incorporating findings from structural MRI, DTI-ALPS, PET, CSF biomarkers, plasma markers, and longitudinal cognitive testing, the review highlights the multidimensional role of the choroid plexus in brain health. Another strength is the identification of shared mechanistic pathways such as protein clearance, inflammation, and glymphatic dysfunction which provide unifying explanations for CP involvement across conditions.\u003c/p\u003e \u003cp\u003eSeveral limitations must be acknowledged. First, substantial heterogeneity existed in MRI acquisition parameters, CP segmentation methods, and cognitive assessments. Second, many studies used cross-sectional designs, limiting causal inference. Third, although several studies adjusted for key confounders, residual confounding (e.g., vascular risk factors, genetic susceptibility, lifestyle variables) remains possible. Fourth, the direction of CPV changes varies by disease and stage, underscoring the need for standardized longitudinal protocols. Finally, mechanistic analyses (e.g., mediation models) were available only in select populations, limiting generalizability.\u003c/p\u003e \u003cp\u003eThis systematic review provides convergent evidence that CP alterations are robustly associated with cognitive impairment across multiple neurological conditions. CP volume whether enlarged or reduced reflects underlying disturbances in CSF dynamics, neuroinflammation, and protein clearance, and predicts cognitive trajectories in several disorders. These findings position the CP as a promising transdiagnostic biomarker and a potential mechanistic contributor to cognitive decline. Further longitudinal and mechanistic studies are needed to clarify causal pathways and evaluate the clinical utility of CP-based measures in diagnosis, prognosis, and therapeutic monitoring\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDamkier HH, Brown PD, Praetorius J (2013) Cerebrospinal fluid secretion by the choroid plexus. Physiol Rev 93(4):1847\u0026ndash;1892\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBitanihirwe BKY, Lizano P, Woo TW (2022) Deconstructing the functional neuroanatomy of the choroid plexus: an ontogenetic perspective for studying neurodevelopmental and neuropsychiatric disorders. Mol Psychiatry 27(9):3573\u0026ndash;3582\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhersi-Egea JF, Strazielle N, Catala M, Silva-Vargas V, Doetsch F, Engelhardt B (2018) Molecular anatomy and functions of the choroidal blood-cerebrospinal fluid barrier in health and disease. 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Acta Neuropathol Commun 8(1):35\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Shahid Beheshti University of Medical Sciences","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Choroid plexus volume, Neurodegeneration, Alzheimer’s disease, Parkinson’s disease, Multiple sclerosis","lastPublishedDoi":"10.21203/rs.3.rs-8854166/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8854166/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eChoroid plexus volume (CPV), a structural marker linked to CSF regulation and neuroimmune activity, has emerged as a potential indicator of cognitive vulnerability across neurological disorders. This systematic review synthesizes evidence on CPV\u0026ndash;cognition relationships in Alzheimer\u0026rsquo;s disease, mild cognitive impairment, Parkinson\u0026rsquo;s disease, multiple sclerosis, and related conditions.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e Following PRISMA guidelines and a PROSPERO-registered protocol, five databases (PubMed, Scopus, Web of Science, Embase, PsycINFO) were searched through October 2025. Eligible human studies used structural MRI to quantify CPV and reported cognitive outcomes. Two independent reviewers conducted screening, data extraction, and quality assessment using the Newcastle\u0026ndash;Ottawa Scale.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e15 studies met inclusion criteria. Across the Alzheimer continuum CP enlargement consistently correlated with poorer global cognition, executive dysfunction, and episodic memory impairment. Longitudinal studies showed that greater CPV predicted faster cognitive decline and stronger amyloid-related pathology. In Parkinson disease, reduced CPV in de novo patients and CP enlargement in later stages were both associated with worse cognition and increased risk of dementia. In multiple sclerosis and white matter hyperintensities -related vascular aging, larger CPV was linked to deficits in processing speed, executive functioning, global cognition, and fatigue. Mechanistic evidence highlighted impaired CSF and glymphatic clearance, amyloid and α-synuclein accumulation, neuroinflammation, and microstructural CP changes as mediators of CPV-related cognitive decline.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAcross conditions, CPV reliably reflects cognitive status and predicts cognitive deterioration. CP alterations signify disturbances in CSF dynamics, neuroinflammatory activity, and protein clearance, positioning CPV as a promising transdiagnostic biomarker. Future longitudinal and multimodal studies are needed to clarify causal mechanisms and evaluate its clinical utility in diagnosis, prognosis, and therapeutic monitoring.\u003c/p\u003e","manuscriptTitle":"The Role of the Choroid Plexus in Cognitive Impairment Across Neurological Disorders: A Systematic Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-13 12:29:02","doi":"10.21203/rs.3.rs-8854166/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9fe81e8c-fcbd-4e28-933f-307d9feb2719","owner":[],"postedDate":"February 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-13T12:29:02+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-13 12:29:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8854166","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8854166","identity":"rs-8854166","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}