Effects of serum hypersensitive C-reactive protein and BMI on cognitive dysfunction in first-episode and drug-naive patients with major depressive disorder

Effects of serum hypersensitive C-reactive protein and BMI on cognitive dysfunction in first-episode and drug-naive patients with major depressive disorder | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects of serum hypersensitive C-reactive protein and BMI on cognitive dysfunction in first-episode and drug-naive patients with major depressive disorder Jingping Wu, Yuanyuan Huang, Hehua Li, Sumiao Zhou, Zhendong Zhang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6915326/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Jan, 2026 Read the published version in BMC Psychiatry → Version 1 posted 14 You are reading this latest preprint version Abstract Background Major depressive disorder (MDD) is a mental illness that is highly prevalent worldwide. Besides its core symptoms, the cognitive dysfunction in MDD patients seriously impairs their social functioning and warrants attention. Cognitive dysfunction in MDD may be related to demographic characteristics, serum inflammatory marker levels and Body Mass Index (BMI, calculated as weight divided by height squared, in kg/m²). This study focuses on the cognitive dysfunction and its associated factors in first-episode, drug-naive patients with MDD . Methods The study enrolled overall 116 first-episode, drug-naive patients with MDD and 100 healthy controls (HC) for comparison. Demographic information was obtained from all participants. We used the Chinese version of the MATRICS Consensus Cognitive Battery (MCCB) to assess cognitive function and the 17-item Hamilton Depression Rating Scale (HAMD-17) to evaluate MDD symptoms. Levels of serum inflammatory markers, such as hypersensitive C-reactive protein (hs-CRP), leukocyte (WBC), neutrophil (NEUR), and eosinophil (EO) were measured. Subsequently, multiple linear regression analysis was utilized to determine factors linked to cognitive dysfunction across the five domains with MDD patients. Results In this study, MDD patients exhibited significantly poorer cognitive function across five domains - speed of processing (SOP), attention/vigilance (AV), working memory (WM), verbal learning (VIS), and visual learning (VRB) - compared with HC ( p < 0.001). Their serum levels of hs-CRP ( p = 0.022), WBC ( p = 0.015), and NEUR ( p < 0.001) were significantly elevated than HC, whereas the level of EO ( p = 0.031) was significantly lower. The results of Spearman correlation analysis indicated that BMI was connected to cognitive function among MDD patients, specifically in the domains of SOP (r = 0.274, p = 0.003) and AV (r = 0.189, p = 0.042). Multiple linear regression analysis indicated that education years and hs-CRP level were significantly influenced by the cognitive function in the VIS domain among patients with MDD. Conclusion Our study shows a potential link between serum hs-CRP levels, BMI and cognitive dysfunction in MDD patients. This indicates that serum hs-CRP could potentially serve as a promising biomarker to forecast cognitive dysfunction in MDD patients, offering significant clinical implications. Additionally, BMI appears to have a certain predictive value regarding cognitive function in patients with MDD. Major Depressive Disorder Cognitive Dysfunction Serum Hypersensitive C-reactive Protein Body Mass Index Figures Figure 1 1 Introduction Major depressive disorder (MDD) is characterized by significant and enduring low mood, which distinguishes it as a mental illness. It is typified by high prevalence, disability, recurrence, and suicide rates, inflicting considerable harm on patients' physical and mental health [ 1 ] . Beyond core symptoms like low mood and diminished interest, cognitive dysfunction represents a crucial clinical feature of MDD. Cognitive function, an advanced brain function covering learning, memory, thinking, attention, and decision-making [ 2 ] . Cognitive dysfunction is highly prevalent among patients with MDD, primarily affecting memory, attention, and executive function [ 3 , 4 ] . Among these, impairments in attention and executive function, which are associated with frontal lobe dysfunction, are particularly prominent [ 5 , 6 ] . Cognitive impairment in MDD is present throughout the entire disease course, persisting even during periods of remission and worsening with disease recurrence. This persistence and exacerbation of cognitive dysfunction increase the complexity of treatment [ 2 , 4 , 7 – 9 ] . In our preliminary research, we have identified that serum indicators such as homocysteine [ 10 , 11 ] and antioxidants [ 2 , 12 ] are closely associated to cognitive function. Many studies indicate educational level [ 13 ] , serum inflammatory factors [ 14 – 16 ] and Body Mass Index (BMI, calculated as weight in kilograms divided by the square of height in meters, in kg/m²) are significant contributors affecting cognitive dysfunction in MDD patients. A positive correlation exists between educational level and cognitive function [ 17 ] . Lower-educated individuals with MDD are more likely to have impaired cognitive functions, such as impairment in language memory [ 13 ] . Inflammation and BMI also play crucial roles in cognitive dysfunction. Research evidence suggests that inflammation may significantly contribute to cognitive dysfunction in MDD [ 18 ] . Activation of peripheral inflammation can affect the brain's immune-inflammatory system via the blood brain barrier (BBB) [ 19 ] . Inflammation inhibits neurogenesis by reducing neuronal proliferation and cell survival, which is associated with structural and functional abnormalities in the hippocampus, as well as deficits in verbal ability and memory [ 20 ] . Alternatively, inflammation may affect cognitive function by decreasing striatal reward-related neural activation, which is linked to corticostriatal circuit dysfunction [ 21 – 24 ] . Chronic long-term inflammation, signified by elevated levels of pro-inflammatory cytokines, may induce neuroinflammation or neurodegeneration, thereby contributing to cognitive deficits [ 25 , 26 ] . Serum inflammatory markers, which reflect peripheral inflammation, are closely associated with cognitive impairment in depression. Specifically, there is an inverse relationship between patients’ cognitive function and levels of Hypersensitive C-reactive protein (hs-CRP), particularly in terms of executive function and psychomotor speed [ 27 ] . Similarly, across other mental illnesses, cognitive deficits are closely associated with serum inflammatory marker levels. In schizophrenia (SCZ), for instance, levels of white blood cells (WBC) are associated with impairments in processing speed, language learning, and working memory. [ 28 ] . In Alzheimer's disease (AD), patients with cognitive dysfunction exhibit higher levels of neutrophils (NEUR) compared to those without cognitive impairment. [ 29 ] . Animal models of AD demonstrate that neutrophils NEUR are involved in BBB disruption, which adversely affects memory function [ 30 ] . This evidence underscores that an imbalance in serum inflammatory markers is closely related to cognitive impairment. BMI, a metric widely utilized to evaluate the correlation between weight and height, also functions as a comprehensive tool for assessing fundamental aspects of physical health. The influence of BMI on cognitive function is complex and multifaceted. A possible association exists between elevated BMI, particularly in cases of obesity, and cognitive impairment. Obesity has been recognized as a predictor linked to cognitive dysfunction. Earlier research has proposed a bidirectional relationship between obesity and cognitive function. Obesity is considered a significant contributor to cognitive decline, particularly in areas such as executive function, intellectual capacity, psychomotor performance and speed, and visuospatial abilities. Conversely, cognitive decline may also increase the risk of obesity [ 31 ] . However, some studies have presented entirely different perspectives on the potential association between obesity and cognitive impairment [ 32 ] . Prior research has noted that in specific populations, BMI is positively correlated with cognitive performance [ 33 ] , highlighting its significance in influencing cognitive function. Several studies have identified peripheral inflammatory markers, including interleukin (IL)-8, as partial mediators of the connection between BMI and cognitive function in patients with MDD [ 16 ] . In a three-year longitudinal study of adolescents with depression, high BMI was found to potentially impair executive function through interleukin-6 [ 34 ] . This suggests that inflammation levels and BMI in MDD patients may be key factors influencing cognitive function. To sum up, the educational level, serum inflammatory factors and BMI are related to cognitive function in MDD. However, a lack of standardized, accessible, and affordable clinical indicators for cognitive dysfunction remains, as these indicators are influenced by factors such as the disease course and pharmacological treatments. Therefore, this study aims to analyze the associations among cognitive function and education years, serum hs-CRP and BMI in first-episode, drug-naive MDD patients. It seeks to identify correlations and impacts on cognitive impairment, deepening our understanding of MDD cognitive pathology and treatment, and establishing quantification standards to detect cognitive impairment early and provide clinical interventions. 2 Method 2.1 Study design and participants A cross-sectional study was performed involving 116 first-episode drug-naive MDD patients from the outpatient department of the Affiliated Brain Hospital of Guangzhou Medical University. Before the study commenced, researchers provided the participants with comprehensive information about the study's objectives and procedures. After ensuring that the participants fully understood the study details, written informed consent was obtained. This study was approved by the Ethics Committee of the Affiliated Brain Hospital of Guangzhou Medical University and was conducted in accordance with the latest version of the Declaration of Helsinki (2013). All participants completed clinical data collection, cognitive function assessment, and blood sample collection at the hospital. The clinical symptoms of MDD patients were evaluated and diagnosed by two trained professional psychiatrists, in accordance with the criteria of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Participants were included in the study based on the following criteria: (1) fulfillment of the DSM-5 diagnostic criteria for MDD; (2) being a first-episode patient whose disease duration did not exceed 2 years from the time of onset; (3) having no prior use of psychiatric medications or having used them irregularly for less than 2 weeks; (4) being aged between 18 and 45 years and of Han ethnicity; and (5) having no antibiotic treatment in the past 3 months. Exclusion criteria encompassed: (1) severe physical illness; (2) presence of other psychiatric conditions or brain organic dysfunction; (3) a history of alcohol or other psychoactive substance misuse; (4) a history of head injury involving loss of consciousness or significant sequelae; (5) pregnancy or breastfeeding; (6) history of electroconvulsive therapy; and (7) inability to participate in cognitive assessments. Additionally, 100 college students and volunteers from nearby universities and communities were enrolled as healthy controls (HC). These controls were matched by gender and age, and none had received antibiotic treatment in the past 3 months. 2.2 Clinical measurements In this study, general information was collected from all the first-episode and drug-naive MDD and HC individuals. This information included basic demographic details such as age, education years, marital status, occupation, and address, as well as physical measurements like height and weight. The 17-item Hamilton Depression Rating Scale (HAMD-17) [ 35 ] was used to assess the clinical psychiatric symptoms of MDD. The evaluation of the current and past-week history of first-episode, drug-naive MDD patients was conducted by experienced psychiatrists who had undergone consistency training and calibration in the HAMD-17. 2.3 Evaluation of cognitive function Drawing on previous studies, our research utilized the MATRICS Consensus Cognitive Battery (MCCB) to assess cognitive function in both groups [ 36 , 37 ] . The analysis focused on five cognitive domains: processing speed (SOP), attention/ vigilance (AV), working memory (WM), verbal learning (VRB), and visual learning (VIS) [ 2 , 12 ] . This approach to evaluating cognitive function in patients with severe mental illnesses has indeed become a standard practice in clinical research [ 38 ] . Cognitive functions of all participants were analyzed across these domains to identify significant deficits in individuals with MDD compared to those in the HC group. 2.4 Analysis of serum inflammatory markers All participants were required to fast for at least 8 hours. Venous blood samples (5 mL) were obtained from each participant within 48 hours following the completion of clinical evaluations. The blood samples were transported to the Laboratory of Affiliated Brain Hospital of Guangzhou Medical University within 30 minutes for processing. A professional technician performed centrifugation for 10 minutes to separate the serum, which was then used to measure levels of Hypersensitive C-reactive protein (hs-CRP), leukocyte (WBC), neutrophil (NEUR), and eosinophil (EO). All experimental procedures were performed strictly following the manufacturer's instructions. 2.5 Statistical analysis Statistical analysis for this study was performed using IBM SPSS Statistics 22.0 (IBM Corp., Chicago, USA), with a two-tailed p-value of less than 0.05 considered statistically significant. Categorical variables (such as gender) between MDD and HC groups were compared using chi-square tests, while continuous variables (such as age and education years) were compared with ANOVA. Clinical characteristics, laboratory results, and cognitive scores were subjected to normality testing. Normally distributed variables (Shapiro-Wilk test, p > 0.05) were described as mean ± standard deviation (SD), with independent t-tests used for group comparisons. Non-normally distributed variables (Shapiro-Wilk test, p < 0.05) were described as median and interquartile range (median [P25, P75]), with Mann-Whitney U tests used for comparisons. Spearman correlation analysis was employed to explore relationships among serum inflammatory markers, clinical data, and cognitive performance. Multiple regression analysis (backward elimination model) with MCCB scores as the dependent variable was conducted to investigated the link between MDD cognitive function and serum inflammatory marker levels. 3 Result 3.1 Demographic and clinical characteristics This investigation involved 216 participants in total, of whom 116 were first-episode, drug-naive patients with MDD, and the remaining 100 participants were HC. The demographic and clinical characteristics of these two groups are presented in Table 1 . In this study, the mean age of the MDD group was 23.06 years (SD = 4.49), whereas the mean age of the HC group was 22.24 years (SD = 2.64). In the MDD group, 60.34% were female and 39.66% were male. No statistically significant differences were found in gender (χ 2 = 2.279, p = 0.095) and age (t = -1.663, p = 0.098) between the MDD and HC groups. However, the two groups exhibited statistically significant differences in education years (Z = -4.039, p < 0.001) and BMI (Z = -2.468, p = 0.014). The mean HAMD-17 score of the MDD patients was 23.68 (SD = 4.93), with a mean age of first onset at 22.23 years (SD = 4.95) and a median total disease duration of ten months. Table 1. The demographic and clinical characteristics of the two groups of participants. MDD (n = 116) HC (n = 100) χ 2 /t/Z p Gender(M/F) 46/70 51/49 2.279 0.095 Age (y) 23.06 (4.49) 22.24 (2.64) -1.663 0.098 Education years (y) 15.00 (12.00, 16.00) 16.00 (14.00, 17.00) -4.039 <0.001 BMI (kg/m 2 ) 21.69 (19.80, 24.60) 21.16 (18.82, 23.82) -2.468 0.014 Age of first onset(y) 22.23 (4.95) - - - Total disease duration(m) 10.00 (3.00, 18.00) - - - HAMD score 23.68 (4.93) - - - Abbreviations: MDD, Major Depressive Disorder; HC, healthy control; BMI, Body Mass Index; HAMD, The 17-item Hamilton Depression Rating Scale; 3.2 Cognitive function of MDD patients and HC The MDD and HC groups exhibited significant differences across the five cognitive domains. The MDD group exhibited lower cognitive scores compared with the HC group in SOP, AV, WM, VRB, and VIS. Even after adjusting for the confounding effect of education years, significant cognitive differences remained in AV, WM, and VIS (all p < 0.05) ( Table 2 ). Table2. Cognitive function of MDD patients and HC. MDD (n = 116) HC (n = 100) t p SOP 32.68 (9.68) 45.70 (9.91) 9.75 <0.001 AV 33.28 (9.24) 42.16 (8.62) 7.26 <0.001 WM 39.17 (11.66) 47.36 (10.70) 5.34 <0.001 VRB 31.57 (9.73) 41.72 (7.80) 8.42 <0.001 VIS 39.03 (9.21) 45.36 (7.08) 5.71 <0.001 Abbreviations: MDD, Major Depressive Disorder; HC, healthy control; SOP, Speed of processing; AV, Attention/vigilance; WM, Working memory; VRB, Verbal learning; VIS, Visual learning; 3.3 The differences in serum inflammatory marker levels between the MDD and HC groups As shown in Table 3 , the MDD and HC groups exhibited substantial differences with respect to the levels of several serum inflammatory markers, including WBC (Z = -2.438, p = 0.015), NEUR (Z = -3.526, p < 0.001), EO (Z = -2.154, p = 0.031), and hs-CRP (Z = -2.290, p = 0.022). Specifically, the MDD group exhibited higher levels of WBC (median 6.35 ([P25, P75] 5.60, 7.98)), NEUR (median 3.85 ([P25, P75] 3.20, 5.18)), and hs-CRP (median 1.10 ([P25, P75] 1.10, 1.98)) compared to the HC group (WBC median 6.05 ([P25, P75] 5.23, 6.98); NEUR median 3.30 ([P25, P75] 2.70, 4.30); and hs-CRP median 1.00 ([P25, P75] 0.53, 1.30). In contrast, the MDD group exhibited a significantly lower level of EO (median 0.09 ([P25, P75] 0.05, 0.17)) compared to the HC group (median 0.13 ([P25, P75] 0.08, 0.19)). Table 3. Comparison of serum inflammatory markers levels between the two groups. MDD (n = 116) HC (n = 100) Z p WBC 6.35 (5.60,7.98) 6.05 (5.23,6.98) -2.438 0.015 NEUR 3.85 (3.20,5.18) 3.30 (2.70,4.30) -3.526 <0.001 EO 0.09 (0.05,0.17) 0.13 (0.08,0.19) -2.154 0.031 hs-CRP 1.10 (1.10,1.98) 1.00 (0.53,1.30) -2.290 0.022 Abbreviations: MDD, Major Depressive Disorder; HC, healthy control; WBC, leukocyte; NEUR, neutrophil; EO, eosinophil; hs-CRP, Hypersensitive C-reactive protein; 3.4 Correlation of cognitive function with serum inflammatory markers and BMI in MDD and HC group After controlling for confounding effect of education years, significant differences in cognitive function remained between the MDD and HC within the domains of AV, WM and VIS (all p < 0.05). Further analysis using Spearman correlation analysis revealed that in the HC, VRB was inversely correlated with NEUR levels (r = -0.201, p = 0.045). In the MDD group, SOP showed a positive association with BMI (r = 0.274, p = 0.003), and AV also showed a positive association with BMI (r = 0.189, p = 0.042). However, no significant correlations were observed between other serum inflammatory markers and cognitive performance ( p > 0.05) ( Table 4 ) ( Fig 1 ). Table 4. Correlation between five dimensions of MCCB and serum inflammatory markers, as well as BMI in HC and MDD groups. SOP AV WM VRB VIS HC BMI r 0.034 -0.027 0.191 -0.004 -0.019 p 0.739 0.790 0.057 0.972 0.849 WBC r -0.013 -0.007 0.077 -0.164 -0.070 p 0.894 0.945 0.447 0.103 0.490 NEUR r -0.015 0.038 0.071 -0.201 0.020 p 0.882 0.707 0.483 0.045 0.843 EO r -0.075 -0.077 -0.141 0.001 -0.112 p 0.459 0.445 0.162 0.993 0.267 hs-CRP r 0.071 0.092 0.039 0.001 0.044 p 0.483 0.365 0.704 0.995 0.661 MDD BMI r 0.274 0.189 0.097 0.169 0.140 p 0.003 0.042 0.299 0.070 0.135 WBC r 0.024 0.017 0.094 -0.030 0.005 p 0.797 0.858 0.315 0.747 0.959 NEUR r 0.033 -0.044 -0.009 -0.057 -0.031 p 0.728 0.639 0.922 0.542 0.740 EO r 0.100 0.065 0.078 0.016 -0.118 p 0.283 0.486 0.406 0.862 0.205 hs-CRP r 0.076 -0.007 0.044 -0.023 -0.002 p 0.416 0.943 0.636 0.810 0.980 Abbreviations: MDD, Major Depressive Disorder; HC, healthy control; SOP, Speed of processing; AV, Attention/vigilance; WM, Working memory; VRB, Verbal learning; VIS, Visual learning; WBC, leukocyte; NEUR, neutrophil; EO, eosinophil; hs-CRP, Hypersensitive C-reactive protein; 3.5 Regression analysis of serum inflammatory markers levels, BMI and cognitive function This study employed multiple regression analysis with a backward elimination model to examine the influence of serum inflammatory markers and BMI on cognitive function in MDD patients. In our analysis, MCCB scores were used as the dependent variable, while demographic data, clinical features and serum inflammatory markers were included as independent variables. The results indicated that the regression model was significant for education years (B = 1.272, t = 3.758, p ＜ 0.001) and hs-CRP levels (B = -1.654, t = -2.085, p = 0.039) in relation to VIS cognitive function performance ( Table 5 ). Table 5. Factors Affecting Cognitive Function in Patients with MDD. B S.E t p -value 95 % CI Lower Upper VIS Education years 1.272 0.338 3.758 <0.001 0.601 1.943 hs-CRP -1.654 0.793 -2.085 0.039 -3.227 -0.081 Abbreviations: MDD, Major Depressive Disorder; VIS, Visual learning; hs-CRP, Hypersensitive C-reactive protein; 4 Discussion The primary results of this study are presented as follows: (1) The T-scores for the five cognitive domains were substantially reduced in the MDD group compared with the HC group. (2) Versus the HC group, the MDD group exhibited markedly elevated levels of WBC, NEUR, and hs-CRP, as well as significantly reduced levels of EO among the serum inflammatory markers. (3) Elevated serum hs-CRP levels were identified as a substantial predictor of cognitive impairment among individuals with MDD. (4) The MDD group had a markedly elevated BMI compared to the HC group. Additionally, BMI was positively correlated with cognitive function in MDD patients, particularly within the domains of SOP and AV. (5) In the HC group, serum NEUR levels exhibited a negative correlation with VRB. Currently, there is no definitive conclusion regarding the impact of serum inflammatory markers on cognitive function in MDD patients. Therefore, our study results will further elucidate the factors contributing to cognitive impairment in these patients and enhance our understanding of the predictive capacity of serum inflammatory marker levels for cognitive decline in MDD. Our study revealed that, contrasted with HC, MDD patients had significantly lower scores across all five dimensions of cognitive function. Even when controlling for education years, significant differences in cognitive function remained in the AV, WM, and VIS dimensions, consistent with our earlier findings [2] . Cognitive dysfunction in MDD can compromise social functioning, attention, learning capacity, and exacerbate depressive symptoms, all of which may influence treatment efficacy and patient prognosis. Cognitive dysfunction in MDD persists even during remission and worsens with each recurrence. Our findings further confirm multi-dimensional cognitive impairment in first-episode, drug-naive MDD patients. Cognitive function serves as an essential clinical feature of MDD and plays a crucial role in predicting and assessing future treatment outcomes. Additionally, significant differences in serum hs-CRP, WBC, NEUR, and EO levels were found between the two groups. Compared to CRP, hs-CRP is more sensitive and can accurately detect low-concentration CRP levels. It is a trace protein in the blood, synthesized in large quantities by hepatocytes during infection or inflammation [39] . Depression is often associated with a pro-inflammatory phenotype, particularly in the central nervous system, where inflammatory conditions can lead to chronic neuroinflammation through the activation of microglia and astrocytes [40] . A review on the potential mechanisms underlying cognitive impairment highlighted that microglial activation can alter the expression of various neurotoxic mediators, promote the accumulation of inflammatory factors, and amplify inflammatory cycles, leading to glial damage and neuronal cell death [41] . The association between serum inflammatory markers and cognitive dysfunction has garnered increasing attention. In particular, serum hs-CRP levels have been highlighted as a significant factor in MDD-related cognitive impairment. Previous research has established a connection between elevated hs-CRP levels and cognitive dysfunction across various conditions, including MDD [27] , mild cognitive impairment (MCI) [42] , and SCZ [43] . These effects not only disrupt the hypothalamic energy homeostasis and appetite regulation centers but also impact other brain regions, including the prefrontal cortex and hippocampus, contributing to corresponding cognitive impairment [44] . This represents a critical factor contributing to progressive neuronal damage. Both acute and chronic systemic inflammation can lead to cognitive dysfunction. On one hand, hs-CRP triggers systemic inflammation, increasing proinflammatory cytokines and causing cognitive dysfunction. On the other hand, inflammation affects vascular reactivity. High hs-CRP levels cause cerebral vasodilation and reduced vascular reactivity, accelerating cognitive decline, particularly in executive function and daily living activities [41, 45] . Previous research has indicated that elevated levels of hs-CRP are linked to an increased likelihood of cognitive impairment [46] . In a longitudinal study spanning 12 years, higher serum hs-CRP levels were found to predict memory decline, suggesting hs-CRP as a simple and objective biomarker for identifying cognitive dysfunction [47] . To explore the relationship between serum inflammatory levels and cognitive function in first-episode, drug-naive patients with MDD, we conducted a correlation analysis between serum inflammatory markers and cognitive domains. Nevertheless, no statistically significant association was observed between hs-CRP and cognitive function. Previous studies have shown that measuring epigenetic levels of CRP (DNAm CRP) in peripheral blood yields more stable inflammation levels and stronger correlations with cognitive impairment than serum CRP [48] . Therefore, the instability of hs-CRP in serum, which is susceptible to rapid concentration changes in plasma, may contribute to our results. Future research could consider measuring DNA methylation levels of more stable inflammatory markers to quantify their association with cognitive function. To further explore the relationship between serum inflammatory markers and cognitive function in first-episode, drug-naive patients with MDD, we conducted multiple linear regression analysis. Our findings reveal a potential link between elevated levels of hs-CRP and cognitive impairment in MDD patients, indicating that hs-CRP might act as a risk factor for cognitive deficits, particularly in the domain of VIS. The result indicates that systemic inflammation from high hs-CRP levels in MDD patients can cause cognitive dysfunction, similar to past reports on inflammation-induced cognitive dysfunction in other diseases [42, 49] . In addition to the findings regarding hs-CRP and cognitive function, our study demonstrated that MDD patients had a significantly higher BMI compared to HC, suggesting that patients with MDD are more likely to experience an increase in BMI. This observation aligns with previous research indicating a higher prevalence of obesity in MDD patients [15, 50] . However, in further correlation analysis, we identified a positive association between BMI and cognitive dysfunction in MDD patients, particularly in the domains of SOP and AV. This observation contrasts with many previous studies that identified obesity as a possible predictor for cognitive dysfunction [51-54] . We hypothesize that first-episode, drug-naive MDD patients might demonstrate reduced BMI levels, which could be attributed to anorexia and weight loss-related nutritional deficiencies. These deficiencies might also contribute to cognitive impairment in these patients. Biologically, the peripheral immune system and central inflammatory mediators communicate bidirectionally. An elevated BMI is associated with increased peripheral and central inflammation, a condition that can trigger the stimulation of brain immune cells, including microglia and astrocytes. Sustained immune-inflammatory activation can alter emotions and cognitive function [55] . Nonetheless, some studies offer different perspectives. For instance, a prior study has identified a significant positive association between BMI and cognitive performance in male patients with SCZ [33] . Additionally, some research suggested that a healthy BMI doesn't adversely affect cognitive function [56] . In other neurodegenerative diseases with cognitive impairment, a reduction in leptin due to weight loss may lead to cognitive dysfunction [57] . Moreover, well-metabolized obesity in older patients may confer a certain protective effect against the pathological mechanisms of AD [58] , which also supports our results to some extent. Subsequent research ought to further explore the complex interplay between BMI, inflammation, and cognitive performance in MDD. Our results indicated a negative correlation between NEUR and VRB within the HC group, a finding that was not replicated in the MDD group, indicating that NEUR is not a strong correlate of VRB in MDD. Previous research in non-demented cohorts has demonstrated that elevated NEUR levels were linked with cognitive dysfunction and accelerated deterioration of episodic memory [59] . These findings collectively highlight the importance of maintaining peripheral immune homeostasis in protecting cognitive function. Future research could investigate this correlation in more diverse populations, both cross-sectionally and longitudinally, to better identify cognitive dysfunction risk factors. 5 Limitations We acknowledge several limitations in our study. First, it is a cross-sectional analysis of MDD patients. Serum inflammatory markers fluctuate over time, and their long-term, stable impact on MDD patients' cognitive function remains unclear. Second, although our study found that serum hs-CRP affects MDD patients' cognitive function, the specific mechanism of action of serum inflammatory markers on cognitive function is still unknown. Therefore, in the future, we plan to expand the cross-sectional study of MDD patients and conduct follow-up assessments after pharmacological intervention. We will also seek more stable measurement methods for serum inflammatory markers and employ more rigorous experimental approaches to analyze risk factors related to cognitive dysfunction in MDD patients. Our ultimate goal is to identify effective biomarkers that can predict cognitive impairment in MDD patients for clinical application. Third, our study sample was drawn from diverse regions, and we did not control for the potential impact of dietary intake on cognitive function. 6 Conclusion Our research reveals that MDD patients suffer from extensive cognitive dysfunction and exhibit markedly higher serum hs-CRP levels than HC. The potential link between serum hs-CRP levels and VIS in MDD patients suggests that hs-CRP might act as a prospective inflammatory biomarker for predicting cognitive impairment in first-episode, drug-naive patients with MDD. Additionally, BMI shows a certain predictive value for cognitive function in MDD patients. In summary, our results show a close relationship between serum inflammatory markers, BMI and cognitive dysfunction in first-episode and drug-naive MDD patients, offering new directions for future research. Abbreviations MDD Major depressive disorder HC Healthy Control MCCB the MATRICS Consensus Cognitive Battery HAMD-17 the 17-item Hamilton Depression Rating Scale hs-CRP hypersensitive C-reactive protein WBC Leukocyte, White blood cells NEUR Neutrophil EO Eosinophil SOP Speed of processing AV Attention/Vigilance WM Working memory VIS Verbal learning VRB Visual learning BMI Body Mass Index BBB Blood Brain Barrier SCZ Schizophrenia AD Alzheimer's disease DSM-5 the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of the Affiliated Brain Hospital of Guangzhou Medical University and was conducted in accordance with the latest version of the Declaration of Helsinki (2013). Before the study, all participants were required to sign the informed consent form. Consent for publication Not applicable. Availability of data and materials The datasets generated during the current study are not publicly available, but can be requested from the corresponding author on reasonable request. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This study was funded by Key-Area Research and Development Program of Guangdong Province (2023B0303020001), National Natural Science Foundation of China (82301688), Natural Science Foundation of Guangdong (2025A1515010507), Science and Technology Program of Guangzhou (2025A03J3357, 202206060005, 2023A03J0856), Guangdong Basic and Applied Basic Research Foundation Outstanding Youth Project (2021B1515020064), Medical Science and Technology Research Foundation of Guangdong (A2023224), Health Science and Technology Program of Guangzhou (20231A010036), Guangzhou Municipal Key Discipline in Medicine (2025-2027), and National Traditional Chinese and Western Medicine Collaborative Project for Major and Complex Diseases (Comprehensive Department of the National Administration of Traditional Chinese Medicine [2024] No. 3), National Integrated Traditional Chinese and Western Medicine "Flagship" Department Construction Project (Comprehensive Department of the National Administration of Traditional Chinese Medicine [2024] No. 221). Authors' contributions Jingping Wu: Writing–original draft, Visualization, Investigation, Formal analysis, Data curation, Conceptualization. Yuanyuan Huang: Writing–review & editing, Methodology, Resources, Funding acquisition. Hehua Li: Validation, Methodology, Resources. Sumiao Zhou: Visualization, Data curation. Zhendong Zhang: Formal analysis. Ziyun Zhang: Software. Shixuan Feng: Data curation. Lam Mei Fong: Visualization. Kai Wu: Resources. Fengchun Wu: Writing–review & editing, Resources, Supervision, Project administration, Funding acquisition, Conceptualization. Acknowledgments All authors thank all the participants who participate in our study training program. Clinical trial number Not applicable. References Gu X, Ke S, Wang Q, et al. Energy metabolism in major depressive disorder: Recent advances from omics technologies and imaging[J]. Biomed Pharmacother. 2021;141:111869. Zhang Z, Huang Y, Zhou S, et al. 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Zenaro E, Pietronigro E, Della Bianca V, et al. Neutrophils promote Alzheimer's disease-like pathology and cognitive decline via LFA-1 integrin[J]. Nat Med. 2015;21(8):880–6. Norris T, Salzmann A, Henry A, et al. The relationship between adiposity and cognitive function: a bidirectional Mendelian randomization study in UK Biobank[J]. Int J Epidemiol. 2023;52(4):1074–85. Ding C, Lu R, Kong Z, et al. Exploring the triglyceride-glucose index's role in depression and cognitive dysfunction: Evidence from NHANES with machine learning support[J]. J Affect Disord. 2025;374:282–9. Li W, Lin S, Yue L, et al. Sex Differences in Obesity and Cognitive Function in Chinese Elderly Patients With Chronic Schizophrenia[J]. Front Endocrinol (Lausanne). 2022;13:742474. Mac GN, Swistun D, Murray S, et al. Executive dysfunction in depression in adolescence: the role of inflammation and higher body mass[J]. Psychol Med. 2020;50(4):683–91. HAMILTON M. A rating scale for depression[J]. J Neurol Neurosurg Psychiatry. 1960;23(1):56–62. Nuechterlein KH, Green MF, Kern RS, et al. The MATRICS Consensus Cognitive Battery, part 1: test selection, reliability, and validity[J]. Am J Psychiatry. 2008;165(2):203–13. Feng S, Zhou S, Huang Y, et al. Correlation between low frequency fluctuation and cognitive performance in bipolar disorder patients with suicidal ideation[J]. J Affect Disord. 2024;344:628–34. Burdick KE, Goldberg TE, Cornblatt BA, et al. The MATRICS consensus cognitive battery in patients with bipolar I disorder[J]. Neuropsychopharmacology. 2011;36(8):1587–92. Ji X, Tian L, Yao S, et al. A Systematic Review of Body Fluids Biomarkers Associated With Early Neurological Deterioration Following Acute Ischemic Stroke[J]. Front Aging Neurosci. 2022;14:918473. De Felice FG, Ferreira ST. Inflammation, defective insulin signaling, and mitochondrial dysfunction as common molecular denominators connecting type 2 diabetes to Alzheimer disease[J]. Diabetes. 2014;63(7):2262–72. John CM, Mohamed Yusof NIS, Abdul Aziz SH et al. Maternal Cognitive Impairment Associated with Gestational Diabetes Mellitus-A Review of Potential Contributing Mechanisms[J]. Int J Mol Sci, 2018,19(12). Roberts RO, Geda YE, Knopman DS, et al. Association of C-reactive protein with mild cognitive impairment[J]. Alzheimers Dement. 2009;5(5):398–405. Weng S, Zheng R, Lin R. Correlation of Serum High-Sensitivity C-Reactive Protein, Homocysteine, and Macrophage Migration Inhibitory Factor Levels With Symptom Severity and Cognitive Function in Patients With Schizophrenia[J]. Clin Neuropharmacol. 2024;47(3):82–6. Guillemot-Legris O, Muccioli GG. Obesity-Induced Neuroinflammation: Beyond the Hypothalamus[J]. Trends Neurosci. 2017;40(4):237–53. Chung C, Pimentel D, Jor'Dan AJ, et al. Inflammation-associated declines in cerebral vasoreactivity and cognition in type 2 diabetes[J]. Neurology. 2015;85(5):450–8. Gorelick PB. Role of inflammation in cognitive impairment: results of observational epidemiological studies and clinical trials[J]. Ann N Y Acad Sci. 2010;1207:155–62. Komulainen P, Lakka TA, Kivipelto M, et al. Serum high sensitivity C-reactive protein and cognitive function in elderly women[J]. Age Ageing. 2007;36(4):443–8. Conole ELS, Stevenson AJ, Muñoz Maniega S, et al. DNA Methylation and Protein Markers of Chronic Inflammation and Their Associations With Brain and Cognitive Aging[J]. Neurology. 2021;97(23):e2340–52. Pan LH, Qian M, Qu W, et al. Serum C-Reactive Protein in Patients with Deficit Schizophrenia and the Relationship with Cognitive Function[J]. Neuropsychiatr Dis Treat. 2020;16:2891–7. Fulton S, Décarie-Spain L, Fioramonti X, et al. The menace of obesity to depression and anxiety prevalence[J]. Trends Endocrinol Metab. 2022;33(1):18–35. Agustí A, García-Pardo MP, López-Almela I, et al. Interplay Between the Gut-Brain Axis, Obesity and Cognitive Function[J]. Front Neurosci. 2018;12:155. Johnson LA, Zuloaga KL, Kugelman TL, et al. Amelioration of Metabolic Syndrome-Associated Cognitive Impairments in Mice via a Reduction in Dietary Fat Content or Infusion of Non-Diabetic Plasma[J]. EBioMedicine. 2016;3:26–42. Gunstad J, Paul RH, Cohen RA, et al. Elevated body mass index is associated with executive dysfunction in otherwise healthy adults[J]. Compr Psychiatry. 2007;48(1):57–61. Liu YE, Zhao Z, He H, et al. Stress-induced obesity in mice causes cognitive decline associated with inhibition of hippocampal neurogenesis and dysfunctional gut microbiota[J]. Front Microbiol. 2024;15:1381423. Fourrier C, Sampson E, Hori H, et al. Exploratory study of association between blood immune markers and cognitive symptom severity in major depressive disorder: Stratification by body mass index status[J]. Brain Behav Immun. 2020;88:242–51. Zhu H, Hei B, Zhou W, et al. Association between Life's Essential 8 and cognitive function among older adults in the United States[J]. Sci Rep. 2024;14(1):19773. Sergi G, De Rui M, Coin A, et al. Weight loss and Alzheimer's disease: temporal and aetiologic connections[J]. Proc Nutr Soc. 2013;72(1):160–5. Xu W, Tan L, Wang H, et al. Meta-analysis of modifiable risk factors for Alzheimer's disease[J]. J Neurol Neurosurg Psychiatry. 2015;86(12):1299–306. Fa W, Liang X, Liu K et al. Associations of Blood Absolute Neutrophil Count and Cytokines With Cognitive Function in Dementia-Free Participants: A Population-Based Cohort Study[J]. J Gerontol Biol Sci Med Sci, 2024,79(1). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6915326","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":502607156,"identity":"404dbeac-9baf-474d-8926-9408c8d13402","order_by":0,"name":"Jingping Wu","email":"","orcid":"","institution":"The Affiliated Brain Hospital, Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jingping","middleName":"","lastName":"Wu","suffix":""},{"id":502607160,"identity":"7bb1b3bb-13ef-4d93-81ef-9703c18394e0","order_by":1,"name":"Yuanyuan Huang","email":"","orcid":"","institution":"The Affiliated Brain Hospital, 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University","correspondingAuthor":false,"prefix":"","firstName":"Chenyu","middleName":"","lastName":"Liu","suffix":""},{"id":502607173,"identity":"e88bf272-6a19-496f-ac84-0d51107bfa34","order_by":8,"name":"Lam Mei Fong","email":"","orcid":"","institution":"the Centro Hospitalar Conde de São Januário","correspondingAuthor":false,"prefix":"","firstName":"Lam","middleName":"Mei","lastName":"Fong","suffix":""},{"id":502607175,"identity":"1e59c93c-2f8e-42fa-a5f5-be927b618da9","order_by":9,"name":"Kai Wu","email":"","orcid":"","institution":"South China University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Wu","suffix":""},{"id":502607177,"identity":"9f012df0-254d-4fd5-99aa-fc348f8231b2","order_by":10,"name":"Fengchun Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYBACNv7+hw8SftjwsMk/bHyQUFFDWAufxBlmg489aXL8DMnNBg/OHCOsRY4hh01yBtthY8mG9DbJhy3MRDiM4exhYx6etMQNBw62VSQ2sDHwt3cn4NfC3Jf4mMfCJnHDwca2G4k7ZBgkzpzdQMCWA8YQWw4zArWcYWMwkMglpCXBTJqH7XDihmOMbQWJbczEaMkxg3i/h7GNgTgtEseSIYEswdgskXDmGA9Bv8j3Nx+ERKUE+8OPPypq5Pjbe/FrwQA8pCkfBaNgFIyCUYAVAABawkx9bXUJ7QAAAABJRU5ErkJggg==","orcid":"","institution":"The Affiliated Brain Hospital, Guangzhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Fengchun","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2025-06-17 14:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6915326/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6915326/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12888-026-07782-y","type":"published","date":"2026-01-27T15:58:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89658889,"identity":"bb759a78-c248-471c-992e-11406bb0fe83","added_by":"auto","created_at":"2025-08-22 10:49:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":126040,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of correlations among cognitive domain T scores, BMI and serum inflammatory markers. The scatter plots, from left to right, depict the relationships between SOP and BMI in the MDD, AV and BMI in the MDD, and VRB, and NEUR levels in the HC.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6915326/v1/5d2092f87d8b0517ef406da1.png"},{"id":101690632,"identity":"e8580d72-0714-463d-9cda-ece176ea46bd","added_by":"auto","created_at":"2026-02-02 16:06:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1147885,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6915326/v1/3e0a8352-03b6-43ca-917d-a6d3da19c3b2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of serum hypersensitive C-reactive protein and BMI on cognitive dysfunction in first-episode and drug-naive patients with major depressive disorder","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eMajor depressive disorder (MDD) is characterized by significant and enduring low mood, which distinguishes it as a mental illness. It is typified by high prevalence, disability, recurrence, and suicide rates, inflicting considerable harm on patients' physical and mental health\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Beyond core symptoms like low mood and diminished interest, cognitive dysfunction represents a crucial clinical feature of MDD. Cognitive function, an advanced brain function covering learning, memory, thinking, attention, and decision-making\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Cognitive dysfunction is highly prevalent among patients with MDD, primarily affecting memory, attention, and executive function\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Among these, impairments in attention and executive function, which are associated with frontal lobe dysfunction, are particularly prominent\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Cognitive impairment in MDD is present throughout the entire disease course, persisting even during periods of remission and worsening with disease recurrence. This persistence and exacerbation of cognitive dysfunction increase the complexity of treatment\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. In our preliminary research, we have identified that serum indicators such as homocysteine\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e and antioxidants\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e are closely associated to cognitive function. Many studies indicate educational level\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e, serum inflammatory factors\u003csup\u003e[\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e and Body Mass Index (BMI, calculated as weight in kilograms divided by the square of height in meters, in kg/m\u0026sup2;) are significant contributors affecting cognitive dysfunction in MDD patients. A positive correlation exists between educational level and cognitive function\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Lower-educated individuals with MDD are more likely to have impaired cognitive functions, such as impairment in language memory\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Inflammation and BMI also play crucial roles in cognitive dysfunction.\u003c/p\u003e\u003cp\u003eResearch evidence suggests that inflammation may significantly contribute to cognitive dysfunction in MDD\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Activation of peripheral inflammation can affect the brain's immune-inflammatory system via the blood brain barrier (BBB)\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Inflammation inhibits neurogenesis by reducing neuronal proliferation and cell survival, which is associated with structural and functional abnormalities in the hippocampus, as well as deficits in verbal ability and memory\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Alternatively, inflammation may affect cognitive function by decreasing striatal reward-related neural activation, which is linked to corticostriatal circuit dysfunction\u003csup\u003e[\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Chronic long-term inflammation, signified by elevated levels of pro-inflammatory cytokines, may induce neuroinflammation or neurodegeneration, thereby contributing to cognitive deficits\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Serum inflammatory markers, which reflect peripheral inflammation, are closely associated with cognitive impairment in depression. Specifically, there is an inverse relationship between patients\u0026rsquo; cognitive function and levels of Hypersensitive C-reactive protein (hs-CRP), particularly in terms of executive function and psychomotor speed\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Similarly, across other mental illnesses, cognitive deficits are closely associated with serum inflammatory marker levels. In schizophrenia (SCZ), for instance, levels of white blood cells (WBC) are associated with impairments in processing speed, language learning, and working memory.\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. In Alzheimer's disease (AD), patients with cognitive dysfunction exhibit higher levels of neutrophils (NEUR) compared to those without cognitive impairment.\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. Animal models of AD demonstrate that neutrophils NEUR are involved in BBB disruption, which adversely affects memory function\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. This evidence underscores that an imbalance in serum inflammatory markers is closely related to cognitive impairment.\u003c/p\u003e\u003cp\u003eBMI, a metric widely utilized to evaluate the correlation between weight and height, also functions as a comprehensive tool for assessing fundamental aspects of physical health. The influence of BMI on cognitive function is complex and multifaceted. A possible association exists between elevated BMI, particularly in cases of obesity, and cognitive impairment. Obesity has been recognized as a predictor linked to cognitive dysfunction. Earlier research has proposed a bidirectional relationship between obesity and cognitive function. Obesity is considered a significant contributor to cognitive decline, particularly in areas such as executive function, intellectual capacity, psychomotor performance and speed, and visuospatial abilities. Conversely, cognitive decline may also increase the risk of obesity\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. However, some studies have presented entirely different perspectives on the potential association between obesity and cognitive impairment\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Prior research has noted that in specific populations, BMI is positively correlated with cognitive performance\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e, highlighting its significance in influencing cognitive function.\u003c/p\u003e\u003cp\u003eSeveral studies have identified peripheral inflammatory markers, including interleukin (IL)-8, as partial mediators of the connection between BMI and cognitive function in patients with MDD\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. In a three-year longitudinal study of adolescents with depression, high BMI was found to potentially impair executive function through interleukin-6\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. This suggests that inflammation levels and BMI in MDD patients may be key factors influencing cognitive function.\u003c/p\u003e\u003cp\u003eTo sum up, the educational level, serum inflammatory factors and BMI are related to cognitive function in MDD. However, a lack of standardized, accessible, and affordable clinical indicators for cognitive dysfunction remains, as these indicators are influenced by factors such as the disease course and pharmacological treatments. Therefore, this study aims to analyze the associations among cognitive function and education years, serum hs-CRP and BMI in first-episode, drug-naive MDD patients. It seeks to identify correlations and impacts on cognitive impairment, deepening our understanding of MDD cognitive pathology and treatment, and establishing quantification standards to detect cognitive impairment early and provide clinical interventions.\u003c/p\u003e"},{"header":"2 Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study design and participants\u003c/h2\u003e\u003cp\u003eA cross-sectional study was performed involving 116 first-episode drug-naive MDD patients from the outpatient department of the Affiliated Brain Hospital of Guangzhou Medical University. Before the study commenced, researchers provided the participants with comprehensive information about the study's objectives and procedures. After ensuring that the participants fully understood the study details, written informed consent was obtained. This study was approved by the Ethics Committee of the Affiliated Brain Hospital of Guangzhou Medical University and was conducted in accordance with the latest version of the Declaration of Helsinki (2013). All participants completed clinical data collection, cognitive function assessment, and blood sample collection at the hospital. The clinical symptoms of MDD patients were evaluated and diagnosed by two trained professional psychiatrists, in accordance with the criteria of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Participants were included in the study based on the following criteria: (1) fulfillment of the DSM-5 diagnostic criteria for MDD; (2) being a first-episode patient whose disease duration did not exceed 2 years from the time of onset; (3) having no prior use of psychiatric medications or having used them irregularly for less than 2 weeks; (4) being aged between 18 and 45 years and of Han ethnicity; and (5) having no antibiotic treatment in the past 3 months. Exclusion criteria encompassed: (1) severe physical illness; (2) presence of other psychiatric conditions or brain organic dysfunction; (3) a history of alcohol or other psychoactive substance misuse; (4) a history of head injury involving loss of consciousness or significant sequelae; (5) pregnancy or breastfeeding; (6) history of electroconvulsive therapy; and (7) inability to participate in cognitive assessments. Additionally, 100 college students and volunteers from nearby universities and communities were enrolled as healthy controls (HC). These controls were matched by gender and age, and none had received antibiotic treatment in the past 3 months.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Clinical measurements\u003c/h2\u003e\u003cp\u003eIn this study, general information was collected from all the first-episode and drug-naive MDD and HC individuals. This information included basic demographic details such as age, education years, marital status, occupation, and address, as well as physical measurements like height and weight. The 17-item Hamilton Depression Rating Scale (HAMD-17)\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e was used to assess the clinical psychiatric symptoms of MDD. The evaluation of the current and past-week history of first-episode, drug-naive MDD patients was conducted by experienced psychiatrists who had undergone consistency training and calibration in the HAMD-17.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Evaluation of cognitive function\u003c/h2\u003e\u003cp\u003eDrawing on previous studies, our research utilized the MATRICS Consensus Cognitive Battery (MCCB) to assess cognitive function in both groups\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. The analysis focused on five cognitive domains: processing speed (SOP), attention/ vigilance (AV), working memory (WM), verbal learning (VRB), and visual learning (VIS)\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. This approach to evaluating cognitive function in patients with severe mental illnesses has indeed become a standard practice in clinical research\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. Cognitive functions of all participants were analyzed across these domains to identify significant deficits in individuals with MDD compared to those in the HC group.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Analysis of serum inflammatory markers\u003c/h2\u003e\u003cp\u003eAll participants were required to fast for at least 8 hours. Venous blood samples (5 mL) were obtained from each participant within 48 hours following the completion of clinical evaluations. The blood samples were transported to the Laboratory of Affiliated Brain Hospital of Guangzhou Medical University within 30 minutes for processing. A professional technician performed centrifugation for 10 minutes to separate the serum, which was then used to measure levels of Hypersensitive C-reactive protein (hs-CRP), leukocyte (WBC), neutrophil (NEUR), and eosinophil (EO). All experimental procedures were performed strictly following the manufacturer's instructions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e\u003cp\u003eStatistical analysis for this study was performed using IBM SPSS Statistics 22.0 (IBM Corp., Chicago, USA), with a two-tailed p-value of less than 0.05 considered statistically significant. Categorical variables (such as gender) between MDD and HC groups were compared using chi-square tests, while continuous variables (such as age and education years) were compared with ANOVA. Clinical characteristics, laboratory results, and cognitive scores were subjected to normality testing. Normally distributed variables (Shapiro-Wilk test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) were described as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), with independent t-tests used for group comparisons. Non-normally distributed variables (Shapiro-Wilk test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were described as median and interquartile range (median [P25, P75]), with Mann-Whitney U tests used for comparisons. Spearman correlation analysis was employed to explore relationships among serum inflammatory markers, clinical data, and cognitive performance. Multiple regression analysis (backward elimination model) with MCCB scores as the dependent variable was conducted to investigated the link between MDD cognitive function and serum inflammatory marker levels.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Result","content":"\u003cp\u003e\u003cstrong\u003e3.1 \u0026nbsp;Demographic and clinical characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis investigation involved 216 participants in total, of whom 116 were first-episode, drug-naive patients with MDD, and the remaining 100 participants were HC. The demographic and clinical characteristics of these two groups are presented in \u003cstrong\u003eTable 1\u003c/strong\u003e. In this study, the mean age of the MDD group was 23.06 years (SD = 4.49), whereas the mean age of the HC group was 22.24 years (SD = 2.64). In the MDD group, 60.34% were female and 39.66% were male. No statistically significant differences were found in gender (\u0026chi;\u003csup\u003e2\u003c/sup\u003e = 2.279, \u003cem\u003ep\u003c/em\u003e = 0.095) and age (t = -1.663, \u003cem\u003ep\u003c/em\u003e = 0.098) between the MDD and HC groups. However, the two groups exhibited statistically significant differences in education years (Z = -4.039, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) and BMI (Z = -2.468, \u003cem\u003ep\u003c/em\u003e = 0.014). The mean HAMD-17 score of the MDD patients was 23.68 (SD = 4.93), with a mean age of first onset at 22.23 years (SD = 4.95) and a median total disease duration of ten months.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eThe demographic and clinical characteristics of the two groups of participants.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eMDD (n = 116)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eHC (n = 100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e/t/Z\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eGender(M/F)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e46/70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e51/49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eAge (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e23.06 (4.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e22.24 (2.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-1.663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eEducation years (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e15.00 (12.00, 16.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e16.00 (14.00, 17.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-4.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e21.69 (19.80, 24.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e21.16 (18.82, 23.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-2.468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eAge of first onset(y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e22.23 (4.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eTotal disease duration(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e10.00 (3.00, 18.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eHAMD score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e23.68 (4.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: MDD, Major Depressive Disorder; HC, healthy control; BMI, Body Mass Index; HAMD, The 17-item Hamilton Depression Rating Scale;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 \u0026nbsp;Cognitive function of MDD patients and HC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe MDD and HC groups exhibited significant differences across the five cognitive domains. The MDD group exhibited lower cognitive scores compared with the HC group in SOP, AV, WM, VRB, and VIS. Even after adjusting for the confounding effect of education years, significant cognitive differences remained in AV, WM, and VIS (all \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) (\u003cstrong\u003eTable 2\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable2.\u0026nbsp;\u003c/strong\u003eCognitive function of MDD patients and HC.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003eMDD (n = 116)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eHC (n = 100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eSOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e32.68 (9.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e45.70 (9.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e9.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eAV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e33.28 (9.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e42.16 (8.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e7.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e39.17 (11.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e47.36 (10.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eVRB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e31.57 (9.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e41.72 (7.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e8.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eVIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e39.03 (9.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e45.36 (7.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: MDD, Major Depressive Disorder; HC, healthy control; SOP, Speed of processing; AV, Attention/vigilance; WM, Working memory; VRB, Verbal learning; VIS, Visual learning;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 \u0026nbsp;The differences in serum inflammatory marker levels between the MDD and HC groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in \u003cstrong\u003eTable 3\u003c/strong\u003e, the MDD and HC groups exhibited substantial differences with respect to the levels of several serum inflammatory markers, including WBC (Z = -2.438, \u003cem\u003ep\u003c/em\u003e = 0.015), NEUR (Z = -3.526, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), EO (Z = -2.154, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.031), and hs-CRP (Z = -2.290, \u003cem\u003ep\u003c/em\u003e = 0.022). Specifically, the MDD group exhibited higher levels of WBC (median 6.35 ([P25, P75] 5.60, 7.98)), NEUR (median 3.85 ([P25, P75] 3.20, 5.18)), and hs-CRP (median 1.10 ([P25, P75] 1.10, 1.98)) compared to the HC group (WBC median 6.05 ([P25, P75] 5.23, 6.98); NEUR median 3.30 ([P25, P75] 2.70, 4.30); and hs-CRP median 1.00 ([P25, P75] 0.53, 1.30). In contrast, the MDD group exhibited a significantly lower level of EO (median 0.09 ([P25, P75] 0.05, 0.17)) compared to the HC group (median 0.13 ([P25, P75] 0.08, 0.19)).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eComparison of serum inflammatory markers levels between the two groups.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003eMDD (n\u003cem\u003e\u0026nbsp;\u003c/em\u003e= 116)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eHC (n = 100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eZ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eWBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e6.35 (5.60,7.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e6.05 (5.23,6.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-2.438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eNEUR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e3.85 (3.20,5.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e3.30 (2.70,4.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-3.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003eEO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0.09 (0.05,0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.13 (0.08,0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-2.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003ehs-CRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e1.10 (1.10,1.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.00 (0.53,1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-2.290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: MDD, Major Depressive Disorder; HC, healthy control; WBC, leukocyte; NEUR, neutrophil; EO, eosinophil; hs-CRP, Hypersensitive C-reactive protein;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 \u0026nbsp; \u0026nbsp; \u0026nbsp; Correlation of cognitive function with serum inflammatory markers and BMI in MDD and HC group\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter controlling for confounding effect of education years, significant differences in cognitive function remained between the MDD and HC within the domains of AV, WM and VIS (all \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Further analysis using Spearman correlation analysis revealed that in the HC, VRB was inversely correlated with NEUR levels (r = -0.201, \u003cem\u003ep\u003c/em\u003e = 0.045). In the MDD group, SOP showed a positive association with BMI (r = 0.274, \u003cem\u003ep\u003c/em\u003e = 0.003), and AV also showed a positive association with BMI (r = 0.189, \u003cem\u003ep\u003c/em\u003e = 0.042). However, no significant correlations were observed between other serum inflammatory markers and cognitive performance (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05) (\u003cstrong\u003eTable 4\u003c/strong\u003e) (\u003cstrong\u003eFig 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eCorrelation between five dimensions of MCCB and serum inflammatory markers, as well as BMI in HC and MDD groups.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eSOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eAV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eVRB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eVIS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eHC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.790\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.972\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.849\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eWBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.490\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eNEUR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eEO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.112\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.459\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.267\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003ehs-CRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.661\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eMDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.135\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eWBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.959\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eNEUR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.740\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003eEO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.205\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003ehs-CRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e0.980\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: MDD, Major Depressive Disorder; HC, healthy control; SOP, Speed of processing; AV, Attention/vigilance; WM, Working memory; VRB, Verbal learning; VIS, Visual learning; WBC, leukocyte; NEUR, neutrophil; EO, eosinophil; hs-CRP, Hypersensitive C-reactive protein;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 \u0026nbsp;Regression analysis of serum inflammatory markers levels, BMI and cognitive function\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study employed multiple regression analysis with a backward elimination model to examine the influence of serum inflammatory markers and BMI on cognitive function in MDD patients. In our analysis, MCCB scores were used as the dependent variable, while demographic data, clinical features and serum inflammatory markers were included as independent variables. The results indicated that the regression model was significant for education years (B = 1.272, t = 3.758, \u003cem\u003ep\u003c/em\u003e ＜ 0.001) and hs-CRP levels (B = -1.654, t = -2.085, \u003cem\u003ep\u003c/em\u003e = 0.039) in relation to VIS cognitive function performance (\u003cstrong\u003eTable 5\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u003c/strong\u003e Factors Affecting Cognitive Function in Patients with MDD.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eS.E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e95 % CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003eUpper\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003eVIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eEducation years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e3.758\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1.943\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003ehs-CRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-1.654\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-2.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-3.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e-0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: MDD, Major Depressive Disorder; VIS, Visual learning; hs-CRP, Hypersensitive C-reactive protein;\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe primary results of this study are presented as follows: (1) The T-scores for the five cognitive domains were substantially reduced in the MDD group compared with the HC group. (2) Versus the HC group, the MDD group exhibited markedly elevated levels of WBC, NEUR, and hs-CRP, as well as significantly reduced levels of EO among the serum inflammatory markers. (3) Elevated serum hs-CRP levels were identified as a substantial predictor of cognitive impairment among individuals with MDD. (4) The MDD group had a markedly elevated BMI compared to the HC group. Additionally, BMI was positively correlated with cognitive function in MDD patients, particularly within the domains of SOP and AV. (5) In the HC group, serum NEUR levels exhibited a negative correlation with VRB. Currently, there is no definitive conclusion regarding the impact of serum inflammatory markers on cognitive function in MDD patients. Therefore, our study results will further elucidate the factors contributing to cognitive impairment in these patients and enhance our understanding of the predictive capacity of serum inflammatory marker levels for cognitive decline in MDD.\u003c/p\u003e\n\u003cp\u003eOur study revealed that, contrasted with HC, MDD patients had significantly lower scores across all five dimensions of cognitive function. Even when controlling for \u0026nbsp;education years, significant differences in cognitive function remained in the AV, WM, and VIS dimensions, consistent with our earlier findings\u003csup\u003e[2]\u003c/sup\u003e. Cognitive dysfunction in MDD can compromise social functioning, attention, learning capacity, and exacerbate depressive symptoms, all of which may influence treatment efficacy and patient prognosis. Cognitive dysfunction in MDD persists even during remission and worsens with each recurrence. Our findings further confirm multi-dimensional cognitive impairment in first-episode, drug-naive MDD patients. Cognitive function serves as an essential clinical feature of MDD and plays a crucial role in predicting and assessing future treatment outcomes.\u003c/p\u003e\n\u003cp\u003eAdditionally, significant differences in serum hs-CRP, WBC, NEUR, and EO levels were found between the two groups. Compared to CRP, hs-CRP is more sensitive and can accurately detect low-concentration CRP levels. It is a trace protein in the blood, synthesized in large quantities by hepatocytes during infection or inflammation\u003csup\u003e[39]\u003c/sup\u003e. Depression is often associated with a pro-inflammatory phenotype, particularly in the central nervous system, where inflammatory conditions can lead to chronic neuroinflammation through the activation of microglia and astrocytes\u003csup\u003e[40]\u003c/sup\u003e. A review on the potential mechanisms underlying cognitive impairment highlighted that microglial activation can alter the expression of various neurotoxic mediators, promote the accumulation of inflammatory factors, and amplify inflammatory cycles, leading to glial damage and neuronal cell death\u003csup\u003e[41]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe association between serum inflammatory markers and cognitive dysfunction has garnered increasing attention. In particular, serum hs-CRP levels have been highlighted as a significant factor in MDD-related cognitive impairment. Previous research has established a connection between elevated hs-CRP levels and cognitive dysfunction across various conditions, including MDD\u003csup\u003e[27]\u003c/sup\u003e, mild cognitive impairment (MCI)\u003csup\u003e[42]\u003c/sup\u003e, and SCZ\u003csup\u003e[43]\u003c/sup\u003e. These effects not only disrupt the hypothalamic energy homeostasis and appetite regulation centers but also impact other brain regions, including the prefrontal cortex and hippocampus, contributing to corresponding cognitive impairment\u003csup\u003e[44]\u003c/sup\u003e. This represents a critical factor contributing to progressive neuronal damage. Both acute and chronic systemic inflammation can lead to cognitive dysfunction. On one hand, hs-CRP triggers systemic inflammation, increasing proinflammatory cytokines and causing cognitive dysfunction. On the other hand, inflammation affects vascular reactivity. High hs-CRP levels cause cerebral vasodilation and reduced vascular reactivity, accelerating cognitive decline, particularly in executive function and daily living activities\u003csup\u003e[41, 45]\u003c/sup\u003e. Previous research has indicated that elevated levels of hs-CRP are linked to an increased likelihood of cognitive impairment\u003csup\u003e[46]\u003c/sup\u003e. In a longitudinal study spanning 12 years, higher serum hs-CRP levels were found to predict memory decline, suggesting hs-CRP as a simple and objective biomarker for identifying cognitive dysfunction\u003csup\u003e[47]\u003c/sup\u003e. To explore the relationship between serum inflammatory levels and cognitive function in first-episode, drug-naive patients with MDD, we conducted a correlation analysis between serum inflammatory markers and cognitive domains. Nevertheless, no statistically significant association was observed between hs-CRP and cognitive function. Previous studies have shown that measuring epigenetic levels of CRP (DNAm CRP) in peripheral blood yields more stable inflammation levels and stronger correlations with cognitive impairment than serum CRP\u003csup\u003e[48]\u003c/sup\u003e. Therefore, the instability of hs-CRP in serum, which is susceptible to rapid concentration changes in plasma, may contribute to our results. Future research could consider measuring DNA methylation levels of more stable inflammatory markers to quantify their association with cognitive function. To further explore the relationship between serum inflammatory markers and cognitive function in first-episode, drug-naive patients with MDD, we conducted multiple linear regression analysis. Our findings reveal a potential link between elevated levels of hs-CRP and cognitive impairment in MDD patients, indicating that hs-CRP might act as a risk factor for cognitive deficits, particularly in the domain of VIS. The result indicates that systemic inflammation from high hs-CRP levels in MDD patients can cause cognitive dysfunction, similar to past reports on inflammation-induced cognitive dysfunction in other diseases\u003csup\u003e[42, 49]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn addition to the findings regarding hs-CRP and cognitive function, our study demonstrated that MDD patients had a significantly higher BMI compared to HC, suggesting that patients with MDD are more likely to experience an increase in BMI. This observation aligns with previous research indicating a higher prevalence of obesity in MDD patients\u003csup\u003e[15, 50]\u003c/sup\u003e. However, in further correlation analysis, we identified a positive association between BMI and cognitive dysfunction in MDD patients, particularly in the domains of SOP and AV. This observation contrasts with many previous studies that identified obesity as a possible predictor for cognitive dysfunction\u003csup\u003e[51-54]\u003c/sup\u003e. We hypothesize that first-episode, drug-naive MDD patients might demonstrate reduced BMI levels, which could be attributed to anorexia and weight loss-related nutritional deficiencies. These deficiencies might also contribute to cognitive impairment in these patients. Biologically, the peripheral immune system and central inflammatory mediators communicate bidirectionally. An elevated BMI is associated with increased peripheral and central inflammation, a condition that can trigger the stimulation of brain immune cells, including microglia and astrocytes. Sustained immune-inflammatory activation can alter emotions and cognitive function\u003csup\u003e[55]\u003c/sup\u003e. Nonetheless, some studies offer different perspectives. For instance, a prior study has identified a significant positive association between BMI and cognitive performance in male patients with SCZ\u003csup\u003e[33]\u003c/sup\u003e. Additionally, some research suggested that a healthy BMI doesn\u0026apos;t adversely affect cognitive function\u003csup\u003e[56]\u003c/sup\u003e. In other neurodegenerative diseases with cognitive impairment, a reduction in leptin due to weight loss may lead to cognitive dysfunction\u003csup\u003e[57]\u003c/sup\u003e. Moreover, well-metabolized obesity in older patients may confer a certain protective effect against the pathological mechanisms of AD\u003csup\u003e[58]\u003c/sup\u003e, which also supports our results to some extent. Subsequent research ought to further explore the complex interplay between BMI, inflammation, and cognitive performance in MDD.\u003c/p\u003e\n\u003cp\u003eOur results indicated a negative correlation between NEUR and VRB within the HC group, a finding that was not replicated in the MDD group, indicating that NEUR is not a strong correlate of VRB in MDD. Previous research in non-demented cohorts has demonstrated that elevated NEUR levels were linked with cognitive dysfunction and accelerated deterioration of episodic memory\u003csup\u003e[59]\u003c/sup\u003e. These findings collectively highlight the importance of maintaining peripheral immune homeostasis in protecting cognitive function. Future research could investigate this correlation in more diverse populations, both cross-sectionally and longitudinally, to better identify cognitive dysfunction risk factors.\u003c/p\u003e"},{"header":"5 Limitations","content":"\u003cp\u003eWe acknowledge several limitations in our study. First, it is a cross-sectional analysis of MDD patients. Serum inflammatory markers fluctuate over time, and their long-term, stable impact on MDD patients' cognitive function remains unclear. Second, although our study found that serum hs-CRP affects MDD patients' cognitive function, the specific mechanism of action of serum inflammatory markers on cognitive function is still unknown. Therefore, in the future, we plan to expand the cross-sectional study of MDD patients and conduct follow-up assessments after pharmacological intervention. We will also seek more stable measurement methods for serum inflammatory markers and employ more rigorous experimental approaches to analyze risk factors related to cognitive dysfunction in MDD patients. Our ultimate goal is to identify effective biomarkers that can predict cognitive impairment in MDD patients for clinical application. Third, our study sample was drawn from diverse regions, and we did not control for the potential impact of dietary intake on cognitive function.\u003c/p\u003e"},{"header":"6 Conclusion","content":"\u003cp\u003eOur research reveals that MDD patients suffer from extensive cognitive dysfunction and exhibit markedly higher serum hs-CRP levels than HC. The potential link between serum hs-CRP levels and VIS in MDD patients suggests that hs-CRP might act as a prospective inflammatory biomarker for predicting cognitive impairment in first-episode, drug-naive patients with MDD. Additionally, BMI shows a certain predictive value for cognitive function in MDD patients. In summary, our results show a close relationship between serum inflammatory markers, BMI and cognitive dysfunction in first-episode and drug-naive MDD patients, offering new directions for future research.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMDD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMajor depressive disorder\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHealthy Control\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMCCB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ethe MATRICS Consensus Cognitive Battery\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHAMD-17\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ethe 17-item Hamilton Depression Rating Scale\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ehs-CRP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehypersensitive C-reactive protein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eWBC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLeukocyte, White blood cells\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNEUR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNeutrophil\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEO\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEosinophil\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSOP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSpeed of processing\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAttention/Vigilance\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eWM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eWorking memory\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eVIS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eVerbal learning\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eVRB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eVisual learning\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBody Mass Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBBB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBlood Brain Barrier\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSCZ\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSchizophrenia\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAlzheimer's disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDSM-5\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ethe fifth edition of the Diagnostic and Statistical Manual of Mental Disorders\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of the Affiliated Brain Hospital of Guangzhou Medical University and was conducted in accordance with the latest version of the Declaration of Helsinki (2013). Before the study, all participants were required to sign the informed consent form.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during the current study are not publicly available, but can be requested from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by Key-Area Research and Development Program of Guangdong Province (2023B0303020001), National Natural Science Foundation of China (82301688), Natural Science Foundation of Guangdong (2025A1515010507), Science and Technology Program of Guangzhou (2025A03J3357, 202206060005, 2023A03J0856), Guangdong Basic and Applied Basic Research Foundation Outstanding Youth Project (2021B1515020064), Medical Science and Technology Research Foundation of Guangdong (A2023224), Health Science and Technology Program of Guangzhou (20231A010036), Guangzhou Municipal Key Discipline in Medicine (2025-2027), and National Traditional Chinese and Western Medicine Collaborative Project for Major and Complex Diseases (Comprehensive Department of the National Administration of Traditional Chinese Medicine [2024] No. 3), National Integrated Traditional Chinese and Western Medicine \u0026quot;Flagship\u0026quot; Department Construction Project (Comprehensive Department of the National Administration of Traditional Chinese Medicine [2024] No. 221).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJingping Wu:\u003c/strong\u003e Writing\u0026ndash;original draft, Visualization, Investigation, Formal analysis, Data curation, Conceptualization. \u003cstrong\u003eYuanyuan Huang:\u003c/strong\u003e Writing\u0026ndash;review \u0026amp; editing, Methodology, Resources, Funding acquisition. \u003cstrong\u003eHehua Li:\u003c/strong\u003e Validation, Methodology, Resources. \u003cstrong\u003eSumiao Zhou:\u003c/strong\u003e Visualization, Data curation. \u003cstrong\u003eZhendong Zhang:\u003c/strong\u003e Formal analysis. \u003cstrong\u003eZiyun Zhang:\u003c/strong\u003e Software. \u003cstrong\u003eShixuan Feng:\u003c/strong\u003e Data curation. \u003cstrong\u003eLam Mei Fong:\u003c/strong\u003e Visualization. \u003cstrong\u003eKai Wu:\u0026nbsp;\u003c/strong\u003eResources. \u003cstrong\u003eFengchun Wu:\u003c/strong\u003e Writing\u0026ndash;review \u0026amp; editing, Resources, Supervision, Project administration, Funding acquisition, Conceptualization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors thank all the participants who participate in our study training program.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGu X, Ke S, Wang Q, et al. 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Sci Rep. 2024;14(1):19773.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSergi G, De Rui M, Coin A, et al. Weight loss and Alzheimer's disease: temporal and aetiologic connections[J]. Proc Nutr Soc. 2013;72(1):160\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu W, Tan L, Wang H, et al. Meta-analysis of modifiable risk factors for Alzheimer's disease[J]. J Neurol Neurosurg Psychiatry. 2015;86(12):1299\u0026ndash;306.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFa W, Liang X, Liu K et al. Associations of Blood Absolute Neutrophil Count and Cytokines With Cognitive Function in Dementia-Free Participants: A Population-Based Cohort Study[J]. J Gerontol Biol Sci Med Sci, 2024,79(1).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Major Depressive Disorder, Cognitive Dysfunction, Serum Hypersensitive C-reactive Protein, Body Mass Index","lastPublishedDoi":"10.21203/rs.3.rs-6915326/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6915326/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eMajor depressive disorder (MDD) is a mental illness that is highly prevalent worldwide. Besides its core symptoms, the cognitive dysfunction in MDD patients seriously impairs their social functioning and warrants attention. Cognitive dysfunction in MDD may be related to demographic characteristics, serum inflammatory marker levels and Body Mass Index (BMI, calculated as weight divided by height squared, in kg/m\u0026sup2;). This study focuses on the cognitive dysfunction and its associated factors in first-episode, drug-naive patients with MDD .\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThe study enrolled overall 116 first-episode, drug-naive patients with MDD and 100 healthy controls (HC) for comparison. Demographic information was obtained from all participants. We used the Chinese version of the MATRICS Consensus Cognitive Battery (MCCB) to assess cognitive function and the 17-item Hamilton Depression Rating Scale (HAMD-17) to evaluate MDD symptoms. Levels of serum inflammatory markers, such as hypersensitive C-reactive protein (hs-CRP), leukocyte (WBC), neutrophil (NEUR), and eosinophil (EO) were measured. Subsequently, multiple linear regression analysis was utilized to determine factors linked to cognitive dysfunction across the five domains with MDD patients.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eIn this study, MDD patients exhibited significantly poorer cognitive function across five domains - speed of processing (SOP), attention/vigilance (AV), working memory (WM), verbal learning (VIS), and visual learning (VRB) - compared with HC (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Their serum levels of hs-CRP (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022), WBC (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015), and NEUR (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly elevated than HC, whereas the level of EO (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031) was significantly lower. The results of Spearman correlation analysis indicated that BMI was connected to cognitive function among MDD patients, specifically in the domains of SOP (r\u0026thinsp;=\u0026thinsp;0.274, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) and AV (r\u0026thinsp;=\u0026thinsp;0.189, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.042). Multiple linear regression analysis indicated that education years and hs-CRP level were significantly influenced by the cognitive function in the VIS domain among patients with MDD.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eOur study shows a potential link between serum hs-CRP levels, BMI and cognitive dysfunction in MDD patients. This indicates that serum hs-CRP could potentially serve as a promising biomarker to forecast cognitive dysfunction in MDD patients, offering significant clinical implications. Additionally, BMI appears to have a certain predictive value regarding cognitive function in patients with MDD.\u003c/p\u003e","manuscriptTitle":"Effects of serum hypersensitive C-reactive protein and BMI on cognitive dysfunction in first-episode and drug-naive patients with major depressive disorder","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-22 10:33:33","doi":"10.21203/rs.3.rs-6915326/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-18T16:13:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-15T07:51:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"162782777397866640011724609095102348946","date":"2025-09-13T05:22:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33004200555428803060512263002894964733","date":"2025-09-10T04:53:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-05T18:08:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"108250260040839050531213536245333447926","date":"2025-09-05T17:28:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-19T13:43:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"189456247011268582160658396874639190265","date":"2025-08-18T09:00:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12177441246574600813379300941612292327","date":"2025-08-17T21:34:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-15T12:03:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-24T07:50:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-23T15:44:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-23T15:43:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2025-06-17T14:15:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"01cfa382-8142-4994-bd5a-4a15ed38944e","owner":[],"postedDate":"August 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-02T16:02:27+00:00","versionOfRecord":{"articleIdentity":"rs-6915326","link":"https://doi.org/10.1186/s12888-026-07782-y","journal":{"identity":"bmc-psychiatry","isVorOnly":false,"title":"BMC Psychiatry"},"publishedOn":"2026-01-27 15:58:18","publishedOnDateReadable":"January 27th, 2026"},"versionCreatedAt":"2025-08-22 10:33:33","video":"","vorDoi":"10.1186/s12888-026-07782-y","vorDoiUrl":"https://doi.org/10.1186/s12888-026-07782-y","workflowStages":[]},"version":"v1","identity":"rs-6915326","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6915326","identity":"rs-6915326","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}