Association between cognitive function, antioxidants, and clinical variables in Chinese patients with schizophrenia

Association between cognitive function, antioxidants, and clinical variables in Chinese patients with schizophrenia | 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 Association between cognitive function, antioxidants, and clinical variables in Chinese patients with schizophrenia Dan Li, Yuanyuan Huang, Hongxin Lu, Sumiao Zhou, Shixuan Feng, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4336905/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Dec, 2024 Read the published version in BMC Psychiatry → Version 1 posted 4 You are reading this latest preprint version Abstract Objective Cognitive dysfunction is a prevalent and intricate manifestation of schizophrenia (SCZ) that may be associated with distinct clinical factors and the presence of antioxidants, which relationship is unclear. The study aimed to investigate cognitive function and its influencing factors in Chinese patients with SCZ. Methods A group of 133 patients with SCZ and 120 healthy controls (HCs) were recruited. The MATRICS Consensus Cognitive Battery (MCCB) was utilized to evaluate cognitive ability, and the Positive and Negative Syndrome Scale (PANSS) was used to assess clinical symptoms. Levels of plasma superoxide dismutase (SOD), serum albumin (ALB) and uric acid (UA) were assessed. Results Compared with HCs, patients with SCZ exhibited lower cognitive performance as indicated by MCCB scores, including the dimensions of speed of processing, attention/vigilance, working memory, verbal learning, and visual learning. In the SCZ group, total PANSS scores were negatively associated with all MCCB dimensions (all p < 0.05), except for the attention/vigilance score. The PANSS-negative and PANSS-cognitive subscores were negatively associated with speed of processing, verbal learning, and visual learning scores (all p < 0.05). The PANSS-excited subscores showed a negative correlation with working memory and visual learning scores (all p < 0.05). ALB levels significantly decreased, and their UA and SOD levels were notably elevated compared to HCs (all p < 0.05). ALB levels and PANSS-negative factors were correlated with to speed of processing, working memory, and visual learning dimensions. SOD levels were independent contributors to the attention/vigilance dimension. Conclusions The cognitive function was decreased in SCZ. The degree of cognitive impairment was closely related to ALB, SOD levels and negative clinical symptoms. cognitive function schizophrenia PANSS superoxide dismutase serum albumin uric acid Figures Figure 1 Figure 2 1. Background Cognitive dysfunction in schizophrenia (SCZ) the core of a kind of serious and common symptoms that affects attention, learning, executive function, processing speed, speech, and memory. Approximately 85% of patients with SCZ exhibit cognitive impairment [ 1 ], which is one explanation for the poor curative effect of current therapies and prognosis of patients, which severely affects social function and the ability to live independently, and even potential impulsive behaviors such as suicide and self-injury[ 2 , 3 ]. To date, many tools have been used in clinical practice to assess cognitive function in patients with SCZ, many of which rely only on the patient’s medical history interview [ 4 ], which is, to some extent, subjectively influenced by the evaluator. Research on cognitive decline in SCZ has emphasized issues with neuronal development, disrupted neurotransmission, viral infections, autoimmune problems, and oxidative stress (OS)[ 5 – 9 ]. Recently, there has been an increasing focus on the relationship between SCZ and OS [ 10 ], which may provide a direction for exploring objectively effective auxiliary diagnostic techniques and methods for clinical evaluation of cognitive function in individuals with SCZ. OS is a process in which the body generates an excessive amount of highly reactive molecules upon encountering specific detrimental stimuli. These molecules cannot be completely eliminated by antioxidants, thereby disrupting the delicate balance between oxidation and antioxidant systems [ 11 , 12 ]. Under normal circumstances, the body possesses a sophisticated antioxidant defense system that uses endogenous antioxidants to effectively eliminate excess free radicals and safeguard tissues from potential damage. Enzymatic and non-enzymatic antioxidants make up the antioxidant defense system [ 11 ], including superoxide dismutase (SOD), catalase, and glutathione peroxidase as enzymatic antioxidants, and albumin (ALB), bilirubin, uric acid (UA), vitamin C, and vitamin E as non-enzymatic antioxidants. Various diseases, like tumors, cardiovascular and neurological disorders (e.g., Alzheimer’s disease, Parkinson’s disease, and Down syndrome), as well as mental illnesses such as depression, SCZ, and bipolar disorder, are closely linked to OS [ 13 – 15 ]. Recent research on SCZ and OS revealed a correlation between thioredoxin and cognitive impairments in SCZ patients [ 16 ], along with increased levels of nitric oxide in the brains of individuals with SCZ. The majority of past research on OS and cognitive abilities has centered around the topics of getting older and Alzheimer's disease [ 17 – 19 ]. Further clinical confirmation is necessary to determine the correlation between OS and cognitive performance in individuals with SCZ. Considering the importance of cognitive function in the rehabilitation and prognosis of patients with SCZ, it is imperative to study its influencing factors and mechanisms, particularly OS. Hardingham et al. [ 20 ] found a link between early-life NMDAR dysfunction and OS in SCZ pathogenesis. Studies have shown elevated levels of SOD activity in the blood, red blood cells, prefrontal cortex, and innominate substances in autopsies of individuals with SCZ[ 21 ]. Some studies have also indicated reduced SOD1 activity. Multiple studies have indicated that OS plays a role in the development of early cognitive impairment in SCZ [ 22 ]. We previously established a correlation between OS markers and cognitive function, gender, and obesity in individuals diagnosed with SCZ, setting the stage for additional research on the link between antioxidant levels and cognitive function in patients with SCZ [ 23 , 24 ]. Although previous investigations have confirmed the correlation between cognitive function and OS in patients with SCZ, most were laboratory studies. Conveniently assessed blood indicators may be more useful for real-time guidance in clinical practice. Considering the critical role of antioxidants in the development of SCZ, there are no standardized, consistent, readily available, and affordable biomarkers that can effectively indicate cognitive impairment in individuals with SCZ. This study is the initial investigation into potential factors that could impact cognitive function in SCZ patients through an examination of plasma SOD, as well as serum levels of UA and ALB, and the relationship(s) with cognitive function and clinical manifestations. This provides an objective method for the clinical assessment of cognitive function in patients with SCZ. 2. Methods 2.1. Participants Prior to participating in the research, all participants and their guardians provided written consent following approval of the study protocol by the Ethics Committee of the Affiliated Brain Hospital of Guangzhou Medical University in Guangzhou, China(Number: AF/SC-08/02.1). From December 2021 to September 2022, a group of 253 individuals (120 HCs and 133 individuals with SCZ) were enrolled in the study. Each patient in the study, aged 18 to 60, of Han Chinese descent, met all inclusion criteria. They were diagnosed with SCZ according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) by two experienced psychiatrists using the Structured Clinical Interview for DSM-IV (SCID-I/P), and had been on a stable dose of antipsychotic medications for at least 8 weeks before the research began. Individuals with significant medical abnormalities, such as unstable or acute medical conditions, comorbid psychiatric disorders, previous history of epilepsy, intellectual disabilities, brain trauma, use of electroconvulsive therapy in the previous six months, and use of any antioxidants or immunomodulators within the last three months were excluded. Han Chinese 18–60 years of age were recruited through advertisements in a local community in Guangzhou, China. No participants reported a history of psychiatric disorders, either personally or within their family, during the informal interviews. They exhibited comparable socioeconomic status and dietary patterns, and had not received any antioxidants or immunomodulators within 3 months. 2.2. Clinical measurements All patients with SCZ and HCs underwent complete medical history taking, laboratory investigations, and physical examinations. General information and sociodemographic characteristics were collected based on questionnaires, and histories of psychiatric disorders and medication use were obtained from medical records by trained research staff. Two trained psychiatrists used the Positive and Negative Syndrome Scale (PANSS) [ 25 ] to assess the psychiatric symptoms of all patients with SCZ. The study utilized the PANSS five-factor model to evaluate individuals in 5 different areas: positive symptoms (P1, P5, G9 ), negative symptoms (N1, N2, N3, N4, N6, G7), excitatory symptoms (P4, P7, G8, G14 ), depressive and anxious symptoms (G2, G3, G6 ), as well as cognitive impairments (P2, N5, G11)[ 26 ]. The inter-rater reliability coefficient for the PANSS total score surpassed 0.8 in repeated evaluations. 2.3. Cognitive assessments Patients' cognitive function, such as speed of processing (SOP), attention/vigilance (AV), working memory (WM), verbal learning (VRB), and visual learning (VIS) reasoning and problem-solving, and social cognition, was assessed using the MATRICS Consensus Cognitive Battery (MCCB) tool [ 27 ]. The first 5 items assess cognitive function. The domains primarily mirror the cognitive abilities of individuals with SCZ[ 28 ]. Research conducted by Shi et al[ 29 ] has shown that the Chinese adaptation of the MCCB exhibits positive psychometric characteristics, suggesting robust reliability and validity. 2.4. Analysis of antioxidants levels Each participant had venous blood samples collected in the early morning after fasting for at least 8 hours. Blood was obtained and placed in an EDTA tube, followed by centrifugation (3000 rpm) for a duration of 10 minutes within 30 min after collection. A clinical laboratory technician at the hospital performed blood biochemical tests without knowledge of participant information. Levels of SOD, ALB, and UA were assessed with an automated biochemical analyzer (Beckman AU480, BD Biosciences, Franklin Lakes, NJ, USA) and kits from Beijing Leadman Biotechnology Co., Ltd (Beijing, China). SOD levels were measured using SOD assay kits (enzyme cycle assays). All experimental procedures followed the manufacturer's instructions meticulously. 2.5. Statistical analysis The chi-squared test was used to compare demographic variables (i.e., categorical) between patients with SCZ and HCs, while analysis of variance (ANOVA) was used to compare continuous variables. Due to the non-normal distribution of ALB levels (Shapiro–Wilk test, p < 0.05), a non-parametric test (Mann–Whitney test) was employed to assess the differences in ALB levels between individuals with SCZ and HCs. ANCOVA was utilized to assess the disparities in levels of UA and SOD, and cognitive performance on the MCCB between the 2 groups after controlling for demographic variables (i.e., education, body mass index [BMI], and marital status) and clinical symptoms (i.e., PANSS total and subscale scores), which revealed significant between-group differences. The relationships among antioxidant enzyme levels, clinical ratings, and cognitive performance were examined using Spearman’s correlation. Furthermore, partial correlation was used to control for additional variables. Multiple tests were adjusted using the Bonferroni correction. Multivariate regression analyses (stepwise regression model) with MCCB subscores were used as dependent variables to investigate the relationship between cognitive function and antioxidant enzyme levels, while controlling for demographic variables and clinical symptoms on the PANSS. Statistical analyses were conducted using SPSS version 18.0 from IBM Corporation in Chicago, IL, USA. Statistically significant differences were defined as those with a two-tailed p-value less than 0.05. 3. Results 3.1 Demographic and clinical data Demographic information and clinical data of the participants included in this study are summarized in Table 1 . There were significant differences in marital status, education, and BMI between the 2 groups (all p < 0.05); however, there were no significant disparities in terms of gender or age. Marital status, education, and BMI were adjusted for in subsequent analyses. Table 1 Demographics of SCZ patients and HCs. Variable SCZ patients n = 133 HCs n = 120 F/χ2 p-value Age (years) 44.74 ± 12.84 43.52 ± 13.06 0.560 0.455 Male/female,n 77/56 63/57 0.743 0.448 Married status 52.774 < 0.001 Married 22(16.5%) 73(60.8%) - - Unmarried 111(83.5%) 47(39.2%) - - Education (years) 11.08 ± 3.36 14.08 ± 3.35 50.089 < 0.001 Body mass index (BMI) (kg/m 2 ) 24.15 ± 4.28 23.08 ± 3.85 4.892 0.028 Family history,n(%) 31(23.3%) - - - Age of onset (years) 25.26 ± 7.43 - - - Duration of disease (months) 220.41 ± 157.73 - - - Antipsychotic dosage (mg/day),CPZ equivalents 406.63 ± 180.06 - - - PANSS total score 58.24 ± 18.86 - - - Positive subscore 6.91 ± 3.69 - - - Negative subscore 14.62 ± 7.57 - - - Excited subscore 5.29 ± 2.17 - - - Depressive subscore 6.16 ± 3.15 - - - Cognitive subscore 4.77 ± 2.39 - - - p < 0.05,the difference was statistically significant;PANSS:Positive and Negative Syndrome Scale. 3.2 Cognitive function of patients with SCZ and HCs Table 2 summarizes information on cognitive function (MCCB performance) in individuals with SCZ and HCs. Compared with HCs, patients with SCZ exhibited worse cognitive performance in terms of SOP, AV, WM, VRB, and VIS. The significant differences persisted even after adjusting for BMI, marital status, and educational level (all p < 0.05). In the SCZ group, the PANSS total scores were negatively associated with all MCCB indices (all p < 0.05) except AV. The PANSS-negative and PANSS-cognitive subscores had a negatively correlation with the SOP, VRB, and VIS scores (all p < 0.05). There was a negative correlation between PANSS-excited subscores and WM and VIS scores (all p < 0.05). Table 2 Cognitive functions (MCCB) of SCZ patients and HCs. Variable SCZ patients n = 133 HCs n = 120 F p-value Adjusted F* Adjusted p * SOP score 31.01 ± 17.18 50.99 ± 9.17 129.180 < 0.001 67.016 < 0.001 AV score 36.55 ± 10.71 49.61 ± 9.89 100.885 < 0.001 60.837 < 0.001 WM score 35.65 ± 13.74 48.89 ± 9.63 77.259 < 0.001 28.888 < 0.001 VRB score 32.29 ± 12.78 45.11 ± 10.45 75.363 < 0.001 44.997 < 0.001 VIS score 34.94 ± 12.19 48.34 ± 10.62 86.292 < 0.001 47.801 < 0.001 *Adjusted values were calculated with age, BMI, marital status, and education as covariates. MCCB, the MATRICS Consensus Cognitive Battery of tests; SOP, speed of processing; AV, attention/vigilance; WM, working memory; VRB, verbal learning and memory; VIS, visual learning and memory. 3.3 ALB, UA, and SOD levels in patients with SCZ and HCs Antioxidant levels (ALB, UA, and SOD) in individuals with SCZ and HCs are presented in Fig. 1 . Serum ALB levels were significantly lower in those with SCZ (median 42.45 ([P25, P75] 39.82, 46.10]) than in HCs (median 44.52 [41.55, 48.48]; z = -2.418; p = 0.016). Even after accounting for BMI, marital status, and educational, the distinction in ALB levels between the two groups continued to be noteworthy ( p < 0.05). Elevated levels of Serum UA and SOD were observed in participants diagnosed with SCZ when compared to HCs (400.16 ± 117.63 versus [vs.] 351.28 ± 105.48 µmol/L; F = 11.991, p = 0.001; 162.94 ± 21.00 vs. 133.22 ± 33.91 U/mL; F = 71.323, p < 0.001). These variations remained significant even after accounting for factors such as BMI, marital status, and educational (F = 8.613, p = 0.004; F = 33.328, p 0.05), except ALB and SOD levels, which were inversely related to age in both the HCs and SCZ groups ( p < 0.05). Within the SCZ cohort, the levels of ALB and SOD showed an inverse correlation with the duration of the disease, while the levels of UA exhibited a positive correlation with PANSS-negative factors. Spearman correlation analysis revealed that antioxidant levels were associated with partial cognitive function in the SCZ group (Table 3 ). Within the SCZ group, there was a positive correlation between ALB levels and cognitive performance across 5 MCCB indexes (r = 0.172–0.281, p < 0.05) (Fig. 2 ). After adjusting for BMI, marital status, and educational, partial correlation analysis reaffirmed the strong connection (r = 0.177–0.292, p < 0.05). All correlations passed Bonferroni correction ( p 0.05). Cognitive performance showed a positive correlation with SOD levels (r = 0.183–0.222, p 0.05). After adjusting for BMI, marital status, and educational, the partial correlation analysis provided additional evidence of a strong link between SOD levels and AV (r = 0.299, p = 0.001; Bonferroni-corrected p 0.05). There was no correlation between the cognitive performance of the HCs and the levels of the 3 antioxidants (all p > 0.05). Levels of UA were not found to be correlated with cognitive performance in SCZ. Table 3 Correlation between five dimensions MCCB and ALB, UA and SOD in patients with SCZ. SOP score AV score WM score VRB score VIS score ALB(g/L) r 0.275 0.270 0.214 0.172 0.281 p 0.001 0.002 0.013 0.048 0.001 SOD(U/ml) r 0.183 0.183 0.183 0.132 0.200 p 0.035 0.035 0.035 0.130 0.021 UA(umol/L) r -0.013 0.032 -0.023 -0.031 0.041 p 0.882 0.717 0.791 0.722 0.642 Additionally, a step-by-step multiple regression analysis was conducted to elucidate how antioxidants, demographic factors, and clinical manifestations impact the cognitive abilities of individuals diagnosed with SCZ. As shown in Table 4 , ALB levels and PANSS-negative factor were independent contributors to the SOP, WM, and VIS indices. SOD levels (beta = 0.14, t = 3.262, p = 0.001) were independent contributors to the AV index. Table 4 Factors for cognitive performance in SCZ patients. dependent variable B S.E t p -value 95% CI Lower Upper SOP score (constant) -10.946 11.655 -0.939 0.349 -34.003 12.112 ALB(g/L) 1.164 0.270 4.307 < 0.001 0.629 1.698 PANSS-negative factor -0.524 0.183 -2.856 0.005 -0.887 -0.161 AV score (constant) 13.779 7.037 1.958 0.052 -0.141 27.699 SOD(U/ml) 0.14 0.043 3.262 0.001 0.055 0.224 WM score (constant) 9.607 9.673 0.993 0.322 -9.529 28.744 ALB(g/L) 0.72 0.224 3.211 0.002 0.277 1.164 PANSS-negative factor -0.319 0.152 -2.096 0.038 -0.62 -0.018 VIS score (constant) 10.59 8.467 1.251 0.213 -6.16 27.34 ALB(g/L) 0.686 0.196 3.494 0.001 0.297 1.074 PANSS-negative factor -0.334 0.133 -2.509 0.013 -0.598 -0.071 Variables in the model: age, marital status, BMI, PANSS total scores and its subscores, ALB, UA, and SOD. 4. Discussion This research was the initial exploration into the correlation between enzymatic and non-enzymatic antioxidants (SOD, ALB, and UA) and the cognitive function and symptoms of individuals diagnosed with SCZ. The primary discoveries of this research were the following. First, patients with SCZ exhibited extensive cognitive impairment compared with HCs. Second, PANSS-negative sub-scores showed a negative correlation with SOP, WM, and VIS scores. Third, SOD levels were positively correlated with cognitive performance (except VRB) in the SCZ group, which was an independent contributor to the AV index. Fourth, ALB levels in the SCZ group were independent contributors to the SOP, WM, and VIS indices. Patients with SCZ had notably elevated UA levels compared to HCs, however, these levels did not show a correlation with cognitive function. These results indicate that different antioxidant enzymes affect different cognitive dimensions in patients with SCZ. Our study found that individuals diagnosed with SCZ exhibited significant cognitive deficits in SOP, AV, WM, VRB and VIS, indicating widespread cognitive impairment, aligning with findings from earlier research studies [ 1 , 30 – 33 ]. Cognitive impairment may impact the daily activities of individuals with SCZ, leading to a suboptimal treatment response, challenges in functional recovery, and an elevated risk for long-term disability. The causes of cognitive decline in SCZ are intricate, with growing proof suggesting a common disease-causing gene, epigenetic control of DNA, and resulting changes in the proteome and metabolome, potentially impacting cognitive abilities [ 34 , 35 ]. The neurobiological basis of cognitive impairment commonly involves reduced levels of gray matter neurons, abnormal myelin density, and white matter cellulose connectivity [ 36 ], impaired signal integration at the neuronal and neural network levels, neurotransmitter abnormalities, immune dysregulation, and OS [ 30 , 37 , 38 ]. We explored the relationship between antioxidant levels and cognitive function in patients with stable SCZ, suggesting the need for future research in first-episode SCZ patients and those who have not yet received medication. In the SCZ group, all MCCB indices showed a strong inverse relationship with the total PANSS score, except AV. Moreover, the adverse factor rating of the PANSS showed a notable inverse correlation with scores for SOP, WM, and VIS, indicating that increased severity of negative symptoms in individuals with SCZ is linked to decreased cognitive abilities, especially in relation to SOP, WM, and VIS. Consequently, it can be deduced that reducing negative symptoms may improve the cognitive function of patients with SCZ. Negative symptoms are a primary factor contributing to disability in individuals with SCZ [ 2 , 39 ]. A meta-analysis of 21 studies concluded that negative symptoms were associated with neurocognitive function [ 27 ], even in high-risk groups [ 40 ], aligning with our own findings and may be related to their common neurobiological mechanisms. Disruption of connectivity or decrease in network functional connectivity between the cerebellum and prefrontal cortex and defects in the glutathione system may be related to negative symptoms and cognitive deficits [ 41 , 42 ]. After stepwise multiple regression analysis, we found that PANSS negative factors independently contributed to the SOP, WM, and VIS indices. Negative symptoms and cognitive deficits may be associated with disruptions in connectivity or reduced functional connectivity between the prefrontal cortex and cerebellum, as well as abnormalities in the glutathione system [ 43 , 44 ], can enhance cognitive function. The research found that levels of SOD were significantly higher in the SCZ group than in HCs, and this was linked to a negative correlation with the progression of the disease. Most previous studies have also reported that SOD levels in patients with chronic SCZ exceeded normal levels[ 45 , 46 ], while others have found no significant change in SOD levels [ 47 ] or decreased manganese SOD levels [ 48 ]. The inconsistent findings may be explained by the different types of samples (such as cerebrospinal fluid, red blood cells, serum) and differences in SOD determination methods, which may have affected test results. The research found that levels of SOD were significantly higher in the SCZ group than in HCs, and this was linked to a negative correlation with the progression of the disease. Prior research has shown elevated SOD levels in individuals with long-term SCZ. Notably, the SOD levels of patients with SCZ were positively correlated with cognitive performance (exceptVRB). Despite this, there was not a notable correlation between the amounts of these 3 antioxidants and cognitive abilities in HCs, suggesting a robust connection between antioxidants and cognitive decline in individuals with SCZ. Serum antioxidants are associated with cognitive pathophysiology in patients [ 49 , 50 ], and SOD is a specific enzyme that “cleans” free radicals and protects the body [ 51 ]. Stepwise multiple regression analysis revealed that SOD level was an independent contributor to the AV index, suggesting that the higher the SOD level, the higher the AV of patients, and the serum SOD level may predict the cognitive level of patients. Our findings are in line with previous research. Lin et al. found that higher SOD levels were associated with better SOP, WM, and VRB in chronic SCZ [ 52 ], aligning somewhat with our findings, possibly attributed to the neuroprotective properties of antioxidants on neurons [ 53 ]. Interestingly, Li et al.found that the correlation between overall antioxidant levels and cognitive abilities in patients could be affected by age [ 52 ]. We also found that SOD levels decreased with increasing disease duration, suggesting that this may be related to age. Hence, our discovery that levels of antioxidants are linked to cognitive abilities in individuals with SCZ may provide a reference for the clinical search for objective markers of cognitive impairment and a basis for clinical interventions. Drugs that can be used early in the clinic, or dietary or behavioral interventions that can affect antioxidant levels, may lead to better cognitive function or, at least, less significant cognitive impairment. A noteworthy discovery from this research was that levels of ALB in the serum were notably reduced in individuals with SCZ compared to controls, and were inversely linked to the length of illness and positively linked to cognitive performance on MCCB (excluding VRB). Prior research has consistently shown results that align with our study, suggesting that a decrease in ALB levels in individuals with SCZ is linked to the advancement of the disease [ 54 ]. This may be attributed to the inhibitory effect of ALB on lipid peroxidation and its direct removal of oxygen free radicals[ 55 ]. The drop in serum ALB levels in individuals with SCZ may be due to the rise in OS damage and antioxidant usage. Moreover, ALB level was correlated with age in all populations, and the slow decline with age may be a natural result of the aging process. Another possible contributing factor is that poor diet may lower ALB levels. The diets of the two groups in this study were essentially the same, which was provided by the hospital. Interestingly, ALB levels remained positively correlated with cognitive performance on the 5 MCCB measures (except VRB) in the SCZ group after removing confounding factors and were an independent contributor to the SOP, WM, and VIS indices. We speculated that ALB levels may be predictive of cognitive function in patients. As simple, convenient, and economical routine clinical examination items, the determination of ALB and SOD levels is undoubtedly a great advantage in clinical applications. If they have the potential to be utilized for an objective assessment of cognitive function in individuals diagnosed with SCZ. Further longitudinal prospective studies with larger sample sizes are required to confirm the role of ALB level in predicting cognitive function in patients with psychiatric disorders. The study revealed that serum UA levels in SCZ patients remained significantly elevated compared to HCs even after controlling for confounding factors and were found to be positively associated with PANSS-negative factors. Most studies reported similar findings[ 56 ]. However, the association between UA levels and SCZ has been a subject of debate in the literature. Based on research investigating SCZ and schizoaffective disorder, and bipolar or depressive disorder, it was found that UA level was decreased in patients with SCZ, while it was unchanged in other diseases [ 54 ]. The heterogeneity of the findings may be due to the limitation of the sample size or confounding factors, such as diet, smoking, and medication. As a simple and easily available laboratory indicator, the relationship between UA and the symptoms and cognition of those with mental disorders merits further exploration. Regrettably, there was no notable correlation discovered between serum UA levels and cognitive performance in individuals with SCZ. Collectively, our findings suggest that different antioxidant enzymes have different effects on cognitive function, providing a direction for future research. This study had several limitations, the first of which was its cross-sectional design, and because redox regulation is dynamic, changes occurred at different stages of disease, as such, longer observation periods are necessary. Second, we only included patients with stable SCZ, excluding those with first-episode SCZ or unmedicated patients, and did not limit the type or dosage of medication. Further research is required in this area. Third, diet tended to influence SOD, UA, and ALB levels. The diets of the patients included in the present investigation were provided by the hospital cafeteria during their hospitalization and were approximately the same, however, the amount of food was not strictly controlled. In conclusion, our research demonstrated that patients with SCZ exhibited extensive cognitive functional impairment. The severity of cognitive function impairment is closely associated with ALB and SOD levels as well as negative symptoms. ALB and SOD levels are stable, easily obtainable, and cost-effective biomarkers for the early identification and intervention in patients with SCZ. However, this cross-sectional study only established an association between cognitive impairment and antioxidants rather than causation. In follow-up studies, large-sample prospective studies with strict control of disease course, drugs, and other factors can better illustrate the role of antioxidant enzyme levels in the cognitive function of individuals diagnosed with SCZ and provide objective evidence supporting clinical evaluation and early intervention. Declarations Acknowledgements All authors thank all the participants who participate in our study training program. Author contributions Dan Li and Yuanyuan Huang : Investigation, Formal analysis, Writing-Original Draft, Visualization. Hongxin Lu, Xuejing Li, Yi Guo , Sumiao Zhou and, Shixuan Feng: Validation, Methodology, Investigation. Hehua Li , Shixuan Feng, Chunlian Fu and Guiying Chen: Investigation. Lianqi Liu , Fengchun Wu and Yuping Ning : Validation, Project administration, Methodology, Investigation. Funding This work was supported by the National Natural Science Foundation of China (82301688), The Science and Technology Program of Guangzhou (202206060005, 202201010093, 2023A03J0856, 2023A03J0839), Guangdong Basic and Applied Basic Research Foundation Outstanding Youth Project (2021B1515020064), Medical Science and Technology Research Foundation of Guangdong (A2023224), The Natural Science Foundation Program of Guangdong (2023A1515011383), The Health Science and Technology Program of Guangzhou (20231A010036), Guangzhou Municipal Key Discipline in Medicine (2021-2023), Guangzhou High-level Clinical Key Specialty, and Guangzhou Research-oriented Hospital. Data availability The datasets generated during the current study are not publicly, but are available from the corresponding author on reasonable request. Ethics approval and consent to participate. The study procedures were carried out in accordance with the Declarationof Helsinki. Prior to participating in the research, all participants and their guardians provided written consent following approval of the study protocol by the Ethics Committee of the Affiliated Brain Hospital of Guangzhou Medical University in Guangzhou, China. Consent for publication Not applicable. Competing interests No conflicts of interest exist for any of the authors. References Uppinkudru C, et al. Prevalence, correlates and explanatory models of cognitive deficits in patients with schizophrenia-A cross sectional study. Indian J Psychiatry. 2023;65(10):1025-34. https://doi.org/10.4103/indianjpsychiatry.indianjpsychiatry_102_23. American PA. Diagnostic and Statistical Manual of Mental Disorders.In: Text Revision.Fifth Edition. American Psychiatric Association.. 2022. Huang Y, et al. Suicide Attempts, Neurocognitive Dysfunctions and Clinical Correlates in Middle-Aged and Elderly Chinese Schizophrenia Patients. Front Psychiatry. 2021;12:684653. https://doi.org/10.3389/fpsyt.2021.684653. Belgaied W, et al. Routine clinical assessment of cognitive functioning in schizophrenia, major depressive disorder, and bipolar disorder. Eur Neuropsychopharmacol. 2014;24(1):133-41. https://doi.org/10.1016/j.euroneuro.2013.11.001. Hope S, et al. Similar immune profile in bipolar disorder and schizophrenia: selective increase in soluble tumor necrosis factor receptor I and von Willebrand factor. Bipolar Disord. 2009;11(7):726-34. https://doi.org/10.1111/j.1399-5618.2009.00757.x. Karlsgodt KH, et al. Developmental disruptions in neural connectivity in the pathophysiology of schizophrenia. Dev Psychopathol. 2008;20(4):1297-327. https://doi.org/10.1017/S095457940800062X. Pantelis C, et al. Neuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparison. Lancet. 2003;361(9354):281-8. https://doi.org/10.1016/S0140-6736(03)12323-9. Kong L, et al. Neurological soft signs and structural network changes: a longitudinal analysis in first-episode schizophrenia. BMC Psychiatry. 2023;23(1):20. https://doi.org/10.1186/s12888-023-04522-4. Rao S, et al. Involvement of the long intergenic non-coding RNA LINC00461 in schizophrenia. BMC Psychiatry. 2022;22(1):59. https://doi.org/10.1186/s12888-022-03718-4. Chen MY, et al. Schizophrenia and oxidative stress from the perspective of bibliometric analysis. Front Psychiatry. 2023;14:1145409. https://doi.org/10.3389/fpsyt.2023.1145409. Cecerska-Heryć E, et al. Importance of oxidative stress in the pathogenesis, diagnosis, and monitoring of patients with neuropsychiatric disorders, a review. Neurochem Int. 2022;153:105269. https://doi.org/10.1016/j.neuint.2021.105269. Somogyi A, et al. Antioxidant measurements. Physiol Meas. 2007;28(4):R41-55. https://doi.org/10.1088/0967-3334/28/4/R01. Jomova K, et al. Reactive oxygen species, toxicity, oxidative stress, and antioxidants: chronic diseases and aging. Arch Toxicol. 2023;97(10):2499-574. https://doi.org/10.1007/s00204-023-03562-9. Mandal PK, et al. Schizophrenia, Bipolar and Major Depressive Disorders: Overview of Clinical Features, Neurotransmitter Alterations, Pharmacological Interventions, and Impact of Oxidative Stress in the Disease Process. ACS Chem Neurosci. 2022;13(19):2784-802. https://doi.org/10.1021/acschemneuro.2c00420. Pisoschi AM, Pop A. The role of antioxidants in the chemistry of oxidative stress: A review. Eur J Med Chem. 2015;97:55-74. https://doi.org/10.1016/j.ejmech.2015.04.040. Zhang XY, et al. Thioredoxin, a novel oxidative stress marker and cognitive performance in chronic and medicated schizophrenia versus healthy controls. Schizophr Res. 2013;143(2-3):301-6. https://doi.org/10.1016/j.schres.2012.11.017. Kapogiannis D, Mattson MP. Disrupted energy metabolism and neuronal circuit dysfunction in cognitive impairment and Alzheimer's disease. Lancet Neurol. 2011;10(2):187-98. https://doi.org/10.1016/S1474-4422(10)70277-5. Niedzielska E, et al. Oxidative Stress in Neurodegenerative Diseases. Mol Neurobiol. 2016;53(6):4094-125. https://doi.org/10.1007/s12035-015-9337-5. Pizzino G, et al. Oxidative Stress: Harms and Benefits for Human Health. Oxid Med Cell Longev. 2017;2017:8416763. https://doi.org/10.1155/2017/8416763. Hardingham GE, Do KQ. Linking early-life NMDAR hypofunction and oxidative stress in schizophrenia pathogenesis. Nat Rev Neurosci. 2016;17(2):125-34. https://doi.org/10.1038/nrn.2015.19. Michel TM, et al. Cu, Zn- and Mn-superoxide dismutase levels in brains of patients with schizophrenic psychosis. J Neural Transm (Vienna). 2004;111(9):1191-201. https://doi.org/10.1007/s00702-004-0160-9. Wang DM, et al. The relationship between cognitive impairment and superoxide dismutase activity in untreated first-episode patients with schizophrenia. World J Biol Psychiatry. 2022;23(7):517-24. https://doi.org/10.1080/15622975.2021.2013093. Li H, et al. Association of serum homocysteine levels with intestinal flora and cognitive function in schizophrenia. J Psychiatr Res. 2023;159:258-65. https://doi.org/10.1016/j.jpsychires.2023.01.045. Zhou S, et al. Gender differences in associations of cognitive impairments with homocysteine in schizophrenia. Asian J Psychiatr. 2022;75:103214. https://doi.org/10.1016/j.ajp.2022.103214. Kay SR, et al. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr Bull. 1987;13(2):261-76. https://doi.org/10.1093/schbul/13.2.261. Wallwork RS, et al. Searching for a consensus five-factor model of the Positive and Negative Syndrome Scale for schizophrenia. Schizophr Res. 2012;137(1-3):246-50. https://doi.org/10.1016/j.schres.2012.01.031. Au-Yeung C, et al. The relationship between negative symptoms and MATRICS neurocognitive domains: A meta-analysis and systematic review. Prog Neuropsychopharmacol Biol Psychiatry. 2023;127:110833. https://doi.org/10.1016/j.pnpbp.2023.110833. Couture SM, et al. A path model investigation of neurocognition, theory of mind, social competence, negative symptoms and real-world functioning in schizophrenia. Schizophr Res. 2011;125(2-3):152-60. https://doi.org/10.1016/j.schres.2010.09.020. Shi C, et al. The MATRICS Consensus Cognitive Battery (MCCB): Co-norming and standardization in China. Schizophr Res. 2015;169(1-3):109-15. https://doi.org/10.1016/j.schres.2015.09.003. Dickinson D, et al. General and specific cognitive deficits in schizophrenia: Goliath defeats David. Biol Psychiatry. 2008;64(9):823-7. https://doi.org/10.1016/j.biopsych.2008.04.005. Heinrichs RW, Zakzanis KK. Neurocognitive deficit in schizophrenia: a quantitative review of the evidence. Neuropsychology. 1998;12(3):426-45. https://doi.org/10.1037//0894-4105.12.3.426. Mohn-Haugen CR, et al. A systematic review of premorbid cognitive functioning and its timing of onset in schizophrenia spectrum disorders. Schizophr Res Cogn. 2022;28:100246. https://doi.org/10.1016/j.scog.2022.100246. Vöhringer PA, et al. Cognitive impairment in bipolar disorder and schizophrenia: a systematic review. Front Psychiatry. 2013;4:87. https://doi.org/10.3389/fpsyt.2013.00087. Morozova A, et al. Neurobiological Highlights of Cognitive Impairment in Psychiatric Disorders. Int J Mol Sci. 2022;23(3):1217. https://doi.org/10.3390/ijms23031217. Ohi K, et al. Genetic Overlap between General Cognitive Function and Schizophrenia: A Review of Cognitive GWASs. Int J Mol Sci. 2018;19(12):3822. https://doi.org/10.3390/ijms19123822. Joo SW, et al. Altered white matter connectivity in patients with schizophrenia: An investigation using public neuroimaging data from SchizConnect. PLoS One. 2018;13(10):e0205369. https://doi.org/10.1371/journal.pone.0205369. Antonova E, et al. The relationship between brain structure and neurocognition in schizophrenia: a selective review. Schizophr Res. 2004;70(2-3):117-45. https://doi.org/10.1016/j.schres.2003.12.002. Hope S, et al. Inflammatory markers are associated with general cognitive abilities in schizophrenia and bipolar disorder patients and healthy controls. Schizophr Res. 2015;165(2-3):188-94. https://doi.org/10.1016/j.schres.2015.04.004. Rabinowitz J, et al. Negative symptoms have greater impact on functioning than positive symptoms in schizophrenia: analysis of CATIE data. Schizophr Res. 2012;137(1-3):147-50. https://doi.org/10.1016/j.schres.2012.01.015. Melillo A, et al. Correlations between Negative Symptoms and Cognitive Deficits in Individuals at First Psychotic Episode or at High Risk of Psychosis: A Systematic Review. Journal of Clinical Medicine. 2023;(2077-0383 (Print)). Brady RO Jr, et al. Cerebellar-Prefrontal Network Connectivity and Negative Symptoms in Schizophrenia. Am J Psychiatry. 2019;176(7):512-20. https://doi.org/10.1176/appi.ajp.2018.18040429. Manoliu A, et al. Insular Dysfunction Reflects Altered Between-Network Connectivity and Severity of Negative Symptoms in Schizophrenia during Psychotic Remission. Front Hum Neurosci. 2013;7:216. https://doi.org/10.3389/fnhum.2013.00216. Garg S, et al. The efficacy of cerebellar vermal deep high frequency (theta range) repetitive transcranial magnetic stimulation (rTMS) in schizophrenia: A randomized rater blind-sham controlled study. Psychiatry Res. 2016;243:413-20. https://doi.org/10.1016/j.psychres.2016.07.023. Pan Z, et al. The Effects of Repetitive Transcranial Magnetic Stimulation in Patients with Chronic Schizophrenia: Insights from EEG Microstates. Psychiatry Res. 2021;299:113866. https://doi.org/10.1016/j.psychres.2021.113866. Sarandol A, et al. First-episode psychosis is associated with oxidative stress: Effects of short-term antipsychotic treatment. Psychiatry Clin Neurosci. 2015;69(11):699-707. https://doi.org/10.1111/pcn.12333. Zhang XY, et al. Superoxide dismutase and cytokines in chronic patients with schizophrenia: association with psychopathology and response to antipsychotics. Psychopharmacology (Berl). 2009;204(1):177-84. https://doi.org/10.1007/s00213-008-1447-6. Srivastava N, et al. Nitrite content and antioxidant enzyme levels in the blood of schizophrenia patients. Psychopharmacology (Berl). 2001;158(2):140-5. https://doi.org/10.1007/s002130100860. Zhang XY, et al. Clinical symptoms and cognitive impairment associated with male schizophrenia relate to plasma manganese superoxide dismutase activity: a case-control study. J Psychiatr Res. 2013;47(8):1049-53. https://doi.org/10.1016/j.jpsychires.2013.03.014. Martínez-Cengotitabengoa M, et al. Cognitive impairment is related to oxidative stress and chemokine levels in first psychotic episodes. Schizophr Res. 2012;137(1-3):66-72. https://doi.org/10.1016/j.schres.2012.03.004. Zhang XY, et al. Plasma total antioxidant status and cognitive impairments in schizophrenia. Schizophr Res. 2012;139(1-3):66-72. https://doi.org/10.1016/j.schres.2012.04.009. Simanjuntak E, Zulham Z. SUPEROKSIDA DISMUTASE (SOD) DAN RADIKAL BEBAS. JURNAL KEPERAWATAN DAN FISIOTERAPI (JKF). 2020;2(2):124-9. Li J, et al. Age of Onset Moderates the Association between Total Antioxidant Capacity and Cognitive Deficits in Patients with Drug-Naïve Schizophrenia. Antioxidants (Basel). 2023;12(6). https://doi.org/10.3390/antiox12061259. Yao JK, Keshavan MS. Antioxidants, redox signaling, and pathophysiology in schizophrenia: an integrative view. Antioxid Redox Signal. 2011;15(7):2011-35. https://doi.org/10.1089/ars.2010.3603. Reddy R, et al. Reduced plasma antioxidants in first-episode patients with schizophrenia. Schizophr Res. 2003;62(3):205-12. https://doi.org/10.1016/s0920-9964(02)00407-3. Belinskaia DA, et al. Serum Albumin in Health and Disease: Esterase, Antioxidant, Transporting and Signaling Properties. Int J Mol Sci. 2021;22(19):10318. https://doi.org/10.3390/ijms221910318. Solberg DK, et al. A five-year follow-up study of antioxidants, oxidative stress and polyunsaturated fatty acids in schizophrenia. Acta Neuropsychiatr. 2019;31(4):202-12. https://doi.org/10.1017/neu.2019.14. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 18 Dec, 2024 Read the published version in BMC Psychiatry → Version 1 posted Editorial decision: Revision requested 20 May, 2024 Submission checks completed at journal 17 May, 2024 Editor assigned by journal 17 May, 2024 First submitted to journal 28 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4336905","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":304550897,"identity":"2b5dbb63-993f-4442-af1b-0156ddbff764","order_by":0,"name":"Dan Li","email":"","orcid":"","institution":"Guangzhou Civil Affairs Bureau Psychiatric Hospital","correspondingAuthor":false,"prefix":"","firstName":"Dan","middleName":"","lastName":"Li","suffix":""},{"id":304550898,"identity":"84f25e03-615c-44b5-a4b2-f34dabf7b605","order_by":1,"name":"Yuanyuan Huang","email":"","orcid":"","institution":"Affiliated Brain Hospital of Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuanyuan","middleName":"","lastName":"Huang","suffix":""},{"id":304550899,"identity":"381950a6-e855-4ea7-9dad-4fea22849124","order_by":2,"name":"Hongxin Lu","email":"","orcid":"","institution":"Longyan Third Hospital of Fujian Province Department of Psychiatric Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hongxin","middleName":"","lastName":"Lu","suffix":""},{"id":304550902,"identity":"db215fbf-2ef8-46c3-9b66-9b6d8491e000","order_by":3,"name":"Sumiao Zhou","email":"","orcid":"","institution":"Affiliated Brain Hospital of Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Sumiao","middleName":"","lastName":"Zhou","suffix":""},{"id":304550903,"identity":"c3b8d772-5b90-4f11-9d10-530572f45fd4","order_by":4,"name":"Shixuan Feng","email":"","orcid":"","institution":"Affiliated Brain Hospital of Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shixuan","middleName":"","lastName":"Feng","suffix":""},{"id":304550905,"identity":"39bd1e2a-04c1-4a18-a4da-b3656e706117","order_by":5,"name":"Hehua Li","email":"","orcid":"","institution":"Affiliated Brain Hospital of Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hehua","middleName":"","lastName":"Li","suffix":""},{"id":304550906,"identity":"a8240a62-d848-4dbe-a44e-885c914097e4","order_by":6,"name":"Xuejing Li","email":"","orcid":"","institution":"Guangzhou Civil Affairs Bureau Psychiatric Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xuejing","middleName":"","lastName":"Li","suffix":""},{"id":304550908,"identity":"cc82d1dc-2d10-44ca-acc6-68b81e9c6caf","order_by":7,"name":"Yi Guo","email":"","orcid":"","institution":"Guangzhou Civil Affairs Bureau Psychiatric Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Guo","suffix":""},{"id":304550911,"identity":"f717891a-37fe-485e-bad9-b85090575920","order_by":8,"name":"Chunlian Fu","email":"","orcid":"","institution":"Guangzhou Civil Affairs Bureau Psychiatric Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chunlian","middleName":"","lastName":"Fu","suffix":""},{"id":304550912,"identity":"ff34b7cb-5086-4c9e-b54d-57981539833e","order_by":9,"name":"Guiying Chen","email":"","orcid":"","institution":"Guangzhou Civil Affairs Bureau Psychiatric Hospital","correspondingAuthor":false,"prefix":"","firstName":"Guiying","middleName":"","lastName":"Chen","suffix":""},{"id":304550914,"identity":"83c4de71-0895-48fd-b9ed-87699f8a8128","order_by":10,"name":"Yuping Ning","email":"","orcid":"","institution":"Affiliated Brain Hospital of Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuping","middleName":"","lastName":"Ning","suffix":""},{"id":304550916,"identity":"4c8b87d3-7b3e-4b1e-a61c-cdcb2c7b9432","order_by":11,"name":"Fengchun Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYBACNv7+hw8SftjwsMk/bHyQUFFDWAufxBlmg489aXL8DMnNBg/OHCOsRY4hh01yBtthY8mG9DbJhy3MRDiM4exhYx6etMQNBw62VSQ2sDHwt3cn4NfC3Jf4mMfCJnHDwca2G4k7ZBgkzpzdQMCWA8YQWw4zArWcYWMwkMglpCXBTJqH7XDihmOMbQWJbczEaMkxg3i/h7GNgTgtEseSIYEswdgskXDmGA9Bv8j3Nx+ERKUE+8OPPypq5Pjbe/FrwQA8pCkfBaNgFIyCUYAVAABawkx9bXUJ7QAAAABJRU5ErkJggg==","orcid":"","institution":"Affiliated Brain Hospital of Guangzhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Fengchun","middleName":"","lastName":"Wu","suffix":""},{"id":304550918,"identity":"5b338003-838a-4bee-bf56-3fb7a3af9b2a","order_by":12,"name":"Lianqi Liu","email":"","orcid":"","institution":"Guangzhou Civil Affairs Bureau Psychiatric Hospital","correspondingAuthor":false,"prefix":"","firstName":"Lianqi","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-04-28 08:15:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4336905/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4336905/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12888-024-06335-5","type":"published","date":"2024-12-18T15:58:34+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57707685,"identity":"9353b87f-d15d-4f56-bc7c-226026c40e98","added_by":"auto","created_at":"2024-06-04 15:12:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":121750,"visible":true,"origin":"","legend":"\u003cp\u003eThe levels of antioxidants between SCZ patients and HCs.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4336905/v1/5f1c6a1e7418214531138bae.png"},{"id":57707686,"identity":"64a4d685-4765-48e0-8eb1-d6cf9ff761a1","added_by":"auto","created_at":"2024-06-04 15:12:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":318634,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between cognitive performance and ALB levels in SCZ patients.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4336905/v1/129311f6e52db78565bcc910.png"},{"id":72201992,"identity":"46208487-fbd0-491d-8862-a74a19e10021","added_by":"auto","created_at":"2024-12-23 16:13:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1155861,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4336905/v1/a28015ab-0b8c-4978-aeed-1369547e96bb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between cognitive function, antioxidants, and clinical variables in Chinese patients with schizophrenia","fulltext":[{"header":"1. Background","content":"\u003cp\u003eCognitive dysfunction in schizophrenia (SCZ) the core of a kind of serious and common symptoms that affects attention, learning, executive function, processing speed, speech, and memory. Approximately 85% of patients with SCZ exhibit cognitive impairment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], which is one explanation for the poor curative effect of current therapies and prognosis of patients, which severely affects social function and the ability to live independently, and even potential impulsive behaviors such as suicide and self-injury[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. To date, many tools have been used in clinical practice to assess cognitive function in patients with SCZ, many of which rely only on the patient\u0026rsquo;s medical history interview [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], which is, to some extent, subjectively influenced by the evaluator. Research on cognitive decline in SCZ has emphasized issues with neuronal development, disrupted neurotransmission, viral infections, autoimmune problems, and oxidative stress (OS)[\u003cspan additionalcitationids=\"CR6 CR7 CR8\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Recently, there has been an increasing focus on the relationship between SCZ and OS [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], which may provide a direction for exploring objectively effective auxiliary diagnostic techniques and methods for clinical evaluation of cognitive function in individuals with SCZ.\u003c/p\u003e \u003cp\u003eOS is a process in which the body generates an excessive amount of highly reactive molecules upon encountering specific detrimental stimuli. These molecules cannot be completely eliminated by antioxidants, thereby disrupting the delicate balance between oxidation and antioxidant systems [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Under normal circumstances, the body possesses a sophisticated antioxidant defense system that uses endogenous antioxidants to effectively eliminate excess free radicals and safeguard tissues from potential damage. Enzymatic and non-enzymatic antioxidants make up the antioxidant defense system [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], including superoxide dismutase (SOD), catalase, and glutathione peroxidase as enzymatic antioxidants, and albumin (ALB), bilirubin, uric acid (UA), vitamin C, and vitamin E as non-enzymatic antioxidants. Various diseases, like tumors, cardiovascular and neurological disorders (e.g., Alzheimer\u0026rsquo;s disease, Parkinson\u0026rsquo;s disease, and Down syndrome), as well as mental illnesses such as depression, SCZ, and bipolar disorder, are closely linked to OS [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Recent research on SCZ and OS revealed a correlation between thioredoxin and cognitive impairments in SCZ patients [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], along with increased levels of nitric oxide in the brains of individuals with SCZ. The majority of past research on OS and cognitive abilities has centered around the topics of getting older and Alzheimer's disease [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Further clinical confirmation is necessary to determine the correlation between OS and cognitive performance in individuals with SCZ.\u003c/p\u003e \u003cp\u003eConsidering the importance of cognitive function in the rehabilitation and prognosis of patients with SCZ, it is imperative to study its influencing factors and mechanisms, particularly OS. Hardingham et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] found a link between early-life NMDAR dysfunction and OS in SCZ pathogenesis. Studies have shown elevated levels of SOD activity in the blood, red blood cells, prefrontal cortex, and innominate substances in autopsies of individuals with SCZ[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Some studies have also indicated reduced SOD1 activity. Multiple studies have indicated that OS plays a role in the development of early cognitive impairment in SCZ [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. We previously established a correlation between OS markers and cognitive function, gender, and obesity in individuals diagnosed with SCZ, setting the stage for additional research on the link between antioxidant levels and cognitive function in patients with SCZ [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Although previous investigations have confirmed the correlation between cognitive function and OS in patients with SCZ, most were laboratory studies. Conveniently assessed blood indicators may be more useful for real-time guidance in clinical practice.\u003c/p\u003e \u003cp\u003eConsidering the critical role of antioxidants in the development of SCZ, there are no standardized, consistent, readily available, and affordable biomarkers that can effectively indicate cognitive impairment in individuals with SCZ. This study is the initial investigation into potential factors that could impact cognitive function in SCZ patients through an examination of plasma SOD, as well as serum levels of UA and ALB, and the relationship(s) with cognitive function and clinical manifestations. This provides an objective method for the clinical assessment of cognitive function in patients with SCZ.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Participants\u003c/h2\u003e \u003cp\u003e Prior to participating in the research, all participants and their guardians provided written consent following approval of the study protocol by the Ethics Committee of the Affiliated Brain Hospital of Guangzhou Medical University in Guangzhou, China(Number: AF/SC-08/02.1). From December 2021 to September 2022, a group of 253 individuals (120 HCs and 133 individuals with SCZ) were enrolled in the study. Each patient in the study, aged 18 to 60, of Han Chinese descent, met all inclusion criteria. They were diagnosed with SCZ according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) by two experienced psychiatrists using the Structured Clinical Interview for DSM-IV (SCID-I/P), and had been on a stable dose of antipsychotic medications for at least 8 weeks before the research began. Individuals with significant medical abnormalities, such as unstable or acute medical conditions, comorbid psychiatric disorders, previous history of epilepsy, intellectual disabilities, brain trauma, use of electroconvulsive therapy in the previous six months, and use of any antioxidants or immunomodulators within the last three months were excluded.\u003c/p\u003e \u003cp\u003eHan Chinese 18\u0026ndash;60 years of age were recruited through advertisements in a local community in Guangzhou, China. No participants reported a history of psychiatric disorders, either personally or within their family, during the informal interviews. They exhibited comparable socioeconomic status and dietary patterns, and had not received any antioxidants or immunomodulators within 3 months.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Clinical measurements\u003c/h2\u003e \u003cp\u003eAll patients with SCZ and HCs underwent complete medical history taking, laboratory investigations, and physical examinations. General information and sociodemographic characteristics were collected based on questionnaires, and histories of psychiatric disorders and medication use were obtained from medical records by trained research staff. Two trained psychiatrists used the Positive and Negative Syndrome Scale (PANSS) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] to assess the psychiatric symptoms of all patients with SCZ. The study utilized the PANSS five-factor model to evaluate individuals in 5 different areas: positive symptoms (P1, P5, G9 ), negative symptoms (N1, N2, N3, N4, N6, G7), excitatory symptoms (P4, P7, G8, G14 ), depressive and anxious symptoms (G2, G3, G6 ), as well as cognitive impairments (P2, N5, G11)[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The inter-rater reliability coefficient for the PANSS total score surpassed 0.8 in repeated evaluations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Cognitive assessments\u003c/h2\u003e \u003cp\u003ePatients' cognitive function, such as speed of processing (SOP), attention/vigilance (AV), working memory (WM), verbal learning (VRB), and visual learning (VIS) reasoning and problem-solving, and social cognition, was assessed using the MATRICS Consensus Cognitive Battery (MCCB) tool [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The first 5 items assess cognitive function. The domains primarily mirror the cognitive abilities of individuals with SCZ[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Research conducted by Shi et al[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] has shown that the Chinese adaptation of the MCCB exhibits positive psychometric characteristics, suggesting robust reliability and validity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003e2.4.\u003c/em\u003e Analysis of antioxidants levels\u003c/h2\u003e \u003cp\u003eEach participant had venous blood samples collected in the early morning after fasting for at least 8 hours. Blood was obtained and placed in an EDTA tube, followed by centrifugation (3000 rpm) for a duration of 10 minutes within 30 min after collection. A clinical laboratory technician at the hospital performed blood biochemical tests without knowledge of participant information.\u003c/p\u003e \u003cp\u003eLevels of SOD, ALB, and UA were assessed with an automated biochemical analyzer (Beckman AU480, BD Biosciences, Franklin Lakes, NJ, USA) and kits from Beijing Leadman Biotechnology Co., Ltd (Beijing, China). SOD levels were measured using SOD assay kits (enzyme cycle assays). All experimental procedures followed the manufacturer's instructions meticulously.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical analysis\u003c/h2\u003e \u003cp\u003eThe chi-squared test was used to compare demographic variables (i.e., categorical) between patients with SCZ and HCs, while analysis of variance (ANOVA) was used to compare continuous variables. Due to the non-normal distribution of ALB levels (Shapiro\u0026ndash;Wilk test, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), a non-parametric test (Mann\u0026ndash;Whitney test) was employed to assess the differences in ALB levels between individuals with SCZ and HCs. ANCOVA was utilized to assess the disparities in levels of UA and SOD, and cognitive performance on the MCCB between the 2 groups after controlling for demographic variables (i.e., education, body mass index [BMI], and marital status) and clinical symptoms (i.e., PANSS total and subscale scores), which revealed significant between-group differences. The relationships among antioxidant enzyme levels, clinical ratings, and cognitive performance were examined using Spearman\u0026rsquo;s correlation. Furthermore, partial correlation was used to control for additional variables. Multiple tests were adjusted using the Bonferroni correction. Multivariate regression analyses (stepwise regression model) with MCCB subscores were used as dependent variables to investigate the relationship between cognitive function and antioxidant enzyme levels, while controlling for demographic variables and clinical symptoms on the PANSS. Statistical analyses were conducted using SPSS version 18.0 from IBM Corporation in Chicago, IL, USA. Statistically significant differences were defined as those with a two-tailed p-value less than 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Demographic and clinical data\u003c/h2\u003e \u003cp\u003eDemographic information and clinical data of the participants included in this study are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There were significant differences in marital status, education, and BMI between the 2 groups (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05); however, there were no significant disparities in terms of gender or age. Marital status, education, and BMI were adjusted for in subsequent analyses.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographics of SCZ patients and HCs.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCZ patients\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;133\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHCs\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;120\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF/χ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.74\u0026thinsp;\u0026plusmn;\u0026thinsp;12.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.52\u0026thinsp;\u0026plusmn;\u0026thinsp;13.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.560\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.455\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale/female,n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77/56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63/57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.743\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22(16.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73(60.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111(83.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47(39.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.08\u0026thinsp;\u0026plusmn;\u0026thinsp;3.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.08\u0026thinsp;\u0026plusmn;\u0026thinsp;3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (BMI) (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.15\u0026thinsp;\u0026plusmn;\u0026thinsp;4.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.08\u0026thinsp;\u0026plusmn;\u0026thinsp;3.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history,n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31(23.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge of onset (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.26\u0026thinsp;\u0026plusmn;\u0026thinsp;7.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of disease (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e220.41\u0026thinsp;\u0026plusmn;\u0026thinsp;157.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntipsychotic dosage (mg/day),CPZ equivalents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e406.63\u0026thinsp;\u0026plusmn;\u0026thinsp;180.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePANSS total score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.24\u0026thinsp;\u0026plusmn;\u0026thinsp;18.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive subscore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.91\u0026thinsp;\u0026plusmn;\u0026thinsp;3.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative subscore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.62\u0026thinsp;\u0026plusmn;\u0026thinsp;7.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExcited subscore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.29\u0026thinsp;\u0026plusmn;\u0026thinsp;2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepressive subscore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.16\u0026thinsp;\u0026plusmn;\u0026thinsp;3.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive subscore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.77\u0026thinsp;\u0026plusmn;\u0026thinsp;2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05,the difference was statistically significant;PANSS:Positive and Negative Syndrome Scale.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Cognitive function of patients with SCZ and HCs\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes information on cognitive function (MCCB performance) in individuals with SCZ and HCs. Compared with HCs, patients with SCZ exhibited worse cognitive performance in terms of SOP, AV, WM, VRB, and VIS. The significant differences persisted even after adjusting for BMI, marital status, and educational level (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In the SCZ group, the PANSS total scores were negatively associated with all MCCB indices (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) except AV. The PANSS-negative and PANSS-cognitive subscores had a negatively correlation with the SOP, VRB, and VIS scores (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). There was a negative correlation between PANSS-excited subscores and WM and VIS scores (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCognitive functions (MCCB) of SCZ patients and HCs.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSCZ patients\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;133\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHCs\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;120\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdjusted F*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eAdjusted \u003cem\u003ep\u003c/em\u003e*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOP score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.01\u0026thinsp;\u0026plusmn;\u0026thinsp;17.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.99\u0026thinsp;\u0026plusmn;\u0026thinsp;9.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e129.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAV score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.55\u0026thinsp;\u0026plusmn;\u0026thinsp;10.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.61\u0026thinsp;\u0026plusmn;\u0026thinsp;9.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWM score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.65\u0026thinsp;\u0026plusmn;\u0026thinsp;13.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.89\u0026thinsp;\u0026plusmn;\u0026thinsp;9.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVRB score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.29\u0026thinsp;\u0026plusmn;\u0026thinsp;12.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.11\u0026thinsp;\u0026plusmn;\u0026thinsp;10.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVIS score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.94\u0026thinsp;\u0026plusmn;\u0026thinsp;12.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.34\u0026thinsp;\u0026plusmn;\u0026thinsp;10.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e*Adjusted values were calculated with age, BMI, marital status, and education as covariates. MCCB, the MATRICS Consensus Cognitive Battery of tests; SOP, speed of processing; AV, attention/vigilance; WM, working memory; VRB, verbal learning and memory; VIS, visual learning and memory.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 ALB, UA, and SOD levels in patients with SCZ and HCs\u003c/h2\u003e \u003cp\u003eAntioxidant levels (ALB, UA, and SOD) in individuals with SCZ and HCs are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Serum ALB levels were significantly lower in those with SCZ (median 42.45 ([P25, P75] 39.82, 46.10]) than in HCs (median 44.52 [41.55, 48.48]; z = -2.418; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016). Even after accounting for BMI, marital status, and educational, the distinction in ALB levels between the two groups continued to be noteworthy (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eElevated levels of Serum UA and SOD were observed in participants diagnosed with SCZ when compared to HCs (400.16\u0026thinsp;\u0026plusmn;\u0026thinsp;117.63 versus [vs.] 351.28\u0026thinsp;\u0026plusmn;\u0026thinsp;105.48 \u0026micro;mol/L; F\u0026thinsp;=\u0026thinsp;11.991, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001; 162.94\u0026thinsp;\u0026plusmn;\u0026thinsp;21.00 vs. 133.22\u0026thinsp;\u0026plusmn;\u0026thinsp;33.91 U/mL; F\u0026thinsp;=\u0026thinsp;71.323, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These variations remained significant even after accounting for factors such as BMI, marital status, and educational (F\u0026thinsp;=\u0026thinsp;8.613, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004; F\u0026thinsp;=\u0026thinsp;33.328, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eLevels of antioxidants did not show any correlation with demographic factors in the two groups (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), except ALB and SOD levels, which were inversely related to age in both the HCs and SCZ groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Within the SCZ cohort, the levels of ALB and SOD showed an inverse correlation with the duration of the disease, while the levels of UA exhibited a positive correlation with PANSS-negative factors.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSpearman correlation analysis revealed that antioxidant levels were associated with partial cognitive function in the SCZ group (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Within the SCZ group, there was a positive correlation between ALB levels and cognitive performance across 5 MCCB indexes (r\u0026thinsp;=\u0026thinsp;0.172\u0026ndash;0.281, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). After adjusting for BMI, marital status, and educational, partial correlation analysis reaffirmed the strong connection (r\u0026thinsp;=\u0026thinsp;0.177\u0026ndash;0.292, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). All correlations passed Bonferroni correction (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05); however, the association between VRB score and ALB level failed (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eCognitive performance showed a positive correlation with SOD levels (r\u0026thinsp;=\u0026thinsp;0.183\u0026ndash;0.222, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), except VRB score (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). After adjusting for BMI, marital status, and educational, the partial correlation analysis provided additional evidence of a strong link between SOD levels and AV (r\u0026thinsp;=\u0026thinsp;0.299, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001; Bonferroni-corrected \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) as well as VIS scores (r\u0026thinsp;=\u0026thinsp;0.217, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014; Bonferroni-corrected \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). There was no correlation between the cognitive performance of the HCs and the levels of the 3 antioxidants (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Levels of UA were not found to be correlated with cognitive performance in SCZ.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between five dimensions MCCB and ALB, UA and SOD in patients with SCZ.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSOP score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAV score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWM score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVRB score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eVIS score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eALB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSOD(U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.035\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.035\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.035\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUA(umol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.041\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.642\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAdditionally, a step-by-step multiple regression analysis was conducted to elucidate how antioxidants, demographic factors, and clinical manifestations impact the cognitive abilities of individuals diagnosed with SCZ. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, ALB levels and PANSS-negative factor were independent contributors to the SOP, WM, and VIS indices. SOD levels (beta\u0026thinsp;=\u0026thinsp;0.14, t\u0026thinsp;=\u0026thinsp;3.262, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) were independent contributors to the AV index.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors for cognitive performance in SCZ patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003edependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS.E\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSOP score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-10.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-34.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eALB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.698\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePANSS-negative factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAV score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.699\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSOD(U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eWM score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-9.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.744\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eALB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePANSS-negative factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.038\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVIS score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-6.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eALB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePANSS-negative factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.071\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eVariables in the model: age, marital status, BMI, PANSS total scores and its subscores, ALB, UA, and SOD.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis research was the initial exploration into the correlation between enzymatic and non-enzymatic antioxidants (SOD, ALB, and UA) and the cognitive function and symptoms of individuals diagnosed with SCZ. The primary discoveries of this research were the following. First, patients with SCZ exhibited extensive cognitive impairment compared with HCs. Second, PANSS-negative sub-scores showed a negative correlation with SOP, WM, and VIS scores. Third, SOD levels were positively correlated with cognitive performance (except VRB) in the SCZ group, which was an independent contributor to the AV index. Fourth, ALB levels in the SCZ group were independent contributors to the SOP, WM, and VIS indices. Patients with SCZ had notably elevated UA levels compared to HCs, however, these levels did not show a correlation with cognitive function. These results indicate that different antioxidant enzymes affect different cognitive dimensions in patients with SCZ.\u003c/p\u003e \u003cp\u003eOur study found that individuals diagnosed with SCZ exhibited significant cognitive deficits in SOP, AV, WM, VRB and VIS, indicating widespread cognitive impairment, aligning with findings from earlier research studies [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Cognitive impairment may impact the daily activities of individuals with SCZ, leading to a suboptimal treatment response, challenges in functional recovery, and an elevated risk for long-term disability. The causes of cognitive decline in SCZ are intricate, with growing proof suggesting a common disease-causing gene, epigenetic control of DNA, and resulting changes in the proteome and metabolome, potentially impacting cognitive abilities [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The neurobiological basis of cognitive impairment commonly involves reduced levels of gray matter neurons, abnormal myelin density, and white matter cellulose connectivity [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], impaired signal integration at the neuronal and neural network levels, neurotransmitter abnormalities, immune dysregulation, and OS [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. We explored the relationship between antioxidant levels and cognitive function in patients with stable SCZ, suggesting the need for future research in first-episode SCZ patients and those who have not yet received medication.\u003c/p\u003e \u003cp\u003eIn the SCZ group, all MCCB indices showed a strong inverse relationship with the total PANSS score, except AV. Moreover, the adverse factor rating of the PANSS showed a notable inverse correlation with scores for SOP, WM, and VIS, indicating that increased severity of negative symptoms in individuals with SCZ is linked to decreased cognitive abilities, especially in relation to SOP, WM, and VIS. Consequently, it can be deduced that reducing negative symptoms may improve the cognitive function of patients with SCZ. Negative symptoms are a primary factor contributing to disability in individuals with SCZ [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. A meta-analysis of 21 studies concluded that negative symptoms were associated with neurocognitive function [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], even in high-risk groups [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], aligning with our own findings and may be related to their common neurobiological mechanisms. Disruption of connectivity or decrease in network functional connectivity between the cerebellum and prefrontal cortex and defects in the glutathione system may be related to negative symptoms and cognitive deficits [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. After stepwise multiple regression analysis, we found that PANSS negative factors independently contributed to the SOP, WM, and VIS indices. Negative symptoms and cognitive deficits may be associated with disruptions in connectivity or reduced functional connectivity between the prefrontal cortex and cerebellum, as well as abnormalities in the glutathione system [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], can enhance cognitive function.\u003c/p\u003e \u003cp\u003eThe research found that levels of SOD were significantly higher in the SCZ group than in HCs, and this was linked to a negative correlation with the progression of the disease. Most previous studies have also reported that SOD levels in patients with chronic SCZ exceeded normal levels[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], while others have found no significant change in SOD levels [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] or decreased manganese SOD levels [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The inconsistent findings may be explained by the different types of samples (such as cerebrospinal fluid, red blood cells, serum) and differences in SOD determination methods, which may have affected test results. The research found that levels of SOD were significantly higher in the SCZ group than in HCs, and this was linked to a negative correlation with the progression of the disease. Prior research has shown elevated SOD levels in individuals with long-term SCZ. Notably, the SOD levels of patients with SCZ were positively correlated with cognitive performance (exceptVRB). Despite this, there was not a notable correlation between the amounts of these 3 antioxidants and cognitive abilities in HCs, suggesting a robust connection between antioxidants and cognitive decline in individuals with SCZ. Serum antioxidants are associated with cognitive pathophysiology in patients [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], and SOD is a specific enzyme that \u0026ldquo;cleans\u0026rdquo; free radicals and protects the body [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Stepwise multiple regression analysis revealed that SOD level was an independent contributor to the AV index, suggesting that the higher the SOD level, the higher the AV of patients, and the serum SOD level may predict the cognitive level of patients. Our findings are in line with previous research. Lin et al. found that higher SOD levels were associated with better SOP, WM, and VRB in chronic SCZ [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], aligning somewhat with our findings, possibly attributed to the neuroprotective properties of antioxidants on neurons [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Interestingly, Li et al.found that the correlation between overall antioxidant levels and cognitive abilities in patients could be affected by age [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. We also found that SOD levels decreased with increasing disease duration, suggesting that this may be related to age. Hence, our discovery that levels of antioxidants are linked to cognitive abilities in individuals with SCZ may provide a reference for the clinical search for objective markers of cognitive impairment and a basis for clinical interventions. Drugs that can be used early in the clinic, or dietary or behavioral interventions that can affect antioxidant levels, may lead to better cognitive function or, at least, less significant cognitive impairment.\u003c/p\u003e \u003cp\u003eA noteworthy discovery from this research was that levels of ALB in the serum were notably reduced in individuals with SCZ compared to controls, and were inversely linked to the length of illness and positively linked to cognitive performance on MCCB (excluding VRB). Prior research has consistently shown results that align with our study, suggesting that a decrease in ALB levels in individuals with SCZ is linked to the advancement of the disease [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. This may be attributed to the inhibitory effect of ALB on lipid peroxidation and its direct removal of oxygen free radicals[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. The drop in serum ALB levels in individuals with SCZ may be due to the rise in OS damage and antioxidant usage. Moreover, ALB level was correlated with age in all populations, and the slow decline with age may be a natural result of the aging process. Another possible contributing factor is that poor diet may lower ALB levels. The diets of the two groups in this study were essentially the same, which was provided by the hospital. Interestingly, ALB levels remained positively correlated with cognitive performance on the 5 MCCB measures (except VRB) in the SCZ group after removing confounding factors and were an independent contributor to the SOP, WM, and VIS indices. We speculated that ALB levels may be predictive of cognitive function in patients. As simple, convenient, and economical routine clinical examination items, the determination of ALB and SOD levels is undoubtedly a great advantage in clinical applications. If they have the potential to be utilized for an objective assessment of cognitive function in individuals diagnosed with SCZ. Further longitudinal prospective studies with larger sample sizes are required to confirm the role of ALB level in predicting cognitive function in patients with psychiatric disorders.\u003c/p\u003e \u003cp\u003eThe study revealed that serum UA levels in SCZ patients remained significantly elevated compared to HCs even after controlling for confounding factors and were found to be positively associated with PANSS-negative factors. Most studies reported similar findings[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. However, the association between UA levels and SCZ has been a subject of debate in the literature. Based on research investigating SCZ and schizoaffective disorder, and bipolar or depressive disorder, it was found that UA level was decreased in patients with SCZ, while it was unchanged in other diseases [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The heterogeneity of the findings may be due to the limitation of the sample size or confounding factors, such as diet, smoking, and medication. As a simple and easily available laboratory indicator, the relationship between UA and the symptoms and cognition of those with mental disorders merits further exploration. Regrettably, there was no notable correlation discovered between serum UA levels and cognitive performance in individuals with SCZ. Collectively, our findings suggest that different antioxidant enzymes have different effects on cognitive function, providing a direction for future research.\u003c/p\u003e \u003cp\u003eThis study had several limitations, the first of which was its cross-sectional design, and because redox regulation is dynamic, changes occurred at different stages of disease, as such, longer observation periods are necessary. Second, we only included patients with stable SCZ, excluding those with first-episode SCZ or unmedicated patients, and did not limit the type or dosage of medication. Further research is required in this area. Third, diet tended to influence SOD, UA, and ALB levels. The diets of the patients included in the present investigation were provided by the hospital cafeteria during their hospitalization and were approximately the same, however, the amount of food was not strictly controlled.\u003c/p\u003e \u003cp\u003eIn conclusion, our research demonstrated that patients with SCZ exhibited extensive cognitive functional impairment. The severity of cognitive function impairment is closely associated with ALB and SOD levels as well as negative symptoms. ALB and SOD levels are stable, easily obtainable, and cost-effective biomarkers for the early identification and intervention in patients with SCZ. However, this cross-sectional study only established an association between cognitive impairment and antioxidants rather than causation. In follow-up studies, large-sample prospective studies with strict control of disease course, drugs, and other factors can better illustrate the role of antioxidant enzyme levels in the cognitive function of individuals diagnosed with SCZ and provide objective evidence supporting clinical evaluation and early intervention.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors thank all the\u0026nbsp;participants who\u0026nbsp;participate in our study training program.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDan Li and Yuanyuan Huang :\u0026nbsp;\u003c/strong\u003eInvestigation, Formal analysis, Writing-Original Draft,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVisualization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHongxin Lu, Xuejing Li, Yi Guo , Sumiao Zhou and, Shixuan Feng:\u0026nbsp;\u003c/strong\u003eValidation, Methodology, Investigation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHehua Li , Shixuan Feng, Chunlian Fu and Guiying Chen:\u0026nbsp;\u003c/strong\u003eInvestigation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLianqi Liu , Fengchun Wu and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eYuping Ning\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eValidation, Project administration, Methodology, Investigation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (82301688), The Science and Technology Program of Guangzhou (202206060005, 202201010093, 2023A03J0856, 2023A03J0839), Guangdong Basic and Applied Basic Research Foundation Outstanding Youth Project (2021B1515020064), Medical Science and Technology Research Foundation of Guangdong (A2023224), The Natural Science Foundation Program of Guangdong (2023A1515011383), The Health Science and Technology Program of Guangzhou (20231A010036), Guangzhou Municipal Key Discipline in Medicine (2021-2023), Guangzhou High-level Clinical Key Specialty, and Guangzhou Research-oriented Hospital.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during the current study are not publicly, but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate. The study procedures were carried out in accordance with the Declarationof Helsinki. Prior to participating in the research, all participants and their guardians provided written consent following approval of the study protocol by the Ethics Committee of the Affiliated Brain Hospital of Guangzhou Medical University in Guangzhou, China.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo conflicts of interest exist for any of the authors.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eUppinkudru C, et al. Prevalence, correlates and explanatory models of cognitive deficits in patients with schizophrenia-A cross sectional study. Indian J Psychiatry. 2023;65(10):1025-34. https://doi.org/10.4103/indianjpsychiatry.indianjpsychiatry_102_23.\u003c/li\u003e\n\u003cli\u003eAmerican PA. Diagnostic and Statistical Manual of Mental Disorders.In: Text Revision.Fifth Edition. American Psychiatric Association.. 2022. \u003c/li\u003e\n\u003cli\u003eHuang Y, et al. Suicide Attempts, Neurocognitive Dysfunctions and Clinical Correlates in Middle-Aged and Elderly Chinese Schizophrenia Patients. Front Psychiatry. 2021;12:684653. https://doi.org/10.3389/fpsyt.2021.684653.\u003c/li\u003e\n\u003cli\u003eBelgaied W, et al. Routine clinical assessment of cognitive functioning in schizophrenia, major depressive disorder, and bipolar disorder. Eur Neuropsychopharmacol. 2014;24(1):133-41. https://doi.org/10.1016/j.euroneuro.2013.11.001.\u003c/li\u003e\n\u003cli\u003eHope S, et al. Similar immune profile in bipolar disorder and schizophrenia: selective increase in soluble tumor necrosis factor receptor I and von Willebrand factor. Bipolar Disord. 2009;11(7):726-34. https://doi.org/10.1111/j.1399-5618.2009.00757.x.\u003c/li\u003e\n\u003cli\u003eKarlsgodt KH, et al. Developmental disruptions in neural connectivity in the pathophysiology of schizophrenia. Dev Psychopathol. 2008;20(4):1297-327. https://doi.org/10.1017/S095457940800062X.\u003c/li\u003e\n\u003cli\u003ePantelis C, et al. Neuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparison. Lancet. 2003;361(9354):281-8. https://doi.org/10.1016/S0140-6736(03)12323-9.\u003c/li\u003e\n\u003cli\u003eKong L, et al. Neurological soft signs and structural network changes: a longitudinal analysis in first-episode schizophrenia. BMC Psychiatry. 2023;23(1):20. https://doi.org/10.1186/s12888-023-04522-4.\u003c/li\u003e\n\u003cli\u003eRao S, et al. Involvement of the long intergenic non-coding RNA LINC00461 in schizophrenia. BMC Psychiatry. 2022;22(1):59. https://doi.org/10.1186/s12888-022-03718-4.\u003c/li\u003e\n\u003cli\u003eChen MY, et al. Schizophrenia and oxidative stress from the perspective of bibliometric analysis. Front Psychiatry. 2023;14:1145409. https://doi.org/10.3389/fpsyt.2023.1145409.\u003c/li\u003e\n\u003cli\u003eCecerska-Heryć E, et al. Importance of oxidative stress in the pathogenesis, diagnosis, and monitoring of patients with neuropsychiatric disorders, a review. Neurochem Int. 2022;153:105269. https://doi.org/10.1016/j.neuint.2021.105269.\u003c/li\u003e\n\u003cli\u003eSomogyi A, et al. Antioxidant measurements. Physiol Meas. 2007;28(4):R41-55. https://doi.org/10.1088/0967-3334/28/4/R01.\u003c/li\u003e\n\u003cli\u003eJomova K, et al. Reactive oxygen species, toxicity, oxidative stress, and antioxidants: chronic diseases and aging. Arch Toxicol. 2023;97(10):2499-574. https://doi.org/10.1007/s00204-023-03562-9.\u003c/li\u003e\n\u003cli\u003eMandal PK, et al. Schizophrenia, Bipolar and Major Depressive Disorders: Overview of Clinical Features, Neurotransmitter Alterations, Pharmacological Interventions, and Impact of Oxidative Stress in the Disease Process. ACS Chem Neurosci. 2022;13(19):2784-802. https://doi.org/10.1021/acschemneuro.2c00420.\u003c/li\u003e\n\u003cli\u003ePisoschi AM, Pop A. The role of antioxidants in the chemistry of oxidative stress: A review. Eur J Med Chem. 2015;97:55-74. https://doi.org/10.1016/j.ejmech.2015.04.040.\u003c/li\u003e\n\u003cli\u003eZhang XY, et al. Thioredoxin, a novel oxidative stress marker and cognitive performance in chronic and medicated schizophrenia versus healthy controls. Schizophr Res. 2013;143(2-3):301-6. https://doi.org/10.1016/j.schres.2012.11.017.\u003c/li\u003e\n\u003cli\u003eKapogiannis D, Mattson MP. Disrupted energy metabolism and neuronal circuit dysfunction in cognitive impairment and Alzheimer\u0026apos;s disease. Lancet Neurol. 2011;10(2):187-98. https://doi.org/10.1016/S1474-4422(10)70277-5.\u003c/li\u003e\n\u003cli\u003eNiedzielska E, et al. Oxidative Stress in Neurodegenerative Diseases. Mol Neurobiol. 2016;53(6):4094-125. https://doi.org/10.1007/s12035-015-9337-5.\u003c/li\u003e\n\u003cli\u003ePizzino G, et al. Oxidative Stress: Harms and Benefits for Human Health. Oxid Med Cell Longev. 2017;2017:8416763. https://doi.org/10.1155/2017/8416763.\u003c/li\u003e\n\u003cli\u003eHardingham GE, Do KQ. Linking early-life NMDAR hypofunction and oxidative stress in schizophrenia pathogenesis. Nat Rev Neurosci. 2016;17(2):125-34. https://doi.org/10.1038/nrn.2015.19.\u003c/li\u003e\n\u003cli\u003eMichel TM, et al. Cu, Zn- and Mn-superoxide dismutase levels in brains of patients with schizophrenic psychosis. J Neural Transm (Vienna). 2004;111(9):1191-201. https://doi.org/10.1007/s00702-004-0160-9.\u003c/li\u003e\n\u003cli\u003eWang DM, et al. The relationship between cognitive impairment and superoxide dismutase activity in untreated first-episode patients with schizophrenia. World J Biol Psychiatry. 2022;23(7):517-24. https://doi.org/10.1080/15622975.2021.2013093.\u003c/li\u003e\n\u003cli\u003eLi H, et al. Association of serum homocysteine levels with intestinal flora and cognitive function in schizophrenia. J Psychiatr Res. 2023;159:258-65. https://doi.org/10.1016/j.jpsychires.2023.01.045.\u003c/li\u003e\n\u003cli\u003eZhou S, et al. Gender differences in associations of cognitive impairments with homocysteine in schizophrenia. Asian J Psychiatr. 2022;75:103214. https://doi.org/10.1016/j.ajp.2022.103214.\u003c/li\u003e\n\u003cli\u003eKay SR, et al. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr Bull. 1987;13(2):261-76. https://doi.org/10.1093/schbul/13.2.261.\u003c/li\u003e\n\u003cli\u003eWallwork RS, et al. Searching for a consensus five-factor model of the Positive and Negative Syndrome Scale for schizophrenia. Schizophr Res. 2012;137(1-3):246-50. https://doi.org/10.1016/j.schres.2012.01.031.\u003c/li\u003e\n\u003cli\u003eAu-Yeung C, et al. The relationship between negative symptoms and MATRICS neurocognitive domains: A meta-analysis and systematic review. Prog Neuropsychopharmacol Biol Psychiatry. 2023;127:110833. https://doi.org/10.1016/j.pnpbp.2023.110833.\u003c/li\u003e\n\u003cli\u003eCouture SM, et al. A path model investigation of neurocognition, theory of mind, social competence, negative symptoms and real-world functioning in schizophrenia. Schizophr Res. 2011;125(2-3):152-60. https://doi.org/10.1016/j.schres.2010.09.020.\u003c/li\u003e\n\u003cli\u003eShi C, et al. The MATRICS Consensus Cognitive Battery (MCCB): Co-norming and standardization in China. Schizophr Res. 2015;169(1-3):109-15. https://doi.org/10.1016/j.schres.2015.09.003.\u003c/li\u003e\n\u003cli\u003eDickinson D, et al. General and specific cognitive deficits in schizophrenia: Goliath defeats David. Biol Psychiatry. 2008;64(9):823-7. https://doi.org/10.1016/j.biopsych.2008.04.005.\u003c/li\u003e\n\u003cli\u003eHeinrichs RW, Zakzanis KK. Neurocognitive deficit in schizophrenia: a quantitative review of the evidence. Neuropsychology. 1998;12(3):426-45. https://doi.org/10.1037//0894-4105.12.3.426.\u003c/li\u003e\n\u003cli\u003eMohn-Haugen CR, et al. A systematic review of premorbid cognitive functioning and its timing of onset in schizophrenia spectrum disorders. Schizophr Res Cogn. 2022;28:100246. https://doi.org/10.1016/j.scog.2022.100246.\u003c/li\u003e\n\u003cli\u003eV\u0026ouml;hringer PA, et al. Cognitive impairment in bipolar disorder and schizophrenia: a systematic review. Front Psychiatry. 2013;4:87. https://doi.org/10.3389/fpsyt.2013.00087.\u003c/li\u003e\n\u003cli\u003eMorozova A, et al. Neurobiological Highlights of Cognitive Impairment in Psychiatric Disorders. Int J Mol Sci. 2022;23(3):1217. https://doi.org/10.3390/ijms23031217.\u003c/li\u003e\n\u003cli\u003eOhi K, et al. Genetic Overlap between General Cognitive Function and Schizophrenia: A Review of Cognitive GWASs. Int J Mol Sci. 2018;19(12):3822. https://doi.org/10.3390/ijms19123822.\u003c/li\u003e\n\u003cli\u003eJoo SW, et al. Altered white matter connectivity in patients with schizophrenia: An investigation using public neuroimaging data from SchizConnect. PLoS One. 2018;13(10):e0205369. https://doi.org/10.1371/journal.pone.0205369.\u003c/li\u003e\n\u003cli\u003eAntonova E, et al. The relationship between brain structure and neurocognition in schizophrenia: a selective review. Schizophr Res. 2004;70(2-3):117-45. https://doi.org/10.1016/j.schres.2003.12.002.\u003c/li\u003e\n\u003cli\u003eHope S, et al. Inflammatory markers are associated with general cognitive abilities in schizophrenia and bipolar disorder patients and healthy controls. Schizophr Res. 2015;165(2-3):188-94. https://doi.org/10.1016/j.schres.2015.04.004.\u003c/li\u003e\n\u003cli\u003eRabinowitz J, et al. Negative symptoms have greater impact on functioning than positive symptoms in schizophrenia: analysis of CATIE data. Schizophr Res. 2012;137(1-3):147-50. https://doi.org/10.1016/j.schres.2012.01.015.\u003c/li\u003e\n\u003cli\u003eMelillo A, et al. Correlations between Negative Symptoms and Cognitive Deficits in Individuals at First Psychotic Episode or at High Risk of Psychosis: A Systematic Review. Journal of Clinical Medicine. 2023;(2077-0383 (Print)). \u003c/li\u003e\n\u003cli\u003eBrady RO Jr, et al. Cerebellar-Prefrontal Network Connectivity and Negative Symptoms in Schizophrenia. Am J Psychiatry. 2019;176(7):512-20. https://doi.org/10.1176/appi.ajp.2018.18040429.\u003c/li\u003e\n\u003cli\u003eManoliu A, et al. Insular Dysfunction Reflects Altered Between-Network Connectivity and Severity of Negative Symptoms in Schizophrenia during Psychotic Remission. Front Hum Neurosci. 2013;7:216. https://doi.org/10.3389/fnhum.2013.00216.\u003c/li\u003e\n\u003cli\u003eGarg S, et al. The efficacy of cerebellar vermal deep high frequency (theta range) repetitive transcranial magnetic stimulation (rTMS) in schizophrenia: A randomized rater blind-sham controlled study. Psychiatry Res. 2016;243:413-20. https://doi.org/10.1016/j.psychres.2016.07.023.\u003c/li\u003e\n\u003cli\u003ePan Z, et al. The Effects of Repetitive Transcranial Magnetic Stimulation in Patients with Chronic Schizophrenia: Insights from EEG Microstates. Psychiatry Res. 2021;299:113866. https://doi.org/10.1016/j.psychres.2021.113866.\u003c/li\u003e\n\u003cli\u003eSarandol A, et al. First-episode psychosis is associated with oxidative stress: Effects of short-term antipsychotic treatment. Psychiatry Clin Neurosci. 2015;69(11):699-707. https://doi.org/10.1111/pcn.12333.\u003c/li\u003e\n\u003cli\u003eZhang XY, et al. Superoxide dismutase and cytokines in chronic patients with schizophrenia: association with psychopathology and response to antipsychotics. Psychopharmacology (Berl). 2009;204(1):177-84. https://doi.org/10.1007/s00213-008-1447-6.\u003c/li\u003e\n\u003cli\u003eSrivastava N, et al. Nitrite content and antioxidant enzyme levels in the blood of schizophrenia patients. Psychopharmacology (Berl). 2001;158(2):140-5. https://doi.org/10.1007/s002130100860.\u003c/li\u003e\n\u003cli\u003eZhang XY, et al. Clinical symptoms and cognitive impairment associated with male schizophrenia relate to plasma manganese superoxide dismutase activity: a case-control study. J Psychiatr Res. 2013;47(8):1049-53. https://doi.org/10.1016/j.jpsychires.2013.03.014.\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;nez-Cengotitabengoa M, et al. Cognitive impairment is related to oxidative stress and chemokine levels in first psychotic episodes. Schizophr Res. 2012;137(1-3):66-72. https://doi.org/10.1016/j.schres.2012.03.004.\u003c/li\u003e\n\u003cli\u003eZhang XY, et al. Plasma total antioxidant status and cognitive impairments in schizophrenia. Schizophr Res. 2012;139(1-3):66-72. https://doi.org/10.1016/j.schres.2012.04.009.\u003c/li\u003e\n\u003cli\u003eSimanjuntak E, Zulham Z. SUPEROKSIDA DISMUTASE (SOD) DAN RADIKAL BEBAS. JURNAL KEPERAWATAN DAN FISIOTERAPI (JKF). 2020;2(2):124-9. \u003c/li\u003e\n\u003cli\u003eLi J, et al. Age of Onset Moderates the Association between Total Antioxidant Capacity and Cognitive Deficits in Patients with Drug-Na\u0026iuml;ve Schizophrenia. Antioxidants (Basel). 2023;12(6). https://doi.org/10.3390/antiox12061259.\u003c/li\u003e\n\u003cli\u003eYao JK, Keshavan MS. Antioxidants, redox signaling, and pathophysiology in schizophrenia: an integrative view. Antioxid Redox Signal. 2011;15(7):2011-35. https://doi.org/10.1089/ars.2010.3603.\u003c/li\u003e\n\u003cli\u003eReddy R, et al. Reduced plasma antioxidants in first-episode patients with schizophrenia. Schizophr Res. 2003;62(3):205-12. https://doi.org/10.1016/s0920-9964(02)00407-3.\u003c/li\u003e\n\u003cli\u003eBelinskaia DA, et al. Serum Albumin in Health and Disease: Esterase, Antioxidant, Transporting and Signaling Properties. Int J Mol Sci. 2021;22(19):10318. https://doi.org/10.3390/ijms221910318.\u003c/li\u003e\n\u003cli\u003eSolberg DK, et al. A five-year follow-up study of antioxidants, oxidative stress and polyunsaturated fatty acids in schizophrenia. Acta Neuropsychiatr. 2019;31(4):202-12. https://doi.org/10.1017/neu.2019.14.\u003c/li\u003e\n\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":"cognitive function, schizophrenia, PANSS, superoxide dismutase, serum albumin, uric acid","lastPublishedDoi":"10.21203/rs.3.rs-4336905/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4336905/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eCognitive dysfunction is a prevalent and intricate manifestation of schizophrenia (SCZ) that may be associated with distinct clinical factors and the presence of antioxidants, which relationship is unclear. The study aimed to investigate cognitive function and its influencing factors in Chinese patients with SCZ.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA group of 133 patients with SCZ and 120 healthy controls (HCs) were recruited. The MATRICS Consensus Cognitive Battery (MCCB) was utilized to evaluate cognitive ability, and the Positive and Negative Syndrome Scale (PANSS) was used to assess clinical symptoms. Levels of plasma superoxide dismutase (SOD), serum albumin (ALB) and uric acid (UA) were assessed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCompared with HCs, patients with SCZ exhibited lower cognitive performance as indicated by MCCB scores, including the dimensions of speed of processing, attention/vigilance, working memory, verbal learning, and visual learning. In the SCZ group, total PANSS scores were negatively associated with all MCCB dimensions (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), except for the attention/vigilance score. The PANSS-negative and PANSS-cognitive subscores were negatively associated with speed of processing, verbal learning, and visual learning scores (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The PANSS-excited subscores showed a negative correlation with working memory and visual learning scores (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). ALB levels significantly decreased, and their UA and SOD levels were notably elevated compared to HCs (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). ALB levels and PANSS-negative factors were correlated with to speed of processing, working memory, and visual learning dimensions. SOD levels were independent contributors to the attention/vigilance dimension.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe cognitive function was decreased in SCZ. The degree of cognitive impairment was closely related to ALB, SOD levels and negative clinical symptoms.\u003c/p\u003e","manuscriptTitle":"Association between cognitive function, antioxidants, and clinical variables in Chinese patients with schizophrenia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-04 15:12:16","doi":"10.21203/rs.3.rs-4336905/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-20T12:45:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-17T12:14:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-17T12:14:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2024-04-28T08:14:11+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":"June 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-23T16:06:14+00:00","versionOfRecord":{"articleIdentity":"rs-4336905","link":"https://doi.org/10.1186/s12888-024-06335-5","journal":{"identity":"bmc-psychiatry","isVorOnly":false,"title":"BMC Psychiatry"},"publishedOn":"2024-12-18 15:58:34","publishedOnDateReadable":"December 18th, 2024"},"versionCreatedAt":"2024-06-04 15:12:16","video":"","vorDoi":"10.1186/s12888-024-06335-5","vorDoiUrl":"https://doi.org/10.1186/s12888-024-06335-5","workflowStages":[]},"version":"v1","identity":"rs-4336905","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4336905","identity":"rs-4336905","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}