Associations of Inflammatory Biomarkers with Brain Atrophy and Clinical Scores in Schizophrenia Patients with Autistic Features

Associations of Inflammatory Biomarkers with Brain Atrophy and Clinical Scores in Schizophrenia Patients with Autistic Features | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Associations of Inflammatory Biomarkers with Brain Atrophy and Clinical Scores in Schizophrenia Patients with Autistic Features Jin Wang, Jie Shen, Yu Pang, Jihui Liu, Lili Zhao, Momo Sun, Yang Yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7715016/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Apr, 2026 Read the published version in BMC Research Notes → Version 1 posted 8 You are reading this latest preprint version Abstract Objectives : This study explored the schizophrenia (SCZ) patients with autistic traits by analyzing inflammatory biomarkers and brain atrophy (BA). Methods : The statistical analysis included 58 males and 55 females. All the subjects underwent computed tomography (CT) and laboratory analysis. SCZ symptom was assessed via the Positive and Negative Syndrome Scale (PANSS). The PANSS Autism Severity Score (PAUSS) was used to assess autistic traits, with a threshold of 30 to identify relevant characteristics. Results : Multiple regression analysis revealed significant associations between positive scores and lymphocyte count (LYM) ,platelet-to-lymphocyte ratio (PLR) , and the minimum width of the anterior horn of the lateral ventricle (WMIN-AH-LV) ( P <0.05). Negative symptom scores were positively correlated with the NLR, transverse diameter of the bilateral caudate nucleus (TD-B-CN) , and third ventricle width(TVW) ( P <0.05). As the WMIN-AH-LV ( P =0.001) increased, the general psychopathological symptom score increased. As the ventricular central indices, the WMIN-AH-LV increased, the total score increased ( P <0.05) . As the NLR, TD-B-CN, WMIN-AH-LV, TVW and the Evans index increased, the PAUSS increased ( P <0.05). Conclusion: Inflammatory biomarker and BA correlate positively with PANSS or PAUSS in SCZ with autistic features. These easily obtainable parameters help clinicians better understand this subgroup in a more objective way. Schizophrenia Brain atrophy Ventricle enlargement Autism Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction SCZ is a complex condition characterized by psychotic symptoms, increased medical comorbidity, and reduced life expectancy [ 1 ] . Age-related degenerative disorders may contribute to SCZ onset in older adults by causing structural brain changes [ 2 ] .Recent studies have shown that mental illnesses, brain structure abnormalities, and metabolic factors significantly influence patient outcomes in patients with SCZ [ 3 ] . Studies indicate that a distinct subgroup of SCZ patients exhibit autistic features and unique clinical characteristics [ 4 ] . This population shows significant social cognitive impairments, poorer functional outcomes, more severe psychiatric symptoms, lower well-being, and reduced responsiveness to antipsychotic therapies [ 5 ] .One study [ 6 ] confirmed increased ventricle volume in adults diagnosed with autism through long-term observation.While many studies have identified brain‒behavior links in SCZ [ 7 ], brain measurement ranges in this population remain understudied.However, the neurobiology of SCZ with autistic traits remains poorly understood and requires further investigation. Moreover, increasing evidence suggests [ 8 ] that immune system activation plays a role in SCZ development and progression. Available data [ 9 ] indicate possible links between SCZ, inflammation, and neuroimmune genetic factors. Given the strong association between immunity and SCZ, a wide range of inflammatory markers have been used in research on this disorder. This study aimed to bridge the existing gap by presenting these advancements to clinicians in a novel way. We developed and used a simple linear measurement method designed to detect diffuse atrophy more quickly to assess BA parameters. The approach maintains sensitivity while avoiding time-consuming volumetric measurements. This study systematically examined the relationships between inflammatory markers and CT-measured BAs in SCZ patients with autistic traits to better understand how these factors are linked to clinical symptoms. 2. Materials and methods 2.1 Subjects As a cross-sectional study, a total of 113 SCZ patients (58 males and 55 females) were recruited from Tianjin Anding Hospital for a study conducted from September 2023 to January 2024.The age of the participants ranged from 19 to 82 years. The exclusion criteria were as follows: 1. Patients diagnosed with primary cranial disorders; 2. Pregnant or lactating women; 3. Patients who did not comply with the examination protocol; 4. Participants with conditions that affect inflammatory marker levels (e.g., infectious diseases, acute or chronic inflammation, allergies, malignancies) or who are receiving medications that alter hematological parameters (e.g., antibiotics, antivirals, antihistamines, immunosuppressants, and leukocyte-stimulating factors). Among the 126 screened individuals, 13 were excluded on the basis of predefined criteria: traumatic brain injury (n = 3), pneumonia (n = 2), burns (n = 1), lymphoma (n = 1), and failure to complete CT scanning (n = 6). The final cohort comprised 113 eligible participants. An international panel consensus [ 10 ] defined age 60 years as the threshold distinguishing middle-aged SCZ patients from very-late-onset schizophrenia-like psychosis patients. Therefore, we classified individuals aged ≥ 60 years as old. 2.2 Clinical assessment Clinical information, including age, sex, and illness duration, was recorded. We assessed SCZ symptoms via the PANSS, a 30-item scale scored from 1 to 7. This produces three subscales: positive symptoms, negative symptoms, and general psychopathology. The PANSS ranges from 30 to 210, with higher scores indicating greater symptom severity [ 11 ] . The PANSS assessment was conducted by two psychiatrists who had no knowledge of the patients' inflammatory profiles or degree of BA. The five-factor model of Mohr's PANSS, encompassing positive, negative, cognitive, mood, and hostility domains, was utilized. The PAUSS [ 6 ] was applied to evaluate autistic traits and comprises three subscales measuring difficulties in social interaction (N1, N3, N4), communication skills (N5, N6), and repetitive behaviors (N7, G5, G15). The use of a cutoff score of 30 for identifying individuals with autism spectrum features has been recommended and validated in previous studies [ 12 , 13 ] . These cutoff values were established and validated by scale developers through comprehensive psychometric analyses of large clinical samples [ 14 ] . 2.3 CT The linear measurements were performed by two radiologists with over five years of experience who were blinded to the patients’ clinical information. CT scans were conducted on all patients via a Philips Ingenuity Core 128-slice spiral CT machine. The slice thickness and spacing were both set at 5 mm, with the tube voltage and current set to 120 kV and 120 mA, respectively. The pitch ranged from 1.0 to 1.5 mm, and the scanning time was set to 5 seconds. The examination procedure was conducted as follows: the patient was positioned supine, with the auditory canthus line serving as the baseline for scanning. An upward continuous scan was performed to evaluate the brain sulci, ventricles, and tissue. The images were then sent to a workstation for 3D reconstruction via 3D volume, multiplanar, and surface reconstruction techniques. The measurement encompasses a wide range of parameters, including the maximum width of the anterior horn of the lateral ventricle (MW-AH-LV), WMIN-AH-LV, TVW, transverse diameter of the choroid plexus of the lateral ventricle (TD-ChP-LV), TD-B-CN, maximum external diameter (MAED) of the body of the LV, maximum external diameter of the cranium (MAED-Cr), maximum internal diameter of the cranium (MAID-Cr), Hackman value (MW-AH-LV + TD-B-CN), the ventricular index (TD-ChP-LV/MW-AH-LV), the LV body index (MAID-Cr/MAED of the body of the LV), the frontal horn index (FHI = MAID-Cr/MW-AH-LV), the Evans index (MW-AH-LV/MAID-Cr), the ventricular central 2.4 Laboratory measurements Morning blood samples were collected from all patients via the peripheral vein. The complete blood count data were obtained close in time to the time of the CT examination. We used the provided formulas to calculate several ratios: the NLR, MLR, PLR, and SII. NLR = neutrophil count/lymphocyte count. MLR = monocyte count/lymphocyte count. PLR = platelet count/lymphocyte count. SII = platelet count × neutrophil count/lymphocyte count. The NLR, MLR, PLR, and SII were used to measure inflammation. 2.5 Statistics Statistical analysis was conducted via SPSS 26.0. Data normality was assessed with the Kolmogorov‒Smirnov test. Normally distributed data are presented as the means ± standard deviations (SDs), whereas nonnormally distributed data are reported as medians and interquartile ranges (IQRs). Differences between the male and female groups were analyzed via either the Mann‒Whitney U test or independent samples t test. Spearman's correlation was used to examine the relationships among inflammatory biomarkers, BA parameters, and PANSS scores. Multiple linear regression analysis was performed to evaluate the effects of inflammatory biomarkers and BA parameters on the scores. Statistical significance was set at P < 0.05. 3. Results 3. 1Comparative analysis of inflammatory biomarkers and BA parameters across sexes Table 1 shows significant sex differences in the NLR, positive symptom score, negative symptom score, total score, and PAUSS. Table 1 Comparative analysis of inflammatory biomarkers and BA parameters across sexes Variable Male (n = 58) Female (n = 55) t/Z P PLT 250.86±,63.7 253.93 ± 66.93 0.249 0.804 1 LYM 1.955(1.73–2.43) 1.900(1.47–2.27) -1.140 0.254 2 NEU 4.42 ± 2.32 3.65 ± 1.94 -1.905 0.059 1 NLR 3.77(2.83–3.77) 3.22(2.49–4.17) 4.253 0.039 2 PLR 122.67(101.16-148.21) 130.46(106.04-158.04) -1.212 0.225 2 MLR 0.25(0.19-148.21) 0.21(0.16–0.266) -1.835 0.066 2 SII 445.58(352.33-635.41) 427.81(307.26-602.33) -1.086 0.278 2 Positive symptom score 34(31-37.25) 31(29–32) -4.172 <0.001 2 Negative symptom score 31(28-36.25) 30(27–32) -2.159 0.031 2 General psychopathological symptoms score 68(65.75–72.25) 68(66–69) -1.517 0.159 2 Total score 134.91 ± 15.47 127.6 ± 5.56 -3.308 0.001 1 PAUSS 37.45 ± 6.27 35.24 ± 3.64 -2.276 0.025 1 MW-AH-LV(mm) 3.52 ± 0.38 3.33 ± 0.4 -2.609 0.01 1 TD-B-CN(mm) 1.72 ± 1.53–1.95 1.34(1.22–1.72) -4.657 <0.01 2 WMIN-AH-LV(mm) 1.79 ± 0.31 1.54 ± 0.29 -4.458 <0.01 1 TVW,(mm) 0.69(0.58–0.80) 0.57(0.47–0.74) -3.037 0.002 2 TD-ChP-LV(mm) 6.02 ± 0.43 5.52 ± 0.58 -5.206 <0.01 1 MAED of body of LV(mm) 2.65 ± 0.37 2.59 ± 0.37 -0.763 0.447 1 MAED-Cr(mm) 14.81 ± 0.59 14.27 ± 0.5 -5.299 <0.01 1 MAID-Cr(mm) 13.29 ± 0.6 12.64 ± 0.54 -6.03 <0.01 1 Hackman value 5.29 ± 0.53 4.81 ± 0.7 -4.11 <0.01 1 ventricular index 1.72 ± 0.17 1.68 ± 0.24 -1.174 0.243 1 the ventricular central indexs 0.14 ± 0.02 0.12 ± 0.02 -2.834 0.005 1 LV body index 5.11 ± 0.69 4.97 ± 0.72 -1.044 0.299 1 FHI 3.74(3.58–3.99) 3.75(3.58–4.13) -0.345 0.730 2 Evans index 0.26 ± 0.03 0.26 ± 0.03 -0.251 0.803 1 1 Independent samples t test 2 Mann‒Whitney U test The NLRs ( P = 0.039) and scale scores ( P < 0.05) of the male individuals were greater than those of their female counterparts. The parameters MW-AH-LV, WMIN-AH-LV, TD-ChP-LV, TD-B-CN, MAED-Cr, MAID-Cr and Hackman values ( P < 0.01), TVW values ( P = 0.002), and ventricular central indices ( P = 0.005) were significantly different between the sexes. The degree of BA was found to be greater in males. 3.2 Comparative analysis of inflammatory biomarkers and BA parameters across age groups The PLT levels were found to be lower in the age group over 60 as compared to those aged 60 or below, P = 0.028 < 0.05.Negative symptom score,Total score( P < 0.01),PAUSS( P = 0.003),the parameters WMIN-AH-LV,TVW,TD-ChP-LV,MAED of body of LV,Evans index, the ventricular central indexs( P < 0.01),MW-AH-LV( P = 0.004),MAID-Cr( P = 0.001),TD-B-CN( P = 0.001),Hackman value( P = 0.001),ventricular index( P = 0.028) ,FHI( P = 0.022).The difference in the aforementioned parameters was found to be statistically significant, with the older group exhibiting a higher BA parameters and higer negative symptom score, total score and PAUSS. 3.3 Correlation analysis of disease duration, inflammatory biomarkers, and BA parameters With prolonged disease duration, the total score ( P = 0.013), general psychopathological symptoms score ( P = 0.001), PAUSS, and the parameters MW-AH-LV, TD-B-CN, TVW, TD-ChP-LV, MAED-Cr, the ventricular index, and the LV body index ( P < 0.01) were significantly positively correlated, as indicated in Table 2 . Table 2 Correlation analysis of age, disease duration, inflammatory biomarkers, and BA parameters disease duration PLT r = -0.333, P <0.01 LYM r = -0.148, P = 0.118 NEU r = -0.197, P = 0.036 NLR r = -0.126, P = 0.184 PLR r = -0.134, P = 0.159 MLR r = 0.145, P = 0.124 SII r = -0.172, P = 0.068 Positive symptom score r = -0.083, P = 0.601 Negative symptom score r = 0.137, P = 0.148 General psychopathological symptoms score r = 0.526, P <0.01 Total score r = 0.232, P = 0.013 PAUSS r = 0.360, P <0.01 MW-AH-LV(mm) r = 0.467, P <0.01 TD-B-CN(mm) r = 0.409, P <0.01 WMIN-AH-LV(mm) r = -0.354, P <0.01 TVW,(mm) r = 0.799, P <0.01 TD-ChP-LV(mm) r = 0.406, P <0.01 MAED of body of LV(mm) r = 0.115, P = 0.227 MAED-Cr(mm) r = 0.360, P <0.01 MAID-Cr(mm) r = -0.155, P = 0.101 Hackman value r = -0.278, P = 0.003 ventricular index r = 0.345, P <0.01 the ventricular central indexs r = -0.08, P = 0.402 LV body index r = 0.531, P <0.01 FHI r = -0.427, P <0.01 Evans index r = -0.295, P = 0.001 The symptoms of autism in the PAUSS worsened significantly as the disease progressed (r = 0.360, P < 0.01).However, there was a negative correlation between the PLT ( P < 0.01), NEU ( P = 0.036), Hackman value ( P = 0.003), FHI ( P < 0.01), and Evans index ( P = 0.001) and disease progression. The levels of inflammatory biomarkers were lower in patients with a longer duration of disease, whereas parameters associated with dilation of the LV and third ventricles were greater ( P < 0.01). 3.4 Correlation analysis of inflammatory biomarkers with the PANSS or PAUSS The negative symptom score was positively correlated with inflammatory biomarkers. Furthermore, the negative symptom score was positively associated with the MLR ( P = 0.026) but negatively associated with the PLT ( P = 0.006) and LYM ( P = 0.049). The PAUSS score was negatively correlated with the PLT ( P = 0.043). 3.5 Correlation analysis of BA parameters and PANSS or PAUSS scores The positive symptom score was positively correlated with the parameters WMIN-AH-LV ( P < 0.001), TD-ChP-LV ( P = 0.008), the ventricular index ( P = 0.047), and the ventricular central index ( P = 0.001). The negative symptom score was positively correlated with the parameters TD-B-CN, WMIN-AH-LV, TVW, ventricular central index ( P < 0.001), TD-ChP-LV ( P = 0.027), and Hackman value ( P = 0.001). The general psychopathological symptom score was positively correlated with the ventricular index ( P = 0.001), FHI ( P = 0.02), and Evans index ( P = 0.035). The total score was positively correlated with TD-B-CN ( P = 0.003), WMIN-AH-LV ( P < 0.001), TVW ( P < 0.001), TD-ChP-LV ( P = 0.008), the ventricular index ( P = 0.013), and the ventricular central indices ( P = 0.001). The PAUSS score was positively correlated with TD-B-CN ( P = 0.001), WMIN-AH-LV ( P = 0.002), TVW ( P < 0.001), TD-ChP-LV ( P = 0.012), Hackman ( P = 0.019), and ventricular central indices ( P = 0.004). 3.6 The combination of BA parameters and inflammatory biomarkers accurately predicted the PANSS and PAUSS scores. In Table 3 , the dependent variable was the positive symptom score. Independent variables for the multiple linear regression analysis included age, sex, BA parameters, and inflammatory biomarkers. The backward method was used. The results revealed a significant negative correlation between positive scores and both the PLT ( P = 0.003) and the Evans index ( P < 0.001), indicating that higher values of these variables were linked to lower positive scores. Additionally, there was a positive association between positive scores and LYM (c) ( P = 0.049), PLR (d) ( P = 0.009), and WMIN-AH-LV (e) ( P < 0.001), suggesting that elevated levels of these factors corresponded to higher positive scores. (Fig. 1 ) Table 3 Multiple regression analysis of positive symptom scores Variable β SE t P VIF Constant 32.428 4.281 PLT -0.028 0.009 -3.097 0.003 2.913 LYM 1.860 0.932 1.995 0.049 3.514 PLR 0.036 0.013 2.659 0.009 6.793 WMIN-AH-LV(mm) 11.446 1.770 6.467 <0.001 2.766 Evans index -59.733 15.688 -3.808 <0.001 2.203 The dependent variable was the negative symptom score, while the independent variables remained unchanged. The backward method was adopted. The results indicated that as the SII ( P = 0.004) (a) increased, negative symptoms decreased. Additionally, as the NLR (b) ( P = 0.006), TD-B-CN (c) ( P = 0.024), and TVW(d) ( P = 0.022) increased, negative symptoms increased. (Fig. 2 ) The dependent variable was the general psychopathological symptoms score, whereas the independent variables remained unchanged. The backward method was adopted. The results indicated that as the MW-AH-LV ( P < 0.001) increased, the ventricular central indices ( P = 0.009) increased, and the general psychopathological symptom score decreased. Additionally, as WMIN-AH-LV ( P = 0.001) increased, the general psychopathological symptom score increased. The dependent variable was the total score, whereas the independent variables remained unchanged. The backward method was adopted. The results indicated that as the PLT ( P = 0.039), MW-AH-LV(a) ( P < 0.001), and ventricular central indices ( P = 0.009) increased, the total score decreased. Additionally, as WMIN-AH-LV(b) ( P < 0.001) increased, the total score increased. (Fig. 3 ) The dependent variable was PAUSS, whereas the independent variables remained unchanged. The backward method was adopted. The results indicated that as the SII(a) ( P = 0.017) and the MW-AH-LV ratio ( P = 0.009) increased, the ventricular central indices increased, and the PAUSS decreased. Additionally, as the NLR (b) ( P = 0.02), TD-B-CN(c) ( P = 0.045), WMIN-AH-LV(d) ( P = 0.028), TVW(e), ( P = 0.011), and Evans index (f) ( P = 0.016) increased, the PAUSS increased. (Fig. 4 ) 4. Discussion Compared with magnetic resonance imaging (MRI), brain measurements from CT scans are significantly correlated with clinical outcomes in patients with SCZ, despite the lower spatial resolution of CT. A previous study [ 15 ] revealed that CT has superior data accessibility, especially for large-scale clinical studies. It also offers shorter scan times and greater patient convenience [ 16 ] . For patients without focal neurological symptoms, routine structural neuroimaging may not be necessary. When imaging is needed, CT has comparable diagnostic efficacy to MRI and is suitable as a first-line modality [ 17 ] . Ventricular expansion is well documented in SCZ patients. It was first observed in an influential CT study by Johnstone et al. [ 18 ] . Further meta-analyses [ 19 ] have confirmed significant enlargements in the LV and third ventricle, with medium to large effect sizes. Similar findings [ 20 ] have also been reported in the LV of individuals at greater risk for psychosis. This study revealed a significant correlation between BA parameters and clinical symptom scores, especially those involving the LV, third ventricle, and caudate nucleus. Both WMIN-AH-LV and TVW strongly influenced all the scores. These results are consistent with previous findings. This study also confirmed a strong link between SCZ and PAUSS with the LV, third ventricle, and caudate nucleus. One study [ 21 ] revealed a temporal association between ventricular expansion and gradual gray matter loss. Those over 60 years of age with longer disease durations presented elevated BA parameters, indicating greater cerebral shrinkage. Studies [ 22 ] suggest that antipsychotic use and illness duration may affect both white and gray matter volumes. A significant association between negative symptoms and BA was found in the LV, caudate nucleus, and ChP. Previous studies have linked ventriculomegaly in individuals with SCZ to negative symptoms and cognitive impairments. Furthermore, patients experiencing global cognitive impairment tend to exhibit more pronounced ventricular enlargement than those who have preserved cognition [ 23 ] . In first-episode psychosis (FEP) patients, lateral and third ventricle sizes are correlated with negative symptom severity [ 24 ] . Periventricular diencephalic structures influence neuropsychological performance, especially through third ventricle volume. In FEP patients, negative symptoms and a higher total PANSS score at follow-up are linked to cognitive impairment [ 25 ] . The correlations between the negative symptom score, PAUSS score, and BA parameters remained consistent. The PAUSS is positively linked to the caudate nucleus, LV, ChP, and third ventricle. The NLR also showed significant correlations in the regression analyses. One study [ 26 ] suggested a link between hypothalamic atrophy and third ventricle enlargement in individuals with ASD. The hypothalamus may atrophy, and the third ventricle may enlarge due to its anatomical proximity. Oxytocin (OXT), a neuropeptide associated with social behavior, is produced in the hypothalamus. We hypothesize that a reduced hypothalamic volume and an enlarged third ventricle are associated with ASD, reflecting their anatomical relationship. This study revealed a positive correlation between the transverse diameter of the ChP in the LV and the positive symptom score, negative symptom score, total score, and PAUSS score in patients. Previous studies [ 27 ] have suggested that the observed BA enlargement in individuals with SCZ may be related to ChP abnormalities and their physiological functions. Enlarged ChP volume in psychosis has been associated with poorer cognitive function, localized BA, and increased ventricular size [ 28 ] . Postmortem studies [ 29 ] in SCZ patients have revealed structural changes in the ChP, including cellular fat accumulation, increased epithelial secretion, and large cystic formations. These changes may be linked to chronic neuroinflammation. Studies [ 30 ] suggest that sex hormones affect ChP function, influencing CSF production and composition, blood–CSF barrier integrity, and immune monitoring. Estrogens have anti-inflammatory properties and can modulate neurotransmission. The sex differences in ChP volume may stem from hormonal variations, which could also explain the observed sex differences in BA parameters in this study. The transverse diameter of the bilateral caudate nucleus was positively correlated with the negative symptom score, PAUSS score, and total score. It was significantly related to the negative symptom score and PAUSS score and was therefore included in the regression model. Numerous [ 31 ] studies have consistently shown a link between various bacterial and viral infections and the occurrence of mental disorders. Elevated levels of diverse autoimmune antibodies have been detected in individuals diagnosed with SCZ [ 32 ] . SCZ patients have abnormal C-reactive protein levels, decreased lymphocytes, and elevated NEU, NLR and MLR. In this study, the negative symptom score was positively correlated with the number of mononuclear cells and the MLR and negatively correlated with the PLT and LYM. These results align with previous findings. Higher LYM and PLR levels were linked to higher positive symptom scores in the regression model. A high NLR was associated with increased negative symptom scores and PAUSS scores. These findings further support that inflammatory biomarkers differentially affect SCZ patients with autistic features. Several studies have reported significantly elevated NLR, PLR, and MLR [ 33 ] . SII, a marker of inflammation that has garnered considerable interest in recent years, has been widely applied in the fields of cancer research, rheumatism studies, and investigations on immunity [ 34 ] . The SII, along with the negative symptom score and PAUSS score, was included in the study’s multiple regression model. However, higher SII values were associated with lower symptom scores. A cross-sectional study [ 35 ] confirmed associations between the NLR, MLR, PLR, SII, and PANSS scores. All the inflammatory markers correlated with the total, positive, negative, and general psychopathology scores. After adjusting for confounders, the NLR remained significantly linked to all clinical outcomes. The SII was the only marker predicting both overall PANSS and general psychopathology scores in SCZ patients. Limitations The inflammatory markers we obtained have certain limitations. The reasons for this might be due to the infection control measures during treatment and restricted blood sample collection due to timing and seasonal factors. Future research will aim to address these issues. As a cross-sectional study, our findings cannot establish causality. Longitudinal studies are needed to track inflammatory markers and cognitive changes over time. Additionally, the study lacked functional MRI comparisons and was limited by a small sample size, both of which will be improved in future research. Conclusion In conclusion, inflammatory biomarker levels and brain atrophy correlate positively with PANSS or PAUSS scores in SCZ patients with autistic features. These easily obtainable parameters help clinicians better understand this subgroup’s manifestations in a more objective and precise way. Abbreviations SCZ schizophrenia BA brain atrophy CT computed tomography NLR: lymphocyte ratio MLR monocyte-to-lymphocyte ratio PLR platelet-to-lymphocyte ratio SII systemic inflammation index Positive and Negative Syndrome Scale (PANSS) PAUSS PANSS Autism Severity Score LYM lymphocyte WMIN-AH-LV minimum width of the anterior horn of the lateral ventricle TD-B-CN transverse diameter of the bilateral caudate nucleus TVW Third Ventricle width MRI magnetic resonance imaging MW-AH-LV maximum width of the anterior horn of the lateral ventricle TD-ChP-LV transverse diameter of the choroid plexus of the lateral ventricle MAED maximum external diameter MAED-Cr maximum external diameter of cranium MAID-Cr maximum internal diameter of cranium SD standard deviation IQR interquartile range Declarations Ethics approval All procedures adhered to the principles outlined in the Declaration of Helsinki.This study was approved by the Tianjin Anding Hospital Ethics Committee (2024-31) and written informed consent was obtained from all participants. Consent to participate All participants provided written consent prior to their inclusion in the research. Consent for publication All patient data have been de-identified to protect patient privacy. Therefore, formal consent for publication was not required. Data Availability The clinical data supporting the findings of this study are not publicly available due to patient privacy concerns but can be made available by the corresponding author after signing a data use agreement and with the permission of the institutional ethics committee. Competing interests The authors declare that they have no competing interests. Funding Funding from studies on nuclide nanoprobes with aggregation-induced luminescence properties in the integration of the diagnosis and treatment of atherosclerotic vulnerable plaques in rabbits (21JCYBJC01060) and the study of PET/CT-based radiomics to predict the pathological characteristics and prognosis of primary liver cancer (TJWJ2021MS013). Acknowledgements We are grateful to the nurses and staff of the Department of General Psychiatry, Tianjin Anding Hospital for their support in patient recruitment. References Lysaker PH, Yanos PT, Outcalt J, et al. Association of stigma, self-esteem, and symptoms with concurrent and prospective assessment of social anxiety in schizophrenia. [J]. Clin Schizophr Relat Psychos. 2010;4(1):41DOI. 10.3371/CSRP.4.1.3 . Verdolini, Norma, et al. Obstetric complications and clinical presentation in first episode of psychosis. Acta neuropsychiatrica. 2023;35:3. Ana Costas Carrera,Clemente Garcia-Rizo,Byron Bitanihirwe & Rafael Penadés. (2020). Obstetric Complications and Brain Imaging in Schizophrenia: A Systematic Review. Biol Psychiatry: Cogn Neurosci Neuroimaging,5(12). Nibbio, Gabriele, et al. Assessment and correlates of autistic symptoms in schizophrenia spectrum disorders measured with the PANSS Autism Severity Score: A systematic review. Front Psychiatry. 2022;13:934005–934005. Prigge Molly BD et al. A 16-year study of longitudinal volumetric brain development in males with autism. NeuroImage 236. (2021):118067–118067. Vita Antonio et al. Influence of autistic symptoms on social and nonsocial cognition and real-life functioning in people with schizophrenia: evidence from the Italian Network for Research on Psychoses multicenter study. Eur psychiatry: J Association Eur Psychiatrists 63.1(2020):21–4. Kuo SS, Pogue-Geile FM. .Variation in Fourteen Brain Structure Volumes in Schizophrenia: A Comprehensive Meta-Analysis of 246 Studies[J].Neuroscience and Biobehavioral Reviews,2018,9885-94. Zhu, Xiaoyu et al. Changes in Inflammatory Biomarkers in Patients with Schizophrenia: A 3-Year Retrospective Study.Neuropsychiatric disease and treatment 19.(2023):1597–604. Rebecca Birnbaum, Daniel R. Weinberger.A Genetics Perspective on the Role of the (Neuro)Immune System in Schizophrenia.Schizophrenia Research 217.(2020):105–13. Howard. Late-onset schizophrenia and very-late-onset schizophrenia-like psychosis: An International Consensus[J]. Am J Psychiatry. 2000;157(2):172–8. 10.1176/appi.ajp.157.2.172 . Pina-Camacho L, Boada L, ,Díaz-Caneja MC et al. The Positive and Negative Syndrome Scale for Schizophrenia Autism Severity Scale (PAUSS) in young people with autism and schizophrenia[J].Revista de psiquiatría y salud mental (Barcelona),2020,13(3):118–30. Peng P, Wang Q. Autistic features in Chinese patients with chronic schizophrenia: Prevalence, clinical characteristics, and relationship with cognitive impairment[J]. Asian J psychiatry, 87:1036972025 -07-06].DOI:10.1016/j.ajp.2023.103697 Li W, Liu Y, ,Tao R, et al. Association of insomnia with suicide attempts in Chinese chronic schizophrenia patients with and without autistic symptoms[J]. BMC Psychiatry. 2025;25(1):604–604. Kästner A, et al. Autism beyond diagnostic categories: characterization of autistic phenotypes in schizophrenia. BMC Psychiatry. 2015;15(1):115. Esra B, Sema P, Mahmut T, et al. Investigation of Skull Cortical Thickness Changes in Healthy Population and Patients With Schizophrenia on Computed Tomography Images[J]. J Craniofac Surg. 2024;435DOI. 10.1097/SCS.0000000000010261 . Yue JK, Upadhyayula PS, Avalos LN, et al. Concussion and Mild-Traumatic Brain Injury in Rural Settings: Epidemiology and Specific Health Care Considerations[J]. J Neurosciences Rural Pract. 2020;11(1). 10.1055/s-0039-3402581 . Khandanpour N, Hoggard N, Connolly DJA. The role of MRI and CT of the brain in first episodes of psychosis.[J].Clinical Radiology, 2013, 68(3):245–50. 10.1016/j.crad.2012.07.010 Johnstone E, Frith CD, Crow TJ, .CEREBRAL VENTRICULAR SIZE AND COGNITIVE IMPAIRMENT IN CHRONIC SCHIZOPHRENIA[J]. 1976, 308(7992):924–6. 10.1016/s0140-6736(76)90890-4 Kuo SS, Pogue-Geile FM. .Variation in Fourteen Brain Structure Volumes in Schizophrenia: A Comprehensive Meta-Analysis of 246 Studies[J].Neuroscience and Biobehavioral Reviews,2018,9885-94. Daiki S, Yoichiro T, ,Tsutomu T et al. Subcortical Brain Volume Abnormalities in Individuals With an At-risk Mental State.[J].Schizophrenia bulletin,2020,46(4):834–45. Chung Y, Haut MK, ,He G et al. Ventricular enlargement and progressive reduction of cortical gray matter are linked in prodromal youth who develop psychosis[J].Schizophrenia Research,2017,189169-174. Qiyong G, Su L, A J S.. A Selective Review of Cerebral Abnormalities in Patients With First-Episode Schizophrenia Before and After Treatment.[J].The American journal of psychiatry,2016,173(3):232–43. Mezquida, Gisela et al. Identifying risk factors for predominant negative symptoms from early stages in schizophrenia: A longitudinal and sex-specific study in first-episode schizophrenia patients. Revista de psiquiatria y salud mental (2023). Isabel V, Stefania T, ,Paolo F et al. Episodic memory dysfunction in individuals at high-risk of psychosis: a systematic review of neuropsychological and neurofunctional studies. [J]. Current pharmaceutical design,2012,18(4):443–58. H F W,Guillaume A, ,Christine D et al. Focal atrophy of the hypothalamus associated with third ventricle enlargement in autism spectrum disorder. [J] Neuroreport 2015,26(17):1017–22. Uvnäs-Moberg K. Oxytocin may mediate the benefits of positive social interaction and emotions. Psychoneuroendocrinology. 1998;23:819–35. Lizano P, Lutz O, Ling G, et al. Association of Choroid Plexus Enlargement With Cognitive, Inflammatory, and Structural Phenotypes Across the Psychosis Spectrum[J]. Am J Psychiatry. 2019;176(7):appiajp201918070825. 10.1176/appi.ajp.2019.18070825 . Zeng, Jiaxin et al. Choroid plexus volume enlargement in first-episode antipsychotic-naïve schizophrenia.Schizophrenia (Heidelberg, Germany) 10.1(2024):1–1. Santos RC, Duarte CA, ,Quintela T et al. The choroid plexus as a sex hormone target: Functional implications[J].Frontiers in Neuroendocrinology,2017,44103-121. van Erp T G M,Hibar D P,Rasmussen J M,Glahn D C,Pearlson G D,Andreassen O A… van Haren N E M.(2016).Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium.Molecular psychiatry,21(4),585. Özdin S. Böke Ö. Neutrophil/lymphocyte, platelet/lymphocyte and monocyte/lymphocyte ratios in different stages of schizophrenia[J].Psychiatry Research,2019,271131-135. Mazza MG, Lucchi S, Rossetti A et al. Neutrophil-lymphocyte ratio, monocyte-lymphocyte ratio and platelet-lymphocyte ratio in nonaffective psychosis: A meta-analysis and systematic review[J]. World J Biol Psychiatry, 2019:1–37. 10.1080/15622975.2019.1583371 Fois AG, Paliogiannis P, Scano V et al. The Systemic Inflammation Index on Admission Predicts In-Hospital Mortality in COVID-19 Patients[J].Molecules, 2020, 25(23):5725. 10.3390/molecules25235725 Gennaro MM, Mariagrazia P, Lorenzo RD, et al. Persistent psychopathology and neurocognitive impairment in COVID-19 survivors: Effect of inflammatory biomarkers at three-month follow-up[J]. Brain Behav Immun. 2021;94. 10.1016/j.bbi.2021.02.021 . Mohr P, Rodriguez M, Bravermanov A, et al. Social and functional capacity of schizophrenia patients: A cross-sectional study[J]. Int J Soc Psychiatry. 2014;60. 10.1177/0020764013489673 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 10 Apr, 2026 Read the published version in BMC Research Notes → Version 1 posted Editorial decision: Revision requested 11 Dec, 2025 Reviews received at journal 07 Dec, 2025 Reviewers agreed at journal 04 Dec, 2025 Reviewers invited by journal 08 Oct, 2025 Editor assigned by journal 08 Oct, 2025 Editor invited by journal 06 Oct, 2025 Submission checks completed at journal 04 Oct, 2025 First submitted to journal 04 Oct, 2025 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-7715016","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":532355474,"identity":"7f79d170-b17d-4b47-8ced-6246710dc2f7","order_by":0,"name":"Jin Wang","email":"","orcid":"","institution":"First Central Hospital of Tianjin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jin","middleName":"","lastName":"Wang","suffix":""},{"id":532355475,"identity":"9e24fceb-abc2-4640-9705-300c04d21644","order_by":1,"name":"Jie Shen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYDACCRA2ABLMDIwPEipsSNPCbPDgTBqRWqCATfJh2yHCOuRnNx97YFFgw2BwnPdYRQLbAQb+9u4EvFoM7hxLN5AwSGMwOMyXdiOB5w6DxJmzG/Brkcgxk5AwOMwg2cxjdiNB4hlQJBe/FvkZ+d+AWv6DtRQkAPUS1MJwI4cNqAXoBWYeM4aEBCK0GNxIAzksGaiFL1ki4UAaD0G/yM9IfiYt8ceOgY3/7MGPP//ZyPG39xJwGBAwA+OmvoGBB8zhIagcBBg/kKB4FIyCUTAKRiAAALbNQAaLErmvAAAAAElFTkSuQmCC","orcid":"","institution":"Tianjin First Central Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jie","middleName":"","lastName":"Shen","suffix":""},{"id":532355476,"identity":"014da117-4fe5-4a4b-bc84-c7033c8eb4d2","order_by":2,"name":"Yu Pang","email":"","orcid":"","institution":"Tianjin Anding Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Pang","suffix":""},{"id":532355477,"identity":"c6ed8ee1-c3de-476b-ad82-b097357f8d6c","order_by":3,"name":"Jihui Liu","email":"","orcid":"","institution":"First Central Hospital of Tianjin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jihui","middleName":"","lastName":"Liu","suffix":""},{"id":532355478,"identity":"6d2d6b14-29ed-48d0-9f55-bf80a28f37e1","order_by":4,"name":"Lili Zhao","email":"","orcid":"","institution":"Tianjin First Hospital","correspondingAuthor":false,"prefix":"","firstName":"Lili","middleName":"","lastName":"Zhao","suffix":""},{"id":532355479,"identity":"ddb66b13-5e82-477c-b5da-06074075dfc6","order_by":5,"name":"Momo Sun","email":"","orcid":"","institution":"Tianjin First Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Momo","middleName":"","lastName":"Sun","suffix":""},{"id":532355480,"identity":"b7753029-a7b0-4ff8-8d07-73b317dd3841","order_by":6,"name":"Yang Yang","email":"","orcid":"","institution":"The Second Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2025-09-25 16:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7715016/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7715016/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13104-026-07746-1","type":"published","date":"2026-04-10T15:58:26+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":94049211,"identity":"df9db6ed-ab23-456f-9663-c6e4223c9049","added_by":"auto","created_at":"2025-10-21 23:30:17","extension":"doc","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":658735,"visible":true,"origin":"","legend":"","description":"","filename":"Revisiedmanuscript.doc","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/1bc44386c67b99ebf1e1d274.doc"},{"id":94049206,"identity":"63644151-e751-407d-b0b8-75a96ef12e56","added_by":"auto","created_at":"2025-10-21 23:30:17","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8436,"visible":true,"origin":"","legend":"","description":"","filename":"07286e3e34d049c5ad0e3b61a96eb4cd.json","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/876006c0fe3eb03a067c3734.json"},{"id":94049212,"identity":"db7138c7-135b-4c39-8af5-f1c23277bbd3","added_by":"auto","created_at":"2025-10-21 23:30:17","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":111030,"visible":true,"origin":"","legend":"","description":"","filename":"07286e3e34d049c5ad0e3b61a96eb4cd1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/1772cf8ed2e426f849038252.xml"},{"id":94050265,"identity":"d5305fdb-db21-4f5e-91f7-9eb7b65df233","added_by":"auto","created_at":"2025-10-21 23:46:17","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":91152,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/3017eb4d06a454e99c49c7b1.png"},{"id":94049440,"identity":"f93500df-d5e6-41c7-b448-9d773a527905","added_by":"auto","created_at":"2025-10-21 23:38:17","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":97235,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/94144a66467de4cb0cf67a92.png"},{"id":94049207,"identity":"1c56e678-3171-431e-83ec-e07d422c600f","added_by":"auto","created_at":"2025-10-21 23:30:17","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":58187,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/ba25b5ba08af8c4e9de12cad.png"},{"id":94049209,"identity":"6d3ec2d2-9a8e-400c-82c3-a75ba20407a6","added_by":"auto","created_at":"2025-10-21 23:30:17","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":112130,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/a020819e10df390c72604126.png"},{"id":94049215,"identity":"3f6e5aea-3d24-4135-ab66-6b5f03379cc3","added_by":"auto","created_at":"2025-10-21 23:30:17","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":30326,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/1f77545bf8ee3a30faeff9e1.png"},{"id":94049438,"identity":"f548dee3-2c94-4e2d-ad4f-c4947d20bf51","added_by":"auto","created_at":"2025-10-21 23:38:17","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":34771,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/00b02d78b72cd749b33c710a.png"},{"id":94049441,"identity":"890e9797-0913-4ec9-906e-09766e794992","added_by":"auto","created_at":"2025-10-21 23:38:17","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":19162,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/62ffc37388ec6abee1d0b2a9.png"},{"id":94049214,"identity":"e7d87f14-0532-4c5c-87bd-bdc43232d9a1","added_by":"auto","created_at":"2025-10-21 23:30:17","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":35547,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/9f9695d6874c69366d634f29.png"},{"id":94049217,"identity":"73e06492-3f2c-4728-89ab-61b534f82237","added_by":"auto","created_at":"2025-10-21 23:30:17","extension":"xml","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":108556,"visible":true,"origin":"","legend":"","description":"","filename":"07286e3e34d049c5ad0e3b61a96eb4cd1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/307484c81624e09a7ff062c7.xml"},{"id":94049442,"identity":"50c6d308-9335-4bfc-bd83-2e460ca7eae3","added_by":"auto","created_at":"2025-10-21 23:38:17","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":120325,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/2e589aed81d5b8734b62c6db.html"},{"id":94049202,"identity":"e645cd45-abc9-4243-b536-afbbd8aadab9","added_by":"auto","created_at":"2025-10-21 23:30:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":90902,"visible":true,"origin":"","legend":"\u003cp\u003eScatterplot for the associations between the PLT (a), the Evans index (b), the LYM (c), the PLR (d), the WMIN-AH-LV (e) and the PANSS positive score\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/b6d4288330e58e34bc42c643.png"},{"id":94049203,"identity":"9a132564-2604-4de7-b3d2-c52374568637","added_by":"auto","created_at":"2025-10-21 23:30:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":96604,"visible":true,"origin":"","legend":"\u003cp\u003eScatterplot for the associations between the SII (a), NLR (b), TD-B-CN (c), TVW (d) and the PANSS positive score\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/41a6a467de2f054111915616.png"},{"id":94049437,"identity":"52daa4b9-7cfd-4347-a9bf-fe1aac207c02","added_by":"auto","created_at":"2025-10-21 23:38:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":58237,"visible":true,"origin":"","legend":"\u003cp\u003eScatterplot for the associations among MW-AH-LV (a), WMIN-AH-LV (b) and total score\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/3fcca0e5f422a0c832fd56e1.png"},{"id":94049436,"identity":"06171b48-d10e-441b-bb5c-d4c125cf4171","added_by":"auto","created_at":"2025-10-21 23:38:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":111303,"visible":true,"origin":"","legend":"\u003cp\u003eScatterplot for the associations among the SII (a), NLR (b), TD-B-CN (c), WMIN-AH-LV (d), TVW (e), Evans index (f) and PAUSS\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/15188f603287b2b7dc056d7d.png"},{"id":106809213,"identity":"126837b5-f4f7-4e3a-a8cb-1515f0943ffe","added_by":"auto","created_at":"2026-04-13 16:08:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1303224,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7715016/v1/23af4681-3953-4a46-b932-29e90ccd1e74.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Associations of Inflammatory Biomarkers with Brain Atrophy and Clinical Scores in Schizophrenia Patients with Autistic Features","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSCZ is a complex condition characterized by psychotic symptoms, increased medical comorbidity, and reduced life expectancy\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Age-related degenerative disorders may contribute to SCZ onset in older adults by causing structural brain changes\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.Recent studies have shown that mental illnesses, brain structure abnormalities, and metabolic factors significantly influence patient outcomes in patients with SCZ\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eStudies indicate that a distinct subgroup of SCZ patients exhibit autistic features and unique clinical characteristics\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. This population shows significant social cognitive impairments, poorer functional outcomes, more severe psychiatric symptoms, lower well-being, and reduced responsiveness to antipsychotic therapies\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e.One study\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e confirmed increased ventricle volume in adults diagnosed with autism through long-term observation.While many studies have identified brain‒behavior links in SCZ \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e],\u003c/sup\u003e brain measurement ranges in this population remain understudied.However, the neurobiology of SCZ with autistic traits remains poorly understood and requires further investigation.\u003c/p\u003e\u003cp\u003eMoreover, increasing evidence suggests \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e that immune system activation plays a role in SCZ development and progression. Available data\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e indicate possible links between SCZ, inflammation, and neuroimmune genetic factors. Given the strong association between immunity and SCZ, a wide range of inflammatory markers have been used in research on this disorder.\u003c/p\u003e\u003cp\u003eThis study aimed to bridge the existing gap by presenting these advancements to clinicians in a novel way. We developed and used a simple linear measurement method designed to detect diffuse atrophy more quickly to assess BA parameters. The approach maintains sensitivity while avoiding time-consuming volumetric measurements. This study systematically examined the relationships between inflammatory markers and CT-measured BAs in SCZ patients with autistic traits to better understand how these factors are linked to clinical symptoms.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Subjects\u003c/h2\u003e\u003cp\u003eAs a cross-sectional study, a total of 113 SCZ patients (58 males and 55 females) were recruited from Tianjin Anding Hospital for a study conducted from September 2023 to January 2024.The age of the participants ranged from 19 to 82 years.\u003c/p\u003e\u003cp\u003eThe exclusion criteria were as follows: 1. Patients diagnosed with primary cranial disorders; 2. Pregnant or lactating women; 3. Patients who did not comply with the examination protocol; 4. Participants with conditions that affect inflammatory marker levels (e.g., infectious diseases, acute or chronic inflammation, allergies, malignancies) or who are receiving medications that alter hematological parameters (e.g., antibiotics, antivirals, antihistamines, immunosuppressants, and leukocyte-stimulating factors). Among the 126 screened individuals, 13 were excluded on the basis of predefined criteria: traumatic brain injury (n\u0026thinsp;=\u0026thinsp;3), pneumonia (n\u0026thinsp;=\u0026thinsp;2), burns (n\u0026thinsp;=\u0026thinsp;1), lymphoma (n\u0026thinsp;=\u0026thinsp;1), and failure to complete CT scanning (n\u0026thinsp;=\u0026thinsp;6). The final cohort comprised 113 eligible participants. An international panel consensus \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e defined age 60 years as the threshold distinguishing middle-aged SCZ patients from very-late-onset schizophrenia-like psychosis patients. Therefore, we classified individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years as old.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Clinical assessment\u003c/h2\u003e\u003cp\u003eClinical information, including age, sex, and illness duration, was recorded. We assessed SCZ symptoms via the PANSS, a 30-item scale scored from 1 to 7. This produces three subscales: positive symptoms, negative symptoms, and general psychopathology. The PANSS ranges from 30 to 210, with higher scores indicating greater symptom severity\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. The PANSS assessment was conducted by two psychiatrists who had no knowledge of the patients' inflammatory profiles or degree of BA.\u003c/p\u003e\u003cp\u003eThe five-factor model of Mohr's PANSS, encompassing positive, negative, cognitive, mood, and hostility domains, was utilized. The PAUSS \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e was applied to evaluate autistic traits and comprises three subscales measuring difficulties in social interaction (N1, N3, N4), communication skills (N5, N6), and repetitive behaviors (N7, G5, G15). The use of a cutoff score of 30 for identifying individuals with autism spectrum features has been recommended and validated in previous studies\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. These cutoff values were established and validated by scale developers through comprehensive psychometric analyses of large clinical samples\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 CT\u003c/h2\u003e\u003cp\u003eThe linear measurements were performed by two radiologists with over five years of experience who were blinded to the patients\u0026rsquo; clinical information. CT scans were conducted on all patients via a Philips Ingenuity Core 128-slice spiral CT machine. The slice thickness and spacing were both set at 5 mm, with the tube voltage and current set to 120 kV and 120 mA, respectively. The pitch ranged from 1.0 to 1.5 mm, and the scanning time was set to 5 seconds. The examination procedure was conducted as follows: the patient was positioned supine, with the auditory canthus line serving as the baseline for scanning. An upward continuous scan was performed to evaluate the brain sulci, ventricles, and tissue. The images were then sent to a workstation for 3D reconstruction via 3D volume, multiplanar, and surface reconstruction techniques.\u003c/p\u003e\u003cp\u003eThe measurement encompasses a wide range of parameters, including the maximum width of the anterior horn of the lateral ventricle (MW-AH-LV), WMIN-AH-LV, TVW, transverse diameter of the choroid plexus of the lateral ventricle (TD-ChP-LV), TD-B-CN, maximum external diameter (MAED) of the body of the LV, maximum external diameter of the cranium (MAED-Cr), maximum internal diameter of the cranium (MAID-Cr), Hackman value (MW-AH-LV\u0026thinsp;+\u0026thinsp;TD-B-CN), the ventricular index (TD-ChP-LV/MW-AH-LV), the LV body index (MAID-Cr/MAED of the body of the LV), the frontal horn index (FHI\u0026thinsp;=\u0026thinsp;MAID-Cr/MW-AH-LV), the Evans index (MW-AH-LV/MAID-Cr), the ventricular central\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Laboratory measurements\u003c/h2\u003e\u003cp\u003eMorning blood samples were collected from all patients via the peripheral vein. The complete blood count data were obtained close in time to the time of the CT examination. We used the provided formulas to calculate several ratios: the NLR, MLR, PLR, and SII. NLR\u0026thinsp;=\u0026thinsp;neutrophil count/lymphocyte count.\u003c/p\u003e\u003cp\u003eMLR\u0026thinsp;=\u0026thinsp;monocyte count/lymphocyte count.\u003c/p\u003e\u003cp\u003ePLR\u0026thinsp;=\u0026thinsp;platelet count/lymphocyte count.\u003c/p\u003e\u003cp\u003eSII\u0026thinsp;=\u0026thinsp;platelet count \u0026times; neutrophil count/lymphocyte count.\u003c/p\u003e\u003cp\u003eThe NLR, MLR, PLR, and SII were used to measure inflammation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistics\u003c/h2\u003e\u003cp\u003eStatistical analysis was conducted via SPSS 26.0. Data normality was assessed with the Kolmogorov‒Smirnov test. Normally distributed data are presented as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations (SDs), whereas nonnormally distributed data are reported as medians and interquartile ranges (IQRs). Differences between the male and female groups were analyzed via either the Mann‒Whitney U test or independent samples t test. Spearman's correlation was used to examine the relationships among inflammatory biomarkers, BA parameters, and PANSS scores. Multiple linear regression analysis was performed to evaluate the effects of inflammatory biomarkers and BA parameters on the scores. Statistical significance was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.\u003c/b\u003e1Comparative analysis of inflammatory biomarkers and BA parameters across sexes\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows significant sex differences in the NLR, positive symptom score, negative symptom score, total score, and PAUSS.\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\u003eComparative analysis of inflammatory biomarkers and BA parameters across sexes\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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\u003eMale (n\u0026thinsp;=\u0026thinsp;58)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFemale (n\u0026thinsp;=\u0026thinsp;55)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et/Z\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\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\u003ePLT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250.86\u0026plusmn;,63.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e253.93\u0026thinsp;\u0026plusmn;\u0026thinsp;66.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.804 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLYM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.955(1.73\u0026ndash;2.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.900(1.47\u0026ndash;2.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.254 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNEU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.905\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.059 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.77(2.83\u0026ndash;3.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.22(2.49\u0026ndash;4.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.039 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e122.67(101.16-148.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e130.46(106.04-158.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.212\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.225 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.25(0.19-148.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.21(0.16\u0026ndash;0.266)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.066 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSII\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e445.58(352.33-635.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e427.81(307.26-602.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.278 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive symptom score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34(31-37.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31(29\u0026ndash;32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-4.172\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative symptom score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31(28-36.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30(27\u0026ndash;32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.031 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeneral psychopathological symptoms score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68(65.75\u0026ndash;72.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68(66\u0026ndash;69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.517\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.159 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e134.91\u0026thinsp;\u0026plusmn;\u0026thinsp;15.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e127.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-3.308\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.001 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePAUSS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37.45\u0026thinsp;\u0026plusmn;\u0026thinsp;6.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35.24\u0026thinsp;\u0026plusmn;\u0026thinsp;3.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.276\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.025 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMW-AH-LV(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.609\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.01 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTD-B-CN(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.72\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u0026ndash;1.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.34(1.22\u0026ndash;1.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-4.657\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.01 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWMIN-AH-LV(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-4.458\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.01 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTVW,(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.69(0.58\u0026ndash;0.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.57(0.47\u0026ndash;0.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-3.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.002 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTD-ChP-LV(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-5.206\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.01 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMAED of body of LV(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.763\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.447 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMAED-Cr(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-5.299\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.01 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMAID-Cr(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-6.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.01 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHackman value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-4.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.01 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eventricular index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.174\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.243 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ethe ventricular central indexs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-2.834\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.005 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLV body index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.299 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFHI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.74(3.58\u0026ndash;3.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.75(3.58\u0026ndash;4.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.345\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.730 \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEvans index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.803 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e1\u003c/sup\u003e Independent samples t test\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e2\u003c/sup\u003e Mann‒Whitney U test\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe NLRs (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.039) and scale scores (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) of the male individuals were greater than those of their female counterparts. The parameters MW-AH-LV, WMIN-AH-LV, TD-ChP-LV, TD-B-CN, MAED-Cr, MAID-Cr and Hackman values (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), TVW values (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), and ventricular central indices (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005) were significantly different between the sexes. The degree of BA was found to be greater in males.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Comparative analysis of inflammatory biomarkers and BA parameters across age groups\u003c/h2\u003e\u003cp\u003eThe PLT levels were found to be lower in the age group over 60 as compared to those aged 60 or below,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028\u0026thinsp;\u0026lt;\u0026thinsp;0.05.Negative symptom score,Total score(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01),PAUSS(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003),the parameters WMIN-AH-LV,TVW,TD-ChP-LV,MAED of body of LV,Evans index, the ventricular central indexs(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01),MW-AH-LV(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004),MAID-Cr(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001),TD-B-CN(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001),Hackman value(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001),ventricular index(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028) ,FHI(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022).The difference in the aforementioned parameters was found to be statistically significant, with the older group exhibiting a higher BA parameters and higer negative symptom score, total score and PAUSS.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.3\u003c/b\u003e Correlation analysis of disease duration, inflammatory biomarkers, and BA parameters\u003c/h2\u003e\u003cp\u003eWith prolonged disease duration, the total score (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013), general psychopathological symptoms score (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), PAUSS, and the parameters MW-AH-LV, TD-B-CN, TVW, TD-ChP-LV, MAED-Cr, the ventricular index, and the LV body index (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were significantly positively correlated, as indicated in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation analysis of age, disease duration, inflammatory biomarkers, and BA parameters\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003edisease duration\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.333,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLYM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.148,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.118\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNEU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.197,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.126,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.184\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.134,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.159\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.145,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.124\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSII\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.172,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.068\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive symptom score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.083,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.601\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative symptom score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.137,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.148\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeneral psychopathological symptoms score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.526,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.232,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePAUSS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.360,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMW-AH-LV(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.467,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTD-B-CN(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.409,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWMIN-AH-LV(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.354,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTVW,(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.799,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTD-ChP-LV(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.406,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMAED of body of LV(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.115,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.227\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMAED-Cr(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.360,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMAID-Cr(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.155,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.101\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHackman value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.278,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eventricular index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.345,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ethe ventricular central indexs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.08,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.402\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLV body index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u0026thinsp;=\u0026thinsp;0.531,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFHI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.427,\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEvans index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er = -0.295,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001\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\u003eThe symptoms of autism in the PAUSS worsened significantly as the disease progressed (r\u0026thinsp;=\u0026thinsp;0.360, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).However, there was a negative correlation between the PLT (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), NEU (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036), Hackman value (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), FHI (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and Evans index (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and disease progression. The levels of inflammatory biomarkers were lower in patients with a longer duration of disease, whereas parameters associated with dilation of the LV and third ventricles were greater (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.4\u003c/b\u003e Correlation analysis of inflammatory biomarkers with the PANSS or PAUSS\u003c/h2\u003e\u003cp\u003eThe negative symptom score was positively correlated with inflammatory biomarkers. Furthermore, the negative symptom score was positively associated with the MLR (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.026) but negatively associated with the PLT (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006) and LYM (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049). The PAUSS score was negatively correlated with the PLT (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.5\u003c/b\u003e Correlation analysis of BA parameters and PANSS or PAUSS scores\u003c/h2\u003e\u003cp\u003eThe positive symptom score was positively correlated with the parameters WMIN-AH-LV (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), TD-ChP-LV (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008), the ventricular index (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.047), and the ventricular central index (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). The negative symptom score was positively correlated with the parameters TD-B-CN, WMIN-AH-LV, TVW, ventricular central index (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), TD-ChP-LV (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.027), and Hackman value (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eThe general psychopathological symptom score was positively correlated with the ventricular index (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), FHI (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02), and Evans index (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.035). The total score was positively correlated with TD-B-CN (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), WMIN-AH-LV (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), TVW (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), TD-ChP-LV (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008), the ventricular index (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013), and the ventricular central indices (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). The PAUSS score was positively correlated with TD-B-CN (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), WMIN-AH-LV (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), TVW (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), TD-ChP-LV (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012), Hackman (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019), and ventricular central indices (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e3.6\u003c/b\u003e The combination of BA parameters and inflammatory biomarkers accurately predicted the PANSS and PAUSS scores.\u003c/h2\u003e\u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the dependent variable was the positive symptom score. Independent variables for the multiple linear regression analysis included age, sex, BA parameters, and inflammatory biomarkers. The backward method was used. The results revealed a significant negative correlation between positive scores and both the PLT (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) and the Evans index (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that higher values of these variables were linked to lower positive scores. Additionally, there was a positive association between positive scores and LYM (c) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049), PLR (d) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009), and WMIN-AH-LV (e) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting that elevated levels of these factors corresponded to higher positive scores. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\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\u003eMultiple regression analysis of positive symptom scores\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\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\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eVIF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e32.428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.281\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-3.097\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.913\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLYM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.860\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.995\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.514\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.659\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6.793\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWMIN-AH-LV(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11.446\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.770\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.467\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.766\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEvans index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-59.733\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15.688\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-3.808\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.203\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\u003eThe dependent variable was the negative symptom score, while the independent variables remained unchanged. The backward method was adopted. The results indicated that as the SII (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004) (a) increased, negative symptoms decreased. Additionally, as the NLR (b) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), TD-B-CN (c) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024), and TVW(d) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022) increased, negative symptoms increased. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe dependent variable was the general psychopathological symptoms score, whereas the independent variables remained unchanged. The backward method was adopted. The results indicated that as the MW-AH-LV (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) increased, the ventricular central indices (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009) increased, and the general psychopathological symptom score decreased. Additionally, as WMIN-AH-LV (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) increased, the general psychopathological symptom score increased.\u003c/p\u003e\u003cp\u003eThe dependent variable was the total score, whereas the independent variables remained unchanged. The backward method was adopted. The results indicated that as the PLT (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.039), MW-AH-LV(a) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and ventricular central indices (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009) increased, the total score decreased. Additionally, as WMIN-AH-LV(b) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) increased, the total score increased. (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe dependent variable was PAUSS, whereas the independent variables remained unchanged. The backward method was adopted. The results indicated that as the SII(a) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017) and the MW-AH-LV ratio (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009) increased, the ventricular central indices increased, and the PAUSS decreased. Additionally, as the NLR (b) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02), TD-B-CN(c) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.045), WMIN-AH-LV(d) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028), TVW(e), (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011), and Evans index (f) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016) increased, the PAUSS increased. (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eCompared with magnetic resonance imaging (MRI), brain measurements from CT scans are significantly correlated with clinical outcomes in patients with SCZ, despite the lower spatial resolution of CT. A previous study \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e revealed that CT has superior data accessibility, especially for large-scale clinical studies. It also offers shorter scan times and greater patient convenience \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. For patients without focal neurological symptoms, routine structural neuroimaging may not be necessary. When imaging is needed, CT has comparable diagnostic efficacy to MRI and is suitable as a first-line modality \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eVentricular expansion is well documented in SCZ patients. It was first observed in an influential CT study by Johnstone et al.\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Further meta-analyses \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e have confirmed significant enlargements in the LV and third ventricle, with medium to large effect sizes. Similar findings \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e have also been reported in the LV of individuals at greater risk for psychosis.\u003c/p\u003e\u003cp\u003eThis study revealed a significant correlation between BA parameters and clinical symptom scores, especially those involving the LV, third ventricle, and caudate nucleus. Both WMIN-AH-LV and TVW strongly influenced all the scores. These results are consistent with previous findings. This study also confirmed a strong link between SCZ and PAUSS with the LV, third ventricle, and caudate nucleus.\u003c/p\u003e\u003cp\u003eOne study \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e revealed a temporal association between ventricular expansion and gradual gray matter loss. Those over 60 years of age with longer disease durations presented elevated BA parameters, indicating greater cerebral shrinkage. Studies \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e suggest that antipsychotic use and illness duration may affect both white and gray matter volumes.\u003c/p\u003e\u003cp\u003eA significant association between negative symptoms and BA was found in the LV, caudate nucleus, and ChP. Previous studies have linked ventriculomegaly in individuals with SCZ to negative symptoms and cognitive impairments. Furthermore, patients experiencing global cognitive impairment tend to exhibit more pronounced ventricular enlargement than those who have preserved cognition\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn first-episode psychosis (FEP) patients, lateral and third ventricle sizes are correlated with negative symptom severity \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Periventricular diencephalic structures influence neuropsychological performance, especially through third ventricle volume. In FEP patients, negative symptoms and a higher total PANSS score at follow-up are linked to cognitive impairment \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe correlations between the negative symptom score, PAUSS score, and BA parameters remained consistent. The PAUSS is positively linked to the caudate nucleus, LV, ChP, and third ventricle. The NLR also showed significant correlations in the regression analyses.\u003c/p\u003e\u003cp\u003eOne study \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e suggested a link between hypothalamic atrophy and third ventricle enlargement in individuals with ASD. The hypothalamus may atrophy, and the third ventricle may enlarge due to its anatomical proximity. Oxytocin (OXT), a neuropeptide associated with social behavior, is produced in the hypothalamus. We hypothesize that a reduced hypothalamic volume and an enlarged third ventricle are associated with ASD, reflecting their anatomical relationship.\u003c/p\u003e\u003cp\u003eThis study revealed a positive correlation between the transverse diameter of the ChP in the LV and the positive symptom score, negative symptom score, total score, and PAUSS score in patients. Previous studies \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e have suggested that the observed BA enlargement in individuals with SCZ may be related to ChP abnormalities and their physiological functions. Enlarged ChP volume in psychosis has been associated with poorer cognitive function, localized BA, and increased ventricular size \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Postmortem studies \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e in SCZ patients have revealed structural changes in the ChP, including cellular fat accumulation, increased epithelial secretion, and large cystic formations. These changes may be linked to chronic neuroinflammation. Studies \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e suggest that sex hormones affect ChP function, influencing CSF production and composition, blood\u0026ndash;CSF barrier integrity, and immune monitoring. Estrogens have anti-inflammatory properties and can modulate neurotransmission. The sex differences in ChP volume may stem from hormonal variations, which could also explain the observed sex differences in BA parameters in this study.\u003c/p\u003e\u003cp\u003eThe transverse diameter of the bilateral caudate nucleus was positively correlated with the negative symptom score, PAUSS score, and total score. It was significantly related to the negative symptom score and PAUSS score and was therefore included in the regression model.\u003c/p\u003e\u003cp\u003eNumerous \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e studies have consistently shown a link between various bacterial and viral infections and the occurrence of mental disorders. Elevated levels of diverse autoimmune antibodies have been detected in individuals diagnosed with SCZ\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. SCZ patients have abnormal C-reactive protein levels, decreased lymphocytes, and elevated NEU, NLR and MLR.\u003c/p\u003e\u003cp\u003eIn this study, the negative symptom score was positively correlated with the number of mononuclear cells and the MLR and negatively correlated with the PLT and LYM. These results align with previous findings. Higher LYM and PLR levels were linked to higher positive symptom scores in the regression model. A high NLR was associated with increased negative symptom scores and PAUSS scores. These findings further support that inflammatory biomarkers differentially affect SCZ patients with autistic features. Several studies have reported significantly elevated NLR, PLR, and MLR \u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSII, a marker of inflammation that has garnered considerable interest in recent years, has been widely applied in the fields of cancer research, rheumatism studies, and investigations on immunity\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. The SII, along with the negative symptom score and PAUSS score, was included in the study\u0026rsquo;s multiple regression model. However, higher SII values were associated with lower symptom scores. A cross-sectional study \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e confirmed associations between the NLR, MLR, PLR, SII, and PANSS scores. All the inflammatory markers correlated with the total, positive, negative, and general psychopathology scores. After adjusting for confounders, the NLR remained significantly linked to all clinical outcomes. The SII was the only marker predicting both overall PANSS and general psychopathology scores in SCZ patients.\u003c/p\u003e\u003cp\u003eLimitations\u003c/p\u003e\u003cp\u003eThe inflammatory markers we obtained have certain limitations. The reasons for this might be due to the infection control measures during treatment and restricted blood sample collection due to timing and seasonal factors. Future research will aim to address these issues. As a cross-sectional study, our findings cannot establish causality. Longitudinal studies are needed to track inflammatory markers and cognitive changes over time. Additionally, the study lacked functional MRI comparisons and was limited by a small sample size, both of which will be improved in future research.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, inflammatory biomarker levels and brain atrophy correlate positively with PANSS or PAUSS scores in SCZ patients with autistic features. These easily obtainable parameters help clinicians better understand this subgroup\u0026rsquo;s manifestations in a more objective and precise way.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSCZ schizophrenia\u003c/p\u003e\n\u003cp\u003eBA brain atrophy\u003c/p\u003e\n\u003cp\u003eCT computed tomography\u003c/p\u003e\n\u003cp\u003eNLR: lymphocyte ratio\u003c/p\u003e\n\u003cp\u003eMLR monocyte-to-lymphocyte ratio\u003c/p\u003e\n\u003cp\u003ePLR platelet-to-lymphocyte ratio\u003c/p\u003e\n\u003cp\u003eSII systemic inflammation index\u003c/p\u003e\n\u003cp\u003ePositive and Negative Syndrome Scale (PANSS)\u003c/p\u003e\n\u003cp\u003ePAUSS PANSS Autism Severity Score\u003c/p\u003e\n\u003cp\u003eLYM lymphocyte\u003c/p\u003e\n\u003cp\u003eWMIN-AH-LV minimum width of the anterior horn of the lateral ventricle\u003c/p\u003e\n\u003cp\u003eTD-B-CN transverse diameter of the bilateral caudate nucleus\u003c/p\u003e\n\u003cp\u003eTVW Third Ventricle width\u003c/p\u003e\n\u003cp\u003eMRI magnetic resonance imaging\u003c/p\u003e\n\u003cp\u003eMW-AH-LV maximum width of the anterior horn of the lateral ventricle\u003c/p\u003e\n\u003cp\u003eTD-ChP-LV transverse diameter of the choroid plexus of the lateral ventricle\u003c/p\u003e\n\u003cp\u003eMAED maximum external diameter\u003c/p\u003e\n\u003cp\u003eMAED-Cr maximum external diameter of cranium\u003c/p\u003e\n\u003cp\u003eMAID-Cr maximum internal diameter of cranium\u003c/p\u003e\n\u003cp\u003eSD standard deviation\u003c/p\u003e\n\u003cp\u003eIQR interquartile range\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures adhered to the principles outlined in the Declaration of Helsinki.This study was approved by the Tianjin Anding Hospital Ethics Committee (2024-31) and written informed consent was obtained from all participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided written consent prior to their inclusion in the research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll patient data have been de-identified to protect patient privacy. Therefore, formal consent for publication was not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe clinical data supporting the findings of this study are not publicly available due to patient privacy concerns but can be made available by the corresponding author after signing a data use agreement and with the permission of the institutional ethics committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding from studies on nuclide nanoprobes with aggregation-induced luminescence properties in the integration of the diagnosis and treatment of atherosclerotic vulnerable plaques in rabbits (21JCYBJC01060) and the study of PET/CT-based radiomics to predict the pathological characteristics and prognosis of primary liver cancer (TJWJ2021MS013).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to the nurses and staff of the Department of \u0026nbsp;General Psychiatry, Tianjin Anding Hospital for their support in patient recruitment.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLysaker PH, Yanos PT, Outcalt J, et al. Association of stigma, self-esteem, and symptoms with concurrent and prospective assessment of social anxiety in schizophrenia. [J]. Clin Schizophr Relat Psychos. 2010;4(1):41DOI. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3371/CSRP.4.1.3\u003c/span\u003e\u003cspan address=\"10.3371/CSRP.4.1.3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVerdolini, Norma, et al. Obstetric complications and clinical presentation in first episode of psychosis. Acta neuropsychiatrica. 2023;35:3.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAna Costas Carrera,Clemente Garcia-Rizo,Byron Bitanihirwe \u0026amp; Rafael Penad\u0026eacute;s. (2020). Obstetric Complications and Brain Imaging in Schizophrenia: A Systematic Review. Biol Psychiatry: Cogn Neurosci Neuroimaging,5(12).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNibbio, Gabriele, et al. Assessment and correlates of autistic symptoms in schizophrenia spectrum disorders measured with the PANSS Autism Severity Score: A systematic review. Front Psychiatry. 2022;13:934005\u0026ndash;934005.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrigge Molly BD et al. A 16-year study of longitudinal volumetric brain development in males with autism. NeuroImage 236. (2021):118067\u0026ndash;118067.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVita Antonio et al. Influence of autistic symptoms on social and nonsocial cognition and real-life functioning in people with schizophrenia: evidence from the Italian Network for Research on Psychoses multicenter study. Eur psychiatry: J Association Eur Psychiatrists 63.1(2020):21\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKuo SS, Pogue-Geile FM. .Variation in Fourteen Brain Structure Volumes in Schizophrenia: A Comprehensive Meta-Analysis of 246 Studies[J].Neuroscience and Biobehavioral Reviews,2018,9885-94.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu, Xiaoyu et al. Changes in Inflammatory Biomarkers in Patients with Schizophrenia: A 3-Year Retrospective Study.Neuropsychiatric disease and treatment 19.(2023):1597\u0026ndash;604.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRebecca Birnbaum, Daniel R. Weinberger.A Genetics Perspective on the Role of the (Neuro)Immune System in Schizophrenia.Schizophrenia Research 217.(2020):105\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHoward. Late-onset schizophrenia and very-late-onset schizophrenia-like psychosis: An International Consensus[J]. Am J Psychiatry. 2000;157(2):172\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1176/appi.ajp.157.2.172\u003c/span\u003e\u003cspan address=\"10.1176/appi.ajp.157.2.172\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePina-Camacho L, Boada L, ,D\u0026iacute;az-Caneja MC et al. The Positive and Negative Syndrome Scale for Schizophrenia Autism Severity Scale (PAUSS) in young people with autism and schizophrenia[J].Revista de psiquiatr\u0026iacute;a y salud mental (Barcelona),2020,13(3):118\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePeng P, Wang Q. Autistic features in Chinese patients with chronic schizophrenia: Prevalence, clinical characteristics, and relationship with cognitive impairment[J]. Asian J psychiatry, 87:1036972025\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e-07-06].DOI:10.1016/j.ajp.2023.103697\u003c/span\u003e\u003cspan address=\"-07-06].DOI:10.1016/j.ajp.2023.103697\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi W, Liu Y, ,Tao R, et al. Association of insomnia with suicide attempts in Chinese chronic schizophrenia patients with and without autistic symptoms[J]. BMC Psychiatry. 2025;25(1):604\u0026ndash;604.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eK\u0026auml;stner A, et al. Autism beyond diagnostic categories: characterization of autistic phenotypes in schizophrenia. BMC Psychiatry. 2015;15(1):115.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEsra B, Sema P, Mahmut T, et al. Investigation of Skull Cortical Thickness Changes in Healthy Population and Patients With Schizophrenia on Computed Tomography Images[J]. J Craniofac Surg. 2024;435DOI. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/SCS.0000000000010261\u003c/span\u003e\u003cspan address=\"10.1097/SCS.0000000000010261\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYue JK, Upadhyayula PS, Avalos LN, et al. Concussion and Mild-Traumatic Brain Injury in Rural Settings: Epidemiology and Specific Health Care Considerations[J]. J Neurosciences Rural Pract. 2020;11(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1055/s-0039-3402581\u003c/span\u003e\u003cspan address=\"10.1055/s-0039-3402581\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhandanpour N, Hoggard N, Connolly DJA. The role of MRI and CT of the brain in first episodes of psychosis.[J].Clinical Radiology, 2013, 68(3):245\u0026ndash;50.\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.crad.2012.07.010\u003c/span\u003e\u003cspan address=\"10.1016/j.crad.2012.07.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJohnstone E, Frith CD, Crow TJ, .CEREBRAL VENTRICULAR SIZE AND COGNITIVE IMPAIRMENT IN CHRONIC SCHIZOPHRENIA[J]. 1976, 308(7992):924\u0026ndash;6.\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/s0140-6736(76)90890-4\u003c/span\u003e\u003cspan address=\"10.1016/s0140-6736(76)90890-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKuo SS, Pogue-Geile FM. .Variation in Fourteen Brain Structure Volumes in Schizophrenia: A Comprehensive Meta-Analysis of 246 Studies[J].Neuroscience and Biobehavioral Reviews,2018,9885-94.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDaiki S, Yoichiro T, ,Tsutomu T et al. Subcortical Brain Volume Abnormalities in Individuals With an At-risk Mental State.[J].Schizophrenia bulletin,2020,46(4):834\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChung Y, Haut MK, ,He G et al. Ventricular enlargement and progressive reduction of cortical gray matter are linked in prodromal youth who develop psychosis[J].Schizophrenia Research,2017,189169-174.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQiyong G, Su L, A J S.. A Selective Review of Cerebral Abnormalities in Patients With First-Episode Schizophrenia Before and After Treatment.[J].The American journal of psychiatry,2016,173(3):232\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMezquida, Gisela et al. Identifying risk factors for predominant negative symptoms from early stages in schizophrenia: A longitudinal and sex-specific study in first-episode schizophrenia patients. Revista de psiquiatria y salud mental (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIsabel V, Stefania T, ,Paolo F et al. Episodic memory dysfunction in individuals at high-risk of psychosis: a systematic review of neuropsychological and neurofunctional studies. [J]. Current pharmaceutical design,2012,18(4):443\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eH F W,Guillaume A, ,Christine D et al. Focal atrophy of the hypothalamus associated with third ventricle enlargement in autism spectrum disorder. [J] Neuroreport 2015,26(17):1017\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUvn\u0026auml;s-Moberg K. Oxytocin may mediate the benefits of positive social interaction and emotions. Psychoneuroendocrinology. 1998;23:819\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLizano P, Lutz O, Ling G, et al. Association of Choroid Plexus Enlargement With Cognitive, Inflammatory, and Structural Phenotypes Across the Psychosis Spectrum[J]. Am J Psychiatry. 2019;176(7):appiajp201918070825. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1176/appi.ajp.2019.18070825\u003c/span\u003e\u003cspan address=\"10.1176/appi.ajp.2019.18070825\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZeng, Jiaxin et al. Choroid plexus volume enlargement in first-episode antipsychotic-na\u0026iuml;ve schizophrenia.Schizophrenia (Heidelberg, Germany) 10.1(2024):1\u0026ndash;1.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSantos RC, Duarte CA, ,Quintela T et al. The choroid plexus as a sex hormone target: Functional implications[J].Frontiers in Neuroendocrinology,2017,44103-121.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Erp T G M,Hibar D P,Rasmussen J M,Glahn D C,Pearlson G D,Andreassen O A\u0026hellip; van Haren N E M.(2016).Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium.Molecular psychiatry,21(4),585.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e\u0026Ouml;zdin S. B\u0026ouml;ke \u0026Ouml;. Neutrophil/lymphocyte, platelet/lymphocyte and monocyte/lymphocyte ratios in different stages of schizophrenia[J].Psychiatry Research,2019,271131-135.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMazza MG, Lucchi S, Rossetti A et al. Neutrophil-lymphocyte ratio, monocyte-lymphocyte ratio and platelet-lymphocyte ratio in nonaffective psychosis: A meta-analysis and systematic review[J]. World J Biol Psychiatry, 2019:1\u0026ndash;37.\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/15622975.2019.1583371\u003c/span\u003e\u003cspan address=\"10.1080/15622975.2019.1583371\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFois AG, Paliogiannis P, Scano V et al. The Systemic Inflammation Index on Admission Predicts In-Hospital Mortality in COVID-19 Patients[J].Molecules, 2020, 25(23):5725.\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/molecules25235725\u003c/span\u003e\u003cspan address=\"10.3390/molecules25235725\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGennaro MM, Mariagrazia P, Lorenzo RD, et al. Persistent psychopathology and neurocognitive impairment in COVID-19 survivors: Effect of inflammatory biomarkers at three-month follow-up[J]. Brain Behav Immun. 2021;94. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.bbi.2021.02.021\u003c/span\u003e\u003cspan address=\"10.1016/j.bbi.2021.02.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMohr P, Rodriguez M, Bravermanov A, et al. Social and functional capacity of schizophrenia patients: A cross-sectional study[J]. Int J Soc Psychiatry. 2014;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/0020764013489673\u003c/span\u003e\u003cspan address=\"10.1177/0020764013489673\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Schizophrenia, Brain atrophy, Ventricle enlargement, Autism","lastPublishedDoi":"10.21203/rs.3.rs-7715016/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7715016/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e: This study explored the schizophrenia (SCZ) patients with autistic traits by analyzing inflammatory biomarkers and brain atrophy (BA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: The statistical analysis included 58 males and 55 females. All the subjects underwent computed tomography (CT) and laboratory analysis. SCZ symptom was assessed via the Positive and Negative Syndrome Scale (PANSS). The PANSS Autism Severity Score (PAUSS) was used to assess autistic traits, with a threshold of 30 to identify relevant characteristics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Multiple regression analysis revealed significant associations between\u003cstrong\u003e \u003c/strong\u003epositive scores and lymphocyte count (LYM) ,platelet-to-lymphocyte ratio (PLR) , and the minimum width of the anterior horn of the lateral ventricle (WMIN-AH-LV) (\u003cem\u003eP \u003c/em\u003e\u0026lt;0.05). Negative symptom scores were positively correlated with\u003cstrong\u003e \u003c/strong\u003ethe\u003cstrong\u003e \u003c/strong\u003eNLR, transverse diameter of the bilateral caudate nucleus (TD-B-CN) , and third ventricle width(TVW) (\u003cem\u003eP \u003c/em\u003e\u0026lt;0.05). As the WMIN-AH-LV (\u003cem\u003eP\u003c/em\u003e=0.001) increased, the general psychopathological symptom score increased. As the ventricular central indices, the WMIN-AH-LV increased, the total score increased (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05) . As the NLR, TD-B-CN, WMIN-AH-LV, TVW and the Evans index increased, the PAUSS increased (\u003cem\u003eP \u003c/em\u003e\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003eInflammatory biomarker and BA correlate positively with PANSS or PAUSS in SCZ with autistic features. These easily obtainable parameters help clinicians better understand this subgroup in a more objective way.\u003c/p\u003e","manuscriptTitle":"Associations of Inflammatory Biomarkers with Brain Atrophy and Clinical Scores in Schizophrenia Patients with Autistic Features","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 23:30:13","doi":"10.21203/rs.3.rs-7715016/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-11T19:33:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-07T11:54:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214322197750197268214975206523070137465","date":"2025-12-04T23:59:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-08T15:39:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-08T15:36:34+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-06T15:30:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-04T17:13:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Research Notes","date":"2025-10-04T13:42:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1953e8b9-904a-46b5-9e05-8b11792aea43","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T16:05:09+00:00","versionOfRecord":{"articleIdentity":"rs-7715016","link":"https://doi.org/10.1186/s13104-026-07746-1","journal":{"identity":"bmc-research-notes","isVorOnly":false,"title":"BMC Research Notes"},"publishedOn":"2026-04-10 15:58:26","publishedOnDateReadable":"April 10th, 2026"},"versionCreatedAt":"2025-10-21 23:30:13","video":"","vorDoi":"10.1186/s13104-026-07746-1","vorDoiUrl":"https://doi.org/10.1186/s13104-026-07746-1","workflowStages":[]},"version":"v1","identity":"rs-7715016","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7715016","identity":"rs-7715016","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}