Abstract
Objectives
This study explored the schizophrenia patients with autistic traits by analyzing clinical characteristics, inflammatory biomarkers and brain atrophy.
Results
Multiple regression analysis indicated significant associations. Positive symptom scores were linked to higher platelet count, elevated platelet-to-lymphocyte ratio, greater minimum width of the anterior horn of the lateral ventricle, higher Evans index, and male sex. Negative symptom scores correlated positively with older age, higher body mass index, wider third ventricle, higher neutrophil-to-lymphocyte ratio, and male sex. General psychopathology scores rose with older age and greater minimum ventricular width, as did total the Positive and Negative Syndrome Scale (PANSS) scores. The PANSS Autism Severity Score increased with higher neutrophil-to-lymphocyte ratio, greater ventricular widths (minimum anterior horn and third ventricle), older age, larger maximum external cranial diameter, and higher Evans index.
Keywords: Schizophrenia, Brain atrophy, Ventricle enlargement, Autism, PAUSS
Introduction
Schizophrenia (SCZ) is a complex disorder marked by psychosis, high comorbidity, and shortened lifespan [1]. Age-related brain changes may contribute to late-onset SCZ [2], while mental illness, brain structure, and metabolism critically shape outcomes [3].
A distinct SCZ subgroup presents with autistic features, exhibiting worse social cognition, functioning, symptom severity, well-being, and treatment response [4, 5]. Although enlarged ventricles are reported in autism [6] and brain-behavior links are established in SCZ [7].
Additionally, immune activation is implicated in SCZ pathogenesis [8], with inflammation and neuroimmune genetics being active research areas [9]. This study therefore aimed to systematically examine the relationships among clinical characteristics, peripheral inflammatory markers, and computed tomography (CT)-based brain atrophy (BA) measures in SCZ patients with autistic traits, and to assess their combined association with clinical severity.
Materials and methods
Subjects
This cross-sectional study enrolled 113 SCZ patients (58 males, 55 females; aged 19–82 years) from Tianjin Anding Hospital between September 2023 and January 2024. Exclusion criteria included primary cranial disorders, pregnancy/lactation, non-compliance, and conditions or medications affecting inflammatory markers. Of 126 screened, 13 were excluded (traumatic brain injury = 3, pneumonia = 2, burns = 1, lymphoma = 1, incomplete CT = 6). Following an international consensus [10], participants aged ≥ 60 years were classified as older adults.
Clinical assessment
Clinical and demographic data (age, sex, illness duration, education, marital status, age of onset, smoking, lifetime suicide attempts, antipsychotic dose in chlorpromazine equivalents, and Body Mass Index (BMI)) were recorded. Symptoms were assessed by two blinded psychiatrists using the 30-item PANSS (score range 30–210, higher scores indicate greater severity) [11, 12], which includes positive, negative, and general psychopathology subscales based on Mohr’s five-factor model. Autistic traits were evaluated with the PANSS Autism Severity Score (PAUSS) [6]. It comprises three subscales measuring difficulties in social interaction (PANSS items N1, N3, N4), communication skills (items N5, N6), and repetitive behaviors (items N7, G5, G15). A cutoff score of 30, as recommended in previous studies [13–15], was used to define clinically relevant autistic features.
CT
Two blinded radiologists (> 5 years’ experience) performed all linear measurements. CT scans were acquired on a Philips Ingenuity Core 128-slice scanner with the following parameters: slice thickness/spacing 5 mm, tube voltage/current 120 kV/120 mA, pitch 1.0–1.5 mm, scan time 5 s. Patients were positioned supine, and scanning proceeded upward from the auditory canthus line. Images were reconstructed using CT Viewer (volume, multiplanar, and surface rendering).
The measured parameters included: the maximum width of the anterior horn of the lateral ventricle (MW-AH-LV), the minimum width of the anterior horn of the lateral ventricle (WMIN-AH-LV), third ventricle width (TVW), transverse diameter of the choroid plexus of the lateral ventricle (TD-ChP-LV), transverse diameter of the bilateral caudate nucleus (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), ventricular index (TD-ChP-LV/MW-AH-LV), LV body index (MAID-Cr/MAED of the body of the LV), frontal horn index (FHI = MAID-Cr/MW-AH-LV), Evans index (MW-AH-LV/MAID-Cr), and ventricular central index (WMIN-AH-LV/MAID-Cr).
Laboratory measurements
Morning peripheral venous blood was collected proximate to CT examination. Complete blood count data were used to calculate the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII).
NLR = neutrophil count (NEU)/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.
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). Group comparisons were performed using independent samples t-test (normal continuous data), Mann-Whitney U test (non-normal continuous data), or Chi-square test (categorical data), as appropriate. Spearman’s correlation was used to examine the relationships among clinical characteristics, inflammatory biomarkers, BA parameters, and PANSS scores. Multiple linear regression analysis was performed using the backward stepwise method to evaluate the effects of inflammatory biomarkers and BA parameters on the scores. Statistical significance was set at P < 0.05.
Results
Comparative analysis of clinical characteristics, inflammatory biomarkers and BA parameters across sexes
Table 1 reveals significant sex differences. Males exhibited higher education levels (P < 0.001), smoking rates (P < 0.01), and suicide attempts (P = 0.037), whereas females received greater psychotropic medication (P = 0.009). Males also showed elevated NLR (P = 0.039), PANSS positive, negative, total scores, and PAUSS (all P < 0.05), along with larger brain atrophy parameters including MW-AH-LV, WMIN-AH-LV, TD-ChP-LV, TD-B-CN, MAED-Cr, MAID-Cr, Hackman values (all P < 0.01), TVW (P = 0.002), and ventricular central indices (P = 0.005), indicating more pronounced BA in males.
Table 1.
Comparative analysis of Clinical Features, inflammatory biomarkers and BA parameters across sexes
| Variable | Male (n = 58) | Female (n = 55) | t/Z/χ2 | P |
|---|---|---|---|---|
| Age | 48.24 ± 13.97 | 53.04 ± 15.81 | 1.711 | 0.0901 |
| Onset of the scz | 18.00 (10.75-31.00) | 26.50 (12.00–38.00) | − 1.270 | 0.2042 |
| Education years | 6 (6–9) | 6 (0–6) | − 3.864 | <0.0012 |
| Onset age of SCZ | 24.00 ( 20.75–30.25) | 26.00 (20.75-31.00) | − 0.242 | 0.8092 |
| History of lifetime suicidal attempts | 3.00 (1.00-5.25) | 2.00 (1.00–4.00) | − 2.091 | 0.0372 |
| Antipsychotic dosages | 344 (200–550) | 500 (300–700) | − 2.608 | 0.0092 |
| Marital status | ||||
| Unmarried | 28 (48.3%) | 17 (30.9%) | 3.553 | 0.0833 |
| Married | 30 (51.7%) | 38 (69.1%) | ||
| Smoking status | ||||
| Yes | 48 (82.8%) | 6 (10.9%) | 58.408 | <0.0013 |
| No | 10 (17.2%) | 49 (89.1%) | ||
| BMI | 24.01 (21.91–27.39) | 24.31 (21.20–29.00) | − 0.261 | 0.794 2 |
| 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 |
1Independent samples t test
2Mann‒Whitney U test
3Chi-square test
Data are presented as median (interquartile range, IQR) for non-normally distributed continuous variables, mean ± standard deviation, SD for normally distributed continuous variables, and number (%) for categorical variables. IQR Interquartile range; SD Standard deviation. BA Brain atrophy; SCZ Schizophrenia; BMI Body mass index; PLT Platelet count; LYM Lymphocyte count; NEU Neutrophil count; NLR NEU/LYM; PLR PLT/LYM; MLR Monocyte count/LYM; SII PLT ×NEU/LYM; PANSS Positive and Negative Syndrome Scale; PAUSS PANSS Autism Severity Score; MW-AH-LV Maximum width of the anterior horn of the lateral ventricle; TD-B-CN Transverse diameter of the bilateral caudate nucleus; WMIN-AH-LV Minimum width of the anterior horn of the lateral ventricle; TVW Third ventricle width; TD-ChP-LV Transverse diameter of the choroid plexus of the lateral ventricle; MAED Maximum external diameter; MAED-Cr Maximum external diameter of cranium; 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 indexs=WMIN-AH-LV/MAID-Cr
Comparative analysis of inflammatory biomarkers and BA parameters across age groups
PLT was lower in patients over 60 (P = 0.028). The older group showed higher negative symptom, total PANSS, and PAUSS scores (P < 0.01), along with greater BA parameters: WMIN-AH-LV, TVW, TD-ChP-LV, MAED of LV body, Evans index, ventricular central index (all 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), and FHI (P = 0.022).
Correlation analysis of disease duration, clinical characteristics, inflammatory biomarkers, and BA parameters
Longer disease duration correlated positively with total score, general psychopathology, PAUSS, MW-AH-LV, TD-B-CN, TVW, TD-ChP-LV, MAED-Cr, ventricular index, LV body index, age, and BMI (all P < 0.01). PAUSS severity increased with disease progression (r = 0.360, P < 0.01). Negative correlations were observed with PLT, NEU, Hackman value, FHI, Evans index, education years, and onset age of SCZ (all P < 0.05). Longer disease duration was associated with lower inflammatory markers but greater ventricular dilation (P < 0.01) (Table 2).
Table 2.
Correlation analysis of disease duration, Clinical Features, inflammatory biomarkers, and BA parameters
| Disease duration | |
|---|---|
| Age | r = 0.812, P < 0.01 |
| Education years | r = − 0.246, P < 0.01 |
| Onset of SCZ | r = − 0.320, P < 0.01 |
| History of lifetime suicidal attempts | r = 0.027, P = 0.774 |
| Antipsychotic dosages | r = 0.008, P = 0.931 |
| Marital status | r = 0.065, P = 0.497 |
| Smoking status | r = 0.006, P = 0.948 |
| BMI | r = 0.200, P = 0.033 |
| 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 |
BA Brain atrophy; SCZ Schizophrenia; BMI Body mass index; PLT Platelet count; LYM Lymphocyte count; NEU neutrophil count; NLR NEU/LYM; PLR PLT/LYM; MLR Monocyte count/LYM; SII PLT ×NEU/LYM; PANSS Positive and Negative Syndrome Scale; PAUSS PANSS Autism Severity Score; MW-AH-LV Maximum width of the anterior horn of the lateral ventricle; TD-B-CN Transverse diameter of the bilateral caudate nucleus; WMIN-AH-LV Minimum width of the anterior horn of the lateral ventricle; TVW Third ventricle width; TD-ChP-LV transverse diameter of the choroid plexus of the lateral ventricle; MAED Maximum external diameter; MAED-Cr Maximum external diameter of cranium; 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 indexs=WMIN-AH-LV/MAID-Cr
Correlation analysis of clinical characteristics, inflammatory biomarkers, and BA parameters with PANSS/PAUSS scores
Significant correlations were identified. Positive symptoms correlated with smoking and suicide attempts. Negative symptoms correlated positively with age, illness duration, and smoking, but negatively with education. The PANSS total and general psychopathology scores were positively associated with age, illness duration, and smoking. PAUSS was positively correlated with age, illness duration, and smoking.
Inflammatory biomarkers showed that negative symptoms were positively associated with MLR but negatively with PLT and LYM. PAUSS was negatively correlated with PLT.
Regarding BA parameters, positive symptoms correlated positively with WMIN-AH-LV, TD-ChP-LV, ventricular index, and ventricular central index. Negative symptoms correlated positively with TD-B-CN, WMIN-AH-LV, TVW, ventricular central index, TD-ChP-LV, and Hackman value. General psychopathology correlated positively with ventricular index, FHI, and Evans index. The total score correlated positively with TD-B-CN, WMIN-AH-LV, TVW, TD-ChP-LV, ventricular index, and ventricular central indices. PAUSS correlated positively with TD-B-CN, WMIN-AH-LV, TVW, TD-ChP-LV, Hackman value, and ventricular central indices. Table 3.
Table 3.
Correlation analysis of Clinical Features, inflammatory biomarkers, and BA parameters and PANSS or PAUSS
| Positive symptom score | Negative symptom score | General psychopathological symptoms score | Total score | PAUSS | |
|---|---|---|---|---|---|
| Age |
r = 0.121, P = 0.201 |
r = 0.457, P < 0.001 |
r = 0.362, P < 0.001 |
r = 0.310, P = 0.001 |
r = 0.188, P = 0.046 |
| Disease duration |
r = 0.145, P = 0.126 |
r = 0.530, P < 0.001 |
r = 0.463, P < 0.001 |
r = 0.379, P < 0.001 |
r = 0.265, P = 0.005 |
| Education years |
r = − 0.001, P = 0.991 |
r = − 0.265, P = 0.005 |
r = − 0.262, P = 0.005 |
r = − 0.139, P = 0.141 |
r = − 0.100, P = 0.292 |
| Onset age of SCZ |
r = − 0.067, P = 0.481 |
r = − 0.135, P = 0.155 |
r = − 0.175, P = 0.064 |
r = − 0.126, P = 0.183 |
r = − 0.117, P = 0.215 |
| History of lifetime suicidal attempts |
r = 0.288, P = 0.002 |
r = 0.043, P = 0.650 |
r = 0.120, P = 0.204 |
r = 0.122, P = 0.196 |
r = − 0.002, P = 0.982 |
| Antipsychotic dosages |
r = 0.134, P = 0.157 |
r = − 0.105, P = 0.273 |
r = − 0.055, P = 0.565 |
r = − 0.108, P = 0.255 |
r = − 0.029, P = 0.759 |
| Marital status |
r = 0.029, P = 0.763 |
r = − 0.006, P = 0.949 |
r = − 0.018, P = 0.852 |
r = 0.066, P = 0.485 |
r = 0.044, P = 0.646 |
| Smoking status |
r = 0.379, P < 0.001 |
r = 0.319, P = 0.001 |
r = 0.268, P = 0.004 |
r = 0.301, P = 0.001 |
r = 0.106, P = 0.264 |
| BMI |
r = 0.025, P = 0.791 |
r = 0.220, P = 0.019 |
r = 0.157, P = 0.096 |
r = 0.151, P = 0.110 |
r = 0.128, P = 0.175 |
| PLT |
r = − 0.113, P = 0.231 |
r = − 0.255, P = 0.006 |
r=− 0.031, P = 0.747 |
r = − 0.142, P = 0.134 |
r = − 0.190, P = 0.043 |
| LYM |
r = − 0.032, P = 0.737 |
r = − 0.186, P = 0.049 |
r=− 0.057, P = 0.549 |
r = − 0.086, P = 0.367 |
r = − 0.159, P = 0.093 |
| NEU |
r = − 0.069, P = 0.47 |
r = − 0.112, P = 0.236 |
r = 0.012, P = 0.899 |
r = − 0.059, P = 0.532 |
r = − 0.114, P = 0.228 |
| NLR |
r = 0.008, P = 0.932 |
r = − 0.051, P = 0.595 |
r = 0.032, P = 0.734 |
r = − 0.01, P = 0.917 |
r = − 0.051, P = 0.594 |
| PLR |
r = 0.016, P = 0.866 |
r = − 0.064, P = 0.498 |
r = 0.026, P = 0.782 |
r = − 0.018, P = 0.853 |
r = − 0.036, P = 0.707 |
| MLR |
r = 0.064, P = 0.501 |
r = 0.210, P = 0.026 |
r = 0.098, P = 0.303 |
r = 0.127, P = 0.18 |
r = 0.125, P = 0.188 |
| SII |
r = − 0.012, P = 0.9 |
r = − 0.101, P = 0.287 |
r = 0.027, P = 0.776 |
r = − 0.035, P = 0.716 |
r = − 0.09, P = 0.345 |
| MW-AH-LV (mm) |
r = 0.005, P = 0.958 |
r = 0.091, P = 0.339 |
r=− 0.169, P = 0.073 |
r = − 0.034, P = 0.724 |
r = 0.056, P = 0.553 |
| TD-B-CN (mm) |
r = 0.157, P = 0.097 |
r = 0.429, P < 0.001 |
r = 0.092, P = 0.334 |
r = 0.274, P = 0.003 |
r = 0.316, P = 0.001 |
| WMIN-AH-LV (mm) |
r = 0.333, P < 0.001 |
r = 0.366, P < 0.001 |
r = 0.137, P = 0.149 |
r = 0.330, P < 0.001 |
r = 0.288, P = 0.002 |
| TVW (mm) |
r = 0.184, P = 0.050 |
r = 0.413, P < 0.001 |
r = 0.138, P = 0.144 |
r = 0.331, P < 0.001 |
r = 0.348, P < 0.001 |
| TD-ChP-LV (mm) |
r = 0.250, P = 0.008 |
r = 0.208, P = 0.027 |
r = 0.152, P = 0.109 |
r = 0.247, P = 0.008 |
r = 0.237, P = 0.012 |
| MAED of body of LV (mm) |
r = 0.068, P = 0.471 |
r = 0.175, P = 0.063 |
r = 0.02, P = 0.834 |
r = 0.117, P = 0.218 |
r = 0.11, P = 0.248 |
| MAED-Cr (mm) |
r = 0.158, P = 0.095 |
r = 0.08, P = 0.401 |
r = 0.027, P = 0.778 |
r = 0.109, P = 0.249 |
r = 0.174, P = 0.066 |
| MAID-Cr (mm) |
r = 0.121, P = 0.2 |
r = 0.02, P = 0.83 |
r = 0.034, P = 0.72 |
r = 0.085, P = 0.373 |
r = 0.069, P = 0.47 |
| Hackman value |
r = 0.095, P = 0.315 |
r = 0.308, P = 0.001 |
r=− 0.049, P = 0.608 |
r = 0.141, P = 0.136 |
r = 0.220, P = 0.019 |
| Ventricular index |
r = 0.187, P = 0.047 |
r = 0.071, P = 0.452 |
r = 0.305, P = 0.001 |
r = 0.234, P = 0.013 |
r = 0.128, P = 0.178 |
| The ventricular central indexs |
r = 0 0.296, P = 0.001 |
r = 0.365, P < 0.001 |
r = 0.12, P = 0.204 |
r = 0.304, P = 0.001 |
r = 0.269, P = 0.004 |
| LV body index |
r = − 0.027, P = 0.773 |
r = − 0.168, P = 0.075 |
r = 0.004, P = 0.969 |
r = − 0.082, P = 0.387 |
r = − 0.088, P = 0.356 |
| FHI |
r = 0.049, P = 0.607 |
r = − 0.095, P = 0.315 |
r = 0.219, P = 0.02 |
r = 0.082, P = 0.389 |
r = − 0.042, P = 0.659 |
| Evans index |
r = − 0.051, P = 0.592 |
r = 0.096, P = 0.313 |
r=− 0.199, P = 0.035 |
r = − 0.072, P = 0.446 |
r = 0.032, P = 0.736 |
BA Brain atrophy; BMI Body mass index; PLT Platelet count; LYM Lymphocyte count; NEU Neutrophil count; NLR NEU/LYM; PLR PLT/LYM; MLR Monocyte count/LYM; SII PLT ×NEU/LYM; PANSS Positive and Negative Syndrome Scale; PAUSS PANSS Autism Severity Score; MW-AH-LV Maximum width of the anterior horn of the lateral ventricle; TD-B-CN transverse diameter of the bilateral caudate nucleus; WMIN-AH-LV minimum width of the anterior horn of the lateral ventricle; TVW Third ventricle width; TD-ChP-LV Transverse diameter of the choroid plexus of the lateral ventricle; MAED Maximum external diameter; MAED-Cr Maximum external diameter of cranium; 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 indexs=WMIN-AH-LV/MAID-Cr
The combination of clinical characteristics, BA parameters and inflammatory biomarkers accurately predicted the PANSS and PAUSS scores
A significant multiple regression model for positive symptoms was identified (F = 6.946, P < 0.001, R2=0.327). Using the backward method with clinical characteristics, BA parameters, and inflammatory biomarkers as independent variables (Table 4), positive scores showed a negative association with PLT (P = 0.036) and Evans index (P = 0.001), and a positive association with WMIN-AH-LV (P < 0.001), PLR (P = 0.009), and male sex (P = 0.012) (Fig. 1).
Table 4.
The multiple regression analysis of Positive symptom score
| Variable | β | SE | t | P |
|---|---|---|---|---|
| Constant | 32.428 | 4.281 | ||
| WMIN-AH-LV (mm) | 8.270 | 2.317 | 3.570 | 0.001 |
| Evans index | − 57.126 | 15.484 | − 3.689 | < 0.001 |
| PLT | − 0.025 | 0.007 | − 2.621 | 0.020 |
| PLR | 0.027 | 0.009 | 2.346 | 0.027 |
| Sex | 2.929 | 0.836 | 3.504 | 0.001 |
WMIN-AH-LV Minimum width of the anterior horn of the lateral ventricle; PLT Platelet count; LYM Lymphocyte count; PLR PLT/LYM; MW-AH-LV Maximum width of the anterior horn of the lateral ventricle; MAID-Cr maximum internal diameter of cranium; the Evans index = MW-AH-LV/MAID-Cr
Fig. 1.
Scatterplot for the association between WMIN-AH-LV (mm) (a), Evans index (b), PLT (c), PLR (d) and positive score. WMIN-AH-LV Minimum width of the anterior horn of the lateral ventricle; PLT Platelet count; LYM Lymphocyte count; PLR PLT/LYM; MW-AH-LV Maximum width of the anterior horn of the lateral ventricle; MAID-Cr Maximum internal diameter of cranium; the Evans index = MW-AH-LV/MAID-Cr
The regression model for negative symptoms was significant (R2=0.518, F = 10.097, P < 0.001) (Table 5). Negative symptoms decreased with higher SII, more education years, and later onset age of SCZ, but increased with higher NLR, wider TVW, older age, male sex, and higher BMI (Fig. 2).
Table 5.
The multiple regression analysis of Negative symptom score
| Variable | β | SE | t | P | VIF |
|---|---|---|---|---|---|
| Constant | 20.538 | 1.665 | |||
| Age | 0.178 | 0.035 | 5.098 | < 0.001 | 2.380 |
| Onset age of SCZ | − 0.122 | 0.042 | − 2.938 | 0.004 | 1.313 |
| Education years | − 0.387 | 0.095 | − 4.060 | < 0.001 | 1.283 |
| BMI | 0.203 | 0.082 | 2.482 | 0.015 | 1.219 |
| TVW | 4.260 | 2.106 | 2.379 | 0.023 | 2.157 |
| NLR | 1.317 | 0.564 | 2.336 | 0.022 | 1.276 |
| SII | − 0.006 | 0.002 | − 2.205 | 0.019 | 1.670 |
| Sex | 3.752 | 0.974 | 3.853 | < 0.001 | 2.067 |
SCZ Schizophrenia; BMI Body Mass Index; TVW Third ventricle width; LYM Lymphocyte count; NEU Neutrophil count; NLR NEU/LYM; PLT Platelet count; SII PLT ×NEU/LYM
Fig. 2.
Scatterplot for the association between Age (a), Onset age of SCZ (b), Education years (c), BMI (d), TVW (e), NLR (f), SII (g) and PANSS negative score. SCZ Schizophrenia; BMI Body Mass Index; TVW Third ventricle width; LYM Lymphocyte count; NEU Neutrophil count; NLR NEU/LYM; PLT Platelet count; SII PLT ×NEU/LYM
The regression model for general psychopathology was significant (R2=0.195, F = 6.312, P < 0.001) (Table 6). The score decreased with larger MW-AH-LV, higher ventricular central indices, and later onset age of SCZ, but increased with larger WMIN-AH-LV and older age (Fig. 3).
Table 6.
The multiple regression analysis of General psychopathological symptoms score
| Variable | β | SE | t | P | VIF |
|---|---|---|---|---|---|
| Constant | 81.259 | 4.695 | |||
| Age | 0.130 | 0.043 | 3.042 | 0.003 | 1.761 |
| Onset age of SCZ | − 0.125 | 0.055 | − 2.272 | 0.025 | 1.131 |
| MW-AH-LV (mm) | − 6.894 | 1.604 | − 4.299 | < 0.001 | 1.804 |
| WMIN-AH-LV (mm) | 24.922 | 6.906 | 3.609 | < 0.001 | 3.054 |
| The ventricular central indexs | − 267.867 | 89.180 | − 3.004 | 0.003 | 3.527 |
SCZ Schizophrenia; MW-AH-LV Maximum width of the anterior horn of the lateral ventricle; WMIN-AH-LV minimum width of the anterior horn of the lateral ventricle; the ventricular central indexs=WMIN-AH-LV/MAID-Cr; MAED-Cr Maximum external diameter of cranium
Fig. 3.
Scatterplot for the association between Age (a), Onset age of SCZ (b), MW-AH-LV (mm) (c), WMIN-AH-LV (mm) (d), and General psychopathological symptoms score. SCZ Schizophrenia; MW-AH-LV Maximum width of the anterior horn of the lateral ventricle; WMIN-AH-LV Minimum width of the anterior horn of the lateral ventricle; the ventricular central indexs=WMIN-AH-LV/MAID-Cr; MAED-Cr maximum external diameter of cranium
The regression model for total score was significant (R2=0.364, F = 8.865, P < 0.001) (Table 7). The score decreased with higher PLT, larger MW-AH-LV, higher ventricular central indices, and later onset age of SCZ, but increased with larger WMIN-AH-LV and older age (Fig. 4).
Table 7.
The multiple regression analysis of Total score
| Variable | β | SE | t | P | VIF |
|---|---|---|---|---|---|
| Constant | 148.079 | 9.651 | |||
| Age | 0.386 | 0.085 | 4.518 | < 0.001 | 1.875 |
| Onset age of SCZ | − 0.296 | 0.108 | − 2.748 | 0.007 | 1.157 |
| MW-AH-LV (mm) | − 13.704 | 3.218 | − 4.258 | < 0.001 | 1.976 |
| WMIN-AH-LV (mm) | 51.837 | 15.662 | 3.310 | 0.001 | 5.276 |
| The ventricular central indexs | − 534.701 | 189.912 | − 2.816 | 0.006 | 5.033 |
| PLT | − 0.024 | 0.011 | − 2.049 | 0.043 | 1.611 |
| Sex | 6.752 | 2.403 | 2.809 | 0.006 | 1.652 |
SCZ schizophrenia; MW-AH-LV Maximum width of the anterior horn of the lateral ventricle; WMIN-AH-LV minimum width of the anterior horn of the lateral ventricle; the ventricular central indexs=WMIN-AH-LV/MAID-Cr; MAED-Cr Maximum external diameter of cranium; PLT platelet count
Fig. 4.
Scatterplot for the association between Age (a), Onset age of SCZ (b), MW-AH-LV (c), WMIN-AH-LV (d) PLT (e) and Total score. SCZ Schizophrenia; MW-AH-LV Maximum width of the anterior horn of the lateral ventricle; WMIN-AH-LV Minimum width of the anterior horn of the lateral ventricle; the ventricular central indexs=WMIN-AH-LV/MAID-Cr; MAED-Cr Maximum external diameter of cranium; PLT Platelet count
The regression model for PAUSS was significant (R2=0.391, F = 11.086, P < 0.001) (Table 8). PAUSS decreased with higher SII, higher ventricular central indices, later onset age of SCZ, and more education years. PAUSS increased with higher NLR, larger MAED-Cr, larger WMIN-AH-LV, wider TVW, higher Evans index, older age, and male sex (Fig. 5).
Table 8.
The multiple regression analysis of PAUSS
| Variable | β | SE | t | P | VIF |
|---|---|---|---|---|---|
| Constant | − 32.035 | 21.227 | |||
| Age | 0.166 | 0.029 | 5.750 | < 0.001 | 1.227 |
| Onset age of SCZ | − 0.127 | 0.045 | − 2.805 | 0.006 | 1.167 |
| Education years | − 0.386 | 0.107 | − 3.618 | < 0.001 | 1.200 |
| MW-AH-LV (mm) | − 50.027 | 18.897 | − 2.211 | 0.017 | 2.874 |
| WMIN-AH-LV (mm) | 74.528 | 30.175 | 1.971 | 0.032 | 6.524 |
| TVW | 5.315 | 1.809 | 2.126 | 0.022 | 5.883 |
| The ventricular central indexs | − 825.493 | 379.761 | − 1.846 | 0.045 | 1.625 |
| MAED-Cr | 1.683 | 0.742 | 2.267 | 0.025 | 1.334 |
| Evans index | 515.407 | 211.560 | 2.109 | 0.021 | 5.503 |
| SII | − 0.006 | 0.002 | − 1.984 | 0.035 | 3.886 |
| NLR | 1.189 | 0.595 | 2.007 | 0.038 | 1.090 |
| Sex | 3.103 | 0.925 | 3.356 | 0.001 | 1.392 |
SCZ Schizophrenia; PLT Platelet count; MW-AH-LV Maximum width of the anterior horn of the lateral ventricle; WMIN-AH-LV Minimum width of the anterior horn of the lateral ventricle; TVW Third ventricle width; the ventricular central indexs=WMIN-AH-LV/MAID-Cr; MAED-Cr Maximum external diameter of cranium; the Evans index = MW-AH-LV/MAID-Cr; LYM Lymphocyte count; NEU Neutrophil count; NLR NEU/LYM; PLT, Platelet count; SII PLT ×NEU/LYM
Fig. 5.
Scatterplot for the association between Age (a), Onset age of SCZ (b), Education years (c), WMIN-AH-LV (mm) (d), TVW (e), MAED-Cr (f), Evans index (g), SII (h), NLR (i) and PAUSS. SCZ Schizophrenia; PLT Platelet count; MW-AH-LV Maximum width of the anterior horn of the lateral ventricle; WMIN-AH-LV Minimum width of the anterior horn of the lateral ventricle; TVW Third ventricle width; the ventricular central indexs=WMIN-AH-LV/MAID-Cr; MAED-Cr Maximum external diameter of cranium; NEU neutrophil count; NLR NEU/LYM; PLT Platelet count; SII PLT ×NEU/LYM
Discussion
Consistent with our findings, prior research has linked elevated BMI to negative symptoms and depression [16]. Epidemiological data show higher smoking rates in male SCZ patients [17], with smokers exhibiting more severe symptoms [18], potentially via reduced gray matter and elevated cytokines [19]. In our study, smoking correlated positively with PANSS scores but did not enter the final regression models.
Earlier onset is associated with more severe symptoms [20, 21], and may reflect prefrontal gray matter deficits [22, 23]. Our findings align, showing significant correlations between onset age and both PANSS and PAUSS scores.
Depressive comorbidity in SCZ (30–70%) varies by sex [24, 25].Our results are consistent with prior work linking learning potential to cognitive and social functioning [26].
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 [27] revealed that CT has superior data accessibility, especially for large-scale clinical studies. It also offers shorter scan times and greater patient convenience [28]. 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 [29].
Ventricular enlargement in SCZ is well-established [7, 30], also observed in high-risk populations [31] and ASD [5, 32]. This study revealed significant correlations between brain atrophy parameters and clinical symptom scores, particularly involving the lateral ventricle, third ventricle, and caudate nucleus. Both WMIN-AH-LV and TVW strongly influenced all scores. These findings are consistent with previous reports and confirm a robust link between schizophrenia with autistic features (PAUSS) and enlargement of the lateral ventricle, third ventricle, and caudate nucleus.
Longer illness duration and age > 60 were associated with greater BA [33], possibly influenced by antipsychotics [34].Ventriculomegaly correlated with negative symptoms and cognitive impairment [35], supported by findings in FEP [36, 37].
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.
Hypothalamic atrophy may underlie third ventricle enlargement in ASD [38], a hypothesis consistent with our findings. ChP enlargement correlated with multiple symptom domains, aligning with reports of ChP dysfunction, chronic inflammation, and hormonal influences on sex differences in BA [39–42].Caudate diameter correlated positively with negative symptoms and PAUSS, supporting its inclusion in regression models.
Inflammation–SCZ links are well-documented [43, 44] has 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 [44]. Our finding that negative symptoms correlated positively with MLR and negatively with PLT/LYM, and that NLR predicted both negative symptoms and PAUSS, aligns with prior reports of elevated NLR, PLR, and MLR in SCZ [45].
SII, though inversely associated with symptom severity in our models, has been linked to PANSS scores in previous work [46]. After confounder adjustment, NLR remained consistently associated with clinical outcomes, whereas SII uniquely predicted global and general psychopathology scores [47].
Limitations
First, the cross-sectional design precludes causal inference. Second, the single-center sample with modest size may limit generalizability. Third, CT linear measurements, though practical, lack MRI’s spatial resolution for detailed volumetric analysis. Fourth, multiple testing corrections were not applied to preserve statistical power for planned, independent hypotheses across distinct variable domains, which increases Type I error risk. Fifth, peripheral inflammatory indices (e.g., NLR, PLR, SII) are indirect proxies susceptible to unmeasured clinical or temporal influences. Finally, potential confounders, including detailed antipsychotic medication history, were not fully accounted for.In summary, limitations include study design, sample, methods, and unmeasured confounders. Future longitudinal, multi-center studies with advanced neuroimaging and specific immune markers are needed.
Conclusion
In SCZ patients with autistic features, clinical characteristics, inflammatory biomarkers, and BA show positive correlations with PANSS or PAUSS scores. These readily available clinical and imaging parameters may serve as adjunctive, objective indicators that could aid in the clinical profiling of this distinct subgroup, warranting further investigation into their utility.
Acknowledgements
We are grateful to the nurses and staff of the Department of General Psychiatry, Tianjin Anding Hospital for their support in patient recruitment.
Abbreviations
- SCZ
Schizophrenia
- BA
Brain atrophy
- CT
Computed tomography
- PLT
Platelet count
- NEU
Neutrophil count
- NLR
Lymphocyte ratio
- MLR
Monocyte-to-lymphocyte ratio
- PLR
Platelet-to-lymphocyte ratio
- SII
Systemic inflammation index
- PANSS
Positive and Negative Syndrome Scale
- PAUSS
PANSS Autism Severity Score
- BMI
Body Mass Index
- 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
Author contributions
The authors’ contribution to the paper is as follows: Conceptualization: Jin Wang, Jie Shen, and Yu Pang; Study design: Jin Wang, Jie Shen, and Yu Pang; Review of literature: Jin Wang, Jihui Liua and Lili Zhao; Data Analysis: Jin Wang, Momo Sun and Yang Yang; Preparation of the first Draft: Jin Wang, and Yu Pang; and Critical revisions: Jie Shen, Jihui Liua, Momo Sun and Yang Yang. All authors read and approved the final version of the manuscript.
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).
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.
Declarations
Ethics approval and consent to participate
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 for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
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.