Investigation of choroid plexus variability in schizophrenia-spectrum disorders—insights from a multimodal study

Cohort characteristics

The study cohort comprised 132 individuals with SSD (76 in- and 56 outpatients) and 107 HCs who underwent brain MRI (Table 1). There were no significant differences regarding sex ratio and age between the HC (66% male; 37.05 years) and the SSD group (77% male; 37.33 years) (p = 0.111; p = 0.721). Individuals with SSD had, on average, higher BMI values (SSD, mean ± SD = 28.09 ± 5.11; HC, mean ± SD = 23.64 ± 3.70, p < 0.001) (Table 1). A strong difference was also evident in smoking status: 50% of the individuals with SSD were active smokers, compared to 11% of the HCs (p < 0.001). The most common diagnosis was schizophrenia (72%), followed by schizoaffective disorder (22%), brief psychotic disorder (5%) and delusional disorder (1%). The mean duration of illness (DUI) was 143.68 months (SD = 115.42), and the mean duration of untreated psychosis (DUP) was 22 months (SD = 34.80), although we could only collect data on the DUP in 78 of the participants. The Positive And Negative Syndrome Scale (PANSS) total scores averaged 54.80 (SD = 15.20), indicating that patients were, on average, “mildly ill”²⁶. Forty-seven individuals (37%) were either being treated with or reported a history of intake of clozapine in their lifetime, while 80 individuals from the SSD cohort have never received clozapine. Out of the 132 participants with SSD, nine were antipsychotic-naïve.

Choroid plexus volume and asymmetry in SSD

First, we aimed to replicate the recently published findings on ChP (Fig. 1A) enlargement in SSD^15,25. For that reason, we compared the ChP volumes between SSD subjects and HCs (Fig. 1B; Table S1a, b). Our analysis showed no significant differences in choroid plexus volumes after controlling for age and sex as covariables (estimate [95% CI] = 19.14 mm³ [−15.37, 53.64]; p = 0.362). Furthermore, the right choroid plexus was significantly larger than the left one, independent of phenotype (estimate [95% CI] = 66.41 mm³ [43.72, 89.1]; p < 0.001). Building on the asymmetry hypothesis in schizophrenia²⁷, we compared the choroid plexus asymmetry index (Suppl. Methods) between individuals with SSD and HCs. We did not find significant differences between both groups (Table S1c, Fig. S2).

A Schematic illustration of the choroid plexus (red) and associated lateral ventricle (blue) of the brain. B Comparison of mean volumes of the left (red) and right (turquoise) choroid plexus between the healthy control (HC) group and the schizophrenia-spectrum disorders (SSD) group, illustrated with a jitter plot. Data points represent individual choroid plexus volumes. Groups were compared using a linear mixed-effect model, controlling for age and sex. N_HC = 107, n_HC = 214, N_SSD = 132, n_SSD = 264. C Forest plot depicting the variability ratio (VR) of choroid plexus, lateral ventricle (red) and other regions of interest, implicated in severe mental illness and schizophrenia (black). N_HC = 107, N_SSD = 132. N number of participants, n number of choroid plexus volumes, VR variability ratio. Created with BioRender.com.

Structural variance of choroid plexus

Driven by the observation of increased scattering of ChP volumes in the SSD group (Fig. 1B), we investigated whether volumes of the choroid plexus and other associated regions (Fig. 1C) show an increased variability (as indicated by variability ratio [VR]) in the SSD group, compared to the HC group. We calculated VR for all regions of interest outlined above and implicated in convergent transdiagnostic or schizophrenia-specific brain networks^28,29 using an established method¹. The variability of the ChP (estimate [95% CI] = 1.249 [1.01, 1.55]) and the associated lateral ventricle (estimate [95% CI] = 1.364 [1.1, 1.69]) was more pronounced in the SSD group compared to the variability in the HC group. Except for the posterior cingulate cortex (estimate [95% CI] = 1.238 [1.0, 1.54]), where we saw a non-significant trend towards increased variance, the variability of the volumes and the cortical thickness of all other regions was not higher in the SSD group compared to the HC group (Table S2a). The VR analyses of the unilaterally computed regions of interest mostly confirmed the results of bilaterally computed regional VRs (Table S2b).

Clusters based on regions with increased variability

Next, we conducted a K-means clustering analysis based on the choroid plexus and lateral ventricle (Lat Vent) volumes to identify subgroups within the SSD cohort with distinct patterns of the ventricular system. These regions were selected based on the empirical observation of increased variability in our data (Fig. 1C) as well as previous implications of the cerebroventricular system in immune dysregulation in SSD^15,16,30,31. Employing the elbow method, we identified the ideal cluster solution to be 3 (Fig. S3). According to the scaled mean volumes of the two features (ChP and lateral ventricle) in each cluster, we deduced that cluster 1 (N = 15, scaled centers ChP/LatVent = 1.18, 1.90) was “large ChP-large lateral ventricle cluster”, cluster 2 (N = 50, scaled centers ChP/LatVent = −0.85, −0.65) was “small ChP-small lateral ventricle cluster,” and cluster 3 (N = 67, scaled centers ChP/LatVent = 0.37, 0.06) was “intermediate ChP-small lateral ventricle cluster” (Table S3a, Fig. 2A).

A Scatter plot depicting the lateral ventricle (x-axis) and choroid plexus (y-axis) residual volumes (after correction for age and sex) of cluster 1 (red), cluster 2 (green) and cluster 3 (blue) within the SSD cohort. B Radar chart illustrating cluster mean scaled scores of age, “duration of untreated psychosis” (DUP), “duration of illness” (DUI), body-mass-index (BMI), and chlorpromazine equivalents (CPZeq). C Radar chart illustrating cluster mean z-scores of different cognitive subdomains, measured by “The Brief Assessment of Cognition in Schizophrenia” (BACS). D Comparison of mean peripheral monocyte counts between cluster 1 (N = 10), cluster 2 (N = 28), and cluster 3 (N = 38). Data points represent individual monocyte counts. *q < 0.05; ***q < 0.001. N number of participants, DUP “duration of untreated psychosis”, DUI “duration of illness”, BMI “body-mass-index”, CPZeq “chlorpromazine equivalents”, BACS “The Brief Assessment of Cognition in Schizophrenia”, Comp composite score, VM verbal memory test, VF verbal fluency test, TL tower of London test, TM token motor test, SC symbol coding test, DS digit sequence test, G/l Giga/liter.

Characteristics of clusters within the SSD group

There were no significant across-cluster differences regarding sex (χ² = 1.47, p = 0.479), diagnosis (χ² = 12.36, p = 0.136), treatment resistance status (χ² = 0.91, p = 0.635), and smoking status (χ² = 2.88, p = 0.237; Table S3a). We found no significant across-cluster differences regarding age, DUI, DUP, BMI, and CPZ equivalent (Table S3b, Fig. 2B).

There were no significant differences regarding psychopathology (operationalized by PANSS) or global functioning (measured with GAF scale) across clusters (Fig. S4A, Table S3c). Furthermore, there were significant differences regarding global cognition (operationalized by BACS composite z-score) (cluster 1, mean ± SD (z-score) = −1.41 ± 1.42; cluster 2, mean ± SD (z-score) = −0.52 ± 0.74; cluster 3, mean ± SD (z-score) = −0.52 ± 1, q = 0.04) and BACS tower of London subtest (cluster 1, mean ± SD (z-score) = −2.7 ± 3.45; cluster 2, mean ± SD = −0.47 ± 1.29, cluster 3, mean ± SD = −0.41 ± 1.14, q < 0.001; Fig. 2C, Table S3d). The Games–Howell post-hoc tests did not find significant between-cluster differences for the BACS composite and tower of London test z scores. Moreover, we observed a trend towards significant across-group differences for BACS digit sequence (q = 0.05), BACS symbol coding (q = 0.084), and BACS token motor (q = 0.084) subtests that didn’t survive FDR correction (Table S3d).

Due to the role of the choroid plexus as an immunological niche in the CNS we compared the across-cluster differences regarding peripheral leukocytes and high-sensitive C-reactive protein (hsCRP) levels in two subgroups of participants. We found significant across-cluster differences regarding absolute monocyte counts (cluster 1, mean ± SD (G/l) = 0.6 ± 0.14; cluster 2, mean ± SD = 0.55 ± 0.14, cluster 3, mean ± SD = 0.48 ± 0.13, q = 0.049; Fig. 2D) as well as hsCRP levels (cluster 1, mean ± SD (pg/ml) = 3.5 × 10⁸ ± 3.73 × 10⁸; cluster 2, mean ± SD = 2.56 × 10⁸ ± 2.43 × 10⁸, cluster 3, mean ± SD = 1.44 × 10⁸± 1.49 × 10⁸, q = 0.032; Fig. S4D). The Games–Howell post-hoc tests revealed a trend towards higher monocyte counts in cluster 1, compared to cluster 3 (p = 0.07) and higher hsCRP levels in cluster 2, compared to cluster 3 (p = 0.083), which did not reach statistical significance (Table S3e). There were no significant across-cluster differences regarding absolute neutrophil or lymphocyte counts (Figs. S4B, C).

Furthermore, we did not find significant across-cluster differences regarding the polygenic risk score for schizophrenia (SZ-PRS) after controlling for age, sex, and the first five or the first ten multidimensional scaling (MDS) components as covariates (Table S3f, Table S3g, Fig. S4E). Those results were stable across different phi thresholds.

Relationship between choroid plexus and brain structure

Next, we explored the relationship between choroid plexus volume and the volumes of cortical and subcortical structures previously associated with peripheral inflammation in SSD¹³ (Tables S4a, S4b). Among the subcortical regions of interest, we discovered a positive association between choroid plexus volume and volumes of hippocampus (estimate [95% CI] = 1.41 [0.78, 2.03]; q = 0.001), thalamus (estimate [95% CI] = 1.93 [0.67, 3.2]; q = 0.024), and putamen (estimate [95% CI] = 1.18 [0.37, 2.0]; q = 0.024), but not amygdala within the SSD cohort (Table S4a, Fig. 3). Furthermore, those associations appeared to be specific for SSD since we did not find significant associations between those structures in the HC group (Table S5, Fig. S7). Interestingly, we did not find significant associations between the choroid plexus volume and the volumes of cortical structures previously associated with peripheral inflammation (Table S4b, Fig. S5). Moreover, there was no association between the volumes of hippocampus, thalamus, putamen, and the volume of the other structure with increased variance, namely the lateral ventricle (Table S4c, Fig. S6).

Regression plots illustrating relationships between choroid plexus volume, (A) hippocampus, (B), thalamus, (C) putamen, and (D) amygdala volumes in SSD. The analyses were conducted via linear regressions, controlling for age and sex. Data points represent individual volumes and are color-coded for “duration of illness” with orange color indicating higher and blue color indicating lower duration. N_SSD = 132. *q < 0.05; **q < 0.01. N number of participants, DUI “duration of illness (months)”, ChP choroid plexus.