CSF1R Contributes to Vascular Association of Microglia and Stress Regulation in Schizophrenia

CSF1R Contributes to Vascular Association of Microglia and Stress Regulation in Schizophrenia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article CSF1R Contributes to Vascular Association of Microglia and Stress Regulation in Schizophrenia Li Tian, Ling Yan, Yanli Li, Fengmei Fan, Fang-Ling Xuan, Wei Feng, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1777009/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Whether and how microglia contribute to stress and anxiety in schizophrenia are not well established. We hypothesized that microglial colony stimulating factor 1 receptor (CSF1R) regulates stress susceptibility in schizophrenia via the hippocampus and associated cortical regions. A cohort of first-episode schizophrenia (FES) patients (n=51) and age- and sex-paired healthy controls (HCs) (n=46) were first recruited. Compared to HCs, FES patients showed higher scores of perceived stress scale (PSS, p <0.01), lower levels of CSF1R mRNA (Log2FC=-0.195, FDR=0.003) and protein (18.31±0.95 vs. 20.49±0.90 µg/ml, p <0.05) in the blood, and smaller volumes of the superiorfrontal gyrus (39.13±0.64 vs. 40.80±0.76 cm 3 , FDR<0.05) and parahippocampal gyrus (3.51±0.048 vs. 3.72±0.058 cm 3 , FDR<0.05). CSF1R facilitated the negative superiorfrontal gyral association with PSS (β=6.109, 95% CI: 1.642~10.578, p <0.01) in HCs but not FES patients. CSF1R-associated gene network contributed to brain development. We further studied a chronic unpredictable stress (CUS) mouse model combined with a CSF1R inhibitor (CSF1Ri). Both CUS and CSF1Ri enhanced anxiety in mice (both p <0.001). RNA-seq revealed downregulation of genes for cell adhesion and angiogenesis after CUS-CSF1Ri treatment. Immunostaining showed downregulation of CD31 and preferential loss of vessel-associated IBA1 + -microglia induced by CUS or CSF1Ri ( p <0.05). Oligodendrocyte precursor cells were however increased after CUS-CSF1Ri treatment ( p <0.01). These results suggest that microglial CSF1R showed a protective effect on stress and anxiety in FES patients and CUS mice via contribution to angiogenesis. Microglia CSF1R Angiogenesis First episode schizophrenia Stress Anxiety Figures Figure 1 Figure 2 Figure 3 Figure 4 Highlights FES patients perceived higher stress than HCs. Blood CSF1R level and volumes of the superiorfrontal and parahippocampal gyri were decreased in FES patients compared to HCs. CSF1R facilitated superiorfrontal gyral regulation of perceived stress in HCs but not FES patients. Both CUS and CSF1Ri induced anxiety in mice. CUS and CSF1Ri downregulated angiogenesis and blood vessel-associated IBA1 + -microglia in mice. Introduction Schizophrenia is a complex neurodevelopmental disorder usually caused by environmental insults on genetically predisposed individuals [ 1 ], which can be recapitulated in animal models [ 2 ]. Psychosocial stressors have been shown to trigger or exacerbate symptoms of schizophrenia [ 3 , 4 ]. Heightened stress response, as measured by perceived stress scale (PSS), preceded the onset of psychosis in both schizophrenia patients [ 5 ] and rodents [ 6 ]. Patients of first episode psychosis also showed higher PSS scores along with affective or psychotic symptoms than healthy controls (HCs) [ 5 , 7 ]. Dystrophies of the cortical and associated limbic structures are frequently observed in both schizophrenia patients [ 8 , 9 , 10 ] and animal models of chronic psychosocial stress [ 11 ]. Neurobiological substrates underlying stress-induced brain changes may include impaired neuronal projections across the hippocampus-associated structures [ 12 ] and enhanced local microglia/astrocytes-mediated neuroinflammation [ 13 , 14 ]. Glia are important regulators for brain development and functional connectivity. Their dysfunctions can enhance synaptic pruning, prevent angiogenesis and neurogenesis, induce neuronal and myelinic loss, as evidenced from both human and animal studies [ 15 , 16 , 17 , 18 , 19 , 20 ]. Colony stimulating factor 1 receptor (CSF1R) is a receptor tyrosine kinase crucial for development, survival, and proliferation of myeloid cells [ 21 ]. Both human subjects with CSF1R loss-of-function mutation and Csf1r −/− mice display shortened lifespan, loss of microglia and macrophages, and neurodevelopmental abnormalities [ 22 , 23 ]. While genetic or pharmacological inhibition of CSF1R (CSF1Ri) produced no gross behavioral changes in adult animals [ 24 ], recent studies demonstrated that Csf1r haplodeficiency was anxiogenic to mice [ 25 ]; CSF1Ri-induced microglial ablation enhanced learning and fear memory [ 26 , 27 ] while microglial repopulation corrected repetitive behaviour and social deficits [ 28 , 29 ]; CSF1-induced microglial proliferation also ameliorated depressive-like behavior in mice after chronic unpredictable stress (CUS) [ 30 ]. Lower CSF1R in the post-mortem brains of chronic schizophrenia patients was reported [ 31 , 32 , 33 ]. However, the exact role of CSF1R in schizophrenia in association with psychosocial stress has remained unclear. We have reported that cumulative stress may contribute to cortical thickness and cognitive deficits in first-episode schizophrenia (FES) patients [ 34 ]. In the present study, we performed blood RNA sequencing (RNA-Seq) and proteomic array, assessed cortical structures by magnetic resonance imaging (MRI), and used a CUS mouse model combined with pharmacological CSF1Ri to characterize the underlying mechanisms of schizophrenia-associated stress and anxiety regulated by microglia. Materials And Methods Participants’ demographic and clinical measures FES Patients (n = 51) recruited for this study were from the Beijing Hui Long Guan Hospital. Patients were diagnosed schizophrenia according to the Structured Clinical Interview for DSM-IV (SCID) independently by two psychiatrists. HC participants (n = 46) matched for age and sex were recruited from local community. Candidates who unmet recruitment criteria were excluded. All participants provided written informed consent. The study was approved by the Institutional Ethical Committee of Beijing Huilongguan Hospital. Participants’ past traumatic experiences were evaluated by Childhood Trauma Questionnaire (CTQ), a 29-item self-reported questionnaire of a retrospective measure encompassing five factors: physical abuse, emotional abuse, sexual abuse, physical neglect, and emotional neglect [ 35 ] validated in Chinese [ 36 ]. Participants’ stress levels were evaluated based on PSS, a 14-item self-reported questionnaire measuring feelings and thoughts during the last month [ 37 ] validated in Chinese [ 38 ]. Positive and Negative Syndrome Scale total scores (PANSSt) were measured independently by two psychiatrists (For details see supplementary materials). Human and mouse RNA-seq and data analysis Human blood (5ml) was collected between 7-9am after overnight fasting using PAXgene™ blood RNA tubes (Applied Biosystems). Tubes were shaken vigorously for at least 10 seconds after sampling and immediately stored at -80°C. Total RNAs were extracted using Mag-MAX™ for Stabilized Blood Tubes RNA Isolation Kit (Applied Biosystems) following the manufacturer’s instructions. Mice were euthanized with CO 2 and the prefrontal cortices were dissected and immediately stored at -80°C. Total RNAs were extracted using Trizol (Molecular Research Center). RNAs were quantified and assessed for purity by optical density ratios of 260nm/280nm and 260nm/230nm using NanoDrop spectrophotometry (ThermoFisher). RNA samples (1µg per sample) were immediately sent to the Beijing Genomics institution (BGI) for mRNA (after globin mRNA removal) sequencing on the BGIseq-500 platform. Quality control (QC) on RNA samples (RIN/RQN ≥ 7.0, 28S/18S ≥ 1.0) was confirmed by BGI. Clean data of at least 4Gb (20M clean reads) per sample were collected. QC of RNA-seq data and gene expression analysis were done on the Galaxy and NetworkAnalyst platforms [ 39 ] using DESEQ2. Data with variance percentile rank < 15% and counts < 4 were filtered out. Counts per million reads were transformed, normalized and calculated to Log2 fold changes (Log2FC) for differentially expressed genes (DEGs). DEGs with Benjamini-Hochberg’s false discovery rate (FDR) < 0.05 were subjected to analyses of gene ontology biological pathway (GO-BP) and protein-protein interaction (PPI) in David ( https://david.ncifcrf.gov/ ) and STRING v11.5 ( https://string-db.org/cgi/input.pl ). GeneWeaver brain functional genomic data GeneWeaver, a database for the integration and analysis of heterogeneous functional genomics data ( https://geneweaver.org/ ), was explored to dig out CSF1R-associated genesets annotated to contribute to human brain development. Annotated gene series GS393224 (Abnormality of brain morphology), GS393415 (Hydrocephalus), GS393709 (Abnormality of neuronal migration), GS395524 (Ventriculomegaly) were retrieved for further comparisons to blood RNA-seq DEGs and GO-BP analysis as described above. Serum CSF1R protein detection by antibody array Blood samples (5ml) were collected as described above. After 15 minutes (min), sera were separated by centrifugation at 4000 rpm for 10min, which were immediately stored at -80°C until assayed. Samples were sent for human antibody microarray detection (AAH-BLG-1000, RayBiotech) to identify candidate biomarkers including CSF1R. Briefly, primary amines of proteins were biotinylated in dialyzed seral samples. Glass slides pre-printed with capture antibodies were blocked, biotin-labelled samples were added and incubated to capture target proteins. Streptavidin-conjugated Cy3 was then applied to the glass slides, which were washed, dried, and finally sent for laser fluorescence scanning (GenePix 4000B scanner). Signal intensity data after background subtraction and normalization were exported into the RayBio® Analysis Tool software for protein quantification. MRI acquisition and processing Brain structural MRI data were acquired using a Siemens Prisma 3.0T MRI scanner with a 64-channel head coil. Sagittal images were collected following the ENIGMA protocol with FreeSurfer software [ 40 , 41 ]. Intracranial volume (ICV) and regional volumes of bi- hemispheric cerebral cortical/subcortical structures were measured (For details see supplementary materials). Mouse CUS and CSF1Ri (PLX3397) treatment procedures Wild-type C57BL/6NTac male mice (3-month-old, Taconic) were bred in laboratory animal facility at the Institute of Biomedicine and Translational Medicine, University of Tartu. Mice were kept under standard breeding conditions. All animal procedures were performed in accordance with the European Communities Directive with the license No. 171 issued from the Estonian National Board of Animal Experiments. After a week (wk) of transfer adaptation, mice were randomly assigned into 4 groups: Control (Ctr)-Vehicle (Veh) (n = 9), CUS-Veh (n = 9), Ctr-CSF1Ri (n = 10), and CUS-CSF1Ri (n = 10), and subject to CUS/Ctr and CSF1Ri (PLX3397)/Veh treatments. CUS procedure was previously described [ 42 ]. PLX3397 (HY-16749/CS-4256, MedChemExpress) was dissolved in DMSO (D8418, Sigma-Aldrich) and freshly diluted with corn oil (#8267, Sigma-Aldrich). Drug-treated mice were daily fed [ 43 , 44 ] with Veh or PLX3397 (~ 120mg/kg bodyweight) in Nutella. Mice were treated with PLX3397 or Veh for 2wk starting from the 7th wk of CUS. Behavioral experiments were performed at the 8th wk (Fig. 3 A) (For details see supplementary materials). Open field test (OFT) Mice were habituated to room light for 1 hour (h). Individual mouse was measured for distance and time travelled in different zones of a digital box (44.8×44.8×45cm) via a software (Technical & Scientific Equipment GmbH) for 30min. The floor of the box was cleaned with 70% ethanol and dried thoroughly after each mouse. Elevated plus maze (EPM) EPM consisted of open and closed arms (30×5cm each) intersected at a central 5×5cm square platform elevated to a height of 80cm. On testing day, mice were habituated to 40W room light for 1 h. Each mouse was placed individually on the central platform facing the open arm and recorded for time spent on open/close arms by a software (EthoVision XT, Noduls) for 5min. The arms were cleaned with 70% ethanol and dried thoroughly after each mouse. Brain tissue processing and immunohistochemistry Mice were anesthetized with intraperitoneal ketamine/xylazine and transcardially perfused with PBS and 4% paraformaldehyde. The post-fixed brains were cryoprotected and stored at -80°C before cryosectioning at -20°C. Coronal sections of the prefrontal cortex (PFC) in 40µm-thickness were processed and incubated with primary antibodies including rabbit anti-IBA1 (#SKL6615, Wako, 1:500) and rat anti-CD31 (#553370, BD Pharmingen, 1:250, kind gift by Prof. Tambet Teesalu) in PBS blocking buffer overnight at 4°C, followed by goat anti-rabbit IgG H&L-AlexaFluor488 (#ab175471, Abcam, 1:500) and goat anti-rat IgG H&L-AlexaFluor546 (#119170, Jackson ImmunoResearch, 1:500) for 2h at room temperature and then in 0.1µg/ml DAPI (#ACRO202710100, VWR) for 5min. After mounting to glass slides with Fluoromount™ Aqueous Mounting Medium (# F4680-25ML, Sigma-Aldrich). Z-stack images were taken by a FV1200MPE laser scanning microscope at 60× resolution with a CCD camera (Olympus) (For details see supplementary materials). Cell numbers and fluorescent intensities of CD31 and IBA1 were quantified using ImageJ. IBA1 + -microglia whose cell soma located within the range of vascular radius surrounding a blood vessel were defined as vessel-associated microglia (VAMg) and others as nonvessel-associated microglia (NVAMg). Three PFC sections per mouse were randomly imaged (n = 3 mice per group). Flow cytometry Mice were euthanized with CO 2 . Dissected hippocampi were gently homogenized through 70µm cell strainers (#352350, BD Bioscience) in ice-cold PBS + 1% fetal bovine serum (FBS). Homogenates were washed, centrifuged at 500g for 5min, and blocked with PBS + 10% rat serum for 1h, then stained with flow markers (BioLegend and Miltenyi) of anti-mouse Csf1r-Brilliant Violet (BV)605 (#135517), CD11b-BV421 (#101251), CD45-BV650 (#103151BioLegend), Glast-APC (#130-123-555), and O4-PE (#130-117-357) for 1h (For isotype control details see supplementary materials). Washed cells were resuspended in 500µl PBS and acquired with a Fortessa flow cytometer (BD Bioscience). Data were analyzed by Kaluza v2.1 software (Beckman Coulter). Astrocytes were defined as Glast + cells, oligodendrocyte precursor cells (OPCs) as O4 + cells, microglia as CD45 low CD11b hi cells. Cell populations were calculated as the % among total brain cells and mean fluorescent intensity (MFI) of Csf1r in Csf1r + microglia were calculated. Statistical Analysis Data distributions were examined by Shapiro-Wilkinson’s test. Depending on data normality, one-way analysis of variance (ANOVA) or Mann-Whitney U test was used for continuous variables and chi-squared tests for categorical variables. Analysis of covariance (ANCOVA) with age and sex as covariates was conducted for serum CSF1R and MRI data, and white blood cells and ICV were included as additional covariates for them, respectively. P values for multiple comparisons were corrected by FDR. Relationships among CSF1R level, cortical size, and PSS score were evaluated using linear regression and moderator analysis by PROCESS v3.5 in SPSS v27.0 (IBM), controlled by age, sex, and ICV. For animal data, two-way ANOVA was used to examine the interaction between CUS and CSF1Ri, as well as their main effects, with post hoc Tukey's correction for post hoc comparisons. Figures were prepared in GraphPad Prism v8.0.1 and online ( http://www.bioinformatics.com.cn/ ). Data were presented as mean ± SEM and p or FDR < 0.05 was considered statistically significant. Results FES patients showed higher perceived stress than HCs. Participants’ demographic and clinical data are listed in Table 1 . FES patients and HCs were not statistically different in age, sex, education years and CTQ score (all p > 0.05). However, compared with HCs, FES patients had higher PSS score (FES: 23.14 ± 0.99, HC: 21.39 ± 0.67; p < 0.05; Fig. 1 A), which was positively correlated with PANSSt score (r = 0.334, p < 0.05; Fig. 1 B ) Table 1 Demographic characteristics of FES patients and HCs Demographics FES (n = 51) HC (n = 46) F or 𝜒2 P Sex (M/F) 18/33 23/23 2.143 0.143 Age (years)* 30.59 (1.18) 34.00 (1.46) 1388.000 0.120 Education (years)* 12.75 (0.49) 13.28 (0.33) 1298.500 0.354 CTQsum* 81.55 (5.49) 70.02 (4.78) 727.500 0.125 PSSsum* 23.14 (0.99) 21.39 (0.67) 893.000 0.043 Age of illness onset (years) 29.27 (1.17) Illness duration (months) 11.70 (2.09) PANSSt 75.69 (2.03) White blood cells (10 6 /ml)* 7.60 (1.08) 6.01 (0.25) 856.000 0.085 Serum CSF1R (µg/ml) 18.31 (0.95) 20.49 (0.90) 4.982 0.028 All data were reported as mean (SEM); FES: first episode schizophrenia; HC: healthy control; FDR: false discovery rate; CSF1R: colony stimulating factor 1 receptor; CTQ: childhood trauma questionnaire; PSS: perceived stress scale; PANSSt: positive and negative symptom scale total score. CSF1R (ANCOVA controlled by age, sex, and white blood cells); Significant p values are shown in bold texts. *: Mann-Whitney U test. Table 2 Cerebral cortical volumes (cm 3 ) in FES patients and HCs Cortical regions FES (n = 51) HC (n = 46) F P -value FDR Anteriocingulate gyrus 7.729 ± 0.126 7.927 ± 0.133 1.124 0.292 0.467 Entorhinal gyrus 3.152 ± 0.069 3.136 ± 0.069 0.442 0.508 0.581 Hippocampus 8.039 ± 0.084 8.109 ± 0.096 0.156 0.694 0.694 Inferiorfrontal gyrus 19.233 ± 0.296 19.679 ± 0.313 1.031 0.312 0.416 Middlefrontal gyrus 40.051 ± 0.502 41.388 ± 0.530 3.23 0.076 0.152 Orbitalfrontal gyrus 23.791 ± 0.203 24.445 ± 0.214 4.706 0.033 0.088 Parahippocampal gyrus 3.505 ± 0.048 3.723 ± 0.058 8.791 0.004 0.032 Superiorfrontal gyrus 39.134 ± 0.641 40.803 ± 0.760 8.327 0.005 0.020 FES: first episode schizophrenia; HC: healthy control; ANCOVA controlled by age, sex and intracranial volume (ICV) and corrected for multiple comparisons among 8 regions; Bold texts indicate those with significant p and false discovery rate (FDR) values. Cerebral cortical regions were smaller in FES patients. We first studied 8 key stress-related brain regions, including the PFC subareas, hippocampus, and hippocampus-associated entorhinal and parahippocampal gyri (Fig. 1 C, Table 2 ), and observed significantly reduced volumes in the superiorfrontal gyrus (FES: 37.134 ± 0.641, HC: 40.803 ± 0.760, p < 0.005, FDR = 0.02; Fig. 1 D) and parahippocampal gyrus (FES: 3.505 ± 0.048, HC: 3.723 ± 0.058; p < 0.004, FDR = 0.032; Fig. 1 E) in FES patients compared to HCs. Additionally, the orbitalfrontal gyrus also showed nominal significance in reduction in FES patients compared to HCs ( p < 0.05, Table 2 ). The hippocampus and other cortical structures did not show significant differences, however (Table 2 ). Blood CSF1R mRNA and protein levels were lower in FES patients. We next endeavoured to find out immune mechanisms underlying stress perception. We earlier had collected whole blood samples from a cohort of 128 FES patients and 111 HCs, including the subjects of our current study, and we identified 9062 DEGs by RNA-seq (submitted work). These DEGs include downregulated CSF1R (Log2FC=-0.195, FDR = 0.003). CSF1R is among the best-known immune receptors to affect microglia-associated brain development and behavior. Hence, we first explored functional genomic data in GeneWeaver and retrieved 64 CSF1R -associted brain genes that contribute to human brain development. We aligned these 64 genes with our RNA-seq DEGs by Venn analysis, which showed 11 overlapping up-regulated genes and 17 overlapping down-regulated genes as visualized in a volcano plot (Fig. 2 A). These 28 DEGs included CSF1R (Fig. 2 B, Table S1 ). We further measured CSF1R protein in the serum and confirmed its downregulation in FES patients compared to HCs (FES: 18.31 ± 0.95, HCs: 20.49 ± 0.90 µg/ml; p < 0.05; Fig. 2 E, Table 1 ). To depict functional relationships among the 28 DEGs, we studied their GO enrichment, showing top-ranked signalling pathways involved in developmental processes (Fig. 2 D, Table S2 ), and PPI, showing three different functional clusters with hub molecules such as AKT1, and CSF1R (Fig. 2 C). CSF1R fully moderated superiorfrontal gyral negative association with stress perception in HCs. We further explored inter-relationships among the cortical structures, CSF1R mRNA or protein, and PSS with linear regression and moderator analyses, predicting that PSSsum was the dependent variable, cortical volumes the independent variables, and CSF1R level the moderator, controlled by age, sex and ICV. The model showed that in HCs but not FES patients, CSF1R mRNA was negatively associated with PSSsum (β=-9.784, p < 0.05; Fig. 2 F). CSF1R also interacted with the superiorfrontal gyrus (R 2 = 0.083, p < 0.05; Fig. 2 F) and fully moderated superiorfrontal gyral regulation of the PSSsum (β = 6.109, 95% confidence interval (CI) = 1.642 ~ 10.578, p < 0.01; Fig. 2 F). We also found that in FES patients, CSF1R mRNA was negatively correlated with PSS score (r=-0.299, p < 0.05; Fig. S1A ) and PANSSt score (r=-0.329, p < 0.05; Fig. S1B). Additionally, CSF1R mRNA and protein also moderated the negative associations of the middlefrontal gyrus (β = 0.383, p < 0.05; Fig. S1C) and the hippocampus (β = 0.477, p < 0.05; Fig. S1C ) with the PSSsum, respectively, in HCs. CUS and CSF1Ri enhanced anxiety in mice. Considering the above clinical observations, we postulated that microglial CSF1R may provide a protective mechanism in the brain for stress regulation. To address this question, we applied a CUS mouse model (lasting 8wk) combined with a CSF1Ri (3mg PLX3397/mouse/day for 2wk) (Fig. 3 A). We first evaluated anxiety of the four groups of mice in response to these treatments, as measured in OFT and EPM. Significant interaction and main effects of CUS and CSF1Ri on the ratio of central distance/total distance in OFT and the ratio of open/close arms time were observed (both p < 0.001). CUS alone induced anxiety compared to Ctr-Veh (OFT: p < 0.001; EPM: p < 0.05 Fig. 3 B- 3 C). CSF1Ri alone also enhanced anxiety compared to Ctr-Veh (both p < 0.001; Fig. 3 B- 3 C). CUS and CSF1Ri inhibited angiogenesis and vascular association of microglia in the mouse PFC. We next studied the PFC by RNA-seq and identified 2750 DEGs including 1204 upregulated and 1546 downregulated DEGs among the four groups. GO-BP enrichment analysis of these DEGs showed cell adhesion and angiogenesis as the top-ranking pathways (Fig. 3 D, Tables S3 and S4 ). There were 115 DEGs involved in cell adhesion ( Fig. S2 ) and 38 DEGs involved in angiogenesis, with most of the angiogenic DEGs downregulated in Ctr-CSF1Ri or CUS-CSF1Ri group than Ctr-Veh group (Fig. 3 E and Fig. 3 F), suggesting that CUS and CSF1Ri could interfere angiogenesis. To verify the effect of CUS and CSF1Ri on angiogenesis, we stained the PFC sections for CD31 and IBA1 (Fig. 4 A ) . There was a significant interaction effect between CUS and CSF1Ri on the intensity of CD31 ( p < 0.01), which was decreased in CUS alone compared to Ctr-Veh group ( p < 0.05; Fig. 4 B) and trendily so in Ctr-CSF1Ri group compared to Ctr-Veh group ( p = 0.08; Fig. 4 B). For IBA1 + -microglia, we classified them into VAMg (e.g., microglia whose cell soma resided on or adjacent to blood vessels) and NVAMg (e.g., non-vessel associated microglia) among the total microglia (TMg) (Fig. 4 C). Significant interaction between CUS and CSF1Ri and main effect of CSF1Ri on the parameters as shown in Fig. 4 C- 4 H were found (all p < 0.05), suggesting antagonizing effects of CUS and CSF1Ri on VAMg. CUS and CSF1Ri alone induced reductions of number (No.) of TMg ( p < 0.05 and 0.001, Fig. 4 C) and IBA1 intensity ( p < 0.01 and 0.001, Fig. 4 D). Interestingly, CSF1Ri alone dampened the ratio of VAMg No./TMg No. but elevated the ratio of NVAMg No./TMg No. compared to Ctr-Veh (both p < 0.05; Fig. 4 E and 4 G). Moreover, CUS and CSF1Ri alone suppressed the ratio of IBA1 intensity in VAMg/TMg but raised the ratio of IBA1 intensity in NVAMg/TMg compared to Ctr-Veh (both p < 0.05; Fig. 4 F and 4 H). CSF1Ri alone also showed similar effects on these two parameters compared to Ctr-Veh (both p < 0.01; Fig. 4 F and 4 H, Fig. S3 ). CUS decreased microglia and dampened microglial Csf1r expression in the mouse hippocampus. We further validated CSF1Ri by quantifying microglia along with other glial populations, namely astrocytes and OPCs, in the hippocampus by flow cytometry. The hierarchical gating strategy is shown by representative dot plots in Fig. 4 I- 4 N and negative staining by isotype control antibodies is shown in Fig. S4 . We first evaluated effects of CUS and CSF1Ri on microglial abundancy and noted a significant interaction effect between CUS and CSF1Ri on the percentage (%) of microglia ( p < 0.05). Also, CSF1Ri showed a significant main effect ( p < 0.0001). CUS alone induced a significant decrease in microglia compared to Ctr-Veh ( p < 0.05; Fig. 4 O). CSF1Ri almost completely depleted microglia in both CUS and CTR conditions (both p < 0.001; Fig. 4 O). Next, to characterize Csf1r level on microglia after CUS and CSF1Ri, we measured MFI of Csf1r and observed a significant decrease induced by CUS compared to Ctr-Veh ( p < 0.01; Fig. 4 P). CUS combined with CSF1Ri increased OPCs in the mouse hippocampus. We observed additional effects of CUS and CSF1Ri on OPCs as well. There was an interaction effect between CUS and CSF1Ri and CSF1Ri had a main effect on OPCs ( p < 0.01 and 0.05). CUS plus CSF1Ri increased OPCs compared to both CUS-Veh and Ctr-CSF1Ri groups (both p < 0.01; Fig. 4 Q). Nevertheless, CUS or CSF1Ri alone didn’t affect OPCs compared to Ctr-Veh (Fig. 4 Q). However, CUS and CSF1Ri did not affect astrocytes (Fig. 4 R). Discussion The current study shows that 1) FES patients perceived higher stress than HCs; 2) CSF1R level and PFC subregional size were decreased in FES patients; 3) CSF1R facilitated supriorfrontal gyral regulation of perceived stress in HCs but not FES patients; 4) CUS and CSF1Ri enhanced anxiety in mice; 5) CUS and/or CSF1Ri downregulated angiogenesis and blood vessel-associated IBA1+-microglia in mice. These are to our knowledge the first evidence revealing the importance of CSF1R in linking vascular microglia with stress regulation as a relevant mechanism in schizophrenia. Our finding of lower CSF1R mRNA in blood cells and CSF1R protein in the serum of FES patients is in line with several previous studies. Lower level of CSF1R mRNA was reported in the cortices [ 31 , 32 , 33 ] and spleens of chronic schizophrenia patients [ 45 ]. The reduction of CSF1R observed in these studies can be affected by disease chronicity or anti-psychotics. By contrast, our current observation on blood CSF1R level had minimal drug effect. Moreover, we found that serum CSF1R protein was negatively correlated with PSS scores and positively moderated hippocampal regulation of PSS scores in HCs but not FES patients, giving hint on impairment of CSF1R function in early stage of schizophrenia. Given that CSF1R is solely expressed by myeloid cells in the brain, and changes in the blood-brain barrier (BBB) permeability have been identified in psychiatric disorders allowing peripheral inflammatory impact on the brain [ 46 ], our findings may be highly relevant for brain pathophysiology of FES. We indeed found that serum CSF1R facilitated hippocampal regulation of perceived stress in HCs but not FES patients. To depict how CSF1R may regulate stress response, we used a CUS mouse model and administered an inhibitor (PLX3397) to block Csf1r in microglia. Importantly, we found that CSF1Ri was anxiogenic to B6N mice similarly as CUS. Our observation corroborates with previous studies reporting that Csf1r +/− mice exhibited anxiety along with cognitive and sensorimotor deficit [ 25 ]. However, other studies have not observed effect of CSF1Ri on anxiety in mice [ 24 ]. These discrepancies may be due to different ways of CSF1Ri administration, which warrant further careful investigations. Interestingly, we found that CUS downregulated some cell adhesion and angiogenic molecules including CD31 in the PFC in mice. IBA1 intensity in VAMg was also more sensitively dampened by CUS compared to NVAMg, implicating a less juxtavascular association of microglial processes. Meanwhile, CUS decreased microglia in the PFC and hippocampus, possibly via inducing apoptosis as suggested by a previous study [ 30 ]. This is supported by our observation that CUS suppressed Csf1r expression that is pivotal for microglial proliferation and survival. Our observation is also in line with an earlier report [ 47 ] and supports our clinical data showing that lower CSF1R was associated with higher PSS. Stress downregulates the BBB tight junction proteins such as Claudin-5, thereby allowing and facilitating the entry of blood-borne components into the brain and glial activation [ 48 , 49 ]. Claudin-5 suppression occurred also in schizophrenia patients and caused schizophrenia-like phenotypes in mice [ 50 ] and changed gene expression of brain endothelial cell adhesion molecules in schizophrenia patients with “high inflammation” was also reported [ 51 ]. Our RNA-seq and IHC findings on CUS are consistent with these previous studies and demonstrate the involvement of microglia in regulating CUS-induced BBB leakage and anxiety. Importantly, we also found that CSF1Ri downregulated most of the cell adhesion and angiogenic DEGs and preferentially diminished juxtavascular VAMg in the PFC in mice. Little is known about microglia-vascular interactions in the adult brain currently. Interestingly, A recent study found that about 30% of microglia are capillary-associated and constantly survey the influx of blood-borne components into living adult mice; furthermore, microglial depletion with CSF1Ri (PLX3397) induced a 15% increase in capillary diameter compared to control [ 52 ]. Our RNA-seq and IHC findings on CSF1Ri strongly support this in vivo imaging study and provide a further depiction of molecular mechanisms on microglial association with neurovascular unit. Other work suggests that microglia could also play a role in repairing damaged BBB caused by systemic inflammation or laser injury [ 53 , 54 ]. However, clinical and preclinical studies on psychiatric conditions are still missing. Out work thereby gives a first glimpse into this theme. The PFC and hippocampus are highly sensitive to stress or anxiety [ 11 ] and schizophrenia patients are well-acknowledged to have cerebral cortical and hippocampal dystrophies [ 8 , 9 , 10 ]. Interestingly, we found that a PFC subarea, the superiorfrontal gyrus, was smaller in FES patients than HCs. Although there was no structural change in the hippocampus, we observed smaller volumes of the neighboring parahippocampal gyrus in FES patients than HCs. Deficits of these regions have been associated with psychotic symptoms such as auditory hallucinations and disordered thoughts in schizophrenia [ 55 , 56 ]. More interestingly, we found that some PFC subregions and the hippocampus were negatively associated with PSS. Furthermore, blood CSF1R mRNA or protein interacted with these brain regions and moderated their negative associations with PSS in HCs but not FES patients. Additionally, CSF1R mRNA level was also negatively correlated with both PSS and PANSSt scores. These suggest the importance of CSF1R in stress regulation via modulating these limbic structures, which might be dysfunctional in FES patients. Besides, PSS scores were positively correlated with PANSSt, supporting the notions that stress exacerbates psychosis [ 4 ] and severity of psychotic symptoms correlates with that of anxiety symptoms [ 57 ]. Our study has several limitations, such as the small sample size in our clinical and preclinical cohorts and the cross-sectional nature of our clinical study design. Nevertheless, our findings suggest that CSF1R may provide a stress-coping mechanism via contribution to microglial patrolling of vasculatures and angiogenesis, which might be disturbed in schizophrenia. These results may be helpful for developing better diagnosis and treatment to tackle neuropsychiatric disorders. List Of Abbreviations ANOVA analysis of variance ANCOVA analysis of covariance BBB blood-brain barrier CSF1R colony stimulating factor 1 receptor CSF1Ri CSF1R inhibition CTR control CUS chronic unpredictable mild stress CTQ childhood trauma questionnaire DEGs differentially expressed genes EPM elevated plus maze FDR false discovery rate FES first-episode schizophrenia GO gene ontology HC healthy controls ICV intracranial volume MFI mean fluorescent intensity MRI magnetic resonance imaging NVAMg nonvessel-associated microglia OFT open field test OPC oligodendrocyte precursor cell PANSSt positive and negative symptom scale-total score PPI protein-protein interaction PSSsum perceived stress scale summation score RNA-seq RNA sequencing TMg total microglia Veh Vehicle VAMg vessel-associated microglia. Declarations Ethics approval and consent to participate The clinical part of the study was approved by the Institutional Ethical Committee of Beijing Huilongguan Hospital. Written informed consent was obtained from each subject. The preclinical part of the study was approved by the Estonian National Board of Animal Experiments. Consent for publication Not applicable Availability of data and materials The data and materials that support the findings of this study are available from the corresponding author upon reasonable request. Conflict of interests LEH has received or plans to receive research funding or consulting fees on research projects from Mitsubishi, Your Energy Systems LLC, Neuralstem, Taisho, Heptares, Pfizer, Luye Pharma, IGC Pharma, Sound Pharma, Takeda, and Regeneron. None was involved in the design, analysis, or outcomes of the study. All other authors declare no competing commercial and financial interests. Funding acknowledgment This work was supported by the National Natural Science Foundation of China grants 81771452 and 82171507, the National Institute of Health grants R01MH112180, the Estonian Research Council-European Union Regional Developmental Fund Mobilitas Plus Program No. MOBTT77 and the Estonian Research Council personal research funding team grant project No. PRG878. Contributions Li Tian, Yunlong Tan, and L. Elliot Hong designed the project and obtained the funding for this study. Yanli Li, Fengmei Fan, Wei Feng, Wei Li, Junchao Huang, Hongna Li, Mengzhuang Gou, and Wenjin Chen were responsible for recruiting patients, performing clinical ratings, neuroimaging, and collecting samples. Ling Yan and Li Tian analyzed all the data and wrote the paper. Yunlong Tan and Li Tian are responsible for the integrity of data and the accuracy of data analysis. Ling Yan performed the CUS model construction and mice behavioural tests and helped Keerthana Chithanathan who did flow cytometry experiment and data analysis. Alexander Zharkovsky was involved in CUS modelling and improved the manuscript. Baopeng Tian, Zhiren Wang, and Shuping Tan were invited in evolving the ideas and editing the manuscript. All authors have contributed to and have approved the final manuscript. References McCutcheon RA, Reis Marques T, and Howes OD. Schizophrenia-An Overview. JAMA Psychiatry. 2020;77:201–10. Winship IR, Dursun SM, Baker GB, Balista PA, Kandratavicius L, Maia-de-Oliveira JP, et al. An Overview of Animal Models Related to Schizophrenia. Can J Psychiatry. 2019;64:5–17. Pruessner M, Cullen AE, Aas M, and Walker EF. The neural diathesis-stress model of schizophrenia revisited: An update on recent findings considering illness stage and neurobiological and methodological complexities. Neurosci Biobehav Rev. 2017;73:191–218. Gomes FV and Grace AA. 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Additional Declarations The authors have declared there is NO conflict of interest to disclose Supplementary Files SupplTables14.xlsx Suppl.Fig.1.png Suppl.Fig.2.png Suppl.Fig.3.png Suppl.Fig.4.png Cite Share Download PDF Status: Posted Version 1 posted 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-1777009","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":115637451,"identity":"39652dd1-4f29-4b75-a3c6-e242482d187b","order_by":0,"name":"Li 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(\u003cstrong\u003eB) \u003c/strong\u003ePANSSt was positively correlated with PSSsum in FES patients (n=51) (Spearman’s correlation). (\u003cstrong\u003eC\u003c/strong\u003e)\u003cstrong\u003e \u003c/strong\u003eExemplary MRI images show the significantly smaller cortical regions in FES patients as compared to HCs, after FDR correction and controlling for age and sex. Color gradient is based on the statistical \u003cem\u003eF\u003c/em\u003e values of group comparison. (\u003cstrong\u003eD and E)\u003c/strong\u003e Volumes of the superiorfrontal and the parahippocampal gyri were smaller in FES patients than HCs.\u003cstrong\u003e \u003c/strong\u003eData presented as mean±SEM; ** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01. See also \u003cstrong\u003eTable 2\u003c/strong\u003e. \u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1777009/v1/d1ba2b93708fd853265c10b4.jpg"},{"id":23335096,"identity":"e4e13b74-19b2-4b33-a489-6167992c1f9d","added_by":"auto","created_at":"2022-07-01 17:10:26","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":735295,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBlood CSF1R was decreased in FES patients along with some blood DEGs associated with brain development and facilitated a negative association of the superiorfrontal gyrus with the PSSsum in HCs. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Volcano plot highlights 28 blood DEGs that were down-regulated (blue, 17 DEGs including \u003cem\u003eCSF1R\u003c/em\u003e) or up-regulated (red, 11 DEGs) in FES patients (n=128) versus HCs (n=111), measured by RNA-seq. Genes with FDR\u0026lt;0.01 are colored. (\u003cstrong\u003eB\u003c/strong\u003e) Venn diagram illustrates the 28 DEGs that are annotated to be associated with human brain structural development in GeneWeaver. (\u003cstrong\u003eC\u003c/strong\u003e) PPI analysis shows interactions of the 28 DEGs with confidence threshold=0.4 and cluster k-means=3. Line between nodes features the type/strength of an interaction according to annotations in String v11. (\u003cstrong\u003eD\u003c/strong\u003e) Chord plot shows top 6 overrepresented GO-BP subontology for the 28 DEGs associated with brain development. Genes are ordered according to the observed Log2FC and linked to their assigned terms via colored ribbons. (\u003cstrong\u003eE\u003c/strong\u003e) CSF1R protein level was significantly downregulated in the sera of FES patients (n=47) compared to HCs (n=40), controlled by age, sex, and total white blood cells. \u0026nbsp;(\u003cstrong\u003eF)\u003c/strong\u003e Blood \u003cem\u003eCSF1R\u003c/em\u003e mRNA level fully moderated the negative association of the superiorfrontal gyral volume (independent variable) with the PSSsum score (dependent variable), controlled by age, sex, and ICV in HCs (n=41). Data presented as mean±SEM; * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 (ANCOVA). See also \u003cstrong\u003eTables S1 \u003c/strong\u003eand\u003cstrong\u003e S2, \u003c/strong\u003eand \u003cstrong\u003eFigure S1\u003c/strong\u003e.\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1777009/v1/7ae36c668257019690dd47c8.jpg"},{"id":23335533,"identity":"6deae353-1361-4ff9-ab43-49e6c5b02991","added_by":"auto","created_at":"2022-07-01 17:15:26","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":676862,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCUS and CSF1Ri enhanced anxiety and inhibited angiogenic genes in mice. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Schema representing experimental design on four groups of 3-month-old male C57BL/6N mice (n=9~10/group). (\u003cstrong\u003eB and C) \u003c/strong\u003eBehavioral tests for anxiety showed enhanced anxiety as indicated by decreases of (\u003cstrong\u003eB\u003c/strong\u003e) the ratio (%) of travel distance in the center (m) against total travel distance (m) in an open field and (\u003cstrong\u003eC) \u003c/strong\u003ethe\u003cstrong\u003e \u003c/strong\u003eratio (%) of time spent in open arm against closed arm in an elevated plus maze after CUS and CSF1Ri as compared to Ctr-Veh. (\u003cstrong\u003eD-F\u003c/strong\u003e) RNA-seq of the PFC (n=7/group). (\u003cstrong\u003eD\u003c/strong\u003e) GO-BP enrichment analysis showed top-ranked pathways involving cell adhesion and angiogenesis. (\u003cstrong\u003eE\u003c/strong\u003e) Volcano plot of DEGs as colored based on -Log10adj.P (1.3) and |Log2FC| (0.2) threshold values. Angiogenic DEGs are labelled and marked in red dots. (\u003cstrong\u003eF\u003c/strong\u003e) Heatmap of 38 angiogenic DEGs, most of which were downregulated after CSF1Ri. CUS: chronic unpredictable stress; Ctr: Control; CSF1Ri: CSF1R inhibitor; Veh: Vehicle. Data presented as mean±SEM; * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 in CUS \u003cem\u003evs \u003c/em\u003eCtr comparisons; # \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, ## \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, ### \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001 in Veh \u003cem\u003evs\u003c/em\u003e CSF1Ri within Ctr groups (Two-way ANOVA). See also \u003cstrong\u003eTables S3 and S4\u003c/strong\u003e.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1777009/v1/2eadeaa808a855d01243e92c.jpg"},{"id":23335098,"identity":"8d18cbbc-0526-4b90-8bd7-7b6ec61424ce","added_by":"auto","created_at":"2022-07-01 17:10:26","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":898136,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCUS and CSF1Ri reduced microglial populations, especially VAMg in mice. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Representative staining of CD31 and IBA1 in the PFC (scale bar=20 µm). (\u003cstrong\u003eB\u003c/strong\u003e) Intensity of CD31 was reduced by CSF1Ri. (\u003cstrong\u003eC and D\u003c/strong\u003e) TMg (including VAMg and NVAMg) and total IBA1 intensity were decreased by CUS and CSF1Ri. (\u003cstrong\u003eE and F\u003c/strong\u003e) Ratios of VAMg No./TMg No. and IBA1 intensity in VAMg/TMg were dampened by CSF1Ri. Ratio of IBA1 intensity was also dampened by CUS. (\u003cstrong\u003eG and H\u003c/strong\u003e) Ratios of NVAMg No./TMg No. and IBA1 intensity in NVAMg/TMg were elevated by CSF1Ri. Ratio of IBA1 intensity was also raised by CUS. All were compared to Ctr-Veh group (n=3 mice per group). (\u003cstrong\u003eI-N\u003c/strong\u003e) Representative flow cytometry dot plots showing gating strategy for hippocampal Mg, Csf1r\u003csup\u003e+\u003c/sup\u003e Mg, OPCs, and astrocytes (n=7 mice per group). (\u003cstrong\u003eO\u003c/strong\u003e) Mg percentage was reduced by CUS and more so by CSF1Ri compared to Ctr-Veh. (\u003cstrong\u003eP\u003c/strong\u003e) Csf1r mean fluorescent intensity (MFI) on Mg was dampened by CUS compared to Ctr-Veh; (\u003cstrong\u003eQ\u003c/strong\u003e) Percentage of OPCs was increased by CUS combined with CSF1Ri. (\u003cstrong\u003eR\u003c/strong\u003e) Percentage of astrocytes was unchanged. Ctr: control; CUS: chronic unpredictable stress; CSF1Ri: CSF1R inhibitor; OPC: oligodendrocyte precursor cell; Veh: vehicle; VAMg: vessel-associated microglia; NVAMG: nonvessel-associated microglia. Data presented as mean±SEM; * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, ** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01 in CUS \u003cem\u003evs \u003c/em\u003eCtr comparison; \u0026amp;\u0026amp; \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, \u0026amp;\u0026amp;\u0026amp; \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001 within CUS groups; # \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, ## \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, ### \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001 within Ctr groups (Two-way ANOVA). See also \u003cstrong\u003eFig. S1 and S2\u003c/strong\u003e. \u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Fig.4vertical.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1777009/v1/2d7d6c6bacb1f2eac94cb09b.jpg"},{"id":29020679,"identity":"6052ba23-db7c-4e7c-b01d-31c56bd7a1bd","added_by":"auto","created_at":"2022-11-14 11:03:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1277737,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1777009/v1/d00a75e9-cdfc-477e-903a-1fd3c453c858.pdf"},{"id":23335104,"identity":"75ef3fcb-00cc-4f96-a1c2-4bc91e14c886","added_by":"auto","created_at":"2022-07-01 17:10:26","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":96573,"visible":true,"origin":"","legend":"","description":"","filename":"SupplTables14.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1777009/v1/5f3997e4be497f31542a638e.xlsx"},{"id":23335103,"identity":"5586b8a8-1a2a-489a-8d34-1352b44b7a3d","added_by":"auto","created_at":"2022-07-01 17:10:26","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":223191,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-1777009/v1/699028a860c0832f0f282c06.png"},{"id":23335534,"identity":"17b1e0fd-a3f8-4336-8e9d-d112c7d0e7de","added_by":"auto","created_at":"2022-07-01 17:15:26","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":562674,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-1777009/v1/06fce51067d6ddc51aa9fe98.png"},{"id":23335101,"identity":"d4a95976-64e7-40d9-ad49-97569ae8b3fa","added_by":"auto","created_at":"2022-07-01 17:10:26","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":262425,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-1777009/v1/bd8ff71be238602845477551.png"},{"id":23335100,"identity":"2072bcca-8b9c-4c25-815a-43c8cf364eff","added_by":"auto","created_at":"2022-07-01 17:10:26","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":1234061,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-1777009/v1/ac4e5b74b6e6c9957f5c19b2.png"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"CSF1R Contributes to Vascular Association of Microglia and Stress Regulation in Schizophrenia","fulltext":[{"header":"Highlights","content":"\u003col\u003e\n \u003cli\u003eFES patients perceived higher stress than HCs.\u003c/li\u003e\n \u003cli\u003eBlood CSF1R level and volumes of the superiorfrontal and parahippocampal gyri were decreased in FES patients compared to HCs.\u003c/li\u003e\n \u003cli\u003eCSF1R facilitated superiorfrontal gyral regulation of perceived stress in HCs but not FES patients.\u003c/li\u003e\n \u003cli\u003eBoth CUS and CSF1Ri induced anxiety in mice.\u003c/li\u003e\n \u003cli\u003eCUS and CSF1Ri downregulated angiogenesis and blood vessel-associated IBA1\u003csup\u003e+\u003c/sup\u003e-microglia in mice.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Introduction","content":"\u003cp\u003eSchizophrenia is a complex neurodevelopmental disorder usually caused by environmental insults on genetically predisposed individuals [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], which can be recapitulated in animal models [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Psychosocial stressors have been shown to trigger or exacerbate symptoms of schizophrenia [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Heightened stress response, as measured by perceived stress scale (PSS), preceded the onset of psychosis in both schizophrenia patients [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and rodents [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Patients of first episode psychosis also showed higher PSS scores along with affective or psychotic symptoms than healthy controls (HCs) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDystrophies of the cortical and associated limbic structures are frequently observed in both schizophrenia patients [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and animal models of chronic psychosocial stress [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Neurobiological substrates underlying stress-induced brain changes may include impaired neuronal projections across the hippocampus-associated structures [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and enhanced local microglia/astrocytes-mediated neuroinflammation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Glia are important regulators for brain development and functional connectivity. Their dysfunctions can enhance synaptic pruning, prevent angiogenesis and neurogenesis, induce neuronal and myelinic loss, as evidenced from both human and animal studies [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eColony stimulating factor 1 receptor (CSF1R) is a receptor tyrosine kinase crucial for development, survival, and proliferation of myeloid cells [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Both human subjects with \u003cem\u003eCSF1R\u003c/em\u003e loss-of-function mutation and \u003cem\u003eCsf1r\u003c/em\u003e\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice display shortened lifespan, loss of microglia and macrophages, and neurodevelopmental abnormalities [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. While genetic or pharmacological inhibition of CSF1R (CSF1Ri) produced no gross behavioral changes in adult animals [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], recent studies demonstrated that \u003cem\u003eCsf1r\u003c/em\u003e haplodeficiency was anxiogenic to mice [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]; CSF1Ri-induced microglial ablation enhanced learning and fear memory [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] while microglial repopulation corrected repetitive behaviour and social deficits [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]; CSF1-induced microglial proliferation also ameliorated depressive-like behavior in mice after chronic unpredictable stress (CUS) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Lower CSF1R in the post-mortem brains of chronic schizophrenia patients was reported [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, the exact role of CSF1R in schizophrenia in association with psychosocial stress has remained unclear.\u003c/p\u003e \u003cp\u003eWe have reported that cumulative stress may contribute to cortical thickness and cognitive deficits in first-episode schizophrenia (FES) patients [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In the present study, we performed blood RNA sequencing (RNA-Seq) and proteomic array, assessed cortical structures by magnetic resonance imaging (MRI), and used a CUS mouse model combined with pharmacological CSF1Ri to characterize the underlying mechanisms of schizophrenia-associated stress and anxiety regulated by microglia.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u0026rsquo; demographic and clinical measures\u003c/h2\u003e \u003cp\u003eFES Patients (n\u0026thinsp;=\u0026thinsp;51) recruited for this study were from the Beijing Hui Long Guan Hospital. Patients were diagnosed schizophrenia according to the Structured Clinical Interview for DSM-IV (SCID) independently by two psychiatrists. HC participants (n\u0026thinsp;=\u0026thinsp;46) matched for age and sex were recruited from local community. Candidates who unmet recruitment criteria were excluded. All participants provided written informed consent. The study was approved by the Institutional Ethical Committee of Beijing Huilongguan Hospital.\u003c/p\u003e \u003cp\u003eParticipants\u0026rsquo; past traumatic experiences were evaluated by Childhood Trauma Questionnaire (CTQ), a 29-item self-reported questionnaire of a retrospective measure encompassing five factors: physical abuse, emotional abuse, sexual abuse, physical neglect, and emotional neglect [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] validated in Chinese [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Participants\u0026rsquo; stress levels were evaluated based on PSS, a 14-item self-reported questionnaire measuring feelings and thoughts during the last month [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] validated in Chinese [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Positive and Negative Syndrome Scale total scores (PANSSt) were measured independently by two psychiatrists (For details see supplementary materials).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eHuman and mouse RNA-seq and data analysis\u003c/h2\u003e \u003cp\u003eHuman blood (5ml) was collected between 7-9am after overnight fasting using PAXgene\u0026trade; blood RNA tubes (Applied Biosystems). Tubes were shaken vigorously for at least 10 seconds after sampling and immediately stored at -80\u0026deg;C. Total RNAs were extracted using Mag-MAX\u0026trade; for Stabilized Blood Tubes RNA Isolation Kit (Applied Biosystems) following the manufacturer\u0026rsquo;s instructions. Mice were euthanized with CO\u003csub\u003e2\u003c/sub\u003e and the prefrontal cortices were dissected and immediately stored at -80\u0026deg;C. Total RNAs were extracted using Trizol (Molecular Research Center). RNAs were quantified and assessed for purity by optical density ratios of 260nm/280nm and 260nm/230nm using NanoDrop spectrophotometry (ThermoFisher). RNA samples (1\u0026micro;g per sample) were immediately sent to the Beijing Genomics institution (BGI) for mRNA (after globin mRNA removal) sequencing on the BGIseq-500 platform. Quality control (QC) on RNA samples (RIN/RQN\u0026thinsp;\u0026ge;\u0026thinsp;7.0, 28S/18S\u0026thinsp;\u0026ge;\u0026thinsp;1.0) was confirmed by BGI. Clean data of at least 4Gb (20M clean reads) per sample were collected.\u003c/p\u003e \u003cp\u003eQC of RNA-seq data and gene expression analysis were done on the Galaxy and NetworkAnalyst platforms [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] using DESEQ2. Data with variance percentile rank\u0026thinsp;\u0026lt;\u0026thinsp;15% and counts\u0026thinsp;\u0026lt;\u0026thinsp;4 were filtered out. Counts per million reads were transformed, normalized and calculated to Log2 fold changes (Log2FC) for differentially expressed genes (DEGs). DEGs with Benjamini-Hochberg\u0026rsquo;s false discovery rate (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were subjected to analyses of gene ontology biological pathway (GO-BP) and protein-protein interaction (PPI) in David (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://david.ncifcrf.gov/\u003c/span\u003e\u003cspan address=\"https://david.ncifcrf.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and STRING v11.5 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org/cgi/input.pl\u003c/span\u003e\u003cspan address=\"https://string-db.org/cgi/input.pl\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eGeneWeaver brain functional genomic data\u003c/h2\u003e \u003cp\u003eGeneWeaver, a database for the integration and analysis of heterogeneous functional genomics data (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://geneweaver.org/\u003c/span\u003e\u003cspan address=\"https://geneweaver.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), was explored to dig out CSF1R-associated genesets annotated to contribute to human brain development. Annotated gene series GS393224 (Abnormality of brain morphology), GS393415 (Hydrocephalus), GS393709 (Abnormality of neuronal migration), GS395524 (Ventriculomegaly) were retrieved for further comparisons to blood RNA-seq DEGs and GO-BP analysis as described above.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSerum CSF1R protein detection by antibody array\u003c/h2\u003e \u003cp\u003eBlood samples (5ml) were collected as described above. After 15 minutes (min), sera were separated by centrifugation at 4000 rpm for 10min, which were immediately stored at -80\u0026deg;C until assayed. Samples were sent for human antibody microarray detection (AAH-BLG-1000, RayBiotech) to identify candidate biomarkers including CSF1R. Briefly, primary amines of proteins were biotinylated in dialyzed seral samples. Glass slides pre-printed with capture antibodies were blocked, biotin-labelled samples were added and incubated to capture target proteins. Streptavidin-conjugated Cy3 was then applied to the glass slides, which were washed, dried, and finally sent for laser fluorescence scanning (GenePix 4000B scanner). Signal intensity data after background subtraction and normalization were exported into the RayBio\u0026reg; Analysis Tool software for protein quantification.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMRI acquisition and processing\u003c/h2\u003e \u003cp\u003eBrain structural MRI data were acquired using a Siemens Prisma 3.0T MRI scanner with a 64-channel head coil. Sagittal images were collected following the ENIGMA protocol with FreeSurfer software [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Intracranial volume (ICV) and regional volumes of bi- hemispheric cerebral cortical/subcortical structures were measured (For details see supplementary materials).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMouse CUS and CSF1Ri (PLX3397) treatment procedures\u003c/h2\u003e \u003cp\u003eWild-type C57BL/6NTac male mice (3-month-old, Taconic) were bred in laboratory animal facility at the Institute of Biomedicine and Translational Medicine, University of Tartu. Mice were kept under standard breeding conditions. All animal procedures were performed in accordance with the European Communities Directive with the license No. 171 issued from the Estonian National Board of Animal Experiments.\u003c/p\u003e \u003cp\u003eAfter a week (wk) of transfer adaptation, mice were randomly assigned into 4 groups: Control (Ctr)-Vehicle (Veh) (n\u0026thinsp;=\u0026thinsp;9), CUS-Veh (n\u0026thinsp;=\u0026thinsp;9), Ctr-CSF1Ri (n\u0026thinsp;=\u0026thinsp;10), and CUS-CSF1Ri (n\u0026thinsp;=\u0026thinsp;10), and subject to CUS/Ctr and CSF1Ri (PLX3397)/Veh treatments. CUS procedure was previously described [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. PLX3397 (HY-16749/CS-4256, MedChemExpress) was dissolved in DMSO (D8418, Sigma-Aldrich) and freshly diluted with corn oil (#8267, Sigma-Aldrich). Drug-treated mice were daily fed [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] with Veh or PLX3397 (~\u0026thinsp;120mg/kg bodyweight) in Nutella. Mice were treated with PLX3397 or Veh for 2wk starting from the 7th wk of CUS. Behavioral experiments were performed at the 8th wk (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eA) (For details see supplementary materials).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eOpen field test (OFT)\u003c/h2\u003e \u003cp\u003eMice were habituated to room light for 1 hour (h). Individual mouse was measured for distance and time travelled in different zones of a digital box (44.8\u0026times;44.8\u0026times;45cm) via a software (Technical \u0026amp; Scientific Equipment GmbH) for 30min. The floor of the box was cleaned with 70% ethanol and dried thoroughly after each mouse.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eElevated plus maze (EPM)\u003c/h2\u003e \u003cp\u003eEPM consisted of open and closed arms (30\u0026times;5cm each) intersected at a central 5\u0026times;5cm square platform elevated to a height of 80cm. On testing day, mice were habituated to 40W room light for 1 h. Each mouse was placed individually on the central platform facing the open arm and recorded for time spent on open/close arms by a software (EthoVision XT, Noduls) for 5min. The arms were cleaned with 70% ethanol and dried thoroughly after each mouse.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBrain tissue processing and immunohistochemistry\u003c/h2\u003e \u003cp\u003eMice were anesthetized with intraperitoneal ketamine/xylazine and transcardially perfused with PBS and 4% paraformaldehyde. The post-fixed brains were cryoprotected and stored at -80\u0026deg;C before cryosectioning at -20\u0026deg;C. Coronal sections of the prefrontal cortex (PFC) in 40\u0026micro;m-thickness were processed and incubated with primary antibodies including rabbit anti-IBA1 (#SKL6615, Wako, 1:500) and rat anti-CD31 (#553370, BD Pharmingen, 1:250, kind gift by Prof. Tambet Teesalu) in PBS blocking buffer overnight at 4\u0026deg;C, followed by goat anti-rabbit IgG H\u0026amp;L-AlexaFluor488 (#ab175471, Abcam, 1:500) and goat anti-rat IgG H\u0026amp;L-AlexaFluor546 (#119170, Jackson ImmunoResearch, 1:500) for 2h at room temperature and then in 0.1\u0026micro;g/ml DAPI (#ACRO202710100, VWR) for 5min. After mounting to glass slides with Fluoromount\u0026trade; Aqueous Mounting Medium (# F4680-25ML, Sigma-Aldrich). Z-stack images were taken by a FV1200MPE laser scanning microscope at 60\u0026times; resolution with a CCD camera (Olympus) (For details see supplementary materials). Cell numbers and fluorescent intensities of CD31 and IBA1 were quantified using ImageJ. IBA1\u003csup\u003e+\u003c/sup\u003e-microglia whose cell soma located within the range of vascular radius surrounding a blood vessel were defined as vessel-associated microglia (VAMg) and others as nonvessel-associated microglia (NVAMg). Three PFC sections per mouse were randomly imaged (n\u0026thinsp;=\u0026thinsp;3 mice per group).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFlow cytometry\u003c/h2\u003e \u003cp\u003eMice were euthanized with CO\u003csub\u003e2\u003c/sub\u003e. Dissected hippocampi were gently homogenized through 70\u0026micro;m cell strainers (#352350, BD Bioscience) in ice-cold PBS\u0026thinsp;+\u0026thinsp;1% fetal bovine serum (FBS). Homogenates were washed, centrifuged at 500g for 5min, and blocked with PBS\u0026thinsp;+\u0026thinsp;10% rat serum for 1h, then stained with flow markers (BioLegend and Miltenyi) of anti-mouse Csf1r-Brilliant Violet (BV)605 (#135517), CD11b-BV421 (#101251), CD45-BV650 (#103151BioLegend), Glast-APC (#130-123-555), and O4-PE (#130-117-357) for 1h (For isotype control details see supplementary materials). Washed cells were resuspended in 500\u0026micro;l PBS and acquired with a Fortessa flow cytometer (BD Bioscience). Data were analyzed by Kaluza v2.1 software (Beckman Coulter). Astrocytes were defined as Glast\u003csup\u003e+\u003c/sup\u003e cells, oligodendrocyte precursor cells (OPCs) as O4\u003csup\u003e+\u003c/sup\u003e cells, microglia as CD45\u003csup\u003elow\u003c/sup\u003eCD11b\u003csup\u003ehi\u003c/sup\u003e cells. Cell populations were calculated as the % among total brain cells and mean fluorescent intensity (MFI) of Csf1r in Csf1r\u003csup\u003e+\u003c/sup\u003e microglia were calculated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData distributions were examined by Shapiro-Wilkinson\u0026rsquo;s test. Depending on data normality, one-way analysis of variance (ANOVA) or Mann-Whitney U test was used for continuous variables and chi-squared tests for categorical variables. Analysis of covariance (ANCOVA) with age and sex as covariates was conducted for serum CSF1R and MRI data, and white blood cells and ICV were included as additional covariates for them, respectively. \u003cem\u003eP\u003c/em\u003e values for multiple comparisons were corrected by FDR. Relationships among CSF1R level, cortical size, and PSS score were evaluated using linear regression and moderator analysis by PROCESS v3.5 in SPSS v27.0 (IBM), controlled by age, sex, and ICV. For animal data, two-way ANOVA was used to examine the interaction between CUS and CSF1Ri, as well as their main effects, with post hoc Tukey's correction for post hoc comparisons. Figures were prepared in GraphPad Prism v8.0.1 and online (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.bioinformatics.com.cn/\u003c/span\u003e\u003cspan address=\"http://www.bioinformatics.com.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Data were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM and \u003cem\u003ep\u003c/em\u003e or FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eFES patients showed higher perceived stress than HCs.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eParticipants\u0026rsquo; demographic and clinical data are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. FES patients and HCs were not statistically different in age, sex, education years and CTQ score (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, compared with HCs, FES patients had higher PSS score (FES: 23.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99, HC: 21.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), which was positively correlated with PANSSt score (r\u0026thinsp;=\u0026thinsp;0.334, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e\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\u003eDemographic characteristics of FES patients and HCs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"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\u003eDemographics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFES (n\u0026thinsp;=\u0026thinsp;51)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHC (n\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF or \u0026#120594;2\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\u003eSex (M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18/33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23/23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.59 (1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.00 (1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1388.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation (years)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.75 (0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.28 (0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1298.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.354\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCTQsum*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.55 (5.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.02 (4.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e727.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSSsum*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.14 (0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.39 (0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e893.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.043\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge of illness onset (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.27 (1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIllness duration (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.70 (2.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePANSSt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.69 (2.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cells (10\u003csup\u003e6\u003c/sup\u003e/ml)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.60 (1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.01 (0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e856.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum CSF1R (\u0026micro;g/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.31 (0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.49 (0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAll data were reported as mean (SEM); FES: first episode schizophrenia; HC: healthy control; FDR: false discovery rate; CSF1R: colony stimulating factor 1 receptor; CTQ: childhood trauma questionnaire; PSS: perceived stress scale; PANSSt: positive and negative symptom scale total score. CSF1R (ANCOVA controlled by age, sex, and white blood cells); Significant \u003cem\u003ep\u003c/em\u003e values are shown in bold texts. *: Mann-Whitney U test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\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\u003eCerebral cortical volumes (cm\u003csup\u003e3\u003c/sup\u003e) in FES patients and HCs\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=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" 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\u003eCortical regions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFES (n\u0026thinsp;=\u0026thinsp;51)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHC (n\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFDR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnteriocingulate gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.729\u0026thinsp;\u0026plusmn;\u0026thinsp;0.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e7.927\u0026thinsp;\u0026plusmn;\u0026thinsp;0.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.467\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEntorhinal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.152\u0026thinsp;\u0026plusmn;\u0026thinsp;0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.136\u0026thinsp;\u0026plusmn;\u0026thinsp;0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.581\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHippocampus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.039\u0026thinsp;\u0026plusmn;\u0026thinsp;0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.109\u0026thinsp;\u0026plusmn;\u0026thinsp;0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInferiorfrontal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e19.233\u0026thinsp;\u0026plusmn;\u0026thinsp;0.296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e19.679\u0026thinsp;\u0026plusmn;\u0026thinsp;0.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.416\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddlefrontal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e40.051\u0026thinsp;\u0026plusmn;\u0026thinsp;0.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e41.388\u0026thinsp;\u0026plusmn;\u0026thinsp;0.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrbitalfrontal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e23.791\u0026thinsp;\u0026plusmn;\u0026thinsp;0.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e24.445\u0026thinsp;\u0026plusmn;\u0026thinsp;0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParahippocampal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.505\u0026thinsp;\u0026plusmn;\u0026thinsp;0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.723\u0026thinsp;\u0026plusmn;\u0026thinsp;0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.032\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuperiorfrontal gyrus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e39.134\u0026thinsp;\u0026plusmn;\u0026thinsp;0.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e40.803\u0026thinsp;\u0026plusmn;\u0026thinsp;0.760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eFES: first episode schizophrenia; HC: healthy control; ANCOVA controlled by age, sex and intracranial volume (ICV) and corrected for multiple comparisons among 8 regions; Bold texts indicate those with significant \u003cem\u003ep\u003c/em\u003e and false discovery rate (FDR) values.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eCerebral cortical regions were smaller in FES patients.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe first studied 8 key stress-related brain regions, including the PFC subareas, hippocampus, and hippocampus-associated entorhinal and parahippocampal gyri (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and observed significantly reduced volumes in the superiorfrontal gyrus (FES: 37.134\u0026thinsp;\u0026plusmn;\u0026thinsp;0.641, HC: 40.803\u0026thinsp;\u0026plusmn;\u0026thinsp;0.760, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005, FDR\u0026thinsp;=\u0026thinsp;0.02; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) and parahippocampal gyrus (FES: 3.505\u0026thinsp;\u0026plusmn;\u0026thinsp;0.048, HC: 3.723\u0026thinsp;\u0026plusmn;\u0026thinsp;0.058; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.004, FDR\u0026thinsp;=\u0026thinsp;0.032; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eE) in FES patients compared to HCs. Additionally, the orbitalfrontal gyrus also showed nominal significance in reduction in FES patients compared to HCs (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The hippocampus and other cortical structures did not show significant differences, however (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eBlood CSF1R mRNA and protein levels were lower in FES patients.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe next endeavoured to find out immune mechanisms underlying stress perception. We earlier had collected whole blood samples from a cohort of 128 FES patients and 111 HCs, including the subjects of our current study, and we identified 9062 DEGs by RNA-seq (submitted work). These DEGs include downregulated \u003cem\u003eCSF1R\u003c/em\u003e (Log2FC=-0.195, FDR\u0026thinsp;=\u0026thinsp;0.003). CSF1R is among the best-known immune receptors to affect microglia-associated brain development and behavior. Hence, we first explored functional genomic data in GeneWeaver and retrieved 64 \u003cem\u003eCSF1R\u003c/em\u003e-associted brain genes that contribute to human brain development. We aligned these 64 genes with our RNA-seq DEGs by Venn analysis, which showed 11 overlapping up-regulated genes and 17 overlapping down-regulated genes as visualized in a volcano plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). These 28 DEGs included \u003cem\u003eCSF1R\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, \u003cb\u003eTable S1\u003c/b\u003e). We further measured CSF1R protein in the serum and confirmed its downregulation in FES patients compared to HCs (FES: 18.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95, HCs: 20.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90 \u0026micro;g/ml; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eE, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). To depict functional relationships among the 28 DEGs, we studied their GO enrichment, showing top-ranked signalling pathways involved in developmental processes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eD, \u003cb\u003eTable S2\u003c/b\u003e), and PPI, showing three different functional clusters with hub molecules such as AKT1, and CSF1R (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eCSF1R\u003c/span\u003e \u003cb\u003efully moderated superiorfrontal gyral negative association with stress perception in HCs.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe further explored inter-relationships among the cortical structures, CSF1R mRNA or protein, and PSS with linear regression and moderator analyses, predicting that PSSsum was the dependent variable, cortical volumes the independent variables, and CSF1R level the moderator, controlled by age, sex and ICV. The model showed that in HCs but not FES patients, \u003cem\u003eCSF1R\u003c/em\u003e mRNA was negatively associated with PSSsum (β=-9.784, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). \u003cem\u003eCSF1R\u003c/em\u003e also interacted with the superiorfrontal gyrus (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.083, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eF) and fully moderated superiorfrontal gyral regulation of the PSSsum (β\u0026thinsp;=\u0026thinsp;6.109, 95% confidence interval (CI)\u0026thinsp;=\u0026thinsp;1.642\u0026thinsp;~\u0026thinsp;10.578, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). We also found that in FES patients, \u003cem\u003eCSF1R\u003c/em\u003e mRNA was negatively correlated with PSS score (r=-0.299, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; \u003cb\u003eFig. S1A\u003c/b\u003e) and PANSSt score (r=-0.329, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; \u003cb\u003eFig. S1B).\u003c/b\u003e Additionally, CSF1R mRNA and protein also moderated the negative associations of the middlefrontal gyrus (β\u0026thinsp;=\u0026thinsp;0.383, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; \u003cb\u003eFig. S1C)\u003c/b\u003e and the hippocampus (β\u0026thinsp;=\u0026thinsp;0.477, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; \u003cb\u003eFig. S1C\u003c/b\u003e) with the PSSsum, respectively, in HCs.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCUS and CSF1Ri enhanced anxiety in mice.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eConsidering the above clinical observations, we postulated that microglial CSF1R may provide a protective mechanism in the brain for stress regulation. To address this question, we applied a CUS mouse model (lasting 8wk) combined with a CSF1Ri (3mg PLX3397/mouse/day for 2wk) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). We first evaluated anxiety of the four groups of mice in response to these treatments, as measured in OFT and EPM. Significant interaction and main effects of CUS and CSF1Ri on the ratio of central distance/total distance in OFT and the ratio of open/close arms time were observed (both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). CUS alone induced anxiety compared to Ctr-Veh (OFT: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; EPM: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). CSF1Ri alone also enhanced anxiety compared to Ctr-Veh (both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCUS and CSF1Ri inhibited angiogenesis and vascular association of microglia in the mouse PFC.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe next studied the PFC by RNA-seq and identified 2750 DEGs including 1204 upregulated and 1546 downregulated DEGs among the four groups. GO-BP enrichment analysis of these DEGs showed cell adhesion and angiogenesis as the top-ranking pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eD, \u003cb\u003eTables S3 and S4\u003c/b\u003e). There were 115 DEGs involved in cell adhesion (\u003cb\u003eFig. S2\u003c/b\u003e) and 38 DEGs involved in angiogenesis, with most of the angiogenic DEGs downregulated in Ctr-CSF1Ri or CUS-CSF1Ri group than Ctr-Veh group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eE \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003eF), suggesting that CUS and CSF1Ri could interfere angiogenesis.\u003c/p\u003e \u003cp\u003eTo verify the effect of CUS and CSF1Ri on angiogenesis, we stained the PFC sections for CD31 and IBA1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. There was a significant interaction effect between CUS and CSF1Ri on the intensity of CD31 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), which was decreased in CUS alone compared to Ctr-Veh group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB) and trendily so in Ctr-CSF1Ri group compared to Ctr-Veh group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.08; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003eFor IBA1\u003csup\u003e+\u003c/sup\u003e-microglia, we classified them into VAMg (e.g., microglia whose cell soma resided on or adjacent to blood vessels) and NVAMg (e.g., non-vessel associated microglia) among the total microglia (TMg) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Significant interaction between CUS and CSF1Ri and main effect of CSF1Ri on the parameters as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH were found (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting antagonizing effects of CUS and CSF1Ri on VAMg. CUS and CSF1Ri alone induced reductions of number (No.) of TMg (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and 0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC) and IBA1 intensity (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and 0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003eInterestingly, CSF1Ri alone dampened the ratio of VAMg No./TMg No. but elevated the ratio of NVAMg No./TMg No. compared to Ctr-Veh (both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG). Moreover, CUS and CSF1Ri alone suppressed the ratio of IBA1 intensity in VAMg/TMg but raised the ratio of IBA1 intensity in NVAMg/TMg compared to Ctr-Veh (both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH). CSF1Ri alone also showed similar effects on these two parameters compared to Ctr-Veh (both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH, \u003cb\u003eFig. S3\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCUS decreased microglia and dampened microglial Csf1r expression in the mouse hippocampus.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe further validated CSF1Ri by quantifying microglia along with other glial populations, namely astrocytes and OPCs, in the hippocampus by flow cytometry. The hierarchical gating strategy is shown by representative dot plots in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eN and negative staining by isotype control antibodies is shown in \u003cb\u003eFig. S4\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eWe first evaluated effects of CUS and CSF1Ri on microglial abundancy and noted a significant interaction effect between CUS and CSF1Ri on the percentage (%) of microglia (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Also, CSF1Ri showed a significant main effect (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). CUS alone induced a significant decrease in microglia compared to Ctr-Veh (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eO). CSF1Ri almost completely depleted microglia in both CUS and CTR conditions (both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eO). Next, to characterize Csf1r level on microglia after CUS and CSF1Ri, we measured MFI of Csf1r and observed a significant decrease induced by CUS compared to Ctr-Veh (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eP).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCUS combined with CSF1Ri increased OPCs in the mouse hippocampus.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe observed additional effects of CUS and CSF1Ri on OPCs as well. There was an interaction effect between CUS and CSF1Ri and CSF1Ri had a main effect on OPCs (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and 0.05). CUS plus CSF1Ri increased OPCs compared to both CUS-Veh and Ctr-CSF1Ri groups (both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eQ). Nevertheless, CUS or CSF1Ri alone didn\u0026rsquo;t affect OPCs compared to Ctr-Veh (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eQ). However, CUS and CSF1Ri did not affect astrocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eR).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current study shows that 1) FES patients perceived higher stress than HCs; 2) CSF1R level and PFC subregional size were decreased in FES patients; 3) \u003cem\u003eCSF1R\u003c/em\u003e facilitated supriorfrontal gyral regulation of perceived stress in HCs but not FES patients; 4) CUS and CSF1Ri enhanced anxiety in mice; 5) CUS and/or CSF1Ri downregulated angiogenesis and blood vessel-associated IBA1+-microglia in mice. These are to our knowledge the first evidence revealing the importance of CSF1R in linking vascular microglia with stress regulation as a relevant mechanism in schizophrenia.\u003c/p\u003e \u003cp\u003eOur finding of lower \u003cem\u003eCSF1R\u003c/em\u003e mRNA in blood cells and CSF1R protein in the serum of FES patients is in line with several previous studies. Lower level of \u003cem\u003eCSF1R\u003c/em\u003e mRNA was reported in the cortices [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and spleens of chronic schizophrenia patients [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The reduction of \u003cem\u003eCSF1R\u003c/em\u003e observed in these studies can be affected by disease chronicity or anti-psychotics. By contrast, our current observation on blood CSF1R level had minimal drug effect. Moreover, we found that serum CSF1R protein was negatively correlated with PSS scores and positively moderated hippocampal regulation of PSS scores in HCs but not FES patients, giving hint on impairment of CSF1R function in early stage of schizophrenia. Given that CSF1R is solely expressed by myeloid cells in the brain, and changes in the blood-brain barrier (BBB) permeability have been identified in psychiatric disorders allowing peripheral inflammatory impact on the brain [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], our findings may be highly relevant for brain pathophysiology of FES. We indeed found that serum CSF1R facilitated hippocampal regulation of perceived stress in HCs but not FES patients.\u003c/p\u003e \u003cp\u003eTo depict how CSF1R may regulate stress response, we used a CUS mouse model and administered an inhibitor (PLX3397) to block Csf1r in microglia. Importantly, we found that CSF1Ri was anxiogenic to B6N mice similarly as CUS. Our observation corroborates with previous studies reporting that \u003cem\u003eCsf1r\u003c/em\u003e\u003csup\u003e+/\u0026minus;\u003c/sup\u003e mice exhibited anxiety along with cognitive and sensorimotor deficit [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, other studies have not observed effect of CSF1Ri on anxiety in mice [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. These discrepancies may be due to different ways of CSF1Ri administration, which warrant further careful investigations.\u003c/p\u003e \u003cp\u003eInterestingly, we found that CUS downregulated some cell adhesion and angiogenic molecules including CD31 in the PFC in mice. IBA1 intensity in VAMg was also more sensitively dampened by CUS compared to NVAMg, implicating a less juxtavascular association of microglial processes. Meanwhile, CUS decreased microglia in the PFC and hippocampus, possibly via inducing apoptosis as suggested by a previous study [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This is supported by our observation that CUS suppressed Csf1r expression that is pivotal for microglial proliferation and survival. Our observation is also in line with an earlier report [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] and supports our clinical data showing that lower CSF1R was associated with higher PSS.\u003c/p\u003e \u003cp\u003eStress downregulates the BBB tight junction proteins such as Claudin-5, thereby allowing and facilitating the entry of blood-borne components into the brain and glial activation [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Claudin-5 suppression occurred also in schizophrenia patients and caused schizophrenia-like phenotypes in mice [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] and changed gene expression of brain endothelial cell adhesion molecules in schizophrenia patients with \u0026ldquo;high inflammation\u0026rdquo; was also reported [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Our RNA-seq and IHC findings on CUS are consistent with these previous studies and demonstrate the involvement of microglia in regulating CUS-induced BBB leakage and anxiety.\u003c/p\u003e \u003cp\u003eImportantly, we also found that CSF1Ri downregulated most of the cell adhesion and angiogenic DEGs and preferentially diminished juxtavascular VAMg in the PFC in mice. Little is known about microglia-vascular interactions in the adult brain currently. Interestingly, A recent study found that about 30% of microglia are capillary-associated and constantly survey the influx of blood-borne components into living adult mice; furthermore, microglial depletion with CSF1Ri (PLX3397) induced a 15% increase in capillary diameter compared to control [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Our RNA-seq and IHC findings on CSF1Ri strongly support this \u003cem\u003ein vivo\u003c/em\u003e imaging study and provide a further depiction of molecular mechanisms on microglial association with neurovascular unit. Other work suggests that microglia could also play a role in repairing damaged BBB caused by systemic inflammation or laser injury [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. However, clinical and preclinical studies on psychiatric conditions are still missing. Out work thereby gives a first glimpse into this theme.\u003c/p\u003e \u003cp\u003eThe PFC and hippocampus are highly sensitive to stress or anxiety [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and schizophrenia patients are well-acknowledged to have cerebral cortical and hippocampal dystrophies [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Interestingly, we found that a PFC subarea, the superiorfrontal gyrus, was smaller in FES patients than HCs. Although there was no structural change in the hippocampus, we observed smaller volumes of the neighboring parahippocampal gyrus in FES patients than HCs. Deficits of these regions have been associated with psychotic symptoms such as auditory hallucinations and disordered thoughts in schizophrenia [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. More interestingly, we found that some PFC subregions and the hippocampus were negatively associated with PSS. Furthermore, blood CSF1R mRNA or protein interacted with these brain regions and moderated their negative associations with PSS in HCs but not FES patients. Additionally, CSF1R mRNA level was also negatively correlated with both PSS and PANSSt scores. These suggest the importance of CSF1R in stress regulation via modulating these limbic structures, which might be dysfunctional in FES patients. Besides, PSS scores were positively correlated with PANSSt, supporting the notions that stress exacerbates psychosis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and severity of psychotic symptoms correlates with that of anxiety symptoms [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study has several limitations, such as the small sample size in our clinical and preclinical cohorts and the cross-sectional nature of our clinical study design. Nevertheless, our findings suggest that CSF1R may provide a stress-coping mechanism via contribution to microglial patrolling of vasculatures and angiogenesis, which might be disturbed in schizophrenia. These results may be helpful for developing better diagnosis and treatment to tackle neuropsychiatric disorders.\u003c/p\u003e"},{"header":"List Of Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANOVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eanalysis of variance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANCOVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eanalysis of covariance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBBB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eblood-brain barrier\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCSF1R\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecolony stimulating factor 1 receptor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCSF1Ri\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCSF1R inhibition\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCTR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econtrol\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003echronic unpredictable mild stress\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCTQ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003echildhood trauma questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDEGs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edifferentially expressed genes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEPM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eelevated plus maze\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFDR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efalse discovery rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFES\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efirst-episode schizophrenia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003egene ontology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehealthy controls\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintracranial volume\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMFI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emean fluorescent intensity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emagnetic resonance imaging\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNVAMg\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enonvessel-associated microglia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOFT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eopen field test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eoligodendrocyte precursor cell\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePANSSt\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epositive and negative symptom scale-total score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprotein-protein interaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSSsum\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eperceived stress scale summation score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRNA-seq\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRNA sequencing\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTMg\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etotal microglia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVeh\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVehicle\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVAMg\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003evessel-associated microglia.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe clinical part of the study was approved by the Institutional Ethical Committee of Beijing Huilongguan Hospital. Written informed consent was obtained from each subject. The preclinical part of the study was approved by the Estonian National Board of Animal Experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data and materials that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLEH has received or plans to receive research funding or consulting fees on research projects from Mitsubishi, Your Energy Systems LLC, Neuralstem, Taisho, Heptares, Pfizer, Luye Pharma, IGC Pharma, Sound Pharma, Takeda, and Regeneron. None was involved in the design, analysis, or outcomes of the study. All other authors declare no competing commercial and financial interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding acknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China grants 81771452 and 82171507, the National Institute of Health grants R01MH112180, the Estonian Research Council-European Union Regional Developmental Fund Mobilitas Plus Program No. MOBTT77 and the Estonian Research Council personal research funding team grant project No. PRG878.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLi Tian, Yunlong Tan, and L. Elliot Hong designed the project and obtained the funding for this study. Yanli Li, Fengmei Fan, Wei Feng, Wei Li, Junchao Huang, Hongna Li, Mengzhuang Gou, and Wenjin Chen were responsible for recruiting patients, performing clinical ratings, neuroimaging, and collecting samples. Ling Yan and Li Tian analyzed all the data and wrote the paper. Yunlong Tan and Li Tian are responsible for the integrity of data and the accuracy of data analysis. Ling Yan performed the CUS model construction and mice behavioural tests and helped Keerthana Chithanathan who did flow cytometry experiment and data analysis. Alexander Zharkovsky was involved in CUS modelling and improved the manuscript. Baopeng Tian, Zhiren Wang, and Shuping Tan were invited in evolving the ideas and editing the manuscript. All authors have contributed to and have approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMcCutcheon RA, Reis Marques T, and Howes OD. Schizophrenia-An Overview. JAMA Psychiatry. 2020;77:201\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWinship IR, Dursun SM, Baker GB, Balista PA, Kandratavicius L, Maia-de-Oliveira JP, et al. 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Schizophr Bull. 2011;37:811\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Microglia, CSF1R, Angiogenesis, First episode schizophrenia, Stress, Anxiety","lastPublishedDoi":"10.21203/rs.3.rs-1777009/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1777009/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWhether and how microglia contribute to stress and anxiety in schizophrenia are not well established. We hypothesized that microglial colony stimulating factor 1 receptor (CSF1R) regulates stress susceptibility in schizophrenia via the hippocampus and associated cortical regions.\u003cstrong\u003e \u003c/strong\u003eA cohort of first-episode schizophrenia (FES) patients (n=51) and age- and sex-paired healthy controls (HCs) (n=46) were first recruited. Compared to HCs, FES patients showed higher scores of perceived stress scale (PSS, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01), lower levels of CSF1R mRNA (Log2FC=-0.195, FDR=0.003) and protein (18.31±0.95 vs. 20.49±0.90 µg/ml, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) in the blood, and smaller volumes of the superiorfrontal gyrus (39.13±0.64 vs. 40.80±0.76 cm\u003csup\u003e3\u003c/sup\u003e, FDR\u0026lt;0.05) and parahippocampal gyrus (3.51±0.048 vs. 3.72±0.058 cm\u003csup\u003e3\u003c/sup\u003e, FDR\u0026lt;0.05). CSF1R facilitated the negative superiorfrontal gyral association with PSS (β=6.109, 95% CI: 1.642~10.578, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01) in HCs but not FES patients. CSF1R-associated gene network contributed to brain development. We further studied a chronic unpredictable stress (CUS) mouse model combined with a CSF1R inhibitor (CSF1Ri). Both CUS and CSF1Ri enhanced anxiety in mice (both \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001).\u003cstrong\u003e \u003c/strong\u003eRNA-seq revealed downregulation of genes for cell adhesion and angiogenesis after CUS-CSF1Ri treatment. Immunostaining showed downregulation of CD31 and preferential loss of vessel-associated IBA1\u003csup\u003e+\u003c/sup\u003e-microglia induced by CUS or CSF1Ri (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). Oligodendrocyte precursor cells were however increased after CUS-CSF1Ri treatment (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01). These results suggest that microglial CSF1R showed a protective effect on stress and anxiety in FES patients and CUS mice via contribution to angiogenesis.\u003c/p\u003e","manuscriptTitle":"CSF1R Contributes to Vascular Association of Microglia and Stress Regulation in Schizophrenia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-07-01 17:10:23","doi":"10.21203/rs.3.rs-1777009/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"183c4bd2-7998-482c-a037-c54ae6df8dd6","owner":[],"postedDate":"July 1st, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-11-14T11:03:23+00:00","versionOfRecord":[],"versionCreatedAt":"2022-07-01 17:10:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1777009","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1777009","identity":"rs-1777009","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}