Multivariate relationships between peripheral inflammatory marker subtypes and cognitive and brain structural measures in psychosis

Dopaminergic dysfunction and excitatory/inhibitory imbalance in treatment-resistant schizophrenia and novel neuromodulatory treatment

Antipsychotic drugs are the mainstay in the treatment of schizophrenia. However, one-third of patients do not show adequate improvement in positive symptoms with non-clozapine antipsychotics. Additionally, approximately half of them show poor response to clozapine, electroconvulsive therapy, or other augmentation strategies. However, the development of novel treatment for these conditions is difficult due to the complex and heterogenous pathophysiology of treatment-resistant schizophrenia (TRS). Therefore, this review provides key findings, potential treatments, and a roadmap for future research in this area. First, we review the neurobiological pathophysiology of TRS, particularly the dopaminergic, glutamatergic, and GABAergic pathways. Next, the limitations of existing and promising treatments are presented. Specifically, this article focuses on the therapeutic potential of neuromodulation, including electroconvulsive therapy, repetitive transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation. Finally, we propose multivariate analyses that integrate various perspectives of the pathogenesis, such as dopaminergic dysfunction and excitatory/inhibitory imbalance, thereby elucidating the heterogeneity of TRS that could not be obtained by conventional statistics. These analyses can in turn lead to a precision medicine approach with closed-loop neuromodulation targeting the detected pathophysiology of TRS.

Distinct Phenotypes of Inflammation Associated Macrophages and Microglia in the Prefrontal Cortex Schizophrenia Compared to Controls

Approximately 40% of people with schizophrenia are classified as having "high inflammation." This subgroup has worse neuropathology than patients with "low inflammation." Thus, one would expect the resident microglia and possibly monocyte-derived macrophages infiltrating from the periphery to be "activated" in those with schizophrenia with elevated neuroinflammation. To test whether microglia and/or macrophages are associated with increased inflammatory signaling in schizophrenia, we measured microglia- and macrophage-associated transcripts in the postmortem dorsolateral prefrontal cortex of 69 controls and 72 people with schizophrenia. Both groups were stratified by neuroinflammatory status based on cortical mRNA levels of cytokines and SERPINA3. We found microglial mRNAs levels were either unchanged (IBA1 and Hexb, p > 0.20) or decreased (CD11c, <62% p < 0.001) in high inflammation schizophrenia compared to controls. Conversely, macrophage CD163 mRNA levels were increased in patients, substantially so in the high inflammation schizophrenia subgroup compared to low inflammation subgroup (>250%, p < 0.0001). In contrast, high inflammation controls did not have elevated CD163 mRNA compared to low inflammation controls (p > 0.05). The pro-inflammatory macrophage marker (CD64 mRNA) was elevated (>160%, all p < 0.05) and more related to CD163 mRNA in the high inflammation schizophrenia subgroup compared to high inflammation controls, while anti-inflammatory macrophage and cytokine markers (CD206 and IL-10 mRNAs) were either unchanged or decreased in schizophrenia. Finally, macrophage recruitment chemokine CCL2 mRNA was increased in schizophrenia (>200%, p < 0.0001) and CCL2 mRNA levels positively correlated with CD163 mRNA (r = 0.46, p < 0.0001). Collectively, our findings support the co-existence of quiescent microglia and increased pro-inflammatory macrophages in the cortex of people with schizophrenia.

Increased blood-brain barrier permeability of the thalamus and the correlation with symptom severity and brain volume alterations in schizophrenia patients

BACKGROUND

Cumulative evidence of microvascular dysfunction has suggested the blood-brain barrier (BBB) disruption in schizophrenia, while the direct in vivo evidence from patients is inadequate. In this study, using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) methods, we tried to test the hypothesis that there was increased BBB permeability in schizophrenia patients, and correlated with the clinical characters, and brain volumetric alterations.

METHODS

Structural MRI and DCE-MRI data from 29 schizophrenia patients and 18 age- and sex- matched controls (HC) were obtained. We calculated the volume transfer constant (K^trans) value and compared the difference between two groups. The regions with the abnormal K^trans value were extracted as ROIs (thalamus), and the correlation with the clinical characters and grey matter volume were analysed.

RESULTS

The results revealed that, compared with the HC, the volume transfer constant (K^trans) value of the bilateral thalamus in the schizophrenia group was increased (p < 0.001). There were significant positive correlations between thalamic mean K^trans value with disease duration (p < 0.05) and symptom severity (p < 0.001). Analysis of the thalamic subregions revealed that the BBB disruption was significant in pulvinar, especially the medial pulvinar nucleus (PuM) and lateral pulvinar nucleus (PuL) (p < 0.001). The K^trans value of the whole brain, thalamus, and thalamic subregions was negatively correlated with their volume separately.

CONCLUSION

These results provided the first in vivo evidence of BBB disruption of thalamus in schizophrenia patients, and the BBB dysfunction might contribute to the pathological brain structural alterations in schizophrenia.

Changes of immune-related factors in the blood of schizophrenia and bipolar disorder patients receiving monotherapy

Schizophrenia (SCZ) and bipolar disorder (BPD) are associated with abnormal expression of immune-related factors (IRFs), which have been proposed as biomarkers of either disease diagnosis (trait markers) or treatment (state markers). However, the state markers have been found to be less reproducible than the trait markers in previous studies. In the current study, we focused on the changes of IRFs in blood of SCZ and BPD patients receiving monotherapy. SCZ (N = 49) and BPD (N = 49) Chinese patients were recruited at acute episode and followed for 9 to 51 days until remission. Blood samples were collected at two state-points, acute state before treatment and remission state after treatment. A total of 41 IRFs in plasma were quantified by the Luminex assay. After adjusting covariates, we found four cytokines or cytokine receptors were significantly increased at remission when compared to acute episode in all the patients, including CD30, BAFF, CCL20, and CXCL10 (Bonferroni corrected p < 0.05). CD30 and BAFF were consistently increased in both SCZ and BPD while the increase of CCL20 was only observed in BPD but not SCZ when analyzing the two disorders separately. CXCL10 change was not significant in either SCZ or BPD alone. The changes of these four factors were correlated with each other, but not with clinical features. CD30 concentration in the BPD acute state was correlated with sleep quality (Spearman's r_s = 0.365, Bonferroni corrected p < 0.05). Overall, we found that four factors (CD30, BAFF, CCL20, and CXCL10) might be associated with treatment of psychosis.

Magnetization transfer imaging alterations and its diagnostic value in antipsychotic-naïve first-episode schizophrenia

Magnetization transfer imaging (MTI) may provide more sensitivity and mechanistic understanding of neuropathological changes associated with schizophrenia than volumetric MRI. This study aims to identify brain magnetization transfer ratio (MTR) changes in antipsychotic-naïve first-episode schizophrenia (FES), and to correlate MTR findings with clinical symptom severity. A total of 143 individuals with antipsychotic-naïve FES and 147 healthy controls (HCs) were included and underwent 3.0 T brain MTI between August 2005 and July 2014. Voxelwise analysis was performed to test for MTR differences with family-wise error corrections. Relationships of these differences to symptom severity were assessed using partial correlations. Exploratory analyses using a support vector machine (SVM) classifier were conducted to discriminate FES from HCs using MTR maps. Model performance was examined using a 10-fold stratified cross-validation. Compared with HCs, individuals with FES exhibited higher MTR values in left thalamus, precuneus, cuneus, and paracentral lobule, that were positively correlated with schizophrenia symptom severity [precuneus (r = 0.34, P = 0.0004), cuneus (r = 0.33, P = 0.0006) and paracentral lobule (r = 0.37, P = 0.001)]. Whole-brain MTR maps identified individuals with FES with overall accuracy 75.5% (219 of 290 individuals) based on SVM approach. In antipsychotic-naïve FES, clinically relevant biophysical abnormalities detected by MTI mainly in the left parieto-occipital regions are informative about local brain pathology, and have potential as diagnostic markers.

Peripheral complement is increased in schizophrenia and inversely related to cortical thickness

BACKGROUND

There is growing evidence for complement system involvement in the pathophysiology of schizophrenia, although the extent and magnitude of complement factor disturbances has not been fully reported. It also remains unclear whether complement abnormalities are characteristic of all patients with schizophrenia or whether they are representative of a subgroup of patients who show signs of heightened inflammation. The aim of the present study was to quantify and compare the levels of a range of complement factors, receptors and regulators in healthy controls and people with schizophrenia and to determine the extent to which the levels of these peripheral molecules relate to measures of brain structure, particularly cortical thickness.

METHOD

Seventy-five healthy controls and 90 patients with schizophrenia or schizoaffective disorder were included in the study. Peripheral blood samples were collected from all participants and mRNA expression was quantified in 20 complement related genes, four complement proteins, as well as for four cytokines. T1-weighted structural MRI scans were acquired and analysed to determine cortical thickness measures.

RESULTS

There were significant increases in peripheral mRNA encoding receptors (C5ar1, CR1, CR3a), regulators (CD55, C59) and protein concentrations (C3, C3b, C4) in people with schizophrenia relative to healthy controls. C4a expression was significantly increased in a subgroup of patients displaying elevated peripheral cytokine levels. A higher inflammation index score derived from mRNA expression patterns predicted reductions in cortical thickness in the temporal lobe (superior temporal gyrus, transverse temporal gyrus, fusiform gyrus, insula) in patients with schizophrenia and healthy controls.

CONCLUSIONS

Analysis of all three major complement pathways supports increased complement activity in schizophrenia and also shows that peripheral C4a up-regulation is related to increased peripheral pro-inflammatory cytokines in healthy controls. Our region-specific, neuroimaging findings linked to an increased peripheral complement mRNA expression pattern suggests a role for complement in cortical thinning. Further studies are required to further clarify clinical and neurobiological consequences of aberrant complement levels in schizophrenia and related psychoses.

Inflammatory Subtypes in Antipsychotic-Naïve First-Episode Schizophrenia are Associated with Altered Brain Morphology and Topological Organization

BACKGROUND

Peripheral inflammation is implicated in schizophrenia, however, not all individuals demonstrate inflammatory alterations. Recent studies identified inflammatory subtypes in chronic psychosis with high inflammation having worse cognitive performance and displaying neuroanatomical enlargement compared to low inflammation subtypes. It is unclear if inflammatory subtypes exist earlier in the disease course, thus, we aim to identify inflammatory subtypes in antipsychotic naïve First-Episode Schizophrenia (FES).

METHODS

12 peripheral inflammatory markers, clinical, cognitive, and neuroanatomical measures were collected from a naturalistic study of antipsychotic-naïve FES patients. A combination of unsupervised principal component analysis and hierarchical clustering was used to categorize inflammatory subtypes from their cytokine data (17 FES High, 30 FES Low, and 33 healthy controls (HCs)). Linear regression analysis was used to assess subtype differences. Neuroanatomical correlations with clinical and cognitive measures were performed using partial Spearman correlations. Graph theoretical analyses were performed to assess global and local network properties across inflammatory subtypes.

RESULTS

The FES High group made up 36% of the FES group and demonstrated significantly greater levels of IL1β, IL6, IL8, and TNFα compared to FES Low, and higher levels of IL1β and IL8 compared to HCs. FES High had greater right parahippocampal, caudal anterior cingulate, and bank superior sulcus thicknesses compared to FES Low. Compared to HCs, FES Low showed smaller bilateral amygdala volumes and widespread cortical thickness. FES High and FES Low groups demonstrated less efficient topological organization compared to HCs. Individual cytokines and/or inflammatory signatures were positively associated with cognition and symptom measures.

CONCLUSIONS

Inflammatory subtypes are present in antipsychotic-naïve FES and are associated with inflammation-mediated cortical expansion. These findings support our previous findings in chronic psychosis and point towards a connection between inflammation and blood-brain barrier disruption. Thus, identifying inflammatory subtypes may provide a novel therapeutic avenue for biomarker-guided treatment involving anti-inflammatory medications.

Quantifying Retinal Microvascular Morphology in Schizophrenia Using Swept-Source Optical Coherence Tomography Angiography

BACKGROUND

Retinovascular changes are reported on fundus imaging in schizophrenia (SZ). This is the first study to use swept-source optical coherence tomography angiography (OCT-A) to comprehensively examine retinal microvascular changes in SZ.

METHODS

This study included 30 patients with SZ/schizoaffective disorder (8 early and 15 chronic) and 22 healthy controls (HCs). All assessments were performed at Beth Israel Deaconess Medical Center and Massachusetts Eye and Ear. All participants underwent swept-source OCT-A of right (oculus dextrus [OD]) and left (oculus sinister [OS]) eye, clinical, and cognitive assessments. Macular OCT-A images (6 × 6 mm) were collected with the DRI Topcon Triton for superficial, deep, and choriocapillaris vascular regions. Microvasculature was quantified using vessel density (VD), skeletonized vessel density (SVD), fractal dimension (FD), and vessel diameter index (VDI).

RESULTS

Twenty-one HCs and 26 SZ subjects were included. Compared to HCs, SZ patients demonstrated higher overall OD superficial SVD, OD choriocapillaris VD, and OD choriocapillaris SVD, which were primarily observed in the central, central and outer superior, and central and outer inferior/superior, respectively. Early-course SZ subjects had significantly higher OD superficial VD, OD choriocapillaris SVD, and OD choriocapillaris FD compared to matched HCs. Higher bilateral (OU) superficial VD correlated with lower Positive and Negative Syndrome Scale (PANSS) positive scores, and higher OU deep VDI was associated with higher PANSS negative scores.

CONCLUSIONS AND RELEVANCE

These results suggest the presence of microvascular dysfunction associated with early-stage SZ. Clinical associations with microvascular alterations further implicate this hypothesis, with higher measures being associated with worse symptom severity and functioning in early stages and with lower symptom severity and better functioning in later stages.

Immune System Abnormalities in Schizophrenia: An Integrative View and Translational Perspectives

The immune system is generally known to be the primary defense mechanism against pathogens. Any pathological conditions are reflected in anomalies in the immune system parameters. Increasing evidence suggests the involvement of immune dysregulation and neuroinflammation in the pathogenesis of schizophrenia. In this systematic review, we summarized the available evidence of abnormalities in the immune system in schizophrenia. We analyzed impairments in all immune system components and assessed the level of bias in the available evidence. It has been shown that schizophrenia is associated with abnormalities in all immune system components: from innate to adaptive immunity and from humoral to cellular immunity. Abnormalities in the immune organs have also been observed in schizophrenia. Evidence of increased C-reactive protein, dysregulation of cytokines and chemokines, elevated levels of neutrophils and autoantibodies, and microbiota dysregulation in schizophrenia have the lowest risk of bias. Peripheral immune abnormalities contribute to neuroinflammation, which is associated with cognitive and neuroanatomical alterations and contributes to the pathogenesis of schizophrenia. However, signs of severe inflammation are observed in only about 1/3 of patients with schizophrenia. Immunological parameters may help identify subgroups of individuals with signs of inflammation who well respond to anti-inflammatory therapy. Our integrative approach also identified gaps in knowledge about immune abnormalities in schizophrenia, and new horizons for the research are proposed.

Inflammation Subtypes and Translating Inflammation-Related Genetic Findings in Schizophrenia and Related Psychoses: A Perspective on Pathways for Treatment Stratification and Novel Therapies

Dysregulation of immunological and inflammatory processes is frequently observed in psychotic disorders. Numerous studies have examined the complex components of innate and adaptive immune processes in schizophrenia and related psychoses. Elevated inflammation in these conditions is related to neurobiological phenotypes and associated with both genetics and environmental exposures. Recent studies have utilized multivariate cytokine approaches to identify what appears to be a subset of individuals with elevated inflammation. The degree to which these findings represent a general process of dysregulated inflammation or whether there are more refined subtypes remains unclear. Brain-imaging studies have attempted to establish the link between peripheral inflammation and gray matter disruption, white matter abnormalities, and neuropsychological phenotypes. However, the interplay between peripheral inflammation and neuroinflammation, as well as the consequences of this interplay, in the context of psychosis remains unclear and requires further investigation. This Perspectives article reviews the following elements of immune dysregulation and its clinical and therapeutic implications: (1) evidence supporting inflammation and immune dysregulation in schizophrenia and related psychoses; (2) recent advances in approaches to characterizing subgroups of patients with elevated inflammation; (3) relationships between peripheral inflammation and brain-imaging indicators of neuroinflammation; (4) convergence of large-scale genetic findings and peripheral inflammation findings; and (5) therapeutic implications: anti-inflammation interventions leveraging genetic findings for drug discovery and repurposing. We offer perspectives and examples of how multiomics technologies may be useful for constructing and studying immunogenetic signatures. Advancing research in this area will facilitate biomarker discovery, disease subtyping, and the development of etiological treatments for immune dysregulation in psychosis.

Diagnosis of Schizophrenia Based on the Data of Various Modalities: Biomarkers and Machine Learning Techniques (Review)

Schizophrenia is a socially significant mental disorder resulting frequently in severe forms of disability. Diagnosis, choice of treatment tactics, and rehabilitation in clinical psychiatry are mainly based on the assessment of behavioral patterns, socio-demographic data, and other investigations such as clinical observations and neuropsychological testing including examination of patients by the psychiatrist, self-reports, and questionnaires. In many respects, these data are subjective and therefore a large number of works have appeared in recent years devoted to the search for objective characteristics (indices, biomarkers) of the processes going on in the human body and reflected in the behavioral and psychoneurological patterns of patients. Such biomarkers are based on the results of instrumental and laboratory studies (neuroimaging, electro-physiological, biochemical, immunological, genetic, and others) and are successfully being used in neurosciences for understanding the mechanisms of the emergence and development of nervous system pathologies. Presently, with the advent of new effective neuroimaging, laboratory, and other methods of investigation and also with the development of modern methods of data analysis, machine learning, and artificial intelligence, a great number of scientific and clinical studies is being conducted devoted to the search for the markers which have diagnostic and prognostic value and may be used in clinical practice to objectivize the processes of establishing and clarifying the diagnosis, choosing and optimizing treatment and rehabilitation tactics, predicting the course and outcome of the disease. This review presents the analysis of the works which describe the correlates between the diagnosis of schizophrenia, established by health professionals, various manifestations of the psychiatric disorder (its subtype, variant of the course, severity degree, observed symptoms, etc.), and objectively measured characteristics/quantitative indicators (anatomical, functional, immunological, genetic, and others) obtained during instrumental and laboratory examinations of patients. A considerable part of these works has been devoted to correlates/biomarkers of schizophrenia based on the data of structural and functional (at rest and under cognitive load) MRI, EEG, tractography, and immunological data. The found correlates/biomarkers reflect anatomic disorders in the specific brain regions, impairment of functional activity of brain regions and their interconnections, specific microstructure of the brain white matter and the levels of connectivity between the tracts of various structures, alterations of electrical activity in various parts of the brain in different EEG spectral ranges, as well as changes in the innate and adaptive links of immunity. Current methods of data analysis and machine learning to search for schizophrenia biomarkers using the data of diverse modalities and their application during building and interpretation of predictive diagnostic models of schizophrenia have been considered in the present review.

Brick by Brick: Building a Transdiagnostic Understanding of Inflammation in Psychiatry

ABSTRACT

Inflammatory phenomena are found in many psychiatric disorders-notably, depression, schizophrenia, and posttraumatic stress disorder. Inflammation has been linked to severity and treatment resistance, and may both contribute to, and result from, the pathophysiology of some psychiatric illnesses. Emerging research suggests that inflammation may contribute to symptom domains of reward, motor processing, and threat reactivity across different psychiatric diagnoses. Reward-processing deficits contribute to motivational impairments in depression and schizophrenia, and motor-processing deficits contribute to psychomotor slowing in both depression and schizophrenia. A number of experimental models and clinical trials suggest that inflammation produces deficits in reward and motor processing through common pathways connecting the cortex and the striatum, which includes the nucleus accumbens, caudate nucleus, and putamen.The observed effects of inflammation on psychiatric disorders may cut across traditional conceptualizations of psychiatric diagnoses. Further study may lead to targeted immunomodulating treatments that address difficult-to-treat symptoms in a number of psychiatric disorders. In this review, we use a Research Domain Criteria framework to discuss proposed mechanisms for inflammation and its effects on the domains of reward processing, psychomotor slowing, and threat reactivity. We also discuss data that support contributing roles of metabolic dysregulation and sex differences on the behavioral outcomes of inflammation. Finally, we discuss ways that future studies can help disentangle this complex topic to yield fruitful results that will help advance the field of psychoneuroimmunology.

The relationship between immune and cognitive dysfunction in mood and psychotic disorder: a systematic review and a meta-analysis

BACKGROUND

In psychotic and mood disorders, immune alterations are hypothesized to underlie cognitive symptoms, as they have been associated with elevated blood levels of inflammatory cytokines, kynurenine metabolites, and markers of microglial activation. The current meta-analysis synthesizes all available clinical evidence on the associations between immunomarkers (IMs) and cognition in these psychiatric illnesses.

METHODS

Pubmed, Web of Science, and Psycinfo were searched for peer-reviewed studies on schizophrenia spectrum disorder (SZ), bipolar disorder (BD), or major depressive disorder (MDD) including an association analysis between at least one baseline neuropsychological outcome measure (NP) and one IM (PROSPERO ID:CRD42021278371). Quality assessment was performed using BIOCROSS. Correlation meta-analyses, and random effect models, were conducted in Comprehensive Meta-Analysis version 3 investigating the association between eight cognitive domains and pro-inflammatory and anti-inflammatory indices (PII and AII) as well as individual IM.

RESULTS

Seventy-five studies (n = 29,104) revealed global cognitive performance (GCP) to be very weakly associated to PII (r = -0.076; p = 0.003; I² = 77.4) or AII (r = 0.067; p = 0.334; I² = 38.0) in the combined patient sample. Very weak associations between blood-based immune markers and global or domain-specific GCP were found, either combined or stratified by diagnostic subgroup (GCP x PII: SZ: r = -0.036, p = 0.370, I² = 70.4; BD: r = -0.095, p = 0.013, I² = 44.0; MDD: r = -0.133, p = 0.040, I² = 83.5). We found evidence of publication bias.

DISCUSSION

There is evidence of only a weak association between blood-based immune markers and cognition in mood and psychotic disorders. Significant publication and reporting biases were observed and most likely underlie the inflation of such associations in individual studies.

Subtypes of schizophrenia identified by multi-omic measures associated with dysregulated immune function

Epigenetic modifications are plausible molecular sources of phenotypic heterogeneity across schizophrenia patients. The current study investigated biological heterogeneity in schizophrenia using peripheral epigenetic profiles to delineate illness subtypes independent of their phenomenological manifestations. We applied epigenome-wide profiling with a DNA methylation array from blood samples of 63 schizophrenia patients and 59 healthy controls. Non-negative matrix factorization (NMF) and k-means clustering were performed to identify DNA methylation-related patient subtypes. The validity of the partition was tested by assessing the profile of the T cell receptor (TCR) repertoires. The uniqueness of the identified subtypes in relation to brain structural and clinical measures were evaluated. Two distinct patterns of DNA methylation profiles were identified in patients. One subtype (60.3% of patients) showed relatively limited changes in methylation levels and cell composition compared to controls, while a second subtype (39.7% of patients) exhibited widespread methylation level alterations among genes enriched in immune cell activity, as well as a higher proportion of neutrophils and lower proportion of lymphocytes. Differentiation of the two patient subtypes was validated by TCR repertoires, which paralleled the partition based on DNA methylation profiles. The subtype with widespread methylation modifications had higher symptom severity, performed worse on cognitive measures, and displayed greater reductions in fractional anisotropy of white matter tracts and evidence of gray matter thickening compared to the other subtype. Identification of a distinct subtype of schizophrenia with unique molecular, cerebral, and clinical features provide a novel parcellation of the schizophrenia syndrome with potential to guide development of individualized therapeutics.

Assessing the effect of interaction between C-reactive protein and gut microbiome on the risks of anxiety and depression

Cumulative evidence shows that gut microbiome can influence brain function and behavior via the inflammatory processes. However, the role of interaction between gut dysbiosis and C-reactive protein (CRP) in the development of anxiety and depression remains to be elucidated. In this study, a total of 3321 independent single nucleotide polymorphism (SNP) loci associated with gut microbiome were driven from genome-wide association study (GWAS). Using individual level genotype data from UK Biobank, we then calculated the polygenetic risk scoring (PRS) of 114 gut microbiome related traits. Moreover, regression analysis was conducted to evaluate the possible effect of interaction between gut microbiome and CRP on the risks of Patient Health Questionnaire-9 (PHQ-9) (N = 113,693) and Generalized Anxiety Disorder-7 (GAD-7) (N = 114,219). At last, 11 candidate CRP × gut microbiome interaction with suggestive significance was detected for PHQ-9 score, such as F_Ruminococcaceae (β = - 0.009, P = 2.2 × 10^-3), G_Akkermansia (β = - 0.008, P = 7.60 × 10^-3), F_Acidaminococcaceae (β = 0.008, P = 1.22 × 10^-2), G_Holdemanella (β = - 0.007, P = 1.39 × 10^-2) and O_Lactobacillales (β = 0.006, P = 1.79× 10^-2). 16 candidate CRP × gut microbiome interaction with suggestive significance was detected for GAD-7 score, such as O_Bacteroidales (β = 0.010, P = 4.00×  10^-4), O_Selenomonadales (β = - 0.010, P = 1.20 × 10^-3), O_Clostridiales (β = 0.009, P = 2.70 × 10^-3) and G_Holdemanella (β = - 0.008, P = 4.20 × 10^-3). Our results support the significant effect of interaction between CRP and gut microbiome on the risks of anxiety and depression, and identified several candidate gut microbiomes for them.

Genome-wide association study accounting for anticholinergic burden to examine cognitive dysfunction in psychotic disorders

Identifying genetic contributors to cognitive impairments in psychosis-spectrum disorders can advance understanding of disease pathophysiology. Although CNS medications are known to affect cognitive performance, they are often not accounted for in genetic association studies. In this study, we performed a genome-wide association study (GWAS) of global cognitive performance, measured as composite z-scores from the Brief Assessment of Cognition in Schizophrenia (BACS), in persons with psychotic disorders and controls (N = 817; 682 cases and 135 controls) from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. Analyses accounting for anticholinergic exposures from both psychiatric and non-psychiatric medications revealed five significantly associated variants located at the chromosome 3p21.1 locus, with the top SNP rs1076425 in the inter-alpha-trypsin inhibitor heavy chain 1 (ITIH1) gene (P = 3.25×E-9). The inclusion of anticholinergic burden improved association models (P < 0.001) and the number of significant SNPs identified. The effect sizes and direction of effect of the top variants remained consistent when investigating findings within individuals receiving specific antipsychotic drugs and after accounting for antipsychotic dose. These associations were replicated in a separate study sample of untreated first-episode psychosis. The chromosome 3p21.1 locus was previously reported to have association with the risk for psychotic disorders and cognitive performance in healthy individuals. Our findings suggest that this region may be a psychosis risk locus that is associated with cognitive mechanisms. Our data highlight the general point that the inclusion of medication exposure information may improve the detection of gene-cognition associations in psychiatric genetic research.

Identification of inflammatory subgroups of schizophrenia and bipolar disorder patients with HERV-W ENV antigenemia by unsupervised cluster analysis

Human endogenous retroviruses (HERVs) are remnants of infections that took place several million years ago and represent around 8% of the human genome. Despite evidence implicating increased expression of HERV type W envelope (HERV-W ENV) in schizophrenia and bipolar disorder, it remains unknown whether such expression is associated with distinct clinical or biological characteristics and symptoms. Accordingly, we performed unsupervised two-step clustering of a multivariate data set that included HERV-W ENV protein antigenemia, serum cytokine levels, childhood trauma scores, and clinical data of cohorts of patients with schizophrenia (n = 29), bipolar disorder (n = 43) and healthy controls (n = 32). We found that subsets of patients with schizophrenia (~41%) and bipolar disorder (~28%) show positive antigenemia for HERV-W ENV protein, whereas the large majority (96%) of controls was found to be negative for ENV protein. Unsupervised cluster analysis identified the presence of two main clusters of patients, which were best predicted by the presence or absence of HERV-W ENV protein. HERV-W expression was associated with increased serum levels of inflammatory cytokines and higher childhood maltreatment scores. Furthermore, patients with schizophrenia who were positive for HERV-W ENV protein showed more manic symptoms and higher daily chlorpromazine (CPZ) equivalents, whereas HERV-W ENV positive patients with bipolar disorder were found to have an earlier disease onset than those who were negative for HERV-W ENV protein. Taken together, our study suggest that HERV-W ENV protein antigenemia and cytokines can be used to stratify patients with major mood and psychotic disorders into subgroups with differing inflammatory and clinical profiles.

Artificial intelligence applications in psychoradiology

One important challenge in psychiatric research is to translate findings from brain imaging research studies that identified brain alterations in patient groups into an accurate diagnosis at an early stage of illness, prediction of prognosis before treatment, and guidance for selection of effective treatments that target patient-relevant pathophysiological features. This is the primary aim of the field of Psychoradiology. Using databases collected from large samples at multiple centers, sophisticated artificial intelligence (AI) algorithms may be used to develop clinically useful image analysis pipelines that can help physicians diagnose, predict, and make treatment decisions. In this review, we selectively summarize psychoradiological research using magnetic resonance imaging of the brain to explore the neural mechanism of psychiatric disorders, and outline progress and the path forward for the combination of psychoradiology and AI for complementing clinical examinations in patients with psychiatric disorders, as well as limitations in the application of AI that should be considered in future translational research.

Cerebrospinal fluid flow cytometry distinguishes psychosis spectrum disorders from differential diagnoses

Psychotic disorders are common and disabling mental conditions. The relative importance of immune-related mechanisms in psychotic disorders remains subject of debate. Here, we present a large-scale retrospective study of blood and cerebrospinal fluid (CSF) immune cell profiles of psychosis spectrum patients. We performed basic CSF analysis and multi-dimensional flow cytometry of CSF and blood cells from 59 patients with primary psychotic disorders (F20, F22, F23, and F25) in comparison to inflammatory (49 RRMS and 16 NMDARE patients) and non-inflammatory controls (52 IIH patients). We replicated the known expansion of monocytes in the blood of psychosis spectrum patients, that we identified to preferentially affect classical monocytes. In the CSF, we found a relative shift from lymphocytes to monocytes, increased protein levels, and evidence of blood-brain barrier disruption in psychosis. In fact, these CSF features confidently distinguished autoimmune encephalitis from psychosis despite similar (initial) clinical features. We then constructed machine learning models incorporating blood and CSF parameters and demonstrated their superior ability to differentiate psychosis from non-inflammatory controls compared to individual parameters. Multi-dimensional and multi-compartment immune cell signatures can thus support the diagnosis of psychosis spectrum disorders with the potential to accelerate diagnosis and initiation of therapy.