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

Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Applications of MRI in Schizophrenia: Current Progress in Establishing Clinical Utility

Schizophrenia is a severe mental illness that significantly impacts the lives of affected individuals and with increasing mortality rates. Early detection and intervention are crucial for improving outcomes but the lack of validated biomarkers poses great challenges in such efforts. The use of magnetic resonance imaging (MRI) in schizophrenia enables the investigation of the disorder's etiological and neuropathological substrates in vivo. After decades of research, promising findings of MRI have been shown to aid in screening high-risk individuals and predicting illness onset, and predicting symptoms and treatment outcomes of schizophrenia. The integration of machine learning and deep learning techniques makes it possible to develop intelligent diagnostic and prognostic tools with extracted or selected imaging features. In this review, we aimed to provide an overview of current progress and prospects in establishing clinical utility of MRI in schizophrenia. We first provided an overview of MRI findings of brain abnormalities that might underpin the symptoms or treatment response process in schizophrenia patients. Then, we summarized the ongoing efforts in the computer-aided utility of MRI in schizophrenia and discussed the gap between MRI research findings and real-world applications. Finally, promising pathways to promote clinical translation were provided. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Eosinophils and Cognitive Impairment in Schizophrenia: A New Perspective

Schizophrenia is a complex psychiatric disorder characterized by a wide array of cognitive impairments. While research has predominantly focused on the neurological aspects of schizophrenia, emerging evidence suggests that the immune system, specifically eosinophils, may play a significant role in the cognitive deficits associated with the disorder. This review presents a novel perspective on the interplay between eosinophils and cognitive impairment in schizophrenia. Eosinophils, traditionally associated with allergic responses and inflammation, have garnered limited attention within the realm of neuropsychiatry. Recent studies have hinted at a potential link between eosinophil activation and the pathogenesis of schizophrenia. In this comprehensive review, we delve into the world of eosinophils, elucidating their nature, functions, and interactions with the immune system. We examine the cognitive deficits observed in individuals with schizophrenia and discuss existing theories on the etiology of these impairments, focusing on immune system involvement. The paper also highlights the evolving body of research that supports the idea of eosinophilic influence on schizophrenia-related cognitive deficits. Furthermore, we explore potential mechanisms through which eosinophils may exert their effects on cognitive function in schizophrenia, including interactions with other immune cells and inflammatory pathways. By discussing the clinical implications and potential therapeutic avenues stemming from this newfound perspective, we underscore the practical significance of this emerging field of research. While this paper acknowledges the limitations and challenges inherent in studying eosinophils within the context of schizophrenia, it serves as a posit for novel thought in this vexing disease space as well as a call to action for future research endeavors. By providing a comprehensive survey of the existing literature and posing unanswered questions, we aim to inspire a reimagining of the relationship between eosinophils and cognitive impairment in schizophrenia, ultimately advancing our understanding and treatment of this debilitating disorder.

Immunophenotypes in psychosis: is it a premature inflamm-aging disorder?

Immunopsychiatric field has rapidly accumulated evidence demonstrating the involvement of both innate and adaptive immune components in psychotic disorders such as schizophrenia. Nevertheless, researchers are facing dilemmas of discrepant findings of immunophenotypes both outside and inside the brains of psychotic patients, as discovered by recent meta-analyses. These discrepancies make interpretations and interrogations on their roles in psychosis remain vague and even controversial, regarding whether certain immune cells are more activated or less so, and whether they are causal or consequential, or beneficial or harmful for psychosis. Addressing these issues for psychosis is not at all trivial, as immune cells either outside or inside the brain are an enormously heterogeneous and plastic cell population, falling into a vast range of lineages and subgroups, and functioning differently and malleably in context-dependent manners. This review aims to overview the currently known immunophenotypes of patients with psychosis, and provocatively suggest the premature immune "burnout" or inflamm-aging initiated since organ development as a potential primary mechanism behind these immunophenotypes and the pathogenesis of psychotic disorders.

A subtype of schizophrenia patients with altered methylation level of genes related to immune cell activity

BACKGROUND

Epigenetic changes are plausible molecular sources of clinical heterogeneity in schizophrenia. A subgroup of schizophrenia patients with elevated inflammatory or immune-dysregulation has been reported by previous studies. However, little is known about epigenetic changes in genes related to immune activation in never-treated first-episode patients with schizophrenia (FES) and its consistency with that in treated long-term ill (LTS) patients.

METHODS

In this study, epigenome-wide profiling with a DNA methylation array was applied using blood samples of both FES and LTS patients, as well as their corresponding healthy controls. Non-negative matrix factorization (NMF) and k -means clustering were performed to parse heterogeneity of schizophrenia, and the consistency of subtyping results from two cohorts. was tested.

RESULTS

This study identified a subtype of patients in FES participants (47.5%) that exhibited widespread methylation level alterations of genes enriched in immune cell activity and a significantly higher proportion of neutrophils. This clustering of FES patients was validated in LTS patients, with high correspondence in epigenetic and clinical features across two cohorts.

CONCLUSIONS

In summary, this study demonstrated a subtype of schizophrenia patients across both FES and LTS cohorts, defined by widespread alterations in methylation profile of genes related to immune function and distinguishing clinical features. This finding illustrates the promise of novel treatment strategies targeting immune dysregulation for a subpopulation of schizophrenia patients.

DNA methylation and the opposing NMDAR dysfunction in schizophrenia and major depression disorders: a converging model for the therapeutic effects of psychedelic compounds in the treatment of psychiatric illness

Psychedelic compounds are being increasingly explored as a potential therapeutic option for treating several psychiatric conditions, despite relatively little being known about their mechanism of action. One such possible mechanism, DNA methylation, is a process of epigenetic regulation that changes gene expression via chemical modification of nitrogenous bases. DNA methylation has been implicated in the pathophysiology of several psychiatric conditions, including schizophrenia (SZ) and major depressive disorder (MDD). In this review, we propose alterations to DNA methylation as a converging model for the therapeutic effects of psychedelic compounds, highlighting the N-methyl D-aspartate receptor (NMDAR), a crucial mediator of synaptic plasticity with known dysfunction in both diseases, as an example and anchoring point. We review the established evidence relating aberrant DNA methylation to NMDAR dysfunction in SZ and MDD and provide a model asserting that psychedelic substances may act through an epigenetic mechanism to provide therapeutic effects in the context of these disorders.

Two neurostructural subtypes: results of machine learning on brain images from 4,291 individuals with schizophrenia

Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Genome-wide DNA methylation analysis in families with multiple individuals diagnosed with schizophrenia and intellectual disability

OBJECTIVES

Schizophrenia (SZ) and intellectual disability (ID) are both included in the continuum of neurodevelopmental disorders (NDDs). DNA methylation is known to be important in the occurrence of NDDs. The family study is conducive to eliminate the effects of relative epigenetic backgrounds, and to screen for differentially methylated positions (DMPs) and regions (DMRs) that are truly associated with NDDs.

METHODS

Four monozygotic twin families were recruited, and both twin individuals suffered from NDDs (either SZ, ID, or SZ plus ID). Genome-wide methylation analysis was performed in all samples and each family. DMPs and DMRs between NDD patients and unaffected individuals were identified. Functional and pathway enrichment analyses were performed on the annotated genes.

RESULTS

Two significant DMPs annotated to CYP2E1 were found in all samples. In Family One, 1476 DMPs mapped to 880 genes, and 162 DMRs overlapping with 153 unique genes were recognised. Our results suggested that the altered methylation levels of FYN, STAT3, RAC1, and NR4A2 were associated with the development of SZ and ID. Neurodevelopment and the immune system may participate in the occurrence of SZ and ID.

CONCLUSIONS

Our findings suggested that DNA methylation participated in the development of NDDs by affecting neurodevelopment and the immune system.

Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia

BACKGROUND

Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity. This study aimed to investigate if the machine learning (ML)-based neuroanatomical and symptomatic subtypes of schizophrenia are associated.

METHODS

A total of 314 schizophrenia patients and 257 healthy controls from four sites were recruited. Gray matter volume (GMV) and Positive and Negative Syndrome Scale (PANSS) scores were employed to recognize schizophrenia neuroanatomical and symptomatic subtypes using K-means and hierarchical methods, respectively.

RESULTS

Patients with ML-based neuroanatomical subtype-1 had focally increased GMV, and subtype-2 had widespread reduced GMV than the healthy controls based on either K-means or Hierarchical methods. In contrast, patients with symptomatic subtype-1 had severe PANSS scores than subtype-2. No differences in PANSS scores were shown between the two neuroanatomical subtypes; similarly, no GMV differences were found between the two symptomatic subtypes. Cohen's Kappa test further demonstrated an apparent dissociation between the ML-based neuroanatomical and symptomatic subtypes (P > 0.05). The dissociation patterns were validated in four independent sites with diverse disease progressions (chronic vs. first episodes) and ancestors (Chinese vs. Western).

CONCLUSIONS

These findings revealed a replicable dissociation between ML-based neuroanatomical and symptomatic subtypes of schizophrenia, which provides a new viewpoint toward understanding the heterogeneity of schizophrenia.

Microglia and Other Cellular Mediators of Immunological Dysfunction in Schizophrenia: A Narrative Synthesis of Clinical Findings

Schizophrenia is a complex psychiatric condition that may involve immune system dysregulation. Since most putative disease mechanisms in schizophrenia have been derived from genetic association studies and fluid-based molecular analyses, this review aims to summarize the emerging evidence on clinical correlates to immune system dysfunction in this psychiatric disorder. We conclude this review by attempting to develop a unifying hypothesis regarding the relative contributions of microglia and various immune cell populations to the development of schizophrenia. This may provide important translational insights that can become useful for addressing the multifaceted clinical presentation of schizophrenia.

Epigenetic Aberrations in Major Psychiatric Diseases Related to Diet and Gut Microbiome Alterations

Nutrition and metabolism modify epigenetic signatures like histone acetylation and DNA methylation. Histone acetylation and DNA methylation in the central nervous system (CNS) can be altered by bioactive nutrients and gut microbiome via the gut-brain axis, which in turn modulate neuronal activity and behavior. Notably, the gut microbiome, with more than 1000 bacterial species, collectively contains almost three million functional genes whose products interact with millions of human epigenetic marks and 30,000 genes in a dynamic manner. However, genetic makeup shapes gut microbiome composition, food/nutrient metabolism, and epigenetic landscape, as well. Here, we first discuss the effect of changes in the microbial structure and composition in shaping specific epigenetic alterations in the brain and their role in the onset and progression of major mental disorders. Afterward, potential interactions among maternal diet/environmental factors, nutrition, and gastrointestinal microbiome, and their roles in accelerating or delaying the onset of severe mental illnesses via epigenetic changes will be discussed. We also provide an overview of the association between the gut microbiome, oxidative stress, and inflammation through epigenetic mechanisms. Finally, we present some underlying mechanisms involved in mediating the influence of the gut microbiome and probiotics on mental health via epigenetic modifications.

Inflammatory disequilibrium and lateral ventricular enlargement in treatment-resistant schizophrenia

Treatment-resistant schizophrenia (TRS) patient respond poorly to antipsychotics. Inflammatory imbalance involving pro- and anti-inflammatory cytokines may play an important role in the mechanism of antipsychotic-medication response. This study aimed to investigate immune imbalance and how the latter relates to clinical manifestations in patients with TRS. The level of net inflammation was estimated by evaluating the immune-inflammatory response system and compensatory immune-regulatory reflex system (IRS/CIRS) in 52 patients with TRS, 47 with non-TRS, and 56 sex and age matched healthy controls. The immune biomarkers mainly included macrophagic M1, T helper, Th-1, Th-2, Th-17, and T regulatory cytokines and receptors. Plasma cytokine levels were measured using enzyme-linked immunosorbent assay. Psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS). Subcortical volumes were quantified using a 3-T Prisma Magnetic Resonance Imaging scanner. The results showed that (1) patients with TRS were characterized by activated pro-inflammatory cytokines and relatively insufficient anti-inflammatory cytokines, with an elevated IRS/CIRS ratio indicating a new homeostatic immune setpoint; (2) IRS/CIRS ratio was positively correlated with larger lateral ventricle volume and higher PANSS score in patients with TRS. Our findings highlighted the inflammatory disequilibrium as a potential pathophysiological process of TRS.

Peripheral inflammation is associated with impairments of inhibitory behavioral control and visual sensorimotor function in psychotic disorders

Elevated markers of peripheral inflammation are common in psychosis spectrum disorders and have been associated with brain anatomy, pathology, and physiology as well as clinical outcomes. Preliminary evidence suggests a link between inflammatory cytokines and C-reactive protein (CRP) with generalized cognitive impairments in a subgroup of individuals with psychosis. Whether these patients with elevated peripheral inflammation demonstrate deficits in specific cognitive domains remains unclear. To examine this, seventeen neuropsychological and sensorimotor tasks and thirteen peripheral inflammatory and microvascular markers were quantified in a subset of B-SNIP consortium participants (129 psychosis, 55 healthy controls). Principal component analysis was conducted across the inflammatory markers, resulting in five inflammation factors. Three discrete latent cognitive domains (Visual Sensorimotor, General Cognitive Ability, and Inhibitory Behavioral Control) were characterized based on the neurobehavioral battery and examined in association with inflammation factors. Hierarchical clustering analysis identified cognition-sensitive high/low inflammation subgroups. Among persons with psychotic disorders but not healthy controls, higher inflammation scores had significant associations with impairments of Inhibitory Control (R2 = 0.100, p-value = 2.69e-4, q-value = 0.004) and suggestive associations with Visual Sensorimotor function (R2 = 0.039, p-value = 0.024, q-value = 0.180), but not with General Cognitive Ability (R2 = 0.015, p-value = 0.162). Greater deficits in Inhibitory Control were observed in the high inflammation patient subgroup, which represented 30.2 % of persons with psychotic disorders, as compared to the low inflammation psychosis subgroup. These findings indicate that inflammation dysregulation may differentially impact specific neurobehavioral domains across psychotic disorders, particularly performance on tasks requiring ongoing behavioral monitoring and control.

A Potential Immune-Related miRNAs Regulatory Network and Corresponding Diagnostic Efficacy in Schizophrenia

PURPOSE

Immune-related pathways actively participate in the progression of schizophrenia (SCZ), however, roles of immune-related miRNAs in SCZ are still unclear.

METHODS

A microarray expression study was conducted to explored roles of immune-related genes in SCZ. Functional enrichment analysis by using "clusterProfiler" was used to identify molecular alterations of SCZ. Protein-protein interaction (PPI) network was constructed and helped core molecular factors identification. Based on The Cancer Genome Atlas (TCGA) database, clinical significances of hub immune-related genes in cancers were also been explored. Then, correlation analyses were used to determine immune-related miRNAs. We further validated that hsa-miR-1299 could be an effective diagnostic biomarker for SCZ via analyzing multi-cohorts' data and quantitative real-time PCR (qRT-PCR).

RESULTS

A total of 455 mRNAs and 70 miRNAs that were differentially expressed between SCZ and control samples. Functional enrichment analysis based on differentially expressed genes (DEGs) hinted that immune-related pathways were significantly correlated with SCZ. Furthermore, a total of 35 immune-related genes that involved in disease onset and showed significant co-expressed relationships. Hub immune-related gene CCL4 and CCL22 are valuable in tumor diagnosis and survival prediction. Furthermore, we also identified 22 immune-related miRNAs that play important roles in this disease. An immune-related miRNAs-mRNAs regulatory network was constructed to provide miRNAs regulatory roles in SCZ. Core miRNAs expression status of hsa-miR-1299 were also validated in another cohort, which suggested its diagnostic performance for SCZ.

CONCLUSIONS

Our study reports the downregulation of some miRNAs in the process of SCZ are important. Shared genomics characteristics between SCZ and cancers also provide novel insights for cancers. A significant alteration of hsa-miR-1299 expression is effective as biomarker for the diagnosis of SCZ, suggesting that this miRNA could be a specific biomarker.

Epigenetic Targets in Schizophrenia Development and Therapy

Schizophrenia is regarded as a neurodevelopmental disorder with its course progressing throughout life. However, the aetiology and development of schizophrenia are still under investigation. Several data suggest that the dysfunction of epigenetic mechanisms is known to be involved in the pathomechanism of this mental disorder. The present article revised the epigenetic background of schizophrenia based on the data available in online databases (PubMed, Scopus). This paper focused on the role of epigenetic regulation, such as DNA methylation, histone modifications, and interference of non-coding RNAs, in schizophrenia development. The article also reviewed the available data related to epigenetic regulation that may modify the severity of the disease as a possible target for schizophrenia pharmacotherapy. Moreover, the effects of antipsychotics on epigenetic malfunction in schizophrenia are discussed based on preclinical and clinical results. The obtainable data suggest alterations of epigenetic regulation in schizophrenia. Moreover, they also showed the important role of epigenetic modifications in antipsychotic action. There is a need for more data to establish the role of epigenetic mechanisms in schizophrenia therapy. It would be of special interest to find and develop new targets for schizophrenia therapy because patients with schizophrenia could show little or no response to current pharmacotherapy and have treatment-resistant schizophrenia.

A machine learning approach on whole blood immunomarkers to identify an inflammation-associated psychosis onset subgroup

Psychosis onset is a transdiagnostic event that leads to a range of psychiatric disorders, which are currently diagnosed through clinical observation. The integration of multimodal biological data could reveal different subtypes of psychosis onset to target for the personalization of care. In this study, we tested the existence of subgroups of patients affected by first-episode psychosis (FEP) with a possible immunopathogenic basis. To do this, we designed a data-driven unsupervised machine learning model to cluster a sample of 127 FEP patients and 117 healthy controls (HC), based on the peripheral blood expression levels of 12 psychosis-related immune gene transcripts. To validate the model, we applied a resampling strategy based on the half-splitting of the total sample with random allocation of the cases. Further, we performed a post-hoc univariate analysis to verify the clinical, cognitive, and structural brain correlates of the subgroups identified. The model identified and validated two distinct clusters: 1) a FEP cluster characterized by the high expression of inflammatory and immune-activating genes (IL1B, CCR7, IL12A and CXCR3); 2) a cluster consisting of an equal number of FEP and HC subjects, which did not show a relative over or under expression of any immune marker (balanced subgroup). None of the subgroups was related to specific symptoms dimensions or longitudinal diagnosis of affective vs non-affective psychosis. FEP patients included in the balanced immune subgroup showed a thinning of the left supramarginal and superiorfrontal cortex (FDR-adjusted p-values < 0.05). Our results demonstrated the existence of a FEP patients' subgroup identified by a multivariate pattern of immunomarkers involved in inflammatory activation. This evidence may pave the way to sample stratification in clinical studies aiming to develop diagnostic tools and therapies targeting specific immunopathogenic pathways of psychosis.

Virtual histology of morphometric similarity network after risperidone monotherapy and imaging-epigenetic biomarkers for treatment response in first-episode schizophrenia

BACKGROUND

Antipsychotic treatment has been conceived to alter brain connectivity, but it is unclear how the changes of network phenotypes relate to the underlying transcriptomics. Given DNA methylation (DNAm) may alter transcriptional levels, we further integrated an imaging-transcriptomic-epigenetic analysis to explore multi-omics treatment response biomarkers.

METHODS

Forty-two treatment-naive first-episode schizophrenia patients were scanned by TI weighted (T1W) imaging and DTI before and after 8-week risperidone monotherapy, and their peripheral blood genomic DNAm values were examined in parallel with MRI scanning. Morphometric similarity network (MSN) quantified with DTI and T1W data were used as a marker of treatment-related alterations in interareal cortical connectivity. We utilized partial least squares (PLS) to examine spatial associations between treatment-related MSN variations and cortical transcriptomic data obtained from the Allen Human Brain Atlas.

RESULTS

Longitudinal MSN alterations were related to treatment response on cognitive function and general psychopathology symptoms, while DNAm values of 59 PLS1 genes were on negative and positive symptoms. Virtual-histology transcriptomic analysis linked the MSN alterations with the neurobiological, cellular and metabolic pathways or processes, and assigned MSN-related genes to multiple cell types, specifying neurons and glial cells as contributing most to the transcriptomic associations of longitudinal changes in MSN.

CONCLUSIONS

We firstly reveal how brain-wide transcriptional levels and cell classes capture molecularly validated cortical connectivity alterations after antipsychotic treatment. Our findings represent a vital step towards the exploration of treatment response biomarkers on the basis of multiple omics rather than a single omics type as a strategy for advancing precise care.

Epigenetic clocks in relapse after a first episode of schizophrenia

The main objective of the present study was to investigate the association between several epigenetic clocks, covering different aspects of aging, with schizophrenia relapse evaluated over a 3-year follow-up period in a cohort of ninety-one first-episode schizophrenia patients. Genome-wide DNA methylation was profiled and four epigenetic clocks, including epigenetic clocks of chronological age, mortality and telomere length were calculated. Patients that relapsed during the follow-up showed epigenetic acceleration of the telomere length clock (p = 0.030). Shorter telomere length was associated with cognitive performance (working memory, r = 0.31 p = 0.015; verbal fluency, r = 0.28 p = 0.028), but no direct effect of cognitive function or symptom severity on relapse was detected. The results of the present study suggest that epigenetic age acceleration could be involved in the clinical course of schizophrenia and could be a useful marker of relapse when measured in remission stages.

Transdiagnostic inflammatory subgroups among psychiatric disorders and their relevance to role functioning: a nested case-control study of the ALSPAC cohort

Individuals with psychotic disorders and depressive disorder exhibit altered concentrations of peripheral inflammatory markers. It has been suggested that clinical trials of anti-inflammatory therapies for psychiatric disorders should stratify patients by their inflammatory profile. Hence, we investigated whether different subgroups of individuals exist across psychiatric disorders, based on their inflammatory biomarker signatures. We measured the plasma concentrations of 17 inflammatory markers and receptors in 380 participants with psychotic disorder, depressive disorder or generalised anxiety disorder and 399 controls without psychiatric symptoms from the ALSPAC cohort at age 24. We employed a semi-supervised clustering algorithm, which discriminates multiple clusters of psychiatric disorder cases from controls. The best fit was for a two-cluster model of participants with psychiatric disorders (Adjusted Rand Index (ARI) = 0.52 ± 0.01) based on the inflammatory markers. Permutation analysis indicated the stability of the clustering solution performed better than chance (ARI = 0.43 ± 0.11; p < 0.001), and the clusters explained the inflammatory marker data better than a Gaussian distribution (p = 0.021). Cluster 2 exhibited marked increases in sTNFR1/2, suPAR, sCD93 and sIL-2RA, compared to cluster 1. Participants in the cluster exhibiting higher inflammation were less likely to be in employment, education or training, indicating poorer role functioning. This study found evidence for a novel pattern of inflammatory markers specific to psychiatric disorders and strongly associated with a transdiagnostic measure of illness severity. sTNFR1/2, suPAR, sCD93 and sIL-2RA could be used to stratify clinical trials of anti-inflammatory therapies for psychiatric disorders.

Considering medication exposure in genomic association studies of cognition in psychotic disorders

Cognitive dysfunction is a core feature of psychosis-spectrum illnesses, and the characterization of related genetic mechanisms may provide insights regarding the disease pathophysiology. Substantial efforts have been made to determine the genetic component of cognitive symptoms, without clear success. Illness-related moderators and environmental factors such as medications hinder the detection of genomic association with cognition. Polypharmacy is common in psychotic disorders, and the cumulative effects of medication regimens can confound gene-cognition associations. A review of the relative contributions of important pharmacological and genetic relationships identifies that the effects of medications on cognition in psychotic disorders may be at least, if not more, impactful than individual genes, thus underscoring the importance of accounting for medication exposure in gene-cognition association studies.

Immune-Related Genomic Schizophrenic Subtyping Identified in DLPFC Transcriptome

Well-documented evidence of the physiologic, genetic, and behavioral heterogeneity of schizophrenia suggests that diagnostic subtyping may clarify the underlying pathobiology of the disorder. Recent studies have demonstrated that increased inflammation may be a prominent feature of a subset of schizophrenics. However, these findings are inconsistent, possibly due to evaluating schizophrenics as a single group. In this study, we segregated schizophrenic patients into two groups (“Type 1”, “Type 2”) by their gene expression in the dorsolateral prefrontal cortex and explored biological differences between the subgroups. The study included post-mortem tissue samples that were sequenced in multiple, publicly available gene datasets using different sequencing methods. To evaluate the role of inflammation, the expression of genes in multiple components of neuroinflammation were examined: complement cascade activation, glial cell activation, pro-inflammatory mediator secretion, blood–brain barrier (BBB) breakdown, chemokine production and peripheral immune cell infiltration. The Type 2 schizophrenics showed widespread abnormal gene expression across all the neuroinflammation components that was not observed in Type 1 schizophrenics. Our results demonstrate the importance of separating schizophrenic patients into their molecularly defined subgroups and provide supporting evidence for the involvement of the immune-related pathways in a schizophrenic subset.