Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: differential involvement of immune-related gene loci

Fine-mapping genomic loci refines bipolar disorder risk genes

Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 17 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, CRTC3, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, DPH1, GSDMB, MED24 and THRA in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of BD polygenic risk scores across diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).

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.

microRNA and the Post-Transcriptional Response to Oxidative Stress during Neuronal Differentiation: Implications for Neurodevelopmental and Psychiatric Disorders

Oxidative stress is one of the most important environmental exposures associated with psychiatric disorders, but the underlying molecular mechanisms remain to be elucidated. In a previous study, we observed a substantial alteration of the gene expression landscape in neuron-like cells that were differentiated from SH-SY5Y cells after or during exposure to oxidative stress, with a subset of dysregulated genes being enriched for neurodevelopmental processes. To further explore the regulatory mechanisms that might account for such profound perturbations, we have now applied small RNA-sequencing to investigate changes in the expression of miRNAs. These molecules are known to play crucial roles in brain development and response to stress through their capacity to suppress gene expression and influence complex biological networks. Through these analyses, we observed more than a hundred differentially expressed miRNAs, including 80 previously reported to be dysregulated in psychiatric disorders. The seven most influential miRNAs associated with pre-treatment exposure, including miR-138-5p, miR-96-5p, miR-34c-5p, miR-1287-5p, miR-497-5p, miR-195-5p, and miR-16-5p, supported by at least 10 negatively correlated mRNA connections, formed hubs in the interaction network with 134 genes enriched with neurobiological function, whereas in the co-treatment condition, miRNA-mRNA interaction pairs were enriched in cardiovascular and immunity-related disease ontologies. Interestingly, 12 differentially expressed miRNAs originated from the DLK1-DIO3 location, which encodes a schizophrenia-associated miRNA signature. Collectively, our findings suggest that early exposure to oxidative stress, before and during prenatal neuronal differentiation, might increase the risk of mental illnesses in adulthood by disturbing the expression of miRNAs that regulate neurodevelopmentally significant genes and networks.

The Genomic Intersection of Oligodendrocyte Dynamics in Schizophrenia and Aging Unravels Novel Pathological Mechanisms and Therapeutic Potentials

Schizophrenia is a significant worldwide health concern, affecting over 20 million individuals and contributing to a potential reduction in life expectancy by up to 14.5 years. Despite its profound impact, the precise pathological mechanisms underlying schizophrenia continue to remain enigmatic, with previous research yielding diverse and occasionally conflicting findings. Nonetheless, one consistently observed phenomenon in brain imaging studies of schizophrenia patients is the disruption of white matter, the bundles of myelinated axons that provide connectivity and rapid signalling between brain regions. Myelin is produced by specialised glial cells known as oligodendrocytes, which have been shown to be disrupted in post-mortem analyses of schizophrenia patients. Oligodendrocytes are generated throughout life by a major population of oligodendrocyte progenitor cells (OPC), which are essential for white matter health and plasticity. Notably, a decline in a specific subpopulation of OPC has been identified as a principal factor in oligodendrocyte disruption and white matter loss in the aging brain, suggesting this may also be a factor in schizophrenia. In this review, we analysed genomic databases to pinpoint intersections between aging and schizophrenia and identify shared mechanisms of white matter disruption and cognitive dysfunction.

Transcriptome profiling as a biological marker for bipolar disorder sub-phenotypes

PURPOSE

Bipolar affective disorder (BP) causes major functional impairment and reduced quality of life not only for patients, but also for many close relatives. We aimed to investigate mRNA levels in BP patients to find differentially expressed genes linked to specific clinical course variants; assuming that several gene expression alterations might indicate vulnerability pathways for specific course and severity of the disease.

MATERIALS

We searched for up- and down-regulated genes comparing patients with diagnosis of BP type I (BPI) vs type II (BPII), history of suicide attempts, psychotic symptoms, predominance of manic/hypomanic episodes, and history of numerous episodes and comorbidity of substance use disorders or anxiety disorders. RNA was extracted from peripheral blood mononuclear cells and analyzed with use of microarray slides.

RESULTS

Differentially expressed genes (DEGs) were found in all disease characteristics compared. The lowest number of DEGs were revealed when comparing BPI and BPII patients (18 genes), and the highest number when comparing patients with and without psychotic symptoms (3223 genes). Down-regulated genes identified here with the use of the DAVID database were among others linked to cell migration, defense response, and inflammatory response.

CONCLUSIONS

The most specific transcriptome profile was revealed in BP with psychotic symptoms. Differentially expressed genes in this variant include, among others, genes involved in inflammatory and immune processes. It might suggest the overlap of biological background between BP with a history of psychotic features and schizophrenia.

Genetic evidence for causal effects of immune dysfunction in psychiatric disorders: where are we?

The question of whether immune dysfunction contributes to risk of psychiatric disorders has long been a subject of interest. To assert this hypothesis a plethora of correlative evidence has been accumulated from the past decades; however, a variety of technical and practical obstacles impeded on a cause-effect interpretation of these data. With the advent of large-scale omics technology and advanced statistical models, particularly Mendelian randomization, new studies testing this old hypothesis are accruing. Here we synthesize these new findings from genomics and genetic causal inference studies on the role of immune dysfunction in major psychiatric disorders and reconcile these new data with pre-omics findings. By reconciling these evidences, we aim to identify key gaps and propose directions for future studies in the field.

HLA-C*07:01 and HLA-DQB1*02:01 protect against white matter hyperintensities and deterioration of cognitive function: A population-based cohort study

BACKGROUND

Neuroinflammation and aberrant immune regulation are increasingly implicated in the pathophysiology of white matter hyperintensities (WMH), an imaging marker of cerebrovascular pathologies and predictor of cognitive impairment. The role of human leukocyte antigen (HLA) genes, critical in immunoregulation and associated with susceptibility to neurodegenerative diseases, in WMH pathophysiology remains unexplored.

METHODS

We performed association analyses between classical HLA alleles and WMH volume, derived from MRI scans of 38 302 participants in the UK Biobank. To identify independent functional alleles driving these associations, we conducted conditional forward stepwise regression and lasso regression. We further investigated whether these functional alleles showed consistent associations with WMH across subgroups characterized by varying levels of clinical determinants. Additionally, we validated the clinical relevance of the identified alleles by examining their association with cognitive function (n = 147 549) and dementia (n = 460 029) in a larger cohort.

FINDINGS

Four HLA alleles (DQB1*02:01, DRB1*03:01, C*07:01, and B*08:01) showed an association with reduced WMH volume after Bonferroni correction for multiple comparisons. Among these alleles, DQB1*02:01 exhibited the most significant association (β = -0.041, 95 % CI: -0.060 to -0.023, p = 1.04 × 10-5). Forward selection and lasso regression analyses indicated that DQB1*02:01 and C*07:01 primarily drove this association. The protective effect against WMH conferred by DQB1*02:01 and C*07:01 persisted in clinically relevant subgroups, with a stronger effect observed in older participants. Carrying DQB1*02:01 and C*07:01 was associated with higher cognitive function, but no association with dementia was found.

INTERPRETATION

Our population-based findings support the involvement of immune-associated mechanisms, particularly both HLA class I and class II genes, in the pathogenesis of WMH and subsequent consequence of cognitive functions.

Shared Genetic Loci Between Schizophrenia and White Blood Cell Counts Suggest Genetically Determined Systemic Immune Abnormalities

BACKGROUND

Immune mechanisms are indicated in schizophrenia (SCZ). Recent genome-wide association studies (GWAS) have identified genetic variants associated with SCZ and immune-related phenotypes. Here, we use cutting edge statistical tools to identify shared genetic variants between SCZ and white blood cell (WBC) counts and further understand the role of the immune system in SCZ.

STUDY DESIGN

GWAS results from SCZ (patients, n = 53 386; controls, n = 77 258) and WBC counts (n = 56 3085) were analyzed. We applied linkage disequilibrium score regression, the conditional false discovery rate method and the bivariate causal mixture model for analyses of genetic associations and overlap, and 2 sample Mendelian randomization to estimate causal effects.

STUDY RESULTS

The polygenicity for SCZ was 7.5 times higher than for WBC count and constituted 32%-59% of WBC count genetic loci. While there was a significant but weak positive genetic correlation between SCZ and lymphocytes (rg = 0.05), the conditional false discovery rate method identified 383 shared genetic loci (53% concordant effect directions), with shared variants encompassing all investigated WBC subtypes: lymphocytes, n = 215 (56% concordant); neutrophils, n = 158 (49% concordant); monocytes, n = 146 (47% concordant); eosinophils, n = 135 (56% concordant); and basophils, n = 64 (53% concordant). A few causal effects were suggested, but consensus was lacking across different Mendelian randomization methods. Functional analyses indicated cellular functioning and regulation of translation as overlapping mechanisms.

CONCLUSIONS

Our results suggest that genetic factors involved in WBC counts are associated with the risk of SCZ, indicating a role of immune mechanisms in subgroups of SCZ with potential for stratification of patients for immune targeted treatment.

Fecal Microbiota Underlying the Coexistence of Schizophrenia and Multiple Sclerosis in Chinese Patients

Both schizophrenia (SZ) and multiple sclerosis (MS) affect millions of people worldwide and impose a great burden on society. Recent studies indicated that MS elevated the risk of SZ and vice versa, whereas the underlying pathological mechanisms are still obscure. Considering that fecal microbiota played a vital role in regulating brain functions, the fecal microbiota and serum cytokines from 90 SZ patients and 71 age-, gender-, and BMI-matched cognitively normal subjects (referred as SZC), 22 MS patients and 33 age-, gender-, and BMI-matched healthy subjects (referred as MSC) were analyzed. We found that both diseases demonstrated similar microbial diversity and shared three differential genera, including the down-regulated Faecalibacterium, Roseburia, and the up-regulated Streptococcus. Functional analysis indicated that the three genera were involved in pathways such as "carbohydrate metabolism" and "amino acid metabolism." Moreover, the variation patterns of serum cytokines associated with MS and SZ patients were a bit different. Among the six cytokines perturbed in both diseases, TNF-α increased, while IL-8 and MIP-1α decreased in both diseases. IL-1ra, PDGF-bb, and RANTES were downregulated in MS patients but upregulated in SZ patients. Association analyses showed that Faecalibacterium demonstrated extensive correlations with cytokines in both diseases. Most notably, Faecalibacterium correlated negatively with TNF-α. In other words, fecal microbiota such as Faecalibacterium may contribute to the coexistence of MS and SZ by regulating serum cytokines. Our study revealed the potential roles of fecal microbiota in linking MS and SZ, which paves the way for developing gut microbiota-targeted therapies that can manage two diseases with a single treat.

The future of diagnosis in clinical neurosciences: Comparing multiple sclerosis and schizophrenia

The ongoing developments of psychiatric classification systems have largely improved reliability of diagnosis, including that of schizophrenia. However, with an unknown pathophysiology and lacking biomarkers, its validity still remains low, requiring further advancements. Research has helped establish multiple sclerosis (MS) as the central nervous system (CNS) disorder with an established pathophysiology, defined biomarkers and therefore good validity and significantly improved treatment options. Before proposing next steps in research that aim to improve the diagnostic process of schizophrenia, it is imperative to recognize its clinical heterogeneity. Indeed, individuals with schizophrenia show high interindividual variability in terms of symptomatic manifestation, response to treatment, course of illness and functional outcomes. There is also a multiplicity of risk factors that contribute to the development of schizophrenia. Moreover, accumulating evidence indicates that several dimensions of psychopathology and risk factors cross current diagnostic categorizations. Schizophrenia shares a number of similarities with MS, which is a demyelinating disease of the CNS. These similarities appear in the context of age of onset, geographical distribution, involvement of immune-inflammatory processes, neurocognitive impairment and various trajectories of illness course. This article provides a critical appraisal of diagnostic process in schizophrenia, taking into consideration advancements that have been made in the diagnosis and management of MS. Based on the comparison between the two disorders, key directions for studies that aim to improve diagnostic process in schizophrenia are formulated. All of them converge on the necessity to deconstruct the psychosis spectrum and adopt dimensional approaches with deep phenotyping to refine current diagnostic boundaries.

Schizophrenia as autoimmune disease: Involvement of Anti-NCAM antibodies

Understanding the etiopathogenesis of schizophrenia has always been an unsolved puzzle for modern medicine. This seems to be due to both disease complexity and lack of sufficient knowledge regarding the biological and non-biological anomalies that exhibit schizophrenia subjects. However, dysregulated immunity is a commonly identified feature in affected individuals. Thus, recently, a hallmark study showed causality relationship between anti-NCAM antibodies and schizophrenia-related behaviors in mice. NCAM plays crucial role in neurodevelopment during early life and neuroplasticity against different stressors during adulthood, and its dysfunction in schizophrenia is increasingly proven. The present review provides the main evidence that support the contribution of autoimmunity and NCAM abnormalities in the development of schizophrenia. Furthermore, it introduces five hypotheses that may explain the mechanism by which anti-NCAM antibodies are produced in the context of schizophrenia: (i) molecular mimicry, (ii) gut dysbiosis, (iii) viral infection, (iv) exposure to environmental pollutants, (v) and NCAM production anomalies.

Regulation of synaptic connectivity in schizophrenia spectrum by mutual neuron-microglia interaction

The examination of post-mortem brain tissue suggests synaptic loss as a central pathological hallmark of schizophrenia spectrum (SCZ), which is potentially related to activated microglia and increased inflammation. Induced pluripotent stem cells serve as a source for neurons and microglia-like cells to address neuron-microglia interactions. Here, we present a co-culture model of neurons and microglia, both of human origin, to show increased susceptibility of neurons to microglia-like cells derived from SCZ patients. Analysis of IBA-1 expression, NFκB signaling, transcription of inflammasome-related genes, and caspase-1 activation shows that enhanced, intrinsic inflammasome activation in patient-derived microglia exacerbates neuronal deficits such as synaptic loss in SCZ. Anti-inflammatory pretreatment of microglia with minocycline specifically rescued aberrant synapse loss in SCZ and reduced microglial activation. These findings open up possibilities for further research in larger cohorts, focused clinical work and longitudinal studies that could facilitate earlier therapeutic intervention.

Neuroimmune, clinical and treatment challenges in multiple sclerosis-related psychoses

In recent years, epidemiological and genetic studies have shown an association between autoimmune diseases and psychosis. The question arises whether patients with schizophrenia are more likely to develop multiple sclerosis (MS) later in life. It is well known that the immune system plays an important role in the etiopathogenesis of both disorders. Immune disturbances may be similar or very different in terms of different types of immune responses, disturbed myelination, and/or immunogenetic predispositions. A psychotic symptom may be a consequence of the MS diagnosis itself or a separate entity. In this review article, we discussed the timing of onset of psychotic symptoms and MS and whether the use of corticosteroids as therapy for acute relapses in MS is unfairly neglected in patients with psychiatric comorbidities. In addition, we discussed that the anti-inflammatory potential of antipsychotics could be useful and should be considered, especially in the treatment of psychosis that coexists with MS. Autoimmune disorders could precipitate psychotic symptoms, and in this context, autoimmune psychosis must be considered as a persistent symptomatology that requires continuous and specific treatment.

[A clinical case of multiple sclerosis with an episode of schizophrenia-like syndrome]

The article presents a clinical observation of a schizophrenia-like disorder in a patient with multiple sclerosis (MS). The patient had highly active MS with a relapsing course, the diagnosis was made based on the McDonald 2017 criteria. During the course of a demyelinating disease of the nervous system, the patient developed an episode of psychotic disorders with symptoms of mutism, hallucinations, delusions and impaired thinking, which was quickly stopped in stationary conditions. This case is of particular interest to neurologists and psychiatrists, since psychotic disorders occur in MS patients and cause difficulties in diagnosis and treatment.

The Influence of HLA Alleles on the Affective Distress Profile

(1) Background: Affective distress can be triggered by aggressive stimuli with an unfavorable role for the individual. Some of the factors that lead to the development and evolution of a mental disorder can be genetic. The aim of this study is to determine some correlations between the human leukocyte antigen (HLA) genes and the affective distress profile (PDA). (2) Methods: A psychological assessment and testing tool for anxiety was applied to 115 people. The low-resolution HLA alleles of class I (HLA-A, HLA-B, and HLA-C) and class II (HLA-DRB1 and HLA-DQB1) were identified by the PCR technique after DNA extraction from the blood. Depending on the PDA, the subjects were divided into two groups: a group with a low PDA and another one with a medium and high PDA. The IBM SPSS software was used to compare the frequency of HLA alleles between the two groups. (3) Results: The univariate analysis revealed a significant association of the HLA-A locus (A*01, A*30), HLA-B (B*08), and HLA-DRB1 (DRB1*11) with the low PDA group and of the HLA-A locus (A*32), HLA-B (B*52), and HLA-C (C*12) with the medium and high PDA group. (4) Conclusions: The present study highlighted potential associations between HLA alleles and anxiety disorders.

The shared genetic basis of mood instability and psychiatric disorders: A cross-trait genome-wide association analysis

Recent genome-wide association studies of mood instability (MOOD) have found significant positive genetic correlation with major depression (DEP) and weak correlations with other psychiatric disorders. We investigated the polygenic overlap between MOOD and psychiatric disorders beyond genetic correlation to better characterize putative shared genetic determinants. GWAS summary statistics for schizophrenia (SCZ, n = 105,318), bipolar disorder (BIP, n = 413,466), DEP (n = 450,619), attention-deficit hyperactivity disorder (ADHD, n = 53,293), and MOOD (n = 363,705) were analyzed using the bivariate causal mixture model and conjunctional false discovery rate methods. MOOD correlated positively with all psychiatric disorders, but with wide variation in strength (r_g  = 0.10-0.62). Of 10.4 K genomic variants influencing MOOD, 4 K-9.4 K influenced psychiatric disorders. Furthermore, MOOD was jointly associated with DEP at 163 loci, SCZ at 110, BIP at 60 and ADHD at 25. Fifty-three jointly associated loci were overlapping across two or more disorders, seven of which had discordant effect directions on psychiatric disorders. Genes mapped to loci associated with MOOD and all four disorders were enriched in a single gene-set, "synapse organization." The extensive polygenic overlap indicates shared molecular underpinnings across MOOD and psychiatric disorders. However, distinct patterns of genetic correlation and effect directions may relate to differences in the core clinical features of each disorder.

Exploring Lead loci shared between schizophrenia and Cardiometabolic traits

Individuals with schizophrenia (SCZ) have, on average, a 10- to 20-year shorter expected life span than the rest of the population, primarily due to cardiovascular disease comorbidity. Genome-wide association studies (GWAS) have previously been used to separately identify common variants in SCZ and cardiometabolic traits. However, genetic variants jointly influencing both traits remain to be fully characterised. To assess overlaps (if any) between the genetic architecture of SCZ and cardiometabolic traits, we used conditional false discovery rate (FDR) and local genetic correlation statistical framework analyses. A conjunctional FDR was used to identify shared genetic traits between SCZ and cardiometabolic risk factors. We identified 144 genetic variants which were shared between SCZ and body mass index (BMI), and 15 variants shared between SCZ and triglycerides (TG). Furthermore, we discovered four novel single nucleotide polymorphisms (SNPs) (rs3865350, rs9860913, rs13307 and rs9614186) and four proximate genes (DERL2, SNX4, LY75 and EFCAB6) which were shared by SCZ and BMI. We observed that the novel genetic variant rs13307 and the most proximate gene LY75 exerted potential effects on SCZ and BMI comorbidity. Also, we observed a mixture of concordant and opposite direction associations with shared genetic variants. We demonstrated a moderate to high genetic overlap between SCZ and cardiometabolic traits associated with a pattern of bidirectional associations. Our data suggested a complex interplay between metabolism-related gene pathways in SCZ pathophysiology.

Genome-wide analysis of schizophrenia and multiple sclerosis identifies shared genomic loci with mixed direction of effects

Common genetic variants identified in genome-wide association studies (GWAS) show varying degrees of genetic pleiotropy across complex human disorders. Clinical studies of schizophrenia (SCZ) suggest that in addition to neuropsychiatric symptoms, patients with SCZ also show variable immune dysregulation. Epidemiological studies of multiple sclerosis (MS), an autoimmune, neurodegenerative disorder of the central nervous system, suggest that in addition to the manifestation of neuroinflammatory complications, patients with MS may also show co-occurring neuropsychiatric symptoms with disease progression. In this study, we analyzed the largest available GWAS datasets for SCZ (N = 161,405) and MS (N = 41,505) using Gaussian causal mixture modeling (MiXeR) and conditional/conjunctional false discovery rate (condFDR) frameworks to explore and quantify the shared genetic architecture of these two complex disorders at common variant level. Despite detecting only a negligible genetic correlation (rG = 0.057), we observe polygenic overlap between SCZ and MS, and a substantial genetic enrichment in SCZ conditional on associations with MS, and vice versa. By leveraging this cross-disorder enrichment, we identified 36 loci jointly associated with SCZ and MS at conjunctional FDR < 0.05 with mixed direction of effects. Follow-up functional analysis of the shared loci implicates candidate genes and biological processes involved in immune response and B-cell receptor signaling pathways. In conclusion, this study demonstrates the presence of polygenic overlap between SCZ and MS in the absence of a genetic correlation and provides new insights into the shared genetic architecture of these two disorders at the common variant level.

fcfdr: an R package to leverage continuous and binary functional genomic data in GWAS

BACKGROUND

Genome-wide association studies (GWAS) are limited in power to detect associations that exceed the stringent genome-wide significance threshold. This limitation can be alleviated by leveraging relevant auxiliary data, such as functional genomic data. Frameworks utilising the conditional false discovery rate have been developed for this purpose, and have been shown to increase power for GWAS discovery whilst controlling the false discovery rate. However, the methods are currently only applicable for continuous auxiliary data and cannot be used to leverage auxiliary data with a binary representation, such as whether SNPs are synonymous or non-synonymous, or whether they reside in regions of the genome with specific activity states.

RESULTS

We describe an extension to the cFDR framework for binary auxiliary data, called "Binary cFDR". We demonstrate FDR control of our method using detailed simulations, and show that Binary cFDR performs better than a comparator method in terms of sensitivity and FDR control. We introduce an all-encompassing user-oriented CRAN R package ( https://annahutch.github.io/fcfdr/ ; https://cran.r-project.org/web/packages/fcfdr/index.html ) and demonstrate its utility in an application to type 1 diabetes, where we identify additional genetic associations.

CONCLUSIONS

Our all-encompassing R package, fcfdr, serves as a comprehensive toolkit to unite GWAS and functional genomic data in order to increase statistical power to detect genetic associations.

Large-scale genomic analyses reveal insights into pleiotropy across circulatory system diseases and nervous system disorders

Clinical and epidemiological studies have shown that circulatory system diseases and nervous system disorders often co-occur in patients. However, genetic susceptibility factors shared between these disease categories remain largely unknown. Here, we characterized pleiotropy across 107 circulatory system and 40 nervous system traits using an ensemble of methods in the eMERGE Network and UK Biobank. Using a formal test of pleiotropy, five genomic loci demonstrated statistically significant evidence of pleiotropy. We observed region-specific patterns of direction of genetic effects for the two disease categories, suggesting potential antagonistic and synergistic pleiotropy. Our findings provide insights into the relationship between circulatory system diseases and nervous system disorders which can provide context for future prevention and treatment strategies.

Limited association between infections, autoimmune disease and genetic risk and immune activation in severe mental disorders

BACKGROUND

Low-grade inflammation may be part of the underlying mechanism of schizophrenia and bipolar disorder. We investigated if genetic susceptibility, infections or autoimmunity could explain the immune activation.

METHODS

Seven immune markers were selected based on indicated associations to severe mental disorders (IL-1Ra, sIL-2R, IL-18, sgp130, sTNFR-1, APRIL, ICAM-1) and measured in plasma of patients with schizophrenia (SCZ, N = 732) and bipolar spectrum disorders (BD, N = 460) and healthy controls (HC, N = 938). Information on rate of infections and autoimmune diseases were obtained from Norwegian national health registries for a twelve-year period. Polygenic risk scores (PRS) of SCZ and BD were calculated from genome-wide association studies. Analysis of covariance were used to test effects of infection rate, autoimmune disease and PRS on differences in immune markers between patients and HC.

RESULTS

Infection rate differed between all groups (BD > HC > SCZ, all p < 0.001) whereas autoimmune disease was more frequent in BD compared to SCZ (p = 0.004) and HC (p = 0.003). sIL-2R was positively associated with autoimmune disease (p = 0.001) and negatively associated with PRS of SCZ (p = 0.006) across SCZ and HC; however, associations represented only small changes in the difference of sIL-2R levels between SCZ and HC.

CONCLUSION

There were few significant associations between rate of infections, autoimmune disease or PRS and altered immune markers in SCZ and BD, and the detected associations represented only small changes in the immune aberrations. The findings suggest that most of the low-grade inflammation in SCZ and BD is explained by other factors than the underlying PRS, autoimmunity and infection rates.

Obesity and the Brain

Innate and adaptive immunity are essential for neurodevelopment and central nervous system (CNS) homeostasis; however, the fragile equilibrium between immune and brain cells can be disturbed by any immune dysregulation and cause detrimental effects. Accumulating evidence indicates that, despite the blood-brain barrier (BBB), overactivation of the immune system leads to brain vulnerability that increases the risk of neuropsychiatric disorders, particularly upon subsequent exposure later in life. Disruption of microglial function in later life can be triggered by various environmental and psychological factors, including obesity-driven chronic low-grade inflammation and gut dysbiosis. Increased visceral adiposity has been recognized as an important risk factor for multiple neuropsychiatric conditions. The review aims to present our current understanding of the topic.

Bipolar spectrum disorders in neurologic disorders

Psychiatric symptoms frequently predate or complicate neurological disorders, such as neurodegenerative diseases. Symptoms of bipolar spectrum disorders (BSD), like mood, behavioral, and psychotic alterations, are known to occur - individually or as a syndromic cluster - in Parkinson's disease and in the behavioral variant of frontotemporal dementia (FTD). Nonetheless, due to shared pathophysiological mechanisms, or genetic predisposition, several other neurological disorders show significant, yet neglected, clinical and biological overlaps with BSD like neuroinflammation, ion channel dysfunctions, neurotransmission imbalance, or neurodegeneration. BSD pathophysiology is still largely unclear, but large-scale network dysfunctions are known to participate in the onset of mood disorders and psychotic symptoms. Thus, functional alterations can unleash BSD symptoms years before the evidence of an organic disease of the central nervous system. The aim of our narrative review was to illustrate the numerous intersections between BSD and neurological disorders from a clinical-biological point of view and the underlying predisposing factors, to guide future diagnostic and therapeutical research in the field.

Systematic Exploration in Tissue-Pathway Associations of Complex Traits Using Comprehensive eQTLs Catalog

The collection of expression quantitative trait loci (eQTLs) is an important resource to study complex traits through understanding where and how transcriptional regulations are controlled by genetic variations in the non-coding regions of the genome. Previous studies have focused on associating eQTLs with traits to identify the roles of trait-related eQTLs and their corresponding target genes involved in trait determination. Since most genes function as a part of pathways in a systematic manner, it is crucial to explore the pathways’ involvements in complex traits to test potentially novel hypotheses and to reveal underlying mechanisms of disease pathogenesis. In this study, we expanded and applied loci2path software to perform large-scale eQTLs enrichment [i.e., eQTLs’ target genes (eGenes) enrichment] analysis at pathway level to identify the tissue-specific enriched pathways within trait-related genomic intervals. By utilizing 13,791,909 eQTLs cataloged in the Genotype-Tissue Expression (GTEx) V8 data for 49 tissue types, 2,893 pathway sets reported from MSigDB, and query regions derived from the Phenotype-Genotype Integrator (PheGenI) catalog, we identified intriguing biological pathways that are likely to be involved in ten traits [Alzheimer’s disease (AD), body mass index, Parkinson’s disease (PD), schizophrenia, amyotrophic lateral sclerosis, non-small cell lung cancer (NSCLC), stroke, blood pressure, autism spectrum disorder, and myocardial infarction]. Furthermore, we extracted the most significant pathways for AD, such as BioCarta D4-GDI pathway and WikiPathways sulfation biotransformation reaction and viral acute myocarditis pathways, to study specific genes within pathways. Our data presented new hypotheses in AD pathogenesis supported by previous studies, like the increased level of caspase-3 in the amygdala that cleaves GDP dissociation inhibitor and binds to beta-amyloid, leading to increased apoptosis and neuronal loss. Our findings also revealed potential pathogenesis mechanisms for PD, schizophrenia, NSCLC, blood pressure, autism spectrum disorder, and myocardial infarction, which were consistent with past studies. Our results indicated that loci2path′s eQTLs enrichment test was valuable in unveiling novel biological mechanisms of complex traits. The discovered mechanisms of disease pathogenesis and traits require further in-depth analysis and experimental validation.

Leveraging auxiliary data from arbitrary distributions to boost GWAS discovery with Flexible cFDR

Genome-wide association studies (GWAS) have identified thousands of genetic variants that are associated with complex traits. However, a stringent significance threshold is required to identify robust genetic associations. Leveraging relevant auxiliary covariates has the potential to boost statistical power to exceed the significance threshold. Particularly, abundant pleiotropy and the non-random distribution of SNPs across various functional categories suggests that leveraging GWAS test statistics from related traits and/or functional genomic data may boost GWAS discovery. While type 1 error rate control has become standard in GWAS, control of the false discovery rate can be a more powerful approach. The conditional false discovery rate (cFDR) extends the standard FDR framework by conditioning on auxiliary data to call significant associations, but current implementations are restricted to auxiliary data satisfying specific parametric distributions, typically GWAS p-values for related traits. We relax these distributional assumptions, enabling an extension of the cFDR framework that supports auxiliary covariates from arbitrary continuous distributions ("Flexible cFDR"). Our method can be applied iteratively, thereby supporting multi-dimensional covariate data. Through simulations we show that Flexible cFDR increases sensitivity whilst controlling FDR after one or several iterations. We further demonstrate its practical potential through application to an asthma GWAS, leveraging various functional genomic data to find additional genetic associations for asthma, which we validate in the larger, independent, UK Biobank data resource.

Characterising the shared genetic determinants of bipolar disorder, schizophrenia and risk-taking

Increased risk-taking is a central component of bipolar disorder (BIP) and is implicated in schizophrenia (SCZ). Risky behaviours, including smoking and alcohol use, are overrepresented in both disorders and associated with poor health outcomes. Positive genetic correlations are reported but an improved understanding of the shared genetic architecture between risk phenotypes and psychiatric disorders may provide insights into underlying neurobiological mechanisms. We aimed to characterise the genetic overlap between risk phenotypes and SCZ, and BIP by estimating the total number of shared variants using the bivariate causal mixture model and identifying shared genomic loci using the conjunctional false discovery rate method. Summary statistics from genome wide association studies of SCZ, BIP, risk-taking and risky behaviours were acquired (n = 82,315-466,751). Genomic loci were functionally annotated using FUMA. Of 8.6-8.7 K variants predicted to influence BIP, 6.6 K and 7.4 K were predicted to influence risk-taking and risky behaviours, respectively. Similarly, of 10.2-10.3 K variants influencing SCZ, 9.6 and 8.8 K were predicted to influence risk-taking and risky behaviours, respectively. We identified 192 loci jointly associated with SCZ and risk phenotypes and 206 associated with BIP and risk phenotypes, of which 68 were common to both risk-taking and risky behaviours and 124 were novel to SCZ or BIP. Functional annotation implicated differential expression in multiple cortical and sub-cortical regions. In conclusion, we report extensive polygenic overlap between risk phenotypes and BIP and SCZ, identify specific loci contributing to this shared risk and highlight biologically plausible mechanisms that may underlie risk-taking in severe psychiatric disorders.

Cerebrospinal Fluid Pathologies in Schizophrenia-Spectrum Disorder-A Retrospective Chart Review

BACKGROUND

The role of inflammatory processes in the etiology of schizophrenia is increasingly being investigated. A link between psychosis and inflammation measured with different biomarkers has been reported in the literature and needs to be further explored. To investigate the presence of inflammatory biomarkers in first-episode psychosis (FEP) we analyzed the largest available FEP cohort to date regarding routine CSF and blood diagnostics.

METHODS

We report a retrospective analysis of clinical data from all inpatients that were admitted to our tertiary care hospital with a ICD-10 diagnosis of F2x (schizophrenia-spectrum) between January 1, 2008 and August 1, 2018 and underwent a lumbar puncture.

RESULTS

A total of n = 314 FEP patients were included in our sample. 42.7% patients (134/314) showed cerebrospinal fluid (CSF) alterations. Oligoclonal bands in the CSF were present in 21.8% of patients (67/307) with 12.4% (27/217) of patients presenting OCBs type 2 or 3. 15.8% (49/310) of our cohort revealed signs of blood-brain-barrier (BBB) dysfunction with increased albumin ratios. Mean serum CRP levels were 2.4 mg/l (SD = 9.5). CRP elevation was present in 116/280 cases (41.4%).

CONCLUSIONS

This large retrospective analysis on FEP cohort greatly enriches the clinical data available on this population and contributes to the discussion around inflammation in psychosis. Of note, even though several inflammatory alterations were found both in CSF and in blood tests, we found no evidence for a significant relationship between peripheral inflammation and inflammatory CSF. Furthermore, no significant relationship between CSF alterations and peripheral inflammation measured with CRP could be established.

Genetic Association Between Schizophrenia and Cortical Brain Surface Area and Thickness

Importance

Schizophrenia is a complex heritable disorder associated with many genetic variants, each with a small effect. While cortical differences between patients with schizophrenia and healthy controls are consistently reported, the underlying molecular mechanisms remain elusive.

Objective

To investigate the extent of shared genetic architecture between schizophrenia and brain cortical surface area (SA) and thickness (TH) and to identify shared genomic loci.

Design, Setting, and Participants

Independent genome-wide association study data on schizophrenia (Psychiatric Genomics Consortium and CLOZUK: n = 105 318) and SA and TH (UK Biobank: n = 33 735) were obtained. The extent of polygenic overlap was investigated using MiXeR. The specific shared genomic loci were identified by conditional/conjunctional false discovery rate analysis and were further examined in 3 independent cohorts. Data were collected from December 2019 to February 2021, and data analysis was performed from May 2020 to February 2021.

Main Outcomes and Measures

The primary outcomes were estimated fractions of polygenic overlap between schizophrenia, total SA, and average TH and a list of functionally characterized shared genomic loci.

Results

Based on genome-wide association study data from 139 053 participants, MiXeR estimated schizophrenia to be more polygenic (9703 single-nucleotide variants [SNVs]) than total SA (2101 SNVs) and average TH (1363 SNVs). Most SNVs associated with total SA (1966 of 2101 [93.6%]) and average TH (1322 of 1363 [97.0%]) may be associated with the development of schizophrenia. Subsequent conjunctional false discovery rate analysis identified 44 and 23 schizophrenia risk loci shared with total SA and average TH, respectively. The SNV associations of shared loci between schizophrenia and total SA revealed en masse concordant association between the discovery and independent cohorts. After removing high linkage disequilibrium regions, such as the major histocompatibility complex region, the shared loci were enriched in immunologic signature gene sets. Polygenic overlap and shared loci between schizophrenia and schizophrenia-associated regions of interest for SA (superior frontal and middle temporal gyri) and for TH (superior temporal, inferior temporal, and superior frontal gyri) were also identified.

Conclusions and Relevance

This study demonstrated shared genetic loci between cortical morphometry and schizophrenia, among which a subset are associated with immunity. These findings provide an insight into the complex genetic architecture and associated with schizophrenia.

Immune system regulation and role of the human leukocyte antigen in posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) is a debilitating condition that adversely affect mental and physical health. Recent studies have increasingly explored the role of the immune system in risk for PTSD and its related symptoms. Dysregulation of the immune system may lead to central nervous system tissue damage and impair learning and memory processes. Individuals with PTSD often have comorbid inflammatory or auto-immune disorders. Evidence shows associations between PTSD and multiple genes that are involved in immune-related or inflammatory pathways. In this review, we will summarize the evidence of immune dysregulation in PTSD, outlining the contributions of distinct cell types, genes, and biological pathways. We use the Human Leukocyte Antigen (HLA) locus to illustrate the contribution of genetic variation to function in different tissues that contribute to PTSD etiology, severity, and comorbidities.

Prevalence of bipolar disorder in multiple sclerosis: a systematic review and meta-analysis

BACKGROUND

Multiple sclerosis (MS) is a chronic disabling, demyelinating disease of the central nervous system and is often associated with psychiatric comorbidities. Some studies suggest increased prevalence of bipolar disorder (BD) in MS.

OBJECTIVE

To conduct a systematic review and meta-analysis assessing the prevalence of BD in adults with MS.

METHODS

We registered this review with PROSPERO and searched electronic databases (Ovid MEDLINE, Central, Embase, PsycINFO and Scopus) for eligible studies from earliest inception to October 2020. Prevalence data of BD in adult patients with MS were extracted. Meta-analysis was conducted using random-effects model.

FINDINGS

Of the 802 articles that were screened, 23 studies enrolling a total of 68 796 patients were included in the systematic review and meta-analysis. The pooled prevalence rate of BD in patients with MS was 2.95% (95% CI 2.12% to 4.09%) with higher prevalence in the Americas versus Europe. The lifetime prevalence of BD was 8.4% in patients with MS. Subgroup analysis showed a higher prevalence of BD in MS in females (7.03%) than in males (5.64%), which did not reach statistical significance (p=0.53).

CONCLUSIONS

This meta-analysis suggests a high lifetime prevalence of BD in patients with MS. Patients with MS should be routinely screened for BD. Further assessment of bipolar comorbidity in MS through prospective studies may help in developing effective management strategies and may improve treatment outcomes in patients with MS.

Detecting local genetic correlations with scan statistics

Genetic correlation analysis has quickly gained popularity in the past few years and provided insights into the genetic etiology of numerous complex diseases. However, existing approaches oversimplify the shared genetic architecture between different phenotypes and cannot effectively identify precise genetic regions contributing to the genetic correlation. In this work, we introduce LOGODetect, a powerful and efficient statistical method to identify small genome segments harboring local genetic correlation signals. LOGODetect automatically identifies genetic regions showing consistent associations with multiple phenotypes through a scan statistic approach. It uses summary association statistics from genome-wide association studies (GWAS) as input and is robust to sample overlap between studies. Applied to seven phenotypically distinct but genetically correlated neuropsychiatric traits, we identify 227 non-overlapping genome regions associated with multiple traits, including multiple hub regions showing concordant effects on five or more traits. Our method addresses critical limitations in existing analytic strategies and may have wide applications in post-GWAS analysis.

Genetic variations in the PSMA6 and PSMC6 proteasome genes are associated with multiple sclerosis and response to interferon-β therapy in Latvians

Several polymorphisms in genes related to the ubiquitin-proteasome system exhibit an association with pathogenesis and prognosis of various human autoimmune diseases. Our previous study reported the association between multiple sclerosis (MS) and the PSMA3-rs2348071 polymorphism in the Latvian population. The current study aimed to evaluate the PSMA6 and PSMC6 genetic variations, their interaction between each other and with the rs2348071, on the susceptibility to MS risk and response to therapy in the Latvian population. PSMA6-rs2277460, -rs1048990 and PSMC6-rs2295826, -rs2295827 were genotyped in the MS case/control study and analysed in terms of genotype-protein correlation network. The possible association with the disease and alleles, single- and multi-locus genotypes and haplotypes of the studied loci was assessed. Response to therapy was evaluated in terms of 'no evidence of disease activity'. To the best of our knowledge, the present study was the first to report that single- and multi-loci variations in the PSMA6, PSMC6 and PSMA3 proteasome genes may have contributed to the risk of MS in the Latvian population. The results of the current study suggested a potential for the PSMA6-rs1048990 to be an independent marker for the prognosis of interferon-β therapy response. The genotype-phenotype network presented in the current study provided a new insight into the pathogenesis of MS and perspectives for future pharmaceutical interventions.

Accurate error control in high-dimensional association testing using conditional false discovery rates

High-dimensional hypothesis testing is ubiquitous in the biomedical sciences, and informative covariates may be employed to improve power. The conditional false discovery rate (cFDR) is a widely used approach suited to the setting where the covariate is a set of p-values for the equivalent hypotheses for a second trait. Although related to the Benjamini–Hochberg procedure, it does not permit any easy control of type-1 error rate and existing methods are over-conservative. We propose a newmethod for type-1 error rate control based on identifyingmappings from the unit square to the unit interval defined by the estimated cFDR and splitting observations so that each map is independent of the observations it is used to test. We also propose an adjustment to the existing cFDR estimator which further improves power. We show by simulation that the new method more than doubles potential improvement in power over unconditional analyses compared to existing methods. We demonstrate our method on transcriptome-wide association studies and show that the method can be used in an iterative way, enabling the use of multiple covariates successively. Our methods substantially improve the power and applicability of cFDR analysis.

Genome-wide Association Analysis of Parkinson's Disease and Schizophrenia Reveals Shared Genetic Architecture and Identifies Novel Risk Loci

BACKGROUND

Parkinson's disease (PD) and schizophrenia (SCZ) are heritable brain disorders that involve dysregulation of the dopaminergic system. Epidemiological studies have reported potential comorbidity between the disorders, and movement disturbances are common in patients with SCZ before treatment with antipsychotic drugs. Despite this, little is known about shared genetic etiology between the disorders.

METHODS

We analyzed recent large genome-wide association studies on patients with SCZ (N = 77,096) and PD (N = 417,508) using a conditional/conjunctional false discovery rate (FDR) approach to evaluate overlap in common genetic variants and improve statistical power for genetic discovery. Using a variety of biological resources, we functionally characterized the identified genomic loci.

RESULTS

We observed genetic enrichment in PD conditional on associations with SCZ and vice versa, indicating polygenic overlap. We then leveraged this cross-trait enrichment using conditional FDR analysis and identified 9 novel PD risk loci and 1 novel SCZ locus at conditional FDR < .01. Furthermore, we identified 9 genomic loci jointly associated with PD and SCZ at conjunctional FDR < .05. There was an even distribution of antagonistic and agonistic effect directions among the shared loci, in line with the insignificant genetic correlation between the disorders. Of 67 genes mapped to the shared loci, 65 are expressed in the human brain and show cell type-specific expression profiles.

CONCLUSIONS

Altogether, the study increases understanding of the genetic architectures underlying SCZ and PD, indicating that common molecular genetic mechanisms may contribute to overlapping pathophysiological and clinical features between the disorders.

Genetic factors underlying the bidirectional relationship between autoimmune and mental disorders - Findings from a Danish population-based study

BACKGROUND

Previous studies have indicated the bidirectionality between autoimmune and mental disorders. However, genetic studies underpinning the co-occurrence of the two disorders have been lacking. In this study, we examined the potential genetic contribution to the association between autoimmune and mental disorders and investigated the genetic basis of overall autoimmune disease.

METHODS

We used diagnostic information from patients with seven autoimmune diseases and six mental disorders from the Danish population-based case-cohort sample (iPSYCH2012). We explored the epidemiological association using survival analysis and modelled the effect of polygenic risk scores (PRSs) on autoimmune and mental diseases. Genetic factors were investigated using GWAS and imputed HLA alleles in the iPSYCH cohort.

RESULTS

Of 64,039 individuals, a total of 43,902 (68.6%) were diagnosed with mental disorders and 1383 (2.2%) with autoimmune diseases. There was a significant comorbidity between the two disease classes (P = 2.67 × 10^-7, OR = 1.38, 95%CI = 1.22-1.56), with an overall bidirectional association, wherein individuals with autoimmune diseases had an increased risk of subsequent mental disorders (HR = 1.13, 95%CI: 1.07-1.21, P = 7.95 × 10^-5) and vice versa (HR = 1.27, 95%CI = 1.16-1.39, P = 8.77 × 10^-15). Adding PRSs to these adjustment models did not have an impact on the associations. PRSs for autoimmune diseases were only slightly associated with increased risk of mental disorders (HR = 1.01, 95%CI: 1.00-1.02, p = 0.038), whereas PRSs for mental disorders were not associated with autoimmune diseases overall. Our GWAS highlighted 12 loci on chromosome 6 (minimum P = 2.74 × 10^-36, OR = 1.80, 95% CI: 1.64-1.96), which were implicated in gene regulation through bioinformatic functional analyses, thereby identifying new candidate genes for overall autoimmune disease. Moreover, we observed 20 human leukocyte antigen (HLA) alleles strongly associated, either positively or negatively, with overall autoimmune disease, but we did not find significant evidence of their associations with overall mental disorders. A GWAS of a comorbid diagnosis of an autoimmune disease and a mental disorder identified a genome-wide significant locus on chromosome 7 as well (P = 1.43 × 10^-8, OR = 10.65, 95%CI = 3.21-35.36).

CONCLUSIONS

Our findings confirm the overall comorbidity and bidirectionality between autoimmune diseases and mental disorders and identify HLA genes which are significantly associated with overall autoimmune disease. Additionally, we identified several new candidate genes for overall autoimmune disease and ranked them based on their association with the investigated diseases.

Understanding the genetic contribution of the human leukocyte antigen system to common major psychiatric disorders in a world pandemic context

The human leukocyte antigen (HLA) is a complex genetic system that encodes proteins which predominantly regulate immune/inflammatory processes. It can be involved in a variety of immuno-inflammatory disorders ranging from infections to autoimmunity and cancers. The HLA system is also suggested to be involved in neurodevelopment and neuroplasticity, especially through microglia regulation and synaptic pruning. Consequently, this highly polymorphic gene region has recently emerged as a major player in the etiology of several major psychiatric disorders, such as schizophrenia, autism spectrum disorder and bipolar disorder and with less evidence for major depressive disorders and attention deficit hyperactivity disorder. We thus review here the role of HLA genes in particular subgroups of psychiatric disorders and foresee their potential implication in future research. In particular, given the prominent role that the HLA system plays in the regulation of viral infection, this review is particularly timely in the context of the Covid-19 pandemic.

Psycho-neuro-endocrino-immunologic issues in multiple sclerosis: a critical review of clinical and therapeutic implications

Multiple sclerosis (MS) is a multifactorial, chronic, immune-mediated, and neurodegenerative disease, having a well-known hypothalamic-pituitary-adrenal (HPA) axis dysfunction. Several hormones have a great impact in the immune dysregulation, psychology, and cognitive status of patients with MS, as also in the fertility and response to treatment. In this comprehensive review, as an introduction, we mention basic data concerning MS: epidemiology, genetics, immunogenetics, epigenetics, pathophysiology, and neuroimmunology. Hormonal components of the disease cascade, mainly glucocorticoids (stress-related hormone), estrogens, prolactin and dehydroepiandrosterone (sex-related hormones), melatonin, and vitamin D, are discussed, aiming at focusing on core data regarding the impact of these hormones in MS pathophysiology, severity of the disease, correlation with comorbid mental disorders, and fertility. A great focus is given in the pre- and post-pregnancy period of MS patients, in the context of the disease-modifying treatments (DMTs) and HPA status, having in mind that there are only very limited knowledge and few papers on this specific life period of these women, having MS. All this data are presented in the main text and also in the workable tables, for the first time, suggesting targeted topics that need to be addressed in the near future.

Neuroimmune Mechanisms and Sex/Gender-Dependent Effects in the Pathophysiology of Mental Disorders

Innate and adaptive immune mechanisms have emerged as critical regulators of CNS homeostasis and mental health. A plethora of immunologic factors have been reported to interact with emotion- and behavior-related neuronal circuits, modulating susceptibility and resilience to mental disorders. However, it remains unclear whether immune dysregulation is a cardinal causal factor or an outcome of the pathologies associated with mental disorders. Emerging variations in immune regulatory pathways based on sex differences provide an additional framework for discussion in these psychiatric disorders. In this review, we present the current literature pertaining to the effects that disrupted immune pathways have in mental disorder pathophysiology, including immune dysregulation in CNS and periphery, microglial activation, and disturbances of the blood-brain barrier. In addition, we present the suggested origins of such immune dysregulation and discuss the gender and sex influence of the neuroimmune substrates that contribute to mental disorders. The findings challenge the conventional view of these disorders and open the window to a diverse spectrum of innovative therapeutic targets that focus on the immune-specific pathophenotypes in neuronal circuits and behavior. SIGNIFICANCE STATEMENT: The involvement of gender-dependent inflammatory mechanisms on the development of mental pathologies is gaining momentum. This review addresses these novel factors and presents the accumulating evidence introducing microglia and proinflammatory elements as critical components and potential targets for the treatment of mental disorders.

Towards an understanding of women's brain aging: the immunology of pregnancy and menopause

Women are at significantly greater risk of developing Alzheimer's disease and show higher prevalence of autoimmune conditions relative to men. Women's brain health is historically understudied, and little is therefore known about the mechanisms underlying epidemiological sex differences in neurodegenerative diseases, and how female-specific factors may influence women's brain health across the lifespan. In this review, we summarize recent studies on the immunology of pregnancy and menopause, emphasizing that these major immunoendocrine transition phases may play a critical part in women's brain aging trajectories.

Shared genetic etiology underlying late-onset Alzheimer's disease and posttraumatic stress syndrome

INTRODUCTION

Late-onset Alzheimer's disease (LOAD) manifests comorbid neuropsychiatric symptoms and posttraumatic stress disorder (PTSD) is associated with an increased risk for dementia in late life, suggesting the two disorders may share genetic etiologies.

METHODS

We performed genetic pleiotropy analysis using LOAD and PTSD genome-wide association study (GWAS) datasets from white and African-American populations, followed by functional-genomic analyses.

RESULTS

We found an enrichment for LOAD across increasingly stringent levels of significance with the PTSD GWAS association (LOAD|PTSD) in the discovery and replication cohorts and a modest enrichment for the reverse conditional association (PTSD|LOAD). LOAD|PTSD association analysis identified and replicated the MS4A genes region. These genes showed similar expression pattern in brain regions affected in LOAD, and across-brain-tissue analysis identified a significant association for MS4A6A. The African-American samples showed moderate enrichment; however, no false discovery rate-significant associations.

DISCUSSION

We demonstrated common genetic signatures for LOAD and PTSD and suggested immune response as a common pathway for these diseases.

Genome-wide association study of cerebral small vessel disease reveals established and novel loci

Intracerebral haemorrhage and small vessel ischaemic stroke (SVS) are the most acute manifestations of cerebral small vessel disease, with no established preventive approaches beyond hypertension management. Combined genome-wide association study (GWAS) of these two correlated diseases may improve statistical power to detect novel genetic factors for cerebral small vessel disease, elucidating underlying disease mechanisms that may form the basis for future treatments. Because intracerebral haemorrhage location is an adequate surrogate for distinct histopathological variants of cerebral small vessel disease (lobar for cerebral amyloid angiopathy and non-lobar for arteriolosclerosis), we performed GWAS of intracerebral haemorrhage by location in 1813 subjects (755 lobar and 1005 non-lobar) and 1711 stroke-free control subjects. Intracerebral haemorrhage GWAS results by location were meta-analysed with GWAS results for SVS from MEGASTROKE, using 'Multi-Trait Analysis of GWAS' (MTAG) to integrate summary data across traits and generate combined effect estimates. After combining intracerebral haemorrhage and SVS datasets, our sample size included 241 024 participants (6255 intracerebral haemorrhage or SVS cases and 233 058 control subjects). Genome-wide significant associations were observed for non-lobar intracerebral haemorrhage enhanced by SVS with rs2758605 [MTAG P-value (P) = 2.6 × 10-8] at 1q22; rs72932727 (P = 1.7 × 10-8) at 2q33; and rs9515201 (P = 5.3 × 10-10) at 13q34. In the GTEx gene expression library, rs2758605 (1q22), rs72932727 (2q33) and rs9515201 (13q34) are significant cis-eQTLs for PMF1 (P = 1 × 10-4 in tibial nerve), NBEAL1, FAM117B and CARF (P < 2.1 × 10-7 in arteries) and COL4A2 and COL4A1 (P < 0.01 in brain putamen), respectively. Leveraging S-PrediXcan for gene-based association testing with the predicted expression models in tissues related with nerve, artery, and non-lobar brain, we found that experiment-wide significant (P < 8.5 × 10-7) associations at three genes at 2q33 including NBEAL1, FAM117B and WDR12 and genome-wide significant associations at two genes including ICA1L at 2q33 and ZCCHC14 at 16q24. Brain cell-type specific expression profiling libraries reveal that SEMA4A, SLC25A44 and PMF1 at 1q22 and COL4A1 and COL4A2 at 13q34 were mainly expressed in endothelial cells, while the genes at 2q33 (FAM117B, CARF and NBEAL1) were expressed in various cell types including astrocytes, oligodendrocytes and neurons. Our cross-phenotype genetic study of intracerebral haemorrhage and SVS demonstrates novel genome-wide associations for non-lobar intracerebral haemorrhage at 2q33 and 13q34. Our replication of the 1q22 locus previous seen in traditional GWAS of intracerebral haemorrhage, as well as the rediscovery of 13q34, which had previously been reported in candidate gene studies with other cerebral small vessel disease-related traits strengthens the credibility of applying this novel genome-wide approach across intracerebral haemorrhage and SVS.

LncRNA GAS5 and miR-137 Polymorphisms and Expression are Associated with Multiple Sclerosis Risk: Mechanistic Insights and Potential Clinical Impact

The pathogenesis of multiple sclerosis (MS) is influenced by the interaction of genetic and epigenetic mechanisms. The long noncoding RNA GAS5 acts as a competing endogenous RNA for microRNA-137 and is involved in demyelination. We investigated the association of GAS5 and miR-137 expression and their polymorphisms with MS susceptibility. One hundred and eight MS patients and 104 healthy controls were included. Expression analysis and genotyping of GAS5-rs2067079 and miR-137-rs1625579 single nucleotide polymorphisms were performed by qPCR. Serum GAS5 was upregulated, while serum miR-137 was downregulated in MS compared with the controls. Serum miR-137 was an excellent discriminator of MS patients from the controls (AUC = 0.97) and a negative independent predictor of MS in multivariate logistic analysis. Serum GAS5 expression was positively correlated with the expanded disability status scale scores in the relapsing-remitting MS patients. The rs2067079TT minor homozygote genotype was associated with an increased MS risk, while the rs1625579G minor allele was protective. rs1625579 showed an age-specific effect, while the rs2067079 affected the MS risk in gender- and age-specific manners. In MS patients, rs2067079TT was associated with a higher serum GAS5 than other genotypes, while serum miR-137 did not differ between rs1625579 genotypes. Our results suggest serum GAS5 and miR-137 as MS biomarkers, with miR-137 as a negative predictor of MS risk and GAS5 as a marker of MS severity. We propose rs2067079 and rs1625579 as novel genetic markers of MS susceptibility, and at least, rs2067079 possibly impacts the crosstalk between GAS5 and miR-137.

Shared Genetic Loci Between Body Mass Index and Major Psychiatric Disorders: A Genome-wide Association Study

Importance

People with major psychiatric disorders (MPDs) have a 10- to 20-year shorter life span than the rest of the population, and this difference is mainly due to comorbid cardiovascular diseases. Genome-wide association studies have identified common variants involved in schizophrenia (SCZ), bipolar disorder (BIP), and major depression (MD) and body mass index (BMI), a key cardiometabolic risk factor. However, genetic variants jointly influencing MPD and BMI remain largely unknown.

Objective

To assess the extent of the overlap between the genetic architectures of MPDs and BMI and identify genetic loci shared between them.

Design, Setting, and Participants

Using a conditional false discovery rate statistical framework, independent genome-wide association study data on individuals with SCZ (n = 82 315), BIP (n = 51 710), MD (n = 480 359), and BMI (n = 795 640) were analyzed. The UK Biobank cohort (n = 29 740) was excluded from the MD data set to avoid sample overlap. Data were collected from August 2017 to May 2018, and analysis began July 2018.

Main Outcomes and Measures

The primary outcomes were a list of genetic loci shared between BMI and MPDs and their functional pathways.

Results

Genome-wide association study data from 1 380 284 participants were analyzed, and the genetic correlation between BMI and MPDs varied (SCZ: r for genetic = -0.11, P = 2.1 × 10-10; BIP: r for genetic = -0.06, P = .0103; MD: r for genetic = 0.12, P = 6.7 × 10-10). Overall, 63, 17, and 32 loci shared between BMI and SCZ, BIP, and MD, respectively, were analyzed at conjunctional false discovery rate less than 0.01. Of the shared loci, 34% (73 of 213) in SCZ, 52% (36 of 69) in BIP, and 57% (56 of 99) in MD had risk alleles associated with higher BMI (conjunctional false discovery rate <0.05), while the rest had opposite directions of associations. Functional analyses indicated that the overlapping loci are involved in several pathways including neurodevelopment, neurotransmitter signaling, and intracellular processes, and the loci with concordant and opposite association directions pointed mostly to different pathways.

Conclusions and Relevance

In this genome-wide association study, extensive polygenic overlap between BMI and SCZ, BIP, and MD were found, and 111 shared genetic loci were identified, implicating novel functional mechanisms. There was mixture of association directions in SCZ and BMI, albeit with a preponderance of discordant ones.

Adaptive Fisher method detects dense and sparse signals in association analysis of SNV sets

BACKGROUND

With the development of next generation sequencing (NGS) technology and genotype imputation methods, statistical methods have been proposed to test a set of genomic variants together to detect if any of them is associated with the phenotype or disease. In practice, within the set, there is an unknown proportion of variants truly causal or associated with the disease. There is a demand for statistical methods with high power in both dense and sparse scenarios, where the proportion of causal or associated variants is large or small respectively.

RESULTS

We propose a new association test - weighted Adaptive Fisher (wAF) that can adapt to both dense and sparse scenarios by adding weights to the Adaptive Fisher (AF) method we developed before. Using simulation, we show that wAF enjoys comparable or better power to popular methods such as sequence kernel association tests (SKAT and SKAT-O) and adaptive SPU (aSPU) test. We apply wAF to a publicly available schizophrenia dataset, and successfully detect thirteen genes. Among them, three genes are supported by existing literature; six are plausible as they either relate to other neurological diseases or have relevant biological functions.

CONCLUSIONS

The proposed wAF method is a powerful disease-variants association test in both dense and sparse scenarios. Both simulation studies and real data analysis indicate the potential of wAF for new biological findings.

Indicated association between polygenic risk score and treatment-resistance in a naturalistic sample of patients with schizophrenia spectrum disorders

BACKGROUND

One third of people diagnosed with schizophrenia fail to respond adequately to antipsychotic medication, resulting in persisting disabling symptoms, higher rates of hospitalization and higher costs for society. In an effort to better understand the mechanisms behind resistance to antipsychotic treatment in schizophrenia, we investigated its potential relationship to the genetic architecture of the disorder.

METHODS

Patients diagnosed with a schizophrenia spectrum disorder (N = 321) were classified as either being treatment-resistant (N = 108) or non-treatment-resistant (N = 213) to antipsychotic medication using defined consensus criteria. A schizophrenia polygenic risk score based on genome-wide association studies (GWAS) was calculated for each patient and binary logistic regression was performed to investigate the association between polygenetic risk and treatment resistance. We adjusted for principal components, batch number, age and sex. Additional analyses were performed to investigate associations with demographic and clinical variables.

RESULTS

High levels of polygenic risk score for schizophrenia significantly predicted treatment resistance (p = 0.003). The positive predictive value of the model was 61.5% and the negative predictive value was 71.7%. The association was significant for one (p = 0.01) out of five tested SNP significance thresholds. Season of birth was able to predict treatment-resistance in the regression model (p = 0.05).

CONCLUSIONS

The study indicates that treatment-resistance to antipsychotic medication is associated with higher polygenetic risk of schizophrenia, suggesting a link between antipsychotics mechanism of action and the genetic underpinnings of the disorder.

Shared genetic etiology underlying Alzheimer's disease and major depressive disorder

Patients with late-onset Alzheimer's disease (LOAD) frequently manifest comorbid neuropsychiatric symptoms with depression and anxiety being most frequent, and individuals with major depressive disorder (MDD) have an increased prevalence of LOAD. This suggests shared etiologies and intersecting pathways between LOAD and MDD. We performed pleiotropy analyses using LOAD and MDD GWAS data sets from the International Genomics of Alzheimer's Project (IGAP) and the Psychiatric Genomics Consortium (PGC), respectively. We found a moderate enrichment for SNPs associated with LOAD across increasingly stringent levels of significance with the MDD GWAS association (LOAD|MDD), of maximum four and eightfolds, including and excluding the APOE-region, respectively. Association analysis excluding the APOE-region identified numerous SNPs corresponding to 40 genes, 9 of which are known LOAD-risk loci primarily in chromosome 11 regions that contain the SPI1 gene and MS4A genes cluster, and others were novel pleiotropic risk-loci for LOAD conditional with MDD. The most significant associated SNPs on chromosome 11 overlapped with eQTLs found in whole-blood and monocytes, suggesting functional roles in gene regulation. The reverse conditional association analysis (MDD|LOAD) showed a moderate level, ~sevenfold, of polygenic overlap, however, no SNP showed significant association. Pathway analyses replicated previously reported LOAD biological pathways related to immune response and regulation of endocytosis. In conclusion, we provide insights into the overlapping genetic signatures underpinning the common phenotypic manifestations and inter-relationship between LOAD and MDD. This knowledge is crucial to the development of actionable targets for novel therapies to treat depression preceding dementia, in an effort to delay or ultimately prevent the onset of LOAD.

A Genetics Perspective on the Role of the (Neuro)Immune System in Schizophrenia

The immune system has long been hypothesized to play a role in schizophrenia pathogenesis based on data from diverse disciplines. Recent reports of the identification of schizophrenia-associated genetic variants and their initial biological characterization have renewed investigation of the role of the immune system in schizophrenia. In the current review, the plausibility of a role of the immune system in schizophrenia pathogenesis is examined, by revisiting epidemiology, neuroimaging, pharmacology, and developmental biology from a genetics perspective, as well as by synthesizing diverse findings from the emerging and dynamic schizophrenia genomics field. Genetic correlations between schizophrenia and immunological disorders are inconsistent and often contradictory, as are neuroimaging studies of microglia markers. Small therapeutic trials of anti-inflammatory agents targeting immune function have been consistently negative. Some gene expression analyses of post-mortem brains of patients with schizophrenia have reported an upregulation of genes of immune function though others report downregulation, and overall transcriptome profiling to date does not support an upregulation of immune pathways associated with schizophrenia genetic risk. The currently reviewed genetic data do not converge to reveal consistent evidence of the neuroimmune system in schizophrenia pathogenesis, and indeed, a substantive role for the neuroimmune system in schizophrenia has yet to be established.

Immunoneuropsychiatry - novel perspectives on brain disorders

Immune processes have a vital role in CNS homeostasis, resilience and brain reserve. Our cognitive and social abilities rely on a highly sensitive and fine-tuned equilibrium of immune responses that involve both innate and adaptive immunity. Autoimmunity, chronic inflammation, infection and psychosocial stress can tip the scales towards disruption of higher-order networks. However, not only classical neuroinflammatory diseases, such as multiple sclerosis and autoimmune encephalitis, are caused by immune dysregulation that affects CNS function. Recent insight indicates that similar processes are involved in psychiatric diseases such as schizophrenia, autism spectrum disorder, bipolar disorder and depression. Pathways that are common to these disorders include microglial activation, pro-inflammatory cytokines, molecular mimicry, anti-neuronal autoantibodies, self-reactive T cells and disturbance of the blood-brain barrier. These discoveries challenge our traditional classification of neurological and psychiatric diseases. New clinical paths are required to identify subgroups of neuropsychiatric disorders that are phenotypically distinct but pathogenically related and to pave the way for mechanism-based immune treatments. Combined expertise from neurologists and psychiatrists will foster translation of these paths into clinical practice. The aim of this Review is to highlight outstanding findings that have transformed our understanding of neuropsychiatric diseases and to suggest new diagnostic and therapeutic criteria for the emerging field of immunoneuropsychiatry.

Inflammation and Negative Symptoms of Schizophrenia: Implications for Reward Processing and Motivational Deficits

Negative symptoms of schizophrenia are debilitating and chronic in nature, are difficult to treat, and contribute to poor functional outcomes. Motivational deficits are a core negative symptom and may involve alterations in reward processing, which involve subcortical regions such as the basal ganglia. More specifically, dopamine-rich regions like the ventral striatum, have been implicated in these reward-processing deficits. Inflammation is one mechanism that may underlie negative symptoms, and specifically motivational deficits, via the effects of inflammatory cytokines on the basal ganglia. Previous work has demonstrated that inflammatory stimuli decrease neural activity in the ventral striatum and decrease connectivity in reward-relevant neural circuitry. The immune system has been shown to be involved in the pathophysiology of schizophrenia, and inflammatory cytokines have been shown to be altered in patients with the disorder. This paper reviews the literature on associations between inflammatory markers and negative symptoms of schizophrenia as well as the role of anti-inflammatory drugs to target negative symptoms. We also review the literature on the role of inflammation and reward processing deficits in both healthy controls and individuals with depression. We use the literature on inflammation and depression as a basis for a model that explores potential mechanisms responsible for inflammation modulating certain aspects of negative symptoms in patients with schizophrenia. This approach may offer novel targets to treat these symptoms of the disorder that are significant barriers to functional recovery and do not respond well to available antipsychotic medications.