Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium. Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways

Review of Genetic Variation as a Predictive Biomarker for Chronic Graft-Versus-Host-Disease After Allogeneic Stem Cell Transplantation

Chronic graft-versus-host disease (cGvHD) is one of the major complications of allogeneic stem cell transplantation (HSCT). cGvHD is an autoimmune-like disorder affecting multiple organs and involves a dermatological rash, tissue inflammation and fibrosis. The incidence of cGvHD has been reported to be as high as 30% to 60% and there are currently no reliable tools for predicting the occurrence of cGvHD. There is therefore an important unmet clinical need for predictive biomarkers. The present review summarizes the state of the art for genetic variation as a predictive biomarker for cGvHD. We discuss three different modes of action for genetic variation in transplantation: genetic associations, genetic matching, and pharmacogenetics. The results indicate that currently, there are no genetic polymorphisms or genetic tools that can be reliably used as validated biomarkers for predicting cGvHD. A number of recommendations for future studies can be drawn. The majority of studies to date have been under-powered and included too few patients and genetic markers. Like in all complex multifactorial diseases, large collaborative genome-level studies are now needed to achieve reliable and unbiased results. Some of the candidate genes, in particular, CTLA4, HSPE, IL1R1, CCR6, FGFR1OP, and IL10, and some non-HLA variants in the HLA gene region have been replicated to be associated with cGvHD risk in independent studies. These associations should now be confirmed in large well-characterized cohorts with fine mapping. Some patients develop cGvHD despite very extensive immunosuppression and other treatments, indicating that the current therapeutic regimens may not always be effective enough. Hence, more studies on pharmacogenetics are also required. Moreover, all of these studies should be adjusted for diagnostic and clinical features of cGvHD. We conclude that future studies should focus on modern genome-level tools, such as machine learning, polygenic risk scores and genome-wide association study-transcription meta-analyses, instead of focusing on just single variants. The risk of cGvHD may be related to the summary level of immunogenetic differences, or whole genome histocompatibility between each donor-recipient pair. As the number of genome-wide analyses in HSCT is increasing, we are approaching an era where there will be sufficient data to incorporate these approaches in the near future.

Enduring neuroimmunological consequences of developmental experiences: From vulnerability to resilience

The immune system is crucial for normal neuronal development and function (neuroimmune system). Both immune and neuronal systems undergo significant postnatal development and are sensitive to developmental programming by environmental experiences. Negative experiences from infection to psychological stress at a range of different time points (in utero to adolescence) can permanently alter the function of the neuroimmune system: given its prominent role in normal brain development and function this dysregulation may increase vulnerability to psychiatric illness. In contrast, positive experiences such as exercise and environmental enrichment are protective and can promote resilience, even restoring the detrimental effects of negative experiences on the neuroimmune system. This suggests the neuroimmune system is a viable therapeutic target for treatment and prevention of psychiatric illnesses, especially those related to stress. In this review we will summarise the main cells, molecules and functions of the immune system in general and with specific reference to central nervous system development and function. We will then discuss the effects of negative and positive environmental experiences, especially during development, in programming the long-term functioning of the neuroimmune system. Finally, we will review the sparse but growing literature on sex differences in neuroimmune development and response to environmental experiences.

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The immune system is essential for development and function of the central nervous system (neuroimmune system)

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Environmental experiences can permanently alter neuroimmune function and associated brain development

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Altered neuroimmune function following negative developmental experiences may play a role in psychiatric illnesses

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Positive experiences can promote resilience and rescue the effects of negative experiences on the neuroimmune system

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The neuroimmune system is therefore a viable therapeutic target for preventing and treating psychiatric illnesses

Integrated genomics analysis highlights important SNPs and genes implicated in moderate-to-severe asthma based on GWAS and eQTL datasets

Background

Severe asthma is a chronic disease contributing to disproportionate disease morbidity and mortality. From the year of 2007, many genome-wide association studies (GWAS) have documented a large number of asthma-associated genetic variants and related genes. Nevertheless, the molecular mechanism of these identified variants involved in asthma or severe asthma risk remains largely unknown.

Methods

In the current study, we systematically integrated 3 independent expression quantitative trait loci (eQTL) data (N = 1977) and a large-scale GWAS summary data of moderate-to-severe asthma (N = 30,810) by using the Sherlock Bayesian analysis to identify whether expression-related variants contribute risk to severe asthma. Furthermore, we performed various bioinformatics analyses, including pathway enrichment analysis, PPI network enrichment analysis, in silico permutation analysis, DEG analysis and co-expression analysis, to prioritize important genes associated with severe asthma.

Results

In the discovery stage, we identified 1129 significant genes associated with moderate-to-severe asthma by using the Sherlock Bayesian analysis. Two hundred twenty-eight genes were prominently replicated by using MAGMA gene-based analysis. These 228 replicated genes were enriched in 17 biological pathways including antigen processing and presentation (Corrected P = 4.30 × 10^− 6), type I diabetes mellitus (Corrected P = 7.09 × 10^− 5), and asthma (Corrected P = 1.72 × 10^− 3). With the use of a series of bioinformatics analyses, we highlighted 11 important genes such as GNGT2, TLR6, and TTC19 as authentic risk genes associated with moderate-to-severe/severe asthma. With respect to GNGT2, there were 3 eSNPs of rs17637472 (P_eQTL = 2.98 × 10^− 8 and P_GWAS = 3.40 × 10^− 8), rs11265180 (P_eQTL = 6.0 × 10^− 6 and P_GWAS = 1.99 × 10^− 3), and rs1867087 (P_eQTL = 1.0 × 10^− 4 and P_GWAS = 1.84 × 10^− 5) identified. In addition, GNGT2 is significantly expressed in severe asthma compared with mild-moderate asthma (P = 0.045), and Gngt2 shows significantly distinct expression patterns between vehicle and various glucocorticoids (Anova P = 1.55 × 10^− 6).

Conclusions

Our current study provides multiple lines of evidence to support that these 11 identified genes as important candidates implicated in the pathogenesis of severe asthma.

The Netrin-1/DCC Guidance Cue Pathway as a Molecular Target in Depression: Translational Evidence

The Netrin-1/DCC guidance cue pathway plays a critical role in guiding growing axons toward the prefrontal cortex during adolescence and in the maturational organization and adult plasticity of prefrontal cortex connectivity. In this review, we put forward the idea that alterations in prefrontal cortex architecture and function, which are intrinsically linked to the development of major depressive disorder, originate in part from the dysregulation of the Netrin-1/DCC pathway by a mechanism that involves microRNA-218. We discuss evidence derived from mouse models of stress and from human postmortem brain and genome-wide association studies indicating an association between the Netrin-1/DCC pathway and major depressive disorder. We propose a potential role of circulating microRNA-218 as a biomarker of stress vulnerability and major depressive disorder.

Integrative genomics approach identifies conserved transcriptomic networks in Alzheimer's disease

Alzheimer's disease (AD) is a devastating neurological disorder characterized by changes in cell-type proportions and consequently marked alterations of the transcriptome. Here we use a data-driven systems biology meta-analytical approach across three human AD cohorts, encompassing six cortical brain regions, and integrate with multi-scale datasets comprising of DNA methylation, histone acetylation, transcriptome- and genome-wide association studies and quantitative trait loci to further characterize the genetic architecture of AD. We perform co-expression network analysis across more than 1200 human brain samples, identifying robust AD-associated dysregulation of the transcriptome, unaltered in normal human aging. We assess the cell-type specificity of AD gene co-expression changes and estimate cell-type proportion changes in human AD by integrating co-expression modules with single-cell transcriptome data generated from 27 321 nuclei from human postmortem prefrontal cortical tissue. We also show that genetic variants of AD are enriched in a microglial AD-associated module and identify key transcription factors regulating co-expressed modules. Additionally, we validate our results in multiple published human AD gene expression datasets, which can be easily accessed using our online resource (https://swaruplab.bio.uci.edu/consensusAD).

Enhancer RNAs predict enhancer-gene regulatory links and are critical for enhancer function in neuronal systems

Genomic enhancer elements regulate gene expression programs important for neuronal fate and function and are implicated in brain disease states. Enhancers undergo bidirectional transcription to generate non-coding enhancer RNAs (eRNAs). However, eRNA function remains controversial. Here, we combined Assay for Transposase-Accessible Chromatin using Sequencing (ATAC-Seq) and RNA-Seq datasets from three distinct neuronal culture systems in two activity states, enabling genome-wide enhancer identification and prediction of putative enhancer-gene pairs based on correlation of transcriptional output. Notably, stimulus-dependent enhancer transcription preceded mRNA induction, and CRISPR-based activation of eRNA synthesis increased mRNA at paired genes, functionally validating enhancer-gene predictions. Focusing on enhancers surrounding the Fos gene, we report that targeted eRNA manipulation bidirectionally modulates Fos mRNA, and that Fos eRNAs directly interact with the histone acetyltransferase domain of the enhancer-linked transcriptional co-activator CREB-binding protein (CBP). Together, these results highlight the unique role of eRNAs in neuronal gene regulation and demonstrate that eRNAs can be used to identify putative target genes.

Genetics and major depressive disorder: clinical implications for disease risk, prognosis and treatment

In the post-genomic era, genetics has led to limited clinical applications in the diagnosis and treatment of major depressive disorder (MDD). Variants in genes coding for cytochrome enzymes are included in guidelines for assisting in antidepressant choice and dosing, but there are no recommendations involving genes responsible for antidepressant pharmacodynamics and no consensus applications for guiding diagnosis or prognosis. However, genetics has contributed to a better understanding of MDD pathogenesis and the mechanisms of antidepressant action, also thanks to recent methodological innovations that overcome the challenges posed by the polygenic architecture of these traits. Polygenic risk scores can be used to estimate the risk of disease at the individual level, which may have clinical relevance in cases with extremely high scores (e.g. top 1%). Genetic studies have also shed light on a wide genetic overlap between MDD and other psychiatric disorders. The relationships between genes/pathways associated with MDD and known drug targets are a promising tool for drug repurposing and identification of new pharmacological targets. Increase in power thanks to larger samples and methods integrating genetic data with gene expression, the integration of common variants and rare variants, are expected to advance our knowledge and assist in personalized psychiatry.

From Rare Copy Number Variants to Biological Processes in ADHD

OBJECTIVE

Attention deficit hyperactivity disorder (ADHD) is a highly heritable psychiatric disorder. The objective of this study was to define ADHD-associated candidate genes and their associated molecular modules and biological themes, based on the analysis of rare genetic variants.

METHODS

The authors combined data from 11 published copy number variation studies in 6,176 individuals with ADHD and 25,026 control subjects and prioritized genes by applying an integrative strategy based on criteria including recurrence in individuals with ADHD, absence in control subjects, complete coverage in copy number gains, and presence in the minimal region common to overlapping copy number variants (CNVs), as well as on protein-protein interactions and information from cross-species genotype-phenotype annotation.

RESULTS

The authors localized 2,241 eligible genes in the 1,532 reported CNVs, of which they classified 432 as high-priority ADHD candidate genes. The high-priority ADHD candidate genes were significantly coexpressed in the brain. A network of 66 genes was supported by ADHD-relevant phenotypes in the cross-species database. Four significantly interconnected protein modules were found among the high-priority ADHD genes. A total of 26 genes were observed across all applied bioinformatic methods. Lookup in the latest genome-wide association study for ADHD showed that among those 26 genes, POLR3C and RBFOX1 were also supported by common genetic variants.

CONCLUSIONS

Integration of a stringent filtering procedure in CNV studies with suitable bioinformatics approaches can identify ADHD candidate genes at increased levels of credibility. The authors' analytic pipeline provides additional insight into the molecular mechanisms underlying ADHD and allows prioritization of genes for functional validation in validated model organisms.

Integrative genomics analysis of various omics data and networks identify risk genes and variants vulnerable to childhood-onset asthma

BACKGROUND

Childhood-onset asthma is highly affected by genetic components. In recent years, many genome-wide association studies (GWAS) have reported a large group of genetic variants and susceptible genes associated with asthma-related phenotypes including childhood-onset asthma. However, the regulatory mechanisms of these genetic variants for childhood-onset asthma susceptibility remain largely unknown.

METHODS

In the current investigation, we conducted a two-stage designed Sherlock-based integrative genomics analysis to explore the cis- and/or trans-regulatory effects of genome-wide SNPs on gene expression as well as childhood-onset asthma risk through incorporating a large-scale GWAS data (N = 314,633) and two independent expression quantitative trait loci (eQTL) datasets (N = 1890). Furthermore, we applied various bioinformatics analyses, including MAGMA gene-based analysis, pathway enrichment analysis, drug/disease-based enrichment analysis, computer-based permutation analysis, PPI network analysis, gene co-expression analysis and differential gene expression analysis, to prioritize susceptible genes associated with childhood-onset asthma.

RESULTS

Based on comprehensive genomics analyses, we found 31 genes with multiple eSNPs to be convincing candidates for childhood-onset asthma risk; such as, PSMB9 (cis-rs4148882 and cis-rs2071534) and TAP2 (cis-rs9267798, cis-rs4148882, cis-rs241456, and trans-10,447,456). These 31 genes were functionally interacted with each other in our PPI network analysis. Our pathway enrichment analysis showed that numerous KEGG pathways including antigen processing and presentation, type I diabetes mellitus, and asthma were significantly enriched to involve in childhood-onset asthma risk. The co-expression patterns among 31 genes were remarkably altered according to asthma status, and 25 of 31 genes (25/31 = 80.65%) showed significantly or suggestively differential expression between asthma group and control group.

CONCLUSIONS

We provide strong evidence to highlight 31 candidate genes for childhood-onset asthma risk, and offer a new insight into the genetic pathogenesis of childhood-onset asthma.

Epigenomic Dysregulation in Schizophrenia: In Search of Disease Etiology and Biomarkers

Schizophrenia is a severe psychiatric disorder with a complex array of signs and symptoms that causes very significant disability in young people. While schizophrenia has a strong genetic component, with heritability around 80%, there is also a very significant range of environmental exposures and stressors that have been implicated in disease development and neuropathology, such as maternal immune infection, obstetric complications, childhood trauma and cannabis exposure. It is postulated that epigenetic factors, as well as regulatory non-coding RNAs, mediate the effects of these environmental stressors. In this review, we explore the most well-known epigenetic marks, including DNA methylation and histone modification, along with emerging RNA mediators of epigenomic state, including miRNAs and lncRNAs, and discuss their collective potential for involvement in the pathophysiology of schizophrenia implicated through the postmortem analysis of brain tissue. Given that peripheral tissues, such as blood, saliva, and olfactory epithelium have the same genetic composition and are exposed to many of the same environmental exposures, we also examine some studies supporting the application of peripheral tissues for epigenomic biomarker discovery in schizophrenia. Finally, we provide some perspective on how these biomarkers may be utilized to capture a signature of past events that informs future treatment.

Update on the genetic architecture of schizophrenia

A long-established hypothesis is that schizophrenia has a strong genetic component. In the early 1990s, the first genetic variant that substantially increases risk for psychosis was identified. Since this initial reporting of deletions in the chromosomal region 22q11.2, nearly two decades passed until substantial insights into schizophrenia’s genetic architecture were gained. Schizophrenia is a polygenic disorder and genetic risk is conferred by both common and rare alleles distributed across the genome. A small number of rare, deleterious copy number variants (CNVs) are associated with moderate to substantial increases in individual risk to schizophrenia. These deletions and duplications are also associated with a range of neurodevelopmental disorders. The diagnostic investigation of CNVs in patients with schizophrenia is likely to represent one of the first examples of genetic testing in clinical psychiatry. The prerequisites for this are currently being defined.

Signaling networks in inflammatory pathways and risk for suicidal behavior

BACKGROUND

Suicide is a leading cause of death in the young adult population, with few biological markers identified thus far to be associated with suicidality. Cytokines (including IL-6 and TNFα) may contribute to increased risk for depression and suicidality. Few studies have examined the associations of cytokine mRNA expression with depression and suicidal ideation and behavior. This study examines these associations and whether cytokine signaling networks differentiate suicide attempters (SA), suicide ideators (SI), and healthy controls (HC).

METHODS

Cytokine pathway marker (CPM; e.g. cytokines and proteins in cytokine signaling pathways) mRNA gene expression in whole blood was examined in suicide attempters (n = 38), suicide ideators (n = 38), and healthy controls (n = 36). Between-group differences in CPM gene expression were examined. We also examined association of the mRNA of these genes with the severity of depression and suicidal ideation. Novel Gaussian Graphical Model (GGM) techniques were utilized to examine between-network partial correlation differences in cytokine signaling networks relevant to IL-6 and TNFα signaling pathways.

RESULTS

The severity of depression symptoms was positively associated with TNFα mRNA levels and negatively associated with IL-10 mRNA levels, but CPM expression was not associated with suicidal ideation severity. There were no between-group differences in CPM markers among healthy controls, SI and SA groups after correcting for multiple comparisons. In network analyses, we found suggestive results of between-group network differences between SI and control groups in gene pairs with IL-6R and STAT3 as common nodes.

DISCUSSION

In a cohort of suicide attempters and ideators, TNFα and IL-10 mRNA levels appear to be associated with depressive symptomology, consistent with elevation of pro-inflammatory cytokine production and reduction of anti-inflammatory cytokine production. Additionally, cytokine signaling networks may differentiate suicide ideators from healthy controls based on between-network differences, with differences possibly related to relationships of IL6R or STAT3 with other components of cytokine signaling networks.

Role of inflammation in the pathogenesis of schizophrenia: A review of the evidence, proposed mechanisms and implications for treatment

AIM

Over the past several decades, there has been a growing research interest in the role of inflammation in the pathogenesis of schizophrenia. This review aims to summarize evidence in support of this relationship, to discuss biological mechanisms that might explain it, and to explore the translational impact by examining evidence from trials of anti-inflammatory and immunomodulatory agents in the treatment of schizophrenia.

METHODS

This narrative review of the literature summarizes evidence from observational studies, clinical trials and meta-analyses to evaluate the role of inflammation in the pathogenesis of schizophrenia and to discuss associated implications for treatment.

RESULTS

Epidemiological evidence and animal models support a hypothesis of maternal immune activation during pregnancy, which increases the risk of schizophrenia in the offspring. Several biomarker studies have found associations between classical pro-inflammatory cytokines and schizophrenia. The precise biological mechanisms by which inflammatory processes might contribute to the pathogenesis of schizophrenia remain unclear, but likely include the actions of microglia and the complement system. Importantly, several trials provide evidence that certain anti-inflammatory and immunomodulatory agents show beneficial effects in the treatment of schizophrenia. Nevertheless, there is a need for further precision-focused basic science and translational research.

CONCLUSIONS

Increasing our understanding of the role of inflammation in schizophrenia will enable novel opportunities for therapeutic and preventative interventions that are informed by the underlying pathogenesis of this complex disorder.

A Review of epigenetics in psychiatry: focus on environmental risk factors

Epigenetic modifications play a key role in development and cell type specificity. These modifications seem to be particularly critical for brain development, where mutations in epigenetic enzymes have been associated with neurodevelopmental disorders as well as with the function of post-mitotic neurons. Epigenetic modifications can be influenced by genetic and environmental factors, both known major risk factors for psychiatric disorders. Epigenetic modifications may thus be an important mediator of the effects of genetic and environmental risk factors on cell function.

This review summarizes the different types of epigenetic regulation and then focuses on the mechanisms transducing environmental signals, especially adverse life events that are major risk factors for psychiatric disorders, into lasting epigenetic changes. This is followed by examples of how the environment can induce epigenetic changes that relate to the risk of psychiatric disorders.

Insights into the genomics of affective disorders

Affective disorders, or mood disorders, are a group of neuropsychiatric illnesses that are characterized by a disturbance of mood or affect. Most genetic research in this field to date has focused on bipolar disorder and major depression. Symptoms of major depression include a depressed mood, reduced energy, and a loss of interest and enjoyment. Bipolar disorder is characterized by the occurrence of (hypo)manic episodes, which generally alternate with periods of depression. Formal and molecular genetic studies have demonstrated that affective disorders are multifactorial diseases, in which both genetic and environmental factors contribute to disease development. Twin and family studies have generated heritability estimates of 58–85 % for bipolar disorder and 40 % for major depression.

Large genome-wide association studies have provided important insights into the genetics of affective disorders via the identification of a number of common genetic risk factors. Based on these studies, the estimated overall contribution of common variants to the phenotypic variability (single-nucleotide polymorphism [SNP]-based heritability) is 17–23 % for bipolar disorder and 9 % for major depression. Bioinformatic analyses suggest that the associated loci and implicated genes converge into specific pathways, including calcium signaling. Research suggests that rare copy number variants make a lower contribution to the development of affective disorders than to other psychiatric diseases, such as schizophrenia or the autism spectrum disorders, which would be compatible with their less pronounced negative impact on reproduction. However, the identification of rare sequence variants remains in its infancy, as available next-generation sequencing studies have been conducted in limited samples. Future research strategies will include the enlargement of genomic data sets via innovative recruitment strategies; functional analyses of known associated loci; and the development of new, etiologically based disease models. Researchers hope that deeper insights into the biological causes of affective disorders will eventually lead to improved diagnostics and disease prediction, as well as to the development of new preventative, diagnostic, and therapeutic strategies. Pharmacogenetics and the application of polygenic risk scores represent promising initial approaches to the future translation of genomic findings into psychiatric clinical practice.

A Regularization-Based Adaptive Test for High-Dimensional Generalized Linear Models

In spite of its urgent importance in the era of big data, testing high-dimensional parameters in generalized linear models (GLMs) in the presence of high-dimensional nuisance parameters has been largely under-studied, especially with regard to constructing powerful tests for general (and unknown) alternatives. Most existing tests are powerful only against certain alternatives and may yield incorrect Type I error rates under high-dimensional nuisance parameter situations. In this paper, we propose the adaptive interaction sum of powered score (aiSPU) test in the framework of penalized regression with a non-convex penalty, called truncated Lasso penalty (TLP), which can maintain correct Type I error rates while yielding high statistical power across a wide range of alternatives. To calculate its p-values analytically, we derive its asymptotic null distribution. Via simulations, its superior finite-sample performance is demonstrated over several representative existing methods. In addition, we apply it and other representative tests to an Alzheimer's Disease Neuroimaging Initiative (ADNI) data set, detecting possible gene-gender interactions for Alzheimer's disease. We also put R package "aispu" implementing the proposed test on GitHub.

Persistent psychotic symptoms following COVID-19 infection

To date, there have been no detailed reports of patients developing persistent psychotic symptoms following Coronavirus disease 2019 (COVID-19) infection. There have been reports of patients developing transient delirium (with and without hypoxia) after COVID-19 infection as well as other neurological manifestations. We report on a female patient who, post-COVID-19 infection, developed an initial delirium followed by persistent and florid psychotic symptoms consisting of persecutory delusion, complex visual and auditory hallucinations and Capgras phenomenon in the absence of hypoxia but elevated tumour necrosis factor (TNF)-α. The psychotic symptoms persisted for about 40 days. Her magnetic resonance imaging brain scan, electroencephalogram, cerebrospinal fluid examination and extensive autoimmune panel did not show any abnormalities. The cause of the psychotic symptoms in this patient were not ascertained but we propose either an inflammatory state, characterised by the patient's elevated TNF-alpha levels as a possible contributing mechanism for her psychosis in line with the proinflammatory changes observed in some cases of psychosis. Or, an alternative, but unproven, hypothesis is one of an antibody-mediated encephalitic event induced by viral infection.

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.

Cannabis Use Is Associated With Increased Levels of Soluble gp130 in Schizophrenia but Not in Bipolar Disorder

The complex effects of plant cannabinoids on human physiology is not yet fully understood, but include a wide spectrum of effects on immune modulation. The immune system and its inflammatory effector pathways are recently emerging as possible causative factors in psychotic disorders. The present study aimed to investigate whether self-administered Cannabis use was associated with changes in circulating immune and neuroendocrine markers in schizophrenia (SCZ) and bipolar disorder (BD) patients. A screening of 13 plasma markers reflecting different inflammatory pathways was performed in SCZ (n = 401) and BD patients (n = 242) after subdividing each group into Cannabis user and non-user subgroups. We found that i) soluble gp130 (sgp130) concentrations were significantly elevated among Cannabis users in the SCZ group (p = 0.002) after multiple testing correction, but not in BD. ii) Nominally significant differences were observed in the levels of IL-1RA (p = 0.0059), YKL40 (p = 0.0069), CatS (p = 0.013), sTNFR1 (p = 0.031), and BDNF (p = 0.020), where these factors exhibited higher plasma levels in Cannabis user SCZ patients than in non-users. iii) These differences in systemic levels were not reflected by altered mRNA expression of genes encoding sgp130, IL-1RA, YKL40, CatS, sTNFR1, and BDNF in whole blood. Our results show that Cannabis self-administration is associated with markedly higher sgp130 levels in SCZ, but not in BD, and that this phenomenon is independent of the modulation of peripheral immune cells. These findings warrant further investigation into the potential IL-6 trans-signaling modulatory, anti-inflammatory, neuroimmune, and biobehavioral-cognitive effects of Cannabis use in SCZ.

Synaptic and brain-expressed gene sets relate to the shared genetic risk across five psychiatric disorders

BACKGROUND

Mounting evidence shows genetic overlap between multiple psychiatric disorders. However, the biological underpinnings of shared risk for psychiatric disorders are not yet fully uncovered. The identification of underlying biological mechanisms is crucial for the progress in the treatment of these disorders.

METHODS

We applied gene-set analysis including 7372 gene sets, and 53 tissue-type specific gene-expression profiles to identify sets of genes that are involved in the etiology of multiple psychiatric disorders. We included genome-wide meta-association data of the five psychiatric disorders schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, and attention-deficit/hyperactivity disorder. The total dataset contained 159 219 cases and 262 481 controls.

RESULTS

We identified 19 gene sets that were significantly associated with the five psychiatric disorders combined, of which we excluded five sets because their associations were likely driven by schizophrenia only. Conditional analyses showed independent effects of several gene sets that in particular relate to the synapse. In addition, we found independent effects of gene expression levels in the cerebellum and frontal cortex.

CONCLUSIONS

We obtained novel evidence for shared biological mechanisms that act across psychiatric disorders and we showed that several gene sets that have been related to individual disorders play a role in a broader range of psychiatric disorders.

Investigation of Schizophrenia with Human Induced Pluripotent Stem Cells

Schizophrenia is a chronic and severe neuropsychiatric condition manifested by cognitive, emotional, affective, perceptual, and behavioral abnormalities. Despite decades of research, the biological substrates driving the signs and symptoms of the disorder remain elusive, thus hampering progress in the development of treatments aimed at disease etiologies. The recent emergence of human induced pluripotent stem cell (hiPSC)-based models has provided the field with a highly innovative approach to generate, study, and manipulate living neural tissue derived from patients, making possible the exploration of fundamental roles of genes and early-life stressors in disease-relevant cell types. Here, we begin with a brief overview of the clinical, epidemiological, and genetic aspects of the condition, with a focus on schizophrenia as a neurodevelopmental disorder. We then highlight relevant technical advancements in hiPSC models and assess novel findings attained using hiPSC-based approaches and their implications for disease biology and treatment innovation. We close with a critical appraisal of the developments necessary for both further expanding knowledge of schizophrenia and the translation of new insights into therapeutic innovations.

Depression and Obesity: Analysis of Common Biomarkers

Depression and obesity are very common pathologies. Both cause significant problems of both morbidity and mortality and have decisive impacts not only on the health and well-being of patients, but also on socioeconomic and health expenditure aspects. Many epidemiological studies, clinical studies and meta-analyses support the association between mood disorders and obesity in relationships to different conditions such as the severity of depression, the severity of obesity, gender, socioeconomic status, genetic susceptibility, environmental influences and adverse experiences of childhood. Currently, both depression and obesity are considered pathologies with a high-inflammatory impact; it is believed that several overlapping factors, such as the activation of the cortico-adrenal axis, the exaggerated and prolonged response of the innate immune system and proinflammatory cytokines to stress factors and pathogens-as well as alterations of the intestinal microbiota which promote intestinal permeability-can favor the expression of an increasingly proinflammatory phenotype that can be considered a key and common phenomenon between these two widespread pathologies. The purpose of this literature review is to evaluate the common and interacting mechanisms between depression and obesity.

Association of a Reproducible Epigenetic Risk Profile for Schizophrenia With Brain Methylation and Function

IMPORTANCE

Schizophrenia is a severe mental disorder in which epigenetic mechanisms may contribute to illness risk. Epigenetic profiles can be derived from blood cells, but to our knowledge, it is unknown whether these predict established brain alterations associated with schizophrenia.

OBJECTIVE

To identify an epigenetic signature (quantified as polymethylation score [PMS]) of schizophrenia using machine learning applied to genome-wide blood DNA-methylation data; evaluate whether differences in blood-derived PMS are mirrored in data from postmortem brain samples; test whether the PMS is associated with alterations of dorsolateral prefrontal cortex hippocampal (DLPFC-HC) connectivity during working memory in healthy controls (HC); explore the association between interactions between polygenic and epigenetic risk with DLPFC-HC connectivity; and test the specificity of the signature compared with other serious psychiatric disorders.

DESIGN, SETTING, AND PARTICIPANTS

In this case-control study conducted from 2008 to 2018 in sites in Germany, the United Kingdom, the United States, and Australia, blood DNA-methylation data from 2230 whole-blood samples from 6 independent cohorts comprising HC (1238 [55.5%]) and participants with schizophrenia (803 [36.0%]), bipolar disorder (39 [1.7%]), major depressive disorder 35 [1.6%]), and autism (27 [1.2%]), and first-degree relatives of all patient groups (88 [3.9%]) were analyzed. DNA-methylation data were further explored from 244 postmortem DLPFC samples from 136 HC and 108 patients with schizophrenia. Neuroimaging and genome-wide association data were available for 393 HC. The latter data was used to calculate a polygenic risk score (PRS) for schizophrenia. The data were analyzed in 2019.

MAIN OUTCOMES AND MEASURES

The accuracy of schizophrenia control classification based on machine learning using epigenetic data; association of schizophrenia PMS scores with DLPFC-HC connectivity; and association of the interaction between PRS and PMS with DLPFC-HC connectivity.

RESULTS

This study included 7488 participants (4395 men [58.7%]), of whom 3158 (2230 men [70.6%]) received a diagnosis of schizophrenia. The PMS signature was associated with schizophrenia across 3 independent data sets (area under the curve [AUC] from 0.69 to 0.78; P value from 0.049 to 1.24 × 10-7) and data from postmortem DLPFC samples (AUC = 0.63; P = 1.42 × 10-4), but not with major depressive disorder (AUC = 0.51; P = .16), autism (AUC = 0.53; P = .66), or bipolar disorder (AUC = 0.58; P = .21). Pathways contributing most to the classification included synaptic processes. Healthy controls with schizophrenia-like PMS showed significantly altered DLPFC-HC connectivity (validation methylation/magnetic resonance imaging, t < -3.81; P for familywise error, <.04; validation magnetic resonance imaging, t < -3.54; P for familywise error, <.02), mirroring the lack of functional decoupling in schizophrenia. There was no significant association of the interaction between PMS and PRS with DLPFC-HC connectivity (P > .19).

CONCLUSIONS AND RELEVANCE

We identified a reproducible blood DNA-methylation signature specific for schizophrenia that was correlated with altered functional DLPFC-HC coupling during working memory and mapped to methylation differences found in DLPFC postmortem samples. This indicates a possible epigenetic contribution to a schizophrenia intermediate phenotype and suggests that PMS could be of interest to be studied in the context of multimodal biomarkers for disease stratification and treatment personalization.

The relevance of transdiagnostic shared networks to the severity of symptoms and cognitive deficits in schizophrenia: a multimodal brain imaging fusion study

Schizophrenia (SZ) is frequently concurrent with substance use, depressive symptoms, social communication and attention deficits. However, the relationship between common brain networks (e.g., SZ vs. substance use, SZ vs. depression, SZ vs. developmental disorders) with SZ on specific symptoms and cognition is unclear. Symptom scores were used as a reference to guide fMRI-sMRI fusion for SZ (n = 94), substance use with drinking (n = 313), smoking (n = 104), major depressive disorder (MDD, n = 260), developmental disorders with autism spectrum disorder (ASD, n = 421) and attention-deficit/hyperactivity disorder (ADHD, n = 244) respectively. Common brain regions were determined by overlapping the symptom-related components between SZ and these other groups. Correlation between the identified common brain regions and cognition/symptoms in an independent SZ dataset (n = 144) was also performed. Results show that (1): substance use was related with cognitive deficits in schizophrenia through gray matter volume (GMV) in anterior cingulate cortex and thalamus; (2) depression was linked to PANSS negative dimensions and reasoning in SZ through a network involving caudate-thalamus-middle/inferior temporal gyrus in GMV; (3) developmental disorders pattern was correlated with poor attention, speed of processing and reasoning in SZ through inferior temporal gyrus in GMV. This study reveals symptom driven transdiagnostic shared networks between SZ and other mental disorders via multi-group data mining, indicating that some potential common underlying brain networks associated with schizophrenia differently with respect to symptoms and cognition. These results have heuristic value and advocate specific approaches to refine available treatment strategies for comorbid conditions in schizophrenia.

Spatio-Temporal Roles of ASD-Associated Variants in Human Brain Development

Transcriptional regulation of the genome arguably provides the basis for the anatomical elaboration and dynamic operation of the human brain. It logically follows that genetic variations affecting gene transcription contribute to mental health disorders, including autism spectrum disorder (ASD). A number of recent studies have shown the role of de novo variants (DNVs) in disrupting early neurodevelopment. However, there is limited knowledge concerning the role of inherited variants during the early brain development of ASD. In this study, we investigate the role of rare inherited variations in neurodevelopment. We conducted co-expression network analyses using an anatomically comprehensive atlas of the developing human brain and examined whether rare coding and regulatory variants, identified from our genetic screening of Australian families with ASD, work in different spatio-temporal functions.

Current challenges and possible future developments in personalized psychiatry with an emphasis on psychotic disorders

A personalized medicine approach seems to be particularly applicable to psychiatry. Indeed, considering mental illness as deregulation, unique to each patient, of molecular pathways, governing the development and functioning of the brain, seems to be the most justified way to understand and treat disorders of this medical category. In order to extract correct information about the implicated molecular pathways, data can be drawn from sampling phenotypic and genetic biomarkers and then analyzed by a machine learning algorithm. This review describes current difficulties in the field of personalized psychiatry and gives several examples of possibly actionable biomarkers of psychotic and other psychiatric disorders, including several examples of genetic studies relevant to personalized psychiatry. Most of these biomarkers are not yet ready to be introduced in clinical practice. In a next step, a perspective on the path personalized psychiatry may take in the future is given, paying particular attention to machine learning algorithms that can be used with the goal of handling multidimensional datasets.

mGluR5 hypofunction is integral to glutamatergic dysregulation in schizophrenia

Multiple lines of evidence point to glutamatergic signaling in the postsynaptic density (PSD) as a pathophysiologic mechanism in schizophrenia. Integral to PSD glutamatergic signaling is reciprocal interplay between GluN and mGluR5 signaling. We examined agonist-induced mGluR5 signaling in the postmortem dorsolateral prefrontal cortex (DLPFC) derived from 17 patients and age-matched and sex-matched controls. The patient group showed a striking reduction in mGluR5 signaling, manifested by decreases in Gq/11 coupling and association with PI3K and Homer compared to controls (p < 0.01 for all). This was accompanied by increases in serine and tyrosine phosphorylation of mGluR5, which can decrease mGluR5 activity via desensitization (p < 0.01). In addition, we find altered protein-protein interaction (PPI) of mGluR5 with RGS4, norbin, Preso 1 and tamalin, which can also attenuate mGluR5 activity. We previously reported molecular underpinnings of GluN hypofunction (decreased GluN2 phosphorylation) and here we show those of reduced mGluR5 signaling in schizophrenia. We find that reduced GluN2 phosphorylation can be precipitated by attenuated mGluR5 activity and that increased mGluR5 phosphorylation can result from decreased GluN function, suggesting a reciprocal interplay between the two pathways in schizophrenia. Interestingly, the patient group showed decreased mGluR5-GluN association (p < 0.01), a mechanistic basis for the reciprocal facilitation. In sum, we present the first direct evidence for mGluR5 hypoactivity, propose a reciprocal interplay between GluN and mGluR5 pathways as integral to glutamatergic dysregulation and suggest protein-protein interactions in mGluR5-GluN complexes as potential targets for intervention in schizophrenia.

Multiparametric Assays for Accelerating Early Drug Discovery

Drug discovery campaigns are hampered by substantial attrition rates largely due to a lack of efficacy and safety reasons associated with candidate drugs. This is true in particular for genetically complex diseases, where insufficient knowledge of the modulatory actions of candidate drugs on targets and entire target pathways further adds to the problem of attrition. To better profile compound actions on targets, potential off-targets, and disease-linked pathways, new innovative technologies need to be developed that can elucidate the complex cellular signaling networks in health and disease. Here, we discuss progress in genetically encoded multiparametric assays and mass spectrometry (MS)-based proteomics, which both represent promising toolkits to profile multifactorial actions of drug candidates in disease-relevant cellular systems to promote drug discovery and personalized medicine.

A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles

Most risk variants for brain disorders identified by genome-wide association studies (GWAS) reside in non-coding genome, which makes deciphering biological mechanisms difficult. A commonly used tool, MAGMA, addresses this issue by aggregating SNP associations to nearest genes. Here, we developed a platform, Hi-C coupled MAGMA (H-MAGMA), that advances MAGMA by incorporating chromatin interaction profiles from human brain tissue across two developmental epochs and two brain cell types. By employing gene regulatory relationships in the disease-relevant tissue, H-MAGMA identifies neurobiologically-relevant target genes. We applied H-MAGMA to five psychiatric disorders and four neurodegenerative disorders to interrogate biological pathways, developmental windows, and cell types implicated for each disorder. Psychiatric disorder risk genes tended to be expressed during mid-gestation and in excitatory neurons, whereas degenerative disorder risk genes showed increasing expression over time and more diverse cell-type specificities. H-MAGMA adds to existing analytic frameworks to help identify the neurobiological consequences of brain disorder genetics.

mGluR5 receptor availability is associated with lower levels of negative symptoms and better cognition in male patients with chronic schizophrenia

Consistent findings postulate disturbed glutamatergic function (more specifically a hypofunction of the ionotropic NMDA receptors) as an important pathophysiologic mechanism in schizophrenia. However, the role of the metabotropic glutamatergic receptors type 5 (mGluR5) in this disease remains unclear. In this study, we investigated their significance (using [¹¹C]ABP688) for psychopathology and cognition in male patients with chronic schizophrenia and healthy controls. In the patient group, lower mGluR5 binding potential (BP_ND) values in the left temporal cortex and caudate were associated with higher general symptom levels (negative and depressive symptoms), lower levels of global functioning and worse cognitive performance. At the same time, in both groups, mGluR5 BP_ND were significantly lower in smokers (F_[27,1] = 15.500; p = .001), but without significant differences between the groups. Our findings provide support for the concept that the impaired function of mGluR5 underlies the symptoms of schizophrenia. They further supply a new perspective on the complex relationship between tobacco addiction and schizophrenia by identifying glutamatergic neurotransmission—in particularly mGluR5—as a possible connection to a shared vulnerability.

Transcriptomic abnormalities in peripheral blood in bipolar disorder, and discrimination of the major psychoses

We performed a transcriptome-wide meta-analysis and gene co-expression network analysis to identify genes and gene networks dysregulated in the peripheral blood of bipolar disorder (BD) cases relative to unaffected comparison subjects, and determined the specificity of the transcriptomic signatures of BD and schizophrenia (SZ). Nineteen genes and 4 gene modules were significantly differentially expressed in BD cases. Thirteen gene modules were shown to be differentially expressed in a combined case-group of BD and SZ subjects called "major psychosis", including genes biologically linked to apoptosis, reactive oxygen, chromatin remodeling, and immune signaling. No modules were differentially expressed between BD and SZ cases. Machine-learning classifiers trained to separate diagnostic classes based solely on gene expression profiles could distinguish BD cases from unaffected comparison subjects with an area under the curve (AUC) of 0.724, as well as BD cases from SZ cases with AUC = 0.677 in withheld test samples. We introduced a novel and straightforward method called "polytranscript risk scoring" that could distinguish BD cases from unaffected subjects (AUC = 0.672) and SZ cases (AUC = 0.607) significantly better than expected by chance. Taken together, our results highlighted gene expression alterations common to BD and SZ that involve biological processes of inflammation, oxidative stress, apoptosis, and chromatin regulation, and highlight disorder-specific changes in gene expression that discriminate the major psychoses.

CRISPR-based functional evaluation of schizophrenia risk variants

As expanding genetic and genomic studies continue to implicate a growing list of variants contributing risk to neuropsychiatric disease, an important next step is to understand the functional impact and points of convergence of these risk factors. Here, with a focus on schizophrenia, we survey the most recent findings of the rare and common variants underlying genetic risk for schizophrenia. We discuss the ongoing efforts to validate these variants in post-mortem brain tissue, as well as new approaches to combine CRISPR-based genome engineering with patient-specific human induced pluripotent stem cell (hiPSC)-based models, in order to identify putative causal schizophrenia loci that regulate gene expression and cellular function. We consider the current limitations of hiPSC-based approaches as well as the future advances necessary to improve the fidelity of this human model. With the objective of utilizing patient genotype data to improve diagnosis and predict treatment response, the integration of CRISPR-genome engineering and hiPSC-based models represent an important strategy with which to systematically demonstrate the cell-type-specific effects of schizophrenia-associated variants.

Genome-wide association studies in schizophrenia: Recent advances, challenges and future perspective

Genome-wide association studies (GWAS) have proved to be a powerful approach for gene discovery in schizophrenia; their findings have important implications not just for our understanding of the genetic architecture of the disorder, but for the potential applications of personalised medicine through improved classification and targeted interventions. In this article we review the current status of the GWAS literature in schizophrenia including functional annotation methods and polygenic risk scoring, as well as the directions and challenges of future research. We consider recent findings in East Asian populations and the advancements from trans-ancestry analysis, as well as the insights gained from research looking across psychiatric disorders.

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.

Neurodevelopmental concepts of schizophrenia in the genome-wide association era: AKT/mTOR signaling as a pathological mediator of genetic and environmental programming during development

Normative brain development is contingent on the complex interplay between genes and environment. Schizophrenia (SCZ) is considered a highly polygenic, neurodevelopmental disorder associated with impaired neural circuit development, neurocognitive function and variations in neurotransmitter signaling systems, including dopamine. Significant evidence, accumulated over the last 30 years indicates a role for the in utero environment in SCZ pathophysiology. Emerging data suggests that changes in placental programming and function may mediate the link between genetic risk, early life complications (ELC) and adverse neurodevelopmental outcomes, with risk highlighted in key developmental drivers that converge on AKT/mTOR signaling. In this article we overview select risk genes identified through recent genome-wide association studies of SCZ including AKT3, miR-137, DRD2, and AKT1 itself. We propose that through convergence on AKT/mTOR signaling, these genes are critical factors directing both placentation and neurodevelopment, influencing risk for SCZ through dysregulation of placental function, metabolism and early brain development. We discuss association of risk genes in the context of their known roles in neurodevelopment, placental expression and their possible mechanistic links to SCZ in the broad context of the 'developmental origins of adult disease' construct. Understanding how common genetic variation impacts early fetal programming may advance our knowledge of disease etiology and identify early critical developmental windows for prevention and intervention.

The association between schizophrenia and the immune system: Review of the evidence from unbiased 'omic-studies'

A role for immune processes in the pathogenesis of schizophrenia has been suggested by genetic and epidemiological studies, as well as cross-sectional studies on blood and brain samples. However, results are heterogeneous, which is likely caused by low samples sizes, insufficient control of confounders that influence immune processes, and potentially publication bias. Large hypothesis-free 'omic' studies partially circumvent these problems and could provide further evidence for a role of immune pathways in schizophrenia. In this review we assessed whether the largest genome, transcriptome and methylome studies in schizophrenia to date support a link with the immune system. We constructed an overview of the schizophrenia-associated genes and transcripts that were identified in these large 'omic' studies. We then performed a hypothesis-driven analysis to examine the association and enrichment of immune system-related genes and transcripts in these datasets. Additionally, we reviewed secondary analyses that were previously performed on these 'omic' studies. Except for the link between complement factor 4 (C4), we found limited evidence for a role of microglia and immune processes among genetic risk variants. Transcriptome and methylome studies point towards alterations in immune system related genes, pathways and cells. This includes changes in microglia, as well as complement, nuclear factor-κB, toll-like receptor and interferon signaling pathways. Many of these associated immune-related genes and pathways have been shown to be involved in neurodevelopment and neuronal functioning. Additional replication of these findings is needed, but once further conformation is provided, these findings could be a potentially interesting target for future therapies.

Schizophrenia and Influenza at the Centenary of the 1918-1919 Spanish Influenza Pandemic: Mechanisms of Psychosis Risk

Associations between influenza infection and psychosis have been reported since the eighteenth century, with acute "psychoses of influenza" documented during multiple pandemics. In the late 20th century, reports of a season-of-birth effect in schizophrenia were supported by large-scale ecological and sero-epidemiological studies suggesting that maternal influenza infection increases the risk of psychosis in offspring. We examine the evidence for the association between influenza infection and schizophrenia risk, before reviewing possible mechanisms via which this risk may be conferred. Maternal immune activation models implicate placental dysfunction, disruption of cytokine networks, and subsequent microglial activation as potentially important pathogenic processes. More recent neuroimmunological advances focusing on neuronal autoimmunity following infection provide the basis for a model of infection-induced psychosis, potentially implicating autoimmunity to schizophrenia-relevant protein targets including the N-methyl-D-aspartate receptor. Finally, we outline areas for future research and relevant experimental approaches and consider whether the current evidence provides a basis for the rational development of strategies to prevent schizophrenia.

Focus on Causality in ESC/iPSC-Based Modeling of Psychiatric Disorders

Genome-wide association studies (GWAS) have identified an increasing number of genetic variants that significantly associate with psychiatric disorders. Despite this wealth of information, our knowledge of which variants causally contribute to disease, how they interact, and even more so of the functions they regulate, is still poor. The availability of embryonic stem cells (ESCs) and the advent of patient-specific induced pluripotent stem cells (iPSCs) has opened new opportunities to investigate genetic risk variants in living disease-relevant cells. Here, we analyze how this progress has contributed to the analysis of causal relationships between genetic risk variants and neuronal phenotypes, especially in schizophrenia (SCZ) and bipolar disorder (BD). Studies on rare, highly penetrant risk variants have originally led the field, until more recently when the development of (epi-) genetic editing techniques spurred studies on cause-effect relationships between common low risk variants and their associated neuronal phenotypes. This reorientation not only offers new insights, but also raises issues on interpretability. Concluding, we consider potential caveats and upcoming developments in the field of ESC/iPSC-based modeling of causality in psychiatric disorders.

Whole-exome sequencing of 81 individuals from 27 multiply affected bipolar disorder families

Bipolar disorder (BD) is a highly heritable neuropsychiatric disease characterized by recurrent episodes of depression and mania. Research suggests that the cumulative impact of common alleles explains 25-38% of phenotypic variance, and that rare variants may contribute to BD susceptibility. To identify rare, high-penetrance susceptibility variants for BD, whole-exome sequencing (WES) was performed in three affected individuals from each of 27 multiply affected families from Spain and Germany. WES identified 378 rare, non-synonymous, and potentially functional variants. These spanned 368 genes, and were carried by all three affected members in at least one family. Eight of the 368 genes harbored rare variants that were implicated in at least two independent families. In an extended segregation analysis involving additional family members, five of these eight genes harbored variants showing full or nearly full cosegregation with BD. These included the brain-expressed genes RGS12 and NCKAP5, which were considered the most promising BD candidates on the basis of independent evidence. Gene enrichment analysis for all 368 genes revealed significant enrichment for four pathways, including genes reported in de novo studies of autism (p_adj < 0.006) and schizophrenia (p_adj = 0.015). These results suggest a possible genetic overlap with BD for autism and schizophrenia at the rare-sequence-variant level. The present study implicates novel candidate genes for BD development, and may contribute to an improved understanding of the biological basis of this common and often devastating disease.

Identification of 34 genes conferring genetic and pharmacological risk for the comorbidity of schizophrenia and smoking behaviors

The prevalence of smoking is significantly higher in persons with schizophrenia (SCZ) than in the general population. However, the biological mechanisms of the comorbidity of smoking and SCZ are largely unknown. This study aimed to reveal shared biological pathways for the two diseases by analyzing data from two genome-wide association studies with a total sample size of 153,898. With pathway-based analysis, we first discovered 18 significantly enriched pathways shared by SCZ and smoking, which were classified into five groups: postsynaptic density, cadherin binding, dendritic spine, long-term depression, and axon guidance. Then, by using an integrative analysis of genetic, epigenetic, and expression data, we found not only 34 critical genes (e.g., PRKCZ, ARHGEF3, and CDKN1A) but also various risk-associated SNPs in these genes, which convey susceptibility to the comorbidity of the two disorders. Finally, using both in vivo and in vitro data, we demonstrated that the expression profiles of the 34 genes were significantly altered by multiple psychotropic drugs. Together, this multi-omics study not only reveals target genes for new drugs to treat SCZ but also reveals new insights into the shared genetic vulnerabilities of SCZ and smoking behaviors.

Overlapping evidence of innate immune dysfunction in psychotic and affective disorders

Disturbances of the immune system and immune responses after activation are a common finding in neuropsychiatric disorders. Psychotic and affective disorders such as major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BD) also share high rates of comorbidity with inflammatory and metabolic disorders. Evidence of elevated circulating inflammatory cytokines, altered numbers and function of immune cells, and evidence of neuroinflammation including activation of microglia in the brain have been found in patients with SCZ, BD and MDD. Often these findings correlate to psychological state at the time of measurement. However, significant variation exists across these studies in many aspects, creating challenges in identifying a specific signature of immune dysfunction in these disorders. Innate immune dysfunction, and alterations in monocytes, the critical sentinel cells of the innate immune system, have been seen repeatedly in all three of these disorders, with frequent overlap in findings. In this review, dysfunction specific to the innate arm of the immune system is compared for overlapping evidence across three major psychotic and affective disorders.

No association between anti-thyroidperoxidase antibodies and bipolar disorder: a study in the Dutch Bipolar Cohort and a meta-analysis

BACKGROUND

Thyroid autoimmunity has been associated with bipolar disorder (BD). However, results from previous studies on the seroprevalence of anti-thyroid peroxidase antibodies (TPO-abs) in BD are inconsistent.

OBJECTIVES

The aim of the present study is to investigate whether the seroprevalence and titer levels of TPO-abs are related to BD.

METHOD

TPO-abs were measured in plasma samples of 760 patients with bipolar disorder, 261 first-degree relatives and 363 controls by enzyme-linked immunosorbent assay (ELISA). To address methodological limitations of previous studies, we assessed clinical characteristics with several (self-reported) questionnaires to investigate whether TPO-abs positivity is related to particular clinical subgroups of BD patients. We performed an additional meta-analysis of seroprevalences of TPO-abs in BD patients including data from present and previous studies.

RESULTS

Seroprevalence or titer levels of TPO-abs did not significantly differ between patients with BD, their first-degree relatives, and controls. In BD patients, the prevalence of TPO-abs was unrelated to specific clinical factors, including lithium use. Our meta-analysis of twelve studies showed an overall odds ratio of 1.3 (CI 95 %: 0.7-2.3; p = 0.30), reaffirming the absence of an association of BD with TPO-abs.

CONCLUSIONS

In the largest study of TPO-abs in BD to date, our findings indicate that TPO-abs are not associated with (the risk for) bipolar disorder.

Novel genetic susceptibility loci identified by family based whole exome sequencing in Han Chinese schizophrenia patients

Schizophrenia (SCZ) is a highly heritable psychiatric disorder that affects approximately 1% of population around the world. However, early relevant studies did not reach clear conclusions of the genetic mechanisms of SCZ, suggesting that additional susceptibility loci that exert significant influence on SCZ are yet to be revealed. So, in order to identify novel susceptibility genes that account for the genetic risk of SCZ, we performed a systematic family-based study using whole exome sequencing (WES) in 65 Han Chinese families. The analysis of 51 SCZ trios with both unaffected parents identified 22 exonic and 1 splice-site de novo mutations (DNMs) on a total of 23 genes, and showed that 12 genes carried rare protein-altering compound heterozygous mutations in more than one trio. In addition, we identified 26 exonic or splice-site single nucleotide polymorphisms (SNPs) on 18 genes with nominal significance (P < 5 × 10-4) using a transmission disequilibrium test (TDT) in all the families. Moreover, TDT result confirmed a SCZ susceptibility locus on 3p21.1, encompassing the multigenetic region NEK4-ITIH1-ITIH3-ITIH4. Through several different strategies to predict the potential pathogenic genes in silico, we revealed 4 previous discovered susceptibility genes (TSNARE1, PBRM1, STAB1 and OLIG2) and 4 novel susceptibility loci (PSEN1, TLR5, MGAT5B and SSPO) in Han Chinese SCZ patients. In summary, we identified a list of putative candidate genes for SCZ using a family-based WES approach, thus improving our understanding of the pathology of SCZ and providing critical clues to future functional validation.

Bivariate genome-wide association analyses of the broad depression phenotype combined with major depressive disorder, bipolar disorder or schizophrenia reveal eight novel genetic loci for depression

Although a genetic basis of depression has been well established in twin studies, identification of genome-wide significant loci has been difficult. We hypothesized that bivariate analyses of findings from a meta-analysis of genome-wide association studies (meta-GWASs) of the broad depression phenotype with those from meta-GWASs of self-reported and recurrent major depressive disorder (MDD), bipolar disorder and schizophrenia would enhance statistical power to identify novel genetic loci for depression. LD score regression analyses were first used to estimate the genetic correlations of broad depression with self-reported MDD, recurrent MDD, bipolar disorder and schizophrenia. Then, we performed four bivariate GWAS analyses. The genetic correlations (r_g ± SE) of broad depression with self-reported MDD, recurrent MDD, bipolar disorder and schizophrenia were 0.79 ± 0.07, 0.24 ± 0.08, 0.53 ± 0.09 and 0.57 ± 0.05, respectively. From a total of 20 independent genome-wide significant loci, 13 loci replicated of which 8 were novel for depression. These were MUC21 for the broad depression phenotype with self-reported MDD and ZNF804A, MIR3143, PSORS1C2, STK19, SPATA31D1, RTN1 and TCF4 for the broad depression phenotype with schizophrenia. Post-GWAS functional analyses of these loci revealed their potential biological involvement in psychiatric disorders. Our results emphasize the genetic similarities among different psychiatric disorders and indicate that cross-disorder analyses may be the best way forward to accelerate gene finding for depression, or psychiatric disorders in general.

Impairments in sensory-motor gating and information processing in a mouse model of Ehmt1 haploinsufficiency

Regulators of chromatin dynamics and transcription are increasingly implicated in the aetiology of neurodevelopmental disorders. Haploinsufficiency of EHMT1, encoding a histone methyltransferase, is associated with several neurodevelopmental disorders, including Kleefstra syndrome, developmental delay and autism spectrum disorder. Using a mouse model of Ehmt1 haploinsufficiency (Ehmt1 D6Cre/+), we examined a number of brain and behavioural endophenotypes of relevance to neurodevelopmental disorders. Specifically, we show that Ehmt1 D6Cre/+ mice have deficits in information processing, evidenced by abnormal sensory-motor gating, a complete absence of object recognition memory, and a reduced magnitude of auditory evoked potentials in both paired-pulse inhibition and mismatch negativity. The electrophysiological experiments show that differences in magnitude response to auditory stimulus were associated with marked reductions in total and evoked beta- and gamma-band oscillatory activity, as well as significant reductions in phase synchronisation. The pattern of electrophysiological deficits in Ehmt1 D6Cre/+ matches those seen in control mice following administration of the selective NMDA-R antagonist, ketamine. This, coupled with reduction of Grin1 mRNA expression in Ehmt1 D6Cre/+ hippocampus, suggests that Ehmt1 haploinsufficiency may lead to disruption in NMDA-R. Taken together, these data indicate that reduced Ehmt1 dosage during forebrain development leads to abnormal circuitry formation, which in turn results in profound information processing deficits. Such information processing deficits are likely paramount to our understanding of the cognitive and neurological dysfunctions shared across the neurodevelopmental disorders associated with EHMT1 haploinsufficiency.

Association Between FoxO1, A2M, and TGF-β1, Environmental Factors, and Major Depressive Disorder

INTRODUCTION

Investigations of gene-environment (G×E) interactions in major depressive disorder (MDD) have been limited to hypothesis testing of candidate genes while poly-gene-environmental causation has not been adequately address. To this end, the present study analyzed the association between three candidate genes, two environmental factors, and MDD using a hypothesis-free testing approach.

METHODS

A logistic regression model was used to analyze interaction effects; a hierarchical regression model was used to evaluate the effects of different genotypes and the dose-response effects of the environment; genetic risk score (GRS) was used to estimate the cumulative contribution of genetic factors to MDD; and protein-protein interaction (PPI) analyses were carried out to evaluate the relationship between candidate genes and top MDD susceptibility genes.

RESULTS

Allelic association analyses revealed significant effects of the interaction between the candidate genes Forkhead box (Fox)O1, α2-macroglobulin (A2M), and transforming growth factor (TGF)-β1 genes and the environment on MDD. Gene-gene (G×G) and gene-gene-environment (G×G×E) interactions in MDD were also included in the model. Hierarchical regression analysis showed that the effect of environmental factors on MDD was greater in homozygous than in heterozygous mutant genotypes of the FoxO1 and TGF-β1 genes; a dose-response effect between environment and MDD on genotypes was also included in this model. Haplotype analyses revealed significant global and individual effects of haplotypes on MDD in the whole sample as well as in subgroups. There was a significant association between GRS and MDD (P = 0.029) and a GRS and environment interaction effect on MDD (P = 0.009). Candidate and top susceptibility genes were connected in PPI networks.

CONCLUSIONS

FoxO1, A2M, and TGF-β1 interact with environmental factors and with each other in MDD. Multi-factorial G×E interactions may be responsible for a higher explained variance and may be associated with causal factors and mechanisms that could inform new diagnosis and therapeutic strategies, which can contribute to the personalized medicine of MDD.

Neurobiological commonalities and distinctions among 3 major psychiatric disorders: a graph theoretical analysis of the structural connectome

BACKGROUND

White matter network alterations have increasingly been implicated in major depressive disorder, bipolar disorder and schizophrenia. The aim of this study was to identify shared and distinct white matter network alterations among the 3 disorders.

METHODS

We used analysis of covariance, with age and gender as covariates, to investigate white matter network alterations in 123 patients with schizophrenia, 123 with bipolar disorder, 124 with major depressive disorder and 209 healthy controls.

RESULTS

We found significant group differences in global network efficiency (F = 3.386, p = 0.018), nodal efficiency (F = 8.015, p < 0.001 corrected for false discovery rate [FDR]) and nodal degree (F = 5.971, pFDR < 0.001) in the left middle occipital gyrus, as well as nodal efficiency (F = 6.930, pFDR < 0.001) and nodal degree (F = 5.884, pFDR < 0.001) in the left postcentral gyrus. We found no significant alterations in patients with major depressive disorder. Post hoc analyses revealed that compared with healthy controls, patients in the schizophrenia and bipolar disorder groups showed decreased global network efficiency, nodal efficiency and nodal degree in the left middle occipital gyrus. Furthermore, patients in the schizophrenia group showed decreased nodal efficiency and nodal degree in the left postcentral gyrus compared with healthy controls.

LIMITATIONS

Our findings could have been confounded in part by treatment differences.

CONCLUSION

Our findings implicate graded white matter network alterations across the 3 disorders, enhancing our understanding of shared and distinct pathophysiological mechanisms across diagnoses and providing vital insights into neuroimaging-based methods for diagnosis and research.

Comorbid Bipolar Disorder and Migraine: From Mechanisms to Treatment

Bipolar disorder (BD) is a severe psychiatric disorder characterized by recurrent episodes of manic/hypomanic or depressive symptoms and euthymic periods, with some patients suffering a gradual deterioration of illness and consequent cognitive deficits during the late stage. Migraine is a disease generally without abnormal medical examinations, neurological examinations or laboratory studies, and the diagnosis is made based on the retrospective demonstration of headache features and groupings of disease-associated symptoms. The epidemiology of comorbid BD and migraine is high and it is obligatory to find effective treatments to improve the prognosis. Recent investigations demonstrated that the close relationship between BD and migraine significantly increased the rapid cycling rates of both BD and migraine in patients. Although the detailed mechanism is complex and largely unclear in comorbid BD and migrain, genetic factors, neurotransmitters, altered signaling pathways, disturbances of inflammatory cytokines, and mitochondrial dysfunction are risk factors of BD and migraine. Particularly these two diseases share some overlapping mechanisms according to previous studies. To this end, we call for further investigations of the potential mechanisms, and more efforts are underway to improve the treatment of people with comorbid BD and migraine. In this review, we provide an overview of the potential mechanisms in patients with BD or migraine and we further discuss the treatment strategies for comorbid BD and migraine and it is obligatory to find effective treatments to improve the prognosis. This work will provide insights for us to know more about the mechanisms of comorbid BD and migraine, provides new therapeutic targets for the treatment and give clinicians some guidance for more appropriate and beneficial treatment.

Neuroimmunological effects of early life experiences

Exposure to adverse experiences during development increases the risk of psychiatric illness later in life. Growing evidence suggests a role for the neuroimmune system in this relationship. There is now substantial evidence that the immune system is critical for normal brain development and behaviour, and responds to environmental perturbations experienced early in life. Severe or chronic stress results in dysregulated neuroimmune function, concomitant with abnormal brain morphology and function. Positive experiences including environmental enrichment and exercise exert the opposite effect, promoting normal brain and immune function even in the face of early life stress. The neuroimmune system may therefore provide a viable target for prevention and treatment of psychiatric illness. This review will briefly summarise the neuroimmune system in brain development and function, and review the effects of stress and positive environmental experiences during development on neuroimmune function. There are also significant sex differences in how the neuroimmune system responds to environmental experiences early in life, which we will briefly review.