The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function

Limited WKY chromosomal regions confer increases in anxiety and fear memory in a F344 congenic rat strain

This study investigated the interaction between genetic differences in stress reactivity/coping and environmental challenges, such as acute stress during adolescence on adult contextual fear memory and anxiety-like behaviors. Fischer 344 (F344) and the inbred F344;WKY-Stresp3/Eer congenic strain (congenic), in which chromosomal regions from the Wistar-Kyoto (WKY) strain were introgressed into the F344 background, were exposed to a modified forced swim test during adolescence, while controls were undisturbed. In adulthood, fear learning and memory, assessed by contextual fear conditioning, were significantly greater in congenic animals compared with F344 animals, and stress during adolescence increased them even further in males of both strains. Anxiety-like behavior, measured by the open field test, was also greater in congenic than F344 animals, and stress during adolescence increased it further in both strains of adult males. Whole genome sequencing of the F344;WKY-Stresp3/Eer strain revealed an enrichment of WKY genotypes in chromosomes 9, 14, and 15. An example of functional WKY sequence variations in the congenic strain, cannabinoid receptor interacting protein 1 (Cnrip1) had a Cnrip1 transcript isoform that lacked two exons. Although the original hypothesis that the genetic predisposition to increased anxiety of the WKY donor strain would exaggerate fear memory relative to the background strain was confirmed, the consequences of adolescent stress were strain independent but sex dependent in adulthood. Molecular genomic approaches combined with genetic mapping of WKY sequence variations in chromosomes 9, 14, and 15 could aid in finding quantitative trait genes contributing to the variation in fear memory.NEW & NOTEWORTHY This study found that 1) whole genome sequencing of congenic strains should be a criterion for their recognition; 2) sequence variations between Wistar-Kyoto and Fischer 344 strains at regions of chromosomes 9, 14, and 15 contribute to differences in contextual fear memory and anxiety-like behaviors; and 3) stress during adolescence affects these behaviors in males, but not females, and is independent of strain.

Precision psychiatry and Research Domain Criteria: Implications for clinical trials and future practice

Psychiatric disorders are associated with significant social and economic burdens, many of which are related to issues with current diagnosis and treatments. The coronavirus (COVID-19) pandemic is estimated to have increased the prevalence and burden of major depressive and anxiety disorders, indicating an urgent need to strengthen mental health systems globally. To date, current approaches adopted in drug discovery and development for psychiatric disorders have been relatively unsuccessful. Precision psychiatry aims to tailor healthcare more closely to the needs of individual patients and, when informed by neuroscience, can offer the opportunity to improve the accuracy of disease classification, treatment decisions, and prevention efforts. In this review, we highlight the growing global interest in precision psychiatry and the potential for the National Institute of Health-devised Research Domain Criteria (RDoC) to facilitate the implementation of transdiagnostic and improved treatment approaches. The need for current psychiatric nosology to evolve with recent scientific advancements and increase awareness in emerging investigators/clinicians of the value of this approach is essential. Finally, we examine current challenges and future opportunities of adopting the RDoC-associated translational and transdiagnostic approaches in clinical studies, acknowledging that the strength of RDoC is that they form a dynamic framework of guiding principles that is intended to evolve continuously with scientific developments into the future. A collaborative approach that recruits expertise from multiple disciplines, while also considering the patient perspective, is needed to pave the way for precision psychiatry that can improve the prognosis and quality of life of psychiatric patients.

Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference

Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings.

14-3-3ε: a protein with complex physiology function but promising therapeutic potential in cancer

Over the past decade, the role of the 14-3-3 protein has received increasing interest. Seven subtypes of 14-3-3 proteins exhibit high homology; however, each subtype maintains its specificity. The 14-3-3ε protein is involved in various physiological processes, including signal transduction, cell proliferation, apoptosis, autophagy, cell cycle regulation, repolarization of cardiac action, cardiac development, intracellular electrolyte homeostasis, neurodevelopment, and innate immunity. It also plays a significant role in the development and progression of various diseases, such as cardiovascular diseases, inflammatory diseases, neurodegenerative disorders, and cancer. These immense and various involvements of 14-3-3ε in diverse processes makes it a promising target for drug development. Although extensive research has been conducted on 14-3-3 dimers, studies on 14-3-3 monomers are limited. This review aimed to provide an overview of recent reports on the molecular mechanisms involved in the regulation of binding partners by 14-3-3ε, focusing on issues that could help advance the frontiers of this field. Video Abstract.

A genome-wide investigation into the underlying genetic architecture of personality traits and overlap with psychopathology

Personality is influenced by both genetic and environmental factors and is associated with other psychiatric traits such as anxiety and depression. The "Big Five" personality traits, which include neuroticism, extraversion, agreeableness, conscientiousness, and openness, are a widely accepted and influential framework for understanding and describing human personality. Of the big five personality traits, neuroticism has most often been the focus of genetic studies and is linked to various mental illnesses including depression, anxiety, and schizophrenia. Our knowledge of the genetic architecture of the other four personality traits is more limited. Utilizing the Million Veteran Program (MVP) cohort we conducted a genome-wide association study (GWAS) in individuals of European and African ancestry. Adding other published data, we performed GWAS meta-analysis for each of the five personality traits with sample sizes ranging from 237,390 to 682,688. We identified 158, 14, 3, 2, and 7 independent genome-wide significant (GWS) loci associated with neuroticism, extraversion, agreeableness, conscientiousness, and openness, respectively. These findings represent 55 novel loci for neuroticism, as well as the first GWS loci discovered for extraversion and agreeableness. Gene-based association testing revealed 254 genes showing significant association with at least one of the five personality traits. Transcriptome-wide and proteome-wide analysis identified altered expression of genes and proteins such as CRHR1, SLC12A5, MAPT, and STX4. Pathway enrichment and drug perturbation analyses identified complex biology underlying human personality traits. We also studied the inter-relationship of personality traits with 1,437 other traits in a phenome-wide genetic correlation analysis, identifying new associations. Mendelian randomization showed positive bidirectional effects between neuroticism and depression and anxiety while a negative bidirectional effect was observed for agreeableness and these psychiatric traits. This study improves our comprehensive understanding of the genetic architecture underlying personality traits and their relationship to other complex human traits.

Genomic Structural Equation Modeling Reveals Latent Phenotypes in the Human Cortex with Distinct Genetic Architecture

Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to map the genetic architecture of cortical surface area (SA) and cortical thickness (CT) for the 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance, which we are denoting genetically informed brain networks (GIBNs). Genomic SEM can fit a multivariate GWAS from summary statistics for each of the GIBNs, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA identified 6 GIBNs and CT identified 4 GIBNs. The multivariate GWASs of these GIBNs identified 74 genome-wide significant (GWS) loci (p<5×10-8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of GIBN GWASs found that SA-derived GIBNs had a positive genetic correlation with bipolar disorder (BPD), and cannabis use disorder, indicating genetic predisposition to a larger SA in the specific GIBN is associated with greater genetic risk of these disorders. A negative genetic correlation was observed with attention deficit hyperactivity disorder (ADHD), major depressive disorder (MDD), and insomnia, indicating genetic predisposition to a larger SA in the specific GIBN is associated with lower genetic risk of these disorders. CT GIBNs displayed a negative genetic correlation with alcohol dependence. Jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across phenotypes offers a new vantage point for mapping the cortex into genetically informed networks.

Polygenic risk of major depressive disorder as a risk factor for venous thromboembolism

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are associated with an increased risk of cardiovascular diseases, including venous thromboembolism (VTE). The reasons for this are complex and include obesity, smoking, and use of hormones and psychotropic medications. Genetic studies have increasingly provided evidence of the shared genetic risk of psychiatric and cardiometabolic illnesses. This study aimed to determine whether a genetic predisposition to MDD, BD, or SCZ is associated with an increased risk of VTE. Genetic correlations using the largest genome-wide genetic meta-analyses summary statistics for MDD, BD, and SCZ (Psychiatric Genetics Consortium) and a recent genome-wide genetic meta-analysis of VTE (INVENT Consortium) demonstrated a positive association between VTE and MDD but not BD or SCZ. The same summary statistics were used to construct polygenic risk scores for MDD, BD, and SCZ in UK Biobank participants of self-reported White British ancestry. These were assessed for impact on self-reported VTE risk (10 786 cases, 285 124 controls), using logistic regression, in sex-specific and sex-combined analyses. We identified significant positive associations between polygenic risk for MDD and the risk of VTE in men, women, and sex-combined analyses, independent of the known risk factors. Secondary analyses demonstrated that this association was not driven by those with lifetime experience of mental illness. Meta-analyses of individual data from 6 additional independent cohorts replicated the sex-combined association. This report provides evidence for shared biological mechanisms leading to MDD and VTE and suggests that, in the absence of genetic data, a family history of MDD might be considered when assessing the risk of VTE.

Genome-wide analysis of anorexia nervosa and major psychiatric disorders and related traits reveals genetic overlap and identifies novel risk loci for anorexia nervosa

Anorexia nervosa (AN) is a heritable eating disorder (50-60%) with an array of commonly comorbid psychiatric disorders and related traits. Although significant genetic correlations between AN and psychiatric disorders and related traits have been reported, their shared genetic architecture is largely understudied. We investigated the shared genetic architecture of AN and schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), mood instability (Mood), neuroticism (NEUR), and intelligence (INT). We applied the conditional false discovery rate (FDR) method to identify novel risk loci for AN, and conjunctional FDR to identify loci shared between AN and related phenotypes, to summarize statistics from relevant genome-wide association studies (GWAS). Individual GWAS samples varied from 72,517 to 420,879 participants. Using conditional FDR we identified 58 novel AN loci. Furthermore, we identified 38 unique loci shared between AN and major psychiatric disorders (SCZ, BIP, and MD) and 45 between AN and psychological traits (Mood, NEUR, and INT). In line with genetic correlations, the majority of shared loci showed concordant effect directions. Functional analyses revealed that the shared loci are involved in 65 unique pathways, several of which overlapped across analyses, including the "signal by MST1" pathway involved in Hippo signaling. In conclusion, we demonstrated genetic overlap between AN and major psychiatric disorders and related traits, and identified novel risk loci for AN by leveraging this overlap. Our results indicate that some shared characteristics between AN and related disorders and traits may have genetic underpinnings.

HSPA12A controls cerebral lactate homeostasis to maintain hippocampal neurogenesis and mood stabilization

Mood instability, a subjective emotional state defined as rapid mood oscillations of up and down, is a symptom that occurs in several psychiatric disorders, particularly major depressive disorder and bipolar disorder. Heat shock protein A12A (HSPA12A) shows decreased expression in the brains of schizophrenia patients. However, the causal effects of HSPA12A in any psychiatric disorders are completely unknown. To investigate whether HSPA12A affects mood stability, Hspa12a-knockout mice (Hspa12a-/-) and wild-type (WT) littermates were subjected to tests of open field, forced swimming, elevated plus maze, and sucrose preference. Cerebral lactate levels were measured in cerebrospinal fluid (CSF). Adult hippocampal neurogenesis (AHN) was assessed by BrdU labeling. We found that acute mood stress increased hippocampal HSPA12A expression and CSF lactate levels in mice. However, Hspa12a-/- mice exhibited behaviors of mood instability (anhedonia, lower locomotor activity, antidepression, and anxiety), which were accompanied by impaired AHN, decreased CSF lactate levels, and downregulated hippocampal glycolytic enzyme expression. By contrast, HSPA12A overexpression increased lactate production and glycolytic enzyme expression of primary hippocampal neurons. Intriguingly, lactate administration alleviated the mood instability and AHN impairment in Hspa12a-/- mice. Further analyses revealed that HSPA12A was necessary for sustaining cerebral lactate homeostasis, which could be mediated by inhibiting GSK3β in hippocampal neurons, to maintain AHN and mood stabilization. Taken together, HSPA12A is defined as a novel regulator of mood stability and exerts therapeutic potential for mood disorder. Our findings establish a framework for determining mood disorder and AHN relevance of cerebral lactate homeostasis. HSPA12A is a novel mood stabilizer through inhibiting GSK3β in hippocampal neurons, thereby sustaining glycolysis-generated lactate to maintain cerebral lactate homeostasis, which ultimately leading to maintenance of hippocampal neurogenesis and mood stabilization.

Identifying genetic loci that are associated with changes in gene expression in PTSD in a South African cohort

The molecular mechanisms underlying posttraumatic stress disorder (PTSD) are yet to be fully elucidated, especially in underrepresented population groups. Expression quantitative trait loci (eQTLs) are DNA sequence variants that influence gene expression, in a local (cis-) or distal (trans-) manner, and subsequently impact cellular, tissue, and system physiology. This study aims to identify genetic loci associated with gene expression changes in a South African PTSD cohort. Genome-wide genotype and RNA-sequencing data were obtained from 32 trauma-exposed controls and 35 PTSD cases of mixed-ancestry, as part of the SHARED ROOTS project. The first approach utilised 108 937 single-nucleotide polymorphisms (SNPs) (MAF > 10%) and 11 312 genes with Matrix eQTL to map potential eQTLs, while controlling for covariates as appropriate. The second analysis was focused on 5638 SNPs related to a previously calculated PTSD polygenic risk score for this cohort. SNP-gene pairs were considered eQTLs if they surpassed Bonferroni correction and had a false discovery rate <0.05. We did not identify eQTLs that significantly influenced gene expression in a PTSD-dependent manner. However, several known cis-eQTLs, independent of PTSD diagnosis, were observed. rs8521 (C > T) was associated with TAGLN and SIDT2 expression, and rs11085906 (C > T) was associated with ZNF333 expression. This exploratory study provides insight into the molecular mechanisms associated with PTSD in a non-European, admixed sample population. This study was limited by the cross-sectional design and insufficient statistical power. Overall, this study should encourage further multi-omics approaches towards investigating PTSD in diverse populations.

Effects of urban living environments on mental health in adults

Urban-living individuals are exposed to many environmental factors that may combine and interact to influence mental health. While individual factors of an urban environment have been investigated in isolation, no attempt has been made to model how complex, real-life exposure to living in the city relates to brain and mental health, and how this is moderated by genetic factors. Using the data of 156,075 participants from the UK Biobank, we carried out sparse canonical correlation analyses to investigate the relationships between urban environments and psychiatric symptoms. We found an environmental profile of social deprivation, air pollution, street network and urban land-use density that was positively correlated with an affective symptom group (r = 0.22, Pperm < 0.001), mediated by brain volume differences consistent with reward processing, and moderated by genes enriched for stress response, including CRHR1, explaining 2.01% of the variance in brain volume differences. Protective factors such as greenness and generous destination accessibility were negatively correlated with an anxiety symptom group (r = 0.10, Pperm < 0.001), mediated by brain regions necessary for emotion regulation and moderated by EXD3, explaining 1.65% of the variance. The third urban environmental profile was correlated with an emotional instability symptom group (r = 0.03, Pperm < 0.001). Our findings suggest that different environmental profiles of urban living may influence specific psychiatric symptom groups through distinct neurobiological pathways.

Leveraging genetic overlap between irritability and psychiatric disorders to identify genetic variants of major psychiatric disorders

Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [n] of additional SNPs = 105), BD I (n = 54), MDD (n = 107), and irritability (n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.

Independent Associated SNPs at SORCS3 and Its Protein Interactors for Multiple Brain-Related Disorders and Traits

Sortilin-related vacuolar protein sorting 10 (VPS10) domain containing receptor 3 (SORCS3) is a neuron-specific transmembrane protein involved in the trafficking of proteins between intracellular vesicles and the plasma membrane. Genetic variation at SORCS3 is associated with multiple neuropsychiatric disorders and behavioural phenotypes. Here, we undertake a systematic search of published genome-wide association studies to identify and catalogue associations between SORCS3 and brain-related disorders and traits. We also generate a SORCS3 gene-set based on protein-protein interactions and investigate the contribution of this gene-set to the heritability of these phenotypes and its overlap with synaptic biology. Analysis of association signals at SORSC3 showed individual SNPs to be associated with multiple neuropsychiatric and neurodevelopmental brain-related disorders and traits that have an impact on the experience of feeling, emotion or mood or cognitive function, while multiple LD-independent SNPs were associated with the same phenotypes. Across these SNPs, alleles associated with the more favourable outcomes for each phenotype (e.g., decreased risk of neuropsychiatric illness) were associated with increased expression of the SORCS3 gene. The SORCS3 gene-set was enriched for heritability contributing to schizophrenia (SCZ), bipolar disorder (BPD), intelligence (IQ) and education attainment (EA). Eleven genes from the SORCS3 gene-set were associated with more than one of these phenotypes at the genome-wide level, with RBFOX1 associated with SCZ, IQ and EA. Functional annotation revealed that the SORCS3 gene-set is enriched for multiple ontologies related to the structure and function of synapses. Overall, we find many independent association signals at SORCS3 with brain-related disorders and traits, with the effect possibly mediated by reduced gene expression, resulting in a negative impact on synaptic function.

New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications

Psychiatric genetics has made substantial progress in the last decade, providing new insights into the genetic etiology of psychiatric disorders, and paving the way for precision psychiatry, in which individual genetic profiles may be used to personalize risk assessment and inform clinical decision-making. Long recognized to be heritable, recent evidence shows that psychiatric disorders are influenced by thousands of genetic variants acting together. Most of these variants are commonly occurring, meaning that every individual has a genetic risk to each psychiatric disorder, from low to high. A series of large-scale genetic studies have discovered an increasing number of common and rare genetic variants robustly associated with major psychiatric disorders. The most convincing biological interpretation of the genetic findings implicates altered synaptic function in autism spectrum disorder and schizophrenia. However, the mechanistic understanding is still incomplete. In line with their extensive clinical and epidemiological overlap, psychiatric disorders appear to exist on genetic continua and share a large degree of genetic risk with one another. This provides further support to the notion that current psychiatric diagnoses do not represent distinct pathogenic entities, which may inform ongoing attempts to reconceptualize psychiatric nosology. Psychiatric disorders also share genetic influences with a range of behavioral and somatic traits and diseases, including brain structures, cognitive function, immunological phenotypes and cardiovascular disease, suggesting shared genetic etiology of potential clinical importance. Current polygenic risk score tools, which predict individual genetic susceptibility to illness, do not yet provide clinically actionable information. However, their precision is likely to improve in the coming years, and they may eventually become part of clinical practice, stressing the need to educate clinicians and patients about their potential use and misuse. This review discusses key recent insights from psychiatric genetics and their possible clinical applications, and suggests future directions.

Injury, illness, and emotion: A review of the motivational continuum from trauma through recovery from an ecological perspective

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Glucocorticoids unmask silent non-coding genetic risk variants for common diseases

Understanding the function of non-coding genomic sequence variants represents a challenge for biomedicine. Many diseases are products of gene-by-environment interactions with complex mechanisms. This study addresses these themes by mechanistic characterization of non-coding variants that influence gene expression only after drug or hormone exposure. Using glucocorticoid signaling as a model system, we integrated genomic, transcriptomic, and epigenomic approaches to unravel mechanisms by which variant function could be revealed by hormones or drugs. Specifically, we identified cis-regulatory elements and 3D interactions underlying ligand-dependent associations between variants and gene expression. One-quarter of the glucocorticoid-modulated variants that we identified had already been associated with clinical phenotypes. However, their affected genes were 'unmasked' only after glucocorticoid exposure and often with function relevant to the disease phenotypes. These diseases involved glucocorticoids as risk factors or therapeutic agents and included autoimmunity, metabolic and mood disorders, osteoporosis and cancer. For example, we identified a novel breast cancer risk gene, MAST4, with expression that was repressed by glucocorticoids in cells carrying the risk genotype, repression that correlated with MAST4 expression in breast cancer and treatment outcomes. These observations provide a mechanistic framework for understanding non-coding genetic variant-chemical environment interactions and their role in disease risk and drug response.

Genetic overlap between mood instability and alcohol-related phenotypes suggests shared biological underpinnings

Alcohol use disorder (AUD) is a pervasive and devastating mental illness with high comorbidity rates with other mental disorders. Understanding the genetic architecture of this comorbidity could be improved by focusing on intermediate traits that show positive genetic correlation with the disorders. Thus, we aimed to characterize the shared vs. unique polygenicity of AUD, alcohol consumption (AC) and mood instability (MOOD) -beyond genetic correlation, and boost discovery for jointly-associated loci. Summary statistics for MOOD (a binary measure of the tendency to report frequent mood swings), AC (number of standard drinks over a typical consumption week) and AUD GWASs (Ns > 200,000) were analyzed to characterize the cross-phenotype associations between MOOD and AC, MOOD and AUD and AC and AUD. To do so, we used a newly established pipeline that combines (i) the bivariate causal mixture model (MiXeR) to quantify polygenic overlap and (ii) the conjunctional false discovery rate (conjFDR) to discover specific jointly associated genomic loci, which were mapped to genes and biological functions. MOOD was highly polygenic (10.4k single nucleotide polymorphisms, SNPs, SD = 2k) compared to AC (4.9k SNPs, SD = 0.6k) and AUD (4.3k SNPs, SD = 2k). The polygenic overlap of MOOD and AC was twice that of MOOD and AUD (98% vs. 49%), with opposite genetic correlation (-0.2 vs. 0.23), as confirmed in independent samples. MOOD&AUD associated SNPs were significantly enriched for brain genes, conversely to MOOD&AC. Among 38 jointly associated loci, fifteen were novel for MOOD, AC and AUD. MOOD, AC and AUD were also strongly associated at the phenotypic level. Overall, using multilevel polygenic quantification, joint loci discovery and functional annotation methods, we evidenced that the polygenic overlap between MOOD and AC/AUD implicated partly shared biological underpinnings, yet, clearly distinct functional patterns between MOOD&AC and MOOD&AUD, suggesting new mechanisms for the comorbidity of AUD with mood 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.

Shared genetic architectures of subjective well-being in East Asian and European ancestry populations

Subjective well-being (SWB) has been explored in European ancestral populations; however, whether the SWB genetic architecture is shared across populations remains unclear. We conducted a cross-population genome-wide association study for SWB using samples from Korean (n = 110,919) and European (n = 563,176) ancestries. Five ancestry-specific loci and twelve cross-ancestry significant genomic loci were identified. One novel locus (rs12298541 near HMGA2) associated with SWB was also identified through the European meta-analysis. Significant cross-ancestry genetic correlation for SWB between samples was observed. Polygenic risk analysis in an independent Korean cohort (n = 22,455) demonstrated transferability between populations. Significant correlations between SWB and major depressive disorder, and significant enrichment of central nervous system-related polymorphisms heritability in both ancestry populations were found. Hence, large-scale cross-ancestry genome-wide association studies can advance our understanding of SWB genetic architecture and mental health.

Borderline personality disorder and the big five: molecular genetic analyses indicate shared genetic architecture with neuroticism and openness

Both environmental (e.g. interpersonal traumatization during childhood and adolescence) and genetic factors may contribute to the development of Borderline Personality Disorder (BPD). Twin studies assessing borderline personality symptoms/features in the general population indicate that genetic factors underlying these symptoms/features are shared in part with the personality traits of the Five Factor Model (FFM) of personality-the "Big Five". In the present study, the genetic overlap of BPD with the Big Five -Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism- was assessed. Linkage disequilibrium score regression was used to calculate genetic correlations between a genome-wide association study (GWAS) in central European populations on BPD (N = 2543) and GWAS on the Big Five (N = 76,551-122,886, Neuroticism N = 390,278). Polygenic scores (PGS) were calculated to test the association of the genetic disposition for the personality traits with BPD case-control status. Significant positive genetic correlations of BPD were found with Neuroticism (rg = 0.34, p = 6.3*10^-5) and Openness (rg = 0.24, p = 0.036), but not with the other personality traits (all | rg | <0.14, all p > 0.30). A cluster and item-level analysis showed positive genetic correlations of BPD with the Neuroticism clusters "Depressed Affect" and "Worry", and with a broad range of Neuroticism items (N = 348,219-376,352). PGS analyses confirmed the genetic correlations, and found an independent contribution of the personality traits to BPD risk. The observed associations indicate a partially shared genetic background of BPD and the personality traits Neuroticism and Openness. Larger GWAS of BPD and the "Big Five" are needed to further explore the role of personality traits in the etiology of BPD.

Genetic common variants associated with cerebellar volume and their overlap with mental disorders: a study on 33,265 individuals from the UK-Biobank

Interest in the cerebellum is expanding given evidence of its contributions to cognition and emotion, and dysfunction in various psychopathologies. However, research into its genetic architecture and shared influences with liability for mental disorders is lacking. We conducted a genome-wide association study (GWAS) of total cerebellar volume and underlying cerebellar lobe volumes in 33,265 UK-Biobank participants. Total cerebellar volume was heritable (h2SNP = 50.6%), showing moderate genetic homogeneity across lobes (h2SNP from 35.4% to 57.1%; mean genetic correlation between lobes rg ≈ 0.44). We identified 33 GWAS signals associated with total cerebellar volume, of which 6 are known to alter protein-coding gene structure, while a further five mapped to genomic regions known to alter cerebellar tissue gene expression. Use of summary data-based Mendelian randomisation further prioritised genes whose change in expression appears to mediate the SNP-trait association. In total, we highlight 21 unique genes of greatest interest for follow-up analyses. Using LD-regression, we report significant genetic correlations between total cerebellar volume and brainstem, pallidum and thalamus volumes. While the same approach did not result in significant correlations with psychiatric phenotypes, we report enrichment of schizophrenia, bipolar disorder and autism spectrum disorder associated signals within total cerebellar GWAS results via conditional and conjunctional-FDR analysis. Via these methods and GWAS catalogue, we identify which of our cerebellar genomic regions also associate with psychiatric traits. Our results provide important insights into the common allele architecture of cerebellar volume and its overlap with other brain volumes and psychiatric phenotypes.

Multi-Trait Genome-Wide Association Study of Atherosclerosis Detects Novel Pleiotropic Loci

Although affecting different arterial territories, the related atherosclerotic vascular diseases coronary artery disease (CAD) and peripheral artery disease (PAD) share similar risk factors and have shared pathobiology. To identify novel pleiotropic loci associated with atherosclerosis, we performed a joint analysis of their shared genetic architecture, along with that of common risk factors. Using summary statistics from genome-wide association studies of nine known atherosclerotic (CAD, PAD) and atherosclerosis risk factors (body mass index, smoking initiation, type 2 diabetes, low density lipoprotein, high density lipoprotein, total cholesterol, and triglycerides), we perform 15 separate multi-trait genetic association scans which resulted in 25 novel pleiotropic loci not yet reported as genome-wide significant for their respective traits. Colocalization with single-tissue eQTLs identified candidate causal genes at 14 of the detected signals. Notably, the signal between PAD and LDL-C at the PCSK6 locus affects PCSK6 splicing in human liver tissue and induced pluripotent derived hepatocyte-like cells. These results show that joint analysis of related atherosclerotic disease traits and their risk factors allowed identification of unified biology that may offer the opportunity for therapeutic manipulation. The signal at PCSK6 represent possible shared causal biology where existing inhibitors may be able to be leveraged for novel therapies.

A scoping review and comparison of approaches for measuring genetic heterogeneity in psychiatric disorders

An improved understanding of genetic etiological heterogeneity in a psychiatric condition may help us (a) isolate a neurophysiological 'final common pathway' by identifying its upstream genetic origins and (b) facilitate characterization of the condition's phenotypic variation. This review aims to identify existing genetic heterogeneity measurements in the psychiatric literature and provides a conceptual review of their mechanisms, limitations, and assumptions. The Scopus database was searched for studies that quantified genetic heterogeneity or correlation of psychiatric phenotypes with human genetic data. Ninety studies were included. Eighty-seven reports quantified genetic correlation, five applied genomic structural equation modelling, three evaluated departure from the Hardy-Weinberg equilibrium at one or more loci, and two applied a novel approach known as MiXeR. We found no study that rigorously measured genetic etiological heterogeneity across a large number of markers. Developing such approaches may help better characterize the biological diversity of psychopathology.

The Neurometabolic Basis of Mood Instability: The Parvalbumin Interneuron Link-A Systematic Review and Meta-Analysis

The neurobiological bases of mood instability are poorly understood. Neuronal network alterations and neurometabolic abnormalities have been implicated in the pathophysiology of mood and anxiety conditions associated with mood instability and hence are candidate mechanisms underlying its neurobiology. Fast-spiking parvalbumin GABAergic interneurons modulate the activity of principal excitatory neurons through their inhibitory action determining precise neuronal excitation balance. These interneurons are directly involved in generating neuronal networks activities responsible for sustaining higher cerebral functions and are especially vulnerable to metabolic stress associated with deficiency of energy substrates or mitochondrial dysfunction. Parvalbumin interneurons are therefore candidate key players involved in mechanisms underlying the pathogenesis of brain disorders associated with both neuronal networks' dysfunction and brain metabolism dysregulation. To provide empirical support to this hypothesis, we hereby report meta-analytical evidence of parvalbumin interneurons loss or dysfunction in the brain of patients with Bipolar Affective Disorder (BPAD), a condition primarily characterized by mood instability for which the pathophysiological role of mitochondrial dysfunction has recently emerged as critically important. We then present a comprehensive review of evidence from the literature illustrating the bidirectional relationship between deficiency in mitochondrial-dependent energy production and parvalbumin interneuron abnormalities. We propose a mechanistic explanation of how alterations in neuronal excitability, resulting from parvalbumin interneurons loss or dysfunction, might manifest clinically as mood instability, a poorly understood clinical phenotype typical of the most severe forms of affective disorders. The evidence we report provides insights on the broader therapeutic potential of pharmacologically targeting parvalbumin interneurons in psychiatric and neurological conditions characterized by both neurometabolic and neuroexcitability abnormalities.

Unveiling the Pathogenesis of Psychiatric Disorders Using Network Models

Psychiatric disorders are complex brain disorders with a high degree of genetic heterogeneity, affecting millions of people worldwide. Despite advances in psychiatric genetics, the underlying pathogenic mechanisms of psychiatric disorders are still largely elusive, which impedes the development of novel rational therapies. There has been accumulating evidence suggesting that the genetics of complex disorders can be viewed through an omnigenic lens, which involves contextualizing genes in highly interconnected networks. Thus, applying network-based multi-omics integration methods could cast new light on the pathophysiology of psychiatric disorders. In this review, we first provide an overview of the recent advances in psychiatric genetics and highlight gaps in translating molecular associations into mechanistic insights. We then present an overview of network methodologies and review previous applications of network methods in the study of psychiatric disorders. Lastly, we describe the potential of such methodologies within a multi-tissue, multi-omics approach, and summarize the future directions in adopting diverse network approaches.

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

Sex-stratified genome-wide association study of multisite chronic pain in UK Biobank

Chronic pain is highly prevalent worldwide and imparts a significant socioeconomic and public health burden. Factors influencing susceptibility to, and mechanisms of, chronic pain development, are not fully understood, but sex is thought to play a significant role, and chronic pain is more prevalent in women than in men. To investigate sex differences in chronic pain, we carried out a sex-stratified genome-wide association study of Multisite Chronic Pain (MCP), a derived chronic pain phenotype, in UK Biobank on 178,556 men and 209,093 women, as well as investigating sex-specific genetic correlations with a range of psychiatric, autoimmune and anthropometric phenotypes and the relationship between sex-specific polygenic risk scores for MCP and chronic widespread pain. We also assessed whether MCP-associated genes showed expression pattern enrichment across tissues. A total of 123 SNPs at five independent loci were significantly associated with MCP in men. In women, a total of 286 genome-wide significant SNPs at ten independent loci were discovered. Meta-analysis of sex-stratified GWAS outputs revealed a further 87 independent associated SNPs. Gene-level analyses revealed sex-specific MCP associations, with 31 genes significantly associated in females, 37 genes associated in males, and a single gene, DCC, associated in both sexes. We found evidence for sex-specific pleiotropy and risk for MCP was found to be associated with chronic widespread pain in a sex-differential manner. Male and female MCP were highly genetically correlated, but at an rg of significantly less than 1 (0.92). All 37 male MCP-associated genes and all but one of 31 female MCP-associated genes were found to be expressed in the dorsal root ganglion, and there was a degree of enrichment for expression in sex-specific tissues. Overall, the findings indicate that sex differences in chronic pain exist at the SNP, gene and transcript abundance level, and highlight possible sex-specific pleiotropy for MCP. Results support the proposition of a strong central nervous-system component to chronic pain in both sexes, additionally highlighting a potential role for the DRG and nociception.

Genome-wide association study of pediatric obsessive-compulsive traits: shared genetic risk between traits and disorder

Using a novel trait-based measure, we examined genetic variants associated with obsessive-compulsive (OC) traits and tested whether OC traits and obsessive-compulsive disorder (OCD) shared genetic risk. We conducted a genome-wide association analysis (GWAS) of OC traits using the Toronto Obsessive-Compulsive Scale (TOCS) in 5018 unrelated Caucasian children and adolescents from the community (Spit for Science sample). We tested the hypothesis that genetic variants associated with OC traits from the community would be associated with clinical OCD using a meta-analysis of all currently available OCD cases. Shared genetic risk was examined between OC traits and OCD in the respective samples using polygenic risk score and genetic correlation analyses. A locus tagged by rs7856850 in an intron of PTPRD (protein tyrosine phosphatase δ) was significantly associated with OC traits at the genome-wide significance level (p = 2.48 × 10-8). rs7856850 was also associated with OCD in a meta-analysis of OCD case/control genome-wide datasets (p = 0.0069). The direction of effect was the same as in the community sample. Polygenic risk scores from OC traits were significantly associated with OCD in case/control datasets and vice versa (p's < 0.01). OC traits were highly, but not significantly, genetically correlated with OCD (rg = 0.71, p = 0.062). We report the first validated genome-wide significant variant for OC traits in PTPRD, downstream of the most significant locus in a previous OCD GWAS. OC traits measured in the community sample shared genetic risk with OCD case/control status. Our results demonstrate the feasibility and power of using trait-based approaches in community samples for genetic discovery.

Exploring the Relationship Between Psychiatric Traits and the Risk of Mouth Ulcers Using Bi-Directional Mendelian Randomization

Background

Although the association between mouth ulcers and psychiatric traits has been reported by observational studies, their causal relationship remains unclear. Mendelian randomization (MR), powered by large-scale genome-wide association studies (GWAS), provides an opportunity to clarify the causality between mouth ulcers and psychiatric traits.

Methods

We collected summary statistics of mouth ulcers (sample size n = 461,106) and 10 psychiatric traits from the largest publicly available GWAS on Europeans, including anxiety disorder (n = 83,566), attention deficit/hyperactivity disorder (n = 53,293), autism spectrum disorder (n = 46,350), bipolar disorder (n = 51,710), insomnia (n = 1,331,010), major depressive disorder (n = 480,359), mood instability (n = 363,705), neuroticism (n = 168,105), schizophrenia (n = 105,318), and subjective wellbeing (n = 388,538). We applied three two-sample bi-directional MR analysis methods, namely the Inverse Variance Weighted (IVW) method, the MR pleiotropy residual sum and outlier (MR-PRESSO) method, and the weighted median method, to assess the causal relationship between each psychiatric trait and mouth ulcers.

Results

We found significant effects of autism spectrum disorder, insomnia, major depressive disorder, and subjective wellbeing on mouth ulcers, with the corresponding odds ratio (OR) from the IVW method being 1.160 [95% confidence interval (CI): 1.066–1.261, P = 5.39 × 10^–4], 1.092 (1.062–1.122, P = 3.37 × 10^–10), 1.234 (1.134–1.342, P = 1.03 × 10^–6), and 0.703 (0.571–0.865, P = 8.97 × 10^–4), respectively. We also observed suggestive evidence for mood instability to cause mouth ulcers [IVW, OR = 1.662 (1.059–2.609), P = 0.027]. These results were robust to weak instrument bias and heterogeneity. We found no evidence on causal effects between other psychiatric traits and mouth ulcers, in either direction.

Conclusion

Our findings suggest a protective effect of subjective wellbeing and risk effects of autism spectrum disorder, insomnia, major depressive disorder, and mood instability on mouth ulcers. These results clarify the causal relationship between psychiatric traits and the development of mouth ulcers.

Big Data and Atrial Fibrillation: Current Understanding and New Opportunities

Atrial fibrillation (AF) is the most common arrhythmia with diverse etiology that remarkably relates to high morbidity and mortality. With the advancements in intensive clinical and basic research, the understanding of electrophysiological and pathophysiological mechanism, as well as treatment of AF have made huge progress. However, many unresolved issues remain, including the core mechanisms and key intervention targets. Big data approach has produced new insights into the improvement of the situation. A large amount of data have been accumulated in the field of AF research, thus using the big data to achieve prevention and precise treatment of AF may be the direction of future development. In this review, we will discuss the current understanding of big data and explore the potential applications of big data in AF research, including predictive models of disease processes, disease heterogeneity, drug safety and development, precision medicine, and the potential source for big data acquisition. Grapical abstract.

Clinical Correlates of False Positive Assignment in Bipolar Screening Measures Across Psychiatric Diagnoses among Patients without Bipolar Disorder

OBJECTIVE

In this study, we aimed to determine clinical correlates of false positive assignment (FPA) on commonly used bipolar screening questionnaires.

METHODS

A retrospective chart review was conducted to a total of 3885 psychiatric outpatients. After excluding patients who have bipolar spectrum illnesses, patients who were assigned as having hypomania on the mood disorder questionnaire (MDQ) or the hypomania checklist-32 (HCL-32) were identified as patients who had FPA. Psychiatric diagnoses and severity of emotional symptoms were compared between patients with and without FPA.

RESULTS

Patients with FPA on the MDQ showed significant associations with presence of major depressive disorder, generalized anxiety disorder, and alcohol-use disorder, while patients with FPA on the HCL-32 showed associations with presence of panic disorder and agoraphobia. FPA on the MDQ was also associated with greater emotional symptoms and lifetime history of suicide attempts. Logistic regression analysis showed that male sex, younger age, presence of alcohol-use disorder, and severity of depression and obsessive-compulsive symptoms were significantly associated with FPA on the MDQ.

CONCLUSION

The FPA for the MDQ was associated with clinical factors linked to trait impulsivity, and the FPA for both the MDQ and the HCL-32 could be related to increased anxiety.

Mitochondrial gene signature in the prefrontal cortex for differential susceptibility to chronic stress

Mitochondrial dysfunction was highlighted as a crucial vulnerability factor for the development of depression. However, systemic studies assessing stress-induced changes in mitochondria-associated genes in brain regions relevant to depression symptomatology remain scarce. Here, we performed a genome-wide transcriptomic study to examine mitochondrial gene expression in the prefrontal cortex (PFC) and nucleus accumbens (NAc) of mice exposed to multimodal chronic restraint stress. We identified mitochondria-associated gene pathways as most prominently affected in the PFC and with lesser significance in the NAc. A more detailed mitochondrial gene expression analysis revealed that in particular mitochondrial DNA-encoded subunits of the oxidative phosphorylation complexes were altered in the PFC. The comparison of our data with a reanalyzed transcriptome data set of chronic variable stress mice and major depression disorder subjects showed that the changes in mitochondrial DNA-encoded genes are a feature generalizing to other chronic stress-protocols as well and might have translational relevance. Finally, we provide evidence for changes in mitochondrial outputs in the PFC following chronic stress that are indicative of mitochondrial dysfunction. Collectively, our work reinforces the idea that changes in mitochondrial gene expression are key players in the prefrontal adaptations observed in individuals with high behavioral susceptibility and resilience to chronic stress.

Whole-Genome Sequencing of Inbred Mouse Strains Selected for High and Low Open-Field Activity

We conducted whole-genome sequencing of four inbred mouse strains initially selected for high (H1, H2) or low (L1, L2) open-field activity (OFA), and then examined strain distribution patterns for all DNA variants that differed between their BALB/cJ and C57BL/6J parental strains. Next, we assessed genome-wide sharing (3,678,826 variants) both between and within the High and Low Activity strains. Results suggested that about 10% of these DNA variants may be associated with OFA, and clearly demonstrated its polygenic nature. Finally, we conducted bioinformatic analyses of functional genomics data from mouse, rat, and human to refine previously identified quantitative trait loci (QTL) for anxiety-related measures. This combination of sequence analysis and genomic-data integration facilitated refinement of previously intractable QTL findings, and identified possible genes for functional follow-up studies.

From Schizophrenia Genetics to Disease Biology: Harnessing New Concepts and Technologies

Schizophrenia (SZ) is a severe mental disorder afflicting around 1% of the population. It is highly heritable but with complex genetics. Recent research has unraveled a plethora of risk loci for SZ. Accordingly, our conceptual understanding of SZ genetics has been rapidly evolving, from oligogenic models towards polygenic or even omnigenic models. A pressing challenge to the field, however, is the translation of the many genetic findings of SZ into disease biology insights leading to more effective treatments. Bridging this gap requires the integration of genetic findings and functional genomics using appropriate cellular models. Harnessing new technologies, such as the development of human induced pluripotent stem cells (hiPSC) and the CRISPR/Cas-based genome/epigenome editing approach are expected to change our understanding of SZ disease biology to a fundamentally higher level. Here, we discuss some new developments.