Identifying genetic differences between bipolar disorder and major depression through multiple GWAS.

Background: Accurate diagnosis of bipolar disorder (BD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A key reason is that the first manic episode is often preceded by a depressive one, making it difficult to distinguish BD from unipolar major depressive disorder (MDD). Aims: Here, we use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores that may aid early differential diagnosis. Methods: Based on individual genotypes from case-control cohorts of BD and MDD shared through the Psychiatric Genomics Consortium, we compile case-case-control cohorts, applying a careful merging and quality control procedure. In a resulting cohort of 51,149 individuals (15,532 BD cases, 12,920 MDD cases and 22,697 controls), we perform a variety of GWAS and polygenic risk scores (PRS) analyses. Results: While our GWAS is not well-powered to identify genome-wide significant loci, we find significant SNP-heritability and demonstrate the ability of the resulting PRS to distinguish BD from MDD, including BD cases with depressive onset. We replicate our PRS findings, but not signals of individual loci in an independent Danish cohort (iPSYCH 2015 case-cohort study, N=25,966). We observe strong genetic correlation between our case-case GWAS and that of case-control BD. Conclusions: We find that MDD and BD, including BD with a depressive onset, are genetically distinct. Further, our findings support the hypothesis that Controls - MDD - BD primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BD and, importantly, BD with depressive onset from MDD.

Preparing for the Bursting of the Psychedelic Hype Bubble.

This Viewpoint presents impediments to the clinical application of psychedelics created by extreme shifts in public perception while advocating further study and encouraging the dispute of claims not supported by available evidence.

Deep learning predicts DNA methylation regulatory variants in the human brain and elucidates the genetics of psychiatric disorders.

There is growing evidence for the role of DNA methylation (DNAm) quantitative trait loci (mQTLs) in the genetics of complex traits, including psychiatric disorders. However, due to extensive linkage disequilibrium (LD) of the genome, it is challenging to identify causal genetic variations that drive DNAm levels by population-based genetic association studies. This limits the utility of mQTLs for fine-mapping risk loci underlying psychiatric disorders identified by genome-wide association studies (GWAS). Here we present INTERACT, a deep learning model that integrates convolutional neural networks with transformer, to predict effects of genetic variations on DNAm levels at CpG sites in the human brain. We show that INTERACT-derived DNAm regulatory variants are not confounded by LD, are concentrated in regulatory genomic regions in the human brain, and are convergent with mQTL evidence from genetic association analysis. We further demonstrate that predicted DNAm regulatory variants are enriched for heritability of brain-related traits and improve polygenic risk prediction for schizophrenia across diverse ancestry samples. Finally, we applied predicted DNAm regulatory variants for fine-mapping schizophrenia GWAS risk loci to identify potential novel risk genes. Our study shows the power of a deep learning approach to identify functional regulatory variants that may elucidate the genetic basis of complex traits.

Investigating the phenotypic and genetic associations between personality traits and suicidal behavior across major mental health diagnoses.

Personality traits influence risk for suicidal behavior. We examined phenotype- and genotype-level associations between the Big Five personality traits and suicidal ideation and attempt in major depressive, bipolar and schizoaffective disorder, and schizophrenia patients (N = 3012) using fixed- and random-effects inverse variance-weighted meta-analyses. Suicidal ideations were more likely to be reported by patients with higher neuroticism and lower extraversion phenotypic scores, but showed no significant association with polygenic load for these personality traits. Our findings provide new insights into the association between personality and suicidal behavior across mental illnesses and suggest that the genetic component of personality traits is unlikely to have strong causal effects on suicidal behavior.

The Role of Sex in Genetic Association Studies of Depression.

Depression is the most common mental illness in the U.S. affecting nearly 40 million adults age 18 years and older. Depression has both genetic and environmental influences. In addition, women are more likely to be affected by depression than men. However, the relationship between genes and depression is complex and may be influenced by sex. Understanding the genetic basis of sex-specific differences for depression has the potential to lead to new biological understanding of the etiology of depression in females compared to males and to promote the development of novel and more effective pharmacotherapies. This review examines the role of sex in genetic associations with depression for both genome-wide association and candidate gene studies. While the genetic association signals of depression differ by sex, the role of sex in the heritability of depression is complex and warrants further investigation.

Leadership Principles to Decrease Psychological Casualties in COVID-19 and Other Disasters of Uncertainty.

Coronavirus disease (COVID-19) is a "disaster of uncertainty" with ambiguity about its nature and trajectory. These features amplify its psychological toxicity and increase the number of psychological casualties it inflicts. Uncertainty was fueled by lack of knowledge about the lethality of a disaster, its duration, and ambiguity in messaging from leaders and health care authorities. Human resilience can have a buffering effect on the psychological impact. Experts have advocated "flattening the curve" to slow the spread of the infection. Our strategy for crisis leadership is focused on flattening the rise in psychological casualties by increasing resilience among health care workers. This paper describes an approach employed at Johns Hopkins to promote and enhance crisis leadership. The approach is based on 4 factors: vision for the future, decisiveness, effective communication, and following a moral compass. We make specific actionable recommendations for implementing these factors that are being disseminated to frontline leaders and managers. The COVID-19 pandemic is destined to have a strong psychological impact that extends far beyond the end of quarantine. Following these guidelines has the potential to build resilience and thus reduce the number of psychological casualties and speed the return to normal - or at least the new normal in the post-COVID world.

Fluoxetine and environmental enrichment similarly reverse chronic social stress-related depression- and anxiety-like behavior, but have differential effects on amygdala gene expression.

The adverse effects of stress on brain and behavior have long been known and well-studied, with abundant evidence linking stress to, among other things, mood and anxiety disorders. Likewise, many have investigated potential treatments for stress-related mood and anxiety phenotypes and demonstrated good response to standard antidepressant medications like selective serotonin reuptake inhibitors (SSRIs), as well as environmental manipulations like exercise or enrichment. However, the extent to which stress and various treatments act on overlapping pathways in the brain is less well understood. Here, we used a widely studied social defeat stress paradigm to induce a robust depression- and anxiety-like phenotype and chronic corticosterone elevation that persisted for at least 4 weeks in wild type male mice. When mice were treated with either the SSRI fluoxetine or an enriched environment, both led to similar behavioral recovery from social defeat. We then focused on the amygdala and assessed the effects of social defeat, fluoxetine, and enrichment on 168 genes broadly related to synaptic plasticity or oxidative stress. We found 24 differentially expressed genes in response to social defeat stress. Interestingly, fluoxetine led to broad normalization of the stress-induced expression pattern while enrichment led to expression changes in a separate set of genes. Together, this study provides additional insight into the chronic effects of social defeat stress on behavior and gene expression in the amygdala. The findings also suggest that, for a subset of genes assessed, fluoxetine and environmental enrichment have strikingly divergent effects on expression in the amygdala, despite leading to similar behavioral outcomes.

Transcriptome-based polygenic score links depression-related corticolimbic gene expression changes to sex-specific brain morphology and depression risk.

Studies in post-mortem human brain tissue have associated major depressive disorder (MDD) with cortical transcriptomic changes, whose potential in vivo impact remains unexplored. To address this translational gap, we recently developed a transcriptome-based polygenic risk score (T-PRS) based on common functional variants capturing 'depression-like' shifts in cortical gene expression. Here, we used a non-clinical sample of young adults (n = 482, Duke Neurogenetics Study: 53% women; aged 19.8 ± 1.2 years) to map T-PRS onto brain morphology measures, including Freesurfer-derived subcortical volume, cortical thickness, surface area, and local gyrification index, as well as broad MDD risk, indexed by self-reported family history of depression. We conducted side-by-side comparisons with a PRS independently derived from a Psychiatric Genomics Consortium (PGC) MDD GWAS (PGC-PRS), and sought to link T-PRS with diagnosis and symptom severity directly in PGC-MDD participants (n = 29,340, 59% women; 12,923 MDD cases, 16,417 controls). T-PRS was associated with smaller amygdala volume in women (t = -3.478, p = 0.001) and lower prefrontal gyrification across sexes. In men, T-PRS was associated with hypergyrification in temporal and occipital regions. Prefrontal hypogyrification mediated a male-specific indirect link between T-PRS and familial depression (b = 0.005, p = 0.029). PGC-PRS was similarly associated with lower amygdala volume and cortical gyrification; however, both effects were male-specific and hypogyrification emerged in distinct parietal and temporo-occipital regions, unassociated with familial depression. In PGC-MDD, T-PRS did not predict diagnosis (OR = 1.007, 95% CI = [0.997-1.018]) but correlated with symptom severity in men (rho = 0.175, p = 7.957 × 10-4) in one cohort (N = 762, 48% men). Depression-like shifts in cortical gene expression have sex-specific effects on brain morphology and may contribute to broad depression vulnerability in men.

Phases of psychological response in COVID-19: A preliminary heuristic.

OBJECTIVE: To explore the putative phases of the psychological response to disaster: preimpact, impact, heroic, honeymoon, disillusionment, and recovery, and make recommendations for corresponding interventions. CONCLUSIONS: Disasters such as the COVID-19 pandemic are often characterized by chaos and uncertainty. As a result, public health disaster planning and response represent formidable challenges. Although disasters can result from a wide array of hazards, regardless of the agent at work, they may follow a rather predictable trajectory of psychological phases. A heuristic of those phases can provide an opportunity for a more organized disaster mental health response and more efficient utilization of scarce resources.

The association between genetically determined ABO blood types and major depressive disorder.

ABO blood types and their corresponding antigens have long been assumed to be related to different human diseases. So far, smaller studies on the relationship between mental disorders and blood types yielded contradicting results. In this study we analyzed the association between ABO blood types and lifetime major depressive disorder (MDD). We performed a pooled analysis with data from 26 cohorts that are part of the MDD working group of the Psychiatric Genomics Consortium (PGC). The dataset included 37,208 individuals of largely European ancestry of which 41.6% were diagnosed with lifetime MDD. ABO blood types were identified using three single nucleotide polymorphisms in the ABO gene: rs505922, rs8176746 and rs8176747. Regression analyses were performed to assess associations between the individual ABO blood types and MDD diagnosis as well as putative interaction effects with sex. The models were adjusted for sex, cohort and the first ten genetic principal components. The percentage of blood type A was slightly lower in cases than controls while blood type O was more prominent in cases. However, these differences were not statistically significant. Our analyses found no evidence of an association between ABO blood types and major depressive disorder.

A Machine Learning Approach to Predicting Autism Risk Genes: Validation of Known Genes and Discovery of New Candidates.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a strong genetic basis. The role of de novo mutations in ASD has been well established, but the set of genes implicated to date is still far from complete. The current study employs a machine learning-based approach to predict ASD risk genes using features from spatiotemporal gene expression patterns in human brain, gene-level constraint metrics, and other gene variation features. The genes identified through our prediction model were enriched for independent sets of ASD risk genes, and tended to be down-expressed in ASD brains, especially in frontal and parietal cortex. The highest-ranked genes not only included those with strong prior evidence for involvement in ASD (for example, NBEA, HERC1, and TCF20), but also indicated potentially novel candidates, such as, MYCBP2 and CAND1, which are involved in protein ubiquitination. We also showed that our method outperformed state-of-the-art scoring systems for ranking curated ASD candidate genes. Gene ontology enrichment analysis of our predicted risk genes revealed biological processes clearly relevant to ASD, including neuronal signaling, neurogenesis, and chromatin remodeling, but also highlighted other potential mechanisms that might underlie ASD, such as regulation of RNA alternative splicing and ubiquitination pathway related to protein degradation. Our study demonstrates that human brain spatiotemporal gene expression patterns and gene-level constraint metrics can help predict ASD risk genes. Our gene ranking system provides a useful resource for prioritizing ASD candidate genes.

Design and Implementation of a Regional Inpatient Psychiatry Unit for Patients who are Positive for Asymptomatic SARS-CoV-2.

BACKGROUND: Patients with psychiatric illnesses are particularly vulnerable to highly contagious, droplet-spread organisms such as SARS-CoV-2. Patients with mental illnesses may not be able to consistently follow up behavioral prescriptions to avoid contagion, and they are frequently found in settings with close contact and inadequate infection control, such as group homes, homeless shelters, residential rehabilitation centers, and correctional facilities. Furthermore, inpatient psychiatry settings are generally designed as communal spaces, with heavy emphasis on group and milieu therapies. As such, inpatient psychiatry services are vulnerable to rampant spread of contagion. OBJECTIVE: With this in mind, the authors outline the decision process and ultimate design and implementation of a regional inpatient psychiatry unit for patients infected with asymptomatic SARS-CoV-2 and share key points for consideration in implementing future units elsewhere. CONCLUSION: A major takeaway point of the analysis is the particular expertise of trained experts in psychosomatic medicine for treating patients infected with SARS-CoV-2.

Minimal phenotyping yields genome-wide association signals of low specificity for major depression.

Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD.

Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression.

BACKGROUND: The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression. METHODS: We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9 × 10-6) and a candidate threshold (1.6 × 10-4). RESULTS: No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio = 0.98, 95% confidence interval = 0.97-0.99). CONCLUSIONS: We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.

Male-specific association of the 2p25 region with suicide attempt in bipolar disorder.

We previously conducted a genome-wide association study (GWAS) of attempted suicide within bipolar disorder, which implicated common variation in the 2p25 region primarily in males. The top association signal from our GWAS occurred in an intergenic region of 2p25 (p = 5.07 × 10-8) and was supported by two independent studies. In the current study, to better characterize the association of the 2p25 region with attempted suicide, we sequenced the entire 350kb 2p25 region in 476 bipolar suicide attempters and 473 bipolar non-attempters using targeted next-generation sequencing. This fine-mapping project identified 4,681 variants in the 2p25 region. We performed both gene-level and individual-variant tests on our sequencing results and identified 375 variants which were nominally significant (p < 0.05) and three common variants that were significantly associated with attempted suicide in males (corrected p = 0.035, odds ratio (OR) = 2.13). These three variants are in strong linkage disequilibrium with the top variant from our GWAS. Our top five variants are also predicted expression quantitative trait loci (eQTL) for three genes in the 2p25 region based on publicly available brain expression databases. Our sequencing and eQTL data implicate these three genes - SH3YL1, ACP1, and FAM150B - and three additional pathways - androgen receptor, Wnt signaling, and glutamatergic/GABAergic signaling - in the association of the 2p25 region with suicide. The current study provides additional support for an association of the 2p25 region with attempted suicide in males and identifies several candidate genes and pathways that warrant further investigation to understand their role in suicidal behavior.

Targeted sequencing of the LRRTM gene family in suicide attempters with bipolar disorder.

Glutamatergic signaling is the primary excitatory neurotransmission pathway in the brain, and its relationship to neuropsychiatric disorders is of considerable interest. Our previous attempted suicide genome-wide association study, and numerous studies investigating gene expression, genetic variation, and DNA methylation have implicated aberrant glutamatergic signaling in suicide risk. The glutamatergic pathway gene LRRTM4 was an associated gene identified in our attempted suicide genome-wide association study, with association support seen primarily in females. Recent evidence has also shown that glutamatergic signaling is partly regulated by sex-related hormones. The LRRTM gene family encodes neuronal leucine-rich transmembrane proteins that localize to and promote glutamatergic synapse development. In this study, we sequenced the coding and regulatory regions of all four LRRTM gene members plus a large intronic region of LRRTM4 in 476 bipolar disorder suicide attempters and 473 bipolar disorder nonattempters. We identified two male-specific variants, one female- and five male-specific haplotypes significantly associated with attempted suicide in LRRTM4. Furthermore, variants within significant haplotypes may be brain expression quantitative trait loci for LRRTM4 and some of these variants overlap with predicted hormone response elements. Overall, these results provide supporting evidence for a sex-specific association of genetic variation in LRRTM4 with attempted suicide.

Affected Sib-Pair Analyses Identify Signaling Networks Associated With Social Behavioral Deficits in Autism.

Autism spectrum disorders (ASDs) are characterized by deficits in three core behavioral domains: reciprocal social interactions, communication, and restricted interests and/or repetitive behaviors. Several hundreds of risk genes for autism have been identified, however, it remains a challenge to associate these genes with specific core behavioral deficits. In multiplex autism families, affected sibs often show significant differences in severity of individual core phenotypes. We hypothesize that a higher mutation burden contributes to a larger difference in the severity of specific core phenotypes between affected sibs. We tested this hypothesis on social behavioral deficits in autism. We sequenced synaptome genes (n = 1,886) in affected male sib-pairs (n = 274) in families from the Autism Genetics Research Exchange (AGRE) and identified rare (MAF ≤ 1%) and predicted functional variants. We selected affected sib-pairs with a large (≥10; n = 92 pairs) or a small (≤4; n = 108 pairs) difference in total cumulative Autism Diagnostic Interview-Revised (ADI-R) social scores (SOCT_CS). We compared burdens of unshared variants present only in sibs with severe social deficits and found a higher burden in SOCT_CS≥10 compared to SOCT_CS ≤ 4 (SOCT_CS≥10: 705.1 ± 16.2; SOCT_CS ≤ 4, 668.3 ± 9.0; p = 0.025). Unshared SOCT_CS≥10 genes only in sibs with severe social deficits are significantly enriched in the SFARI gene set. Network analyses of these genes using InWeb_IM, molecular signatures database (MSigDB), and GeNetMeta identified enrichment for phosphoinositide 3-kinase (PI3K)-AKT-mammalian target of rapamycin (mTOR) (Enrichment Score [eScore] p value = 3.36E-07; n = 8 genes) and Nerve growth factor (NGF) (eScore p value = 8.94E-07; n = 9 genes) networks. These studies support a key role for these signaling networks in social behavioral deficits and present a novel approach to associate risk genes and signaling networks with core behavioral domains in autism.

Differentially methylated regions in bipolar disorder and suicide.

The addition of a methyl group to, typically, a cytosine-guanine dinucleotide (CpG) creates distinct DNA methylation patterns across the genome that can regulate gene expression. Aberrant DNA methylation of CpG sites has been associated with many psychiatric disorders including bipolar disorder (BD) and suicide. Using the SureSelectXT system, Methyl-Seq, we investigated the DNA methylation status of CpG sites throughout the genome in 50 BD individuals (23 subjects who died by suicide and 27 subjects who died from other causes) and 31 nonpsychiatric controls. We identified differentially methylated regions (DMRs) from three analyses: (a) BD subjects compared to nonpsychiatric controls (BD-NC), (b) BD subjects who died by suicide compared to nonpsychiatric controls (BDS-NC), and (c) BDS subjects compared to BD subjects who died from other causes (BDS-BDNS). One DMR from the BDS-NC analysis, located in ARHGEF38, was significantly hypomethylated (23.4%) in BDS subjects. This finding remained significant after multiple testing (PBootstrapped = 9.0 × 10-3 ), was validated using pyrosequencing, and was more significant in males. A secondary analysis utilized Ingenuity Pathway Analysis to identify enrichment in nominally significant DMRs. This identified an association with several pathways including axonal guidance signaling, calcium signaling, ß-adrenergic signaling, and opioid signaling. Our comprehensive study provides further support that DNA methylation alterations influence the risk for BD and suicide. However, further investigation is required to confirm these associations and identify their functional consequences.

Genome-wide Burden of Rare Short Deletions Is Enriched in Major Depressive Disorder in Four Cohorts.

BACKGROUND: Major depressive disorder (MDD) is moderately heritable, with a high prevalence and a presumed high heterogeneity. Copy number variants (CNVs) could contribute to the heritable component of risk, but the two previous genome-wide association studies of rare CNVs did not report significant findings. METHODS: In this meta-analysis of four cohorts (5780 patients and 6626 control subjects), we analyzed the association of MDD to 1) genome-wide burden of rare deletions and duplications, partitioned by length (<100 kb or >100 kb) and other characteristics, and 2) individual rare exonic CNVs and CNV regions. RESULTS: Patients with MDD carried significantly more short deletions than control subjects (p = .0059) but not long deletions or short or long duplications. The confidence interval for long deletions overlapped with that for short deletions, but long deletions were 70% less frequent genome-wide, reducing the power to detect increased burden. The increased burden of short deletions was primarily in intergenic regions. Short deletions in cases were also modestly enriched for high-confidence enhancer regions. No individual CNV achieved thresholds for suggestive or significant association after genome-wide correction. p values < .01 were observed for 15q11.2 duplications (TUBGCP5, CYFIP1, NIPA1, and NIPA2), deletions in or near PRKN or MSR1, and exonic duplications of ATG5. CONCLUSIONS: The increased burden of short deletions in patients with MDD suggests that rare CNVs increase the risk of MDD by disrupting regulatory regions. Results for longer deletions were less clear, but no large effects were observed for long multigenic CNVs (as seen in schizophrenia and autism). Further studies with larger sample sizes are warranted.