Explore the vast range of titles available.

To identify bipolar disorder (BD) genetic susceptibility factors, we conducted two genome-wide association (GWA) studies: one involving a sample of individuals of European ancestry (EA; n =1001 cases; n =1033 controls), and one involving a sample of individuals of African ancestry (AA; n =345 cases; n =670 controls). For the EA sample, single-nucleotide polymorphisms (SNPs) with the strongest statistical evidence for association included rs5907577 in an intergenic region at Xq27.1 ( P =1.6 × 10 −6 ) and rs10193871 in NAP5 at 2q21.2 ( P =9.8 × 10 −6 ). For the AA sample, SNPs with the strongest statistical evidence for association included rs2111504 in DPY19L3 at 19q13.11 ( P =1.5 × 10 −6 ) and rs2769605 in NTRK2 at 9q21.33 ( P =4.5 × 10 −5 ). We also investigated whether we could provide support for three regions previously associated with BD, and we showed that the ANK3 region replicates in our sample, along with some support for C15Orf53 ; other evidence implicates BD candidate genes such as SLITRK2 . We also tested the hypothesis that BD susceptibility variants exhibit genetic background-dependent effects. SNPs with the strongest statistical evidence for genetic background effects included rs11208285 in ROR1 at 1p31.3 ( P =1.4 × 10 −6 ), rs4657247 in RGS5 at 1q23.3 ( P =4.1 × 10 −6 ), and rs7078071 in BTBD16 at 10q26.13 ( P =4.5 × 10 −6 ). This study is the first to conduct GWA of BD in individuals of AA and suggests that genetic variations that contribute to BD may vary as a function of ancestry.

Major depressive disorder (MDD) is among the leading causes of worldwide disability. Despite its significant heritability, large-scale genome-wide association studies (GWASs) of MDD have yet to identify robustly associated common variants. Although increased sample sizes are being amassed for the next wave of GWAS, few studies have as yet focused on rare genetic variants in the study of MDD. We sequenced the exons of 1742 synaptic genes previously identified by proteomic experiments. PLINK/SEQ was used to perform single variant, gene burden and gene set analyses. The GeneMANIA interaction database was used to identify protein–protein interaction-based networks. Cases were selected from a familial collection of early-onset, recurrent depression and were compared with screened controls. After extensive quality control, we analyzed 259 cases with familial, early-onset MDD and 334 controls. The distribution of association test statistics for the single variant and gene burden analyses were consistent with the null hypothesis. However, analysis of prioritized gene sets showed a significant association with damaging singleton variants in a Cav2-adaptor gene set (odds ratio=2.6; P =0.0008) that survived correction for all gene sets and annotation categories tested (empirical P =0.049). In addition, we also found statistically significant evidence for an enrichment of rare variants in a protein-based network of 14 genes involved in actin polymerization and dendritic spine formation (nominal P =0.0031). In conclusion, we have identified a statistically significant gene set and gene network of rare variants that are over-represented in MDD, providing initial evidence that calcium signaling and dendrite regulation may be involved in the etiology of depression.

We conducted a systematic study of top susceptibility variants from a genome-wide association (GWA) study of bipolar disorder to gain insight into the functional consequences of genetic variation influencing disease risk. We report here the results of experiments to explore the effects of these susceptibility variants on DNA methylation and mRNA expression in human cerebellum samples. Among the top susceptibility variants, we identified an enrichment of cis regulatory loci on mRNA expression (eQTLs), and a significant excess of quantitative trait loci for DNA CpG methylation, hereafter referred to as methylation quantitative trait loci (mQTLs). Bipolar disorder susceptibility variants that cis regulate both cerebellar expression and methylation of the same gene are a very small proportion of bipolar disorder susceptibility variants. This finding suggests that mQTLs and eQTLs provide orthogonal ways of functionally annotating genetic variation within the context of studies of pathophysiology in brain. No lymphocyte mQTL enrichment was found, suggesting that mQTL enrichment was specific to the cerebellum, in contrast to eQTLs. Separately, we found that using mQTL information to restrict the number of single-nucleotide polymorphisms studied enhances our ability to detect a significant association. With this restriction a priori informed by the observed functional enrichment, we identified a significant association ( rs12618769 , P bonferroni <0.05) from two other GWA studies (TGen+GAIN; 2191 cases and 1434 controls) of bipolar disorder, which we replicated in an independent GWA study (WTCCC). Collectively, our findings highlight the importance of integrating functional annotation of genetic variants for gene expression and DNA methylation to advance the biological understanding of bipolar disorder.

Previous studies suggest that the relationship between genetic risk and depression may be moderated by stressful life events (SLEs). The goal of this study was to assess whether SLEs moderate the association between polygenic risk of major depressive disorder (MDD) and depressive symptoms in older adults. We used logistic and negative binomial regressions to assess the associations between polygenic risk, SLEs and depressive symptoms in a sample of 8761 participants from the Health and Retirement Study. Polygenic scores were derived from the Psychiatric Genomics Consortium genome-wide association study of MDD. SLEs were operationalized as a dichotomous variable indicating whether participants had experienced at least one stressful event during the previous 2 years. Depressive symptoms were measured using an eight-item Center for Epidemiologic Studies Depression Scale subscale and operationalized as both a dichotomous and a count variable. The odds of reporting four or more depressive symptoms were over twice as high among individuals who experienced at least one SLE (odds ratio 2.19, 95% confidence interval 1.86-2.58). Polygenic scores were significantly associated with depressive symptoms (β = 0.21, p ⩽ 0.0001), although the variance explained was modest (pseudo r 2 = 0.0095). None of the interaction terms for polygenic scores and SLEs was statistically significant. Polygenic risk and SLEs are robust, independent predictors of depressive symptoms in older adults. Consistent with an additive model, we found no evidence that SLEs moderated the association between common variant polygenic risk and depressive symptoms.

The FKBP5 gene product forms part of a complex with the glucocorticoid receptor and can modulate cortisol-binding affinity. Variations in the gene have been associated with increased recurrence of depression and with rapid response to antidepressant treatment. We sought to determine whether common FKBP5 variants confer risk for bipolar disorder. We genotyped seven tag single-nucleotide polymorphisms (SNPs) in FKBP5, plus two SNPs previously associated with illness, in 317 families with 554 bipolar offspring, derived primarily from two studies. Single marker and haplotypic analyses were carried out with FBAT and EATDT employing the standard bipolar phenotype. Association analyses were also conducted using 11 disease-related variables as covariates. Under an additive genetic model, rs4713902 showed significant overtransmission of the major allele ( P =0.0001), which was consistent across the two sample sets ( P =0.004 and 0.006). rs7757037 showed evidence of association that was strongest under the dominant model ( P =0.001). This result was consistent across the two datasets ( P =0.017 and 0.019). The dominant model yielded modest evidence for association ( P <0.05) for three additional markers. Covariate-based analyses suggested that genetic variation within FKBP5 may influence attempted suicide and number of depressive episodes in bipolar subjects. Our results are consistent with the well-established relationship between the hypothalamic–pituitary–adrenal (HPA) axis, which mediates the stress response through regulation of cortisol, and mood disorders. Ongoing whole-genome association studies in bipolar disorder and major depression should further clarify the role of FKBP5 and other HPA genes in these illnesses.

Major Depressive Disorder (MDD) is a common, complex disorder that is a leading cause of disability worldwide and a significant risk factor for suicide. In this study, we have performed the largest molecular analysis of MDD in postmortem human brains (846 samples across 458 individuals) in the subgenual Anterior Cingulate Cortex (sACC) and the Amygdala, two regions central to mood regulation and the pathophysiology of MDD. We found extensive expression differences, particularly at the level of specific transcripts, with prominent enrichment for genes associated with the vesicular functioning, the postsynaptic density, GTPase signaling, and gene splicing. We find associated transcriptional features in 107 of 243 genome-wide significant loci for MDD and, through integrative analyses, highlight convergence of genetic risk, gene expression, and network-based analyses on dysregulated glutamatergic signaling and synaptic vesicular functioning. Together, these results provide an initial mechanistic understanding of MDD and highlight potential targets for novel drug discovery. Major Depressive Disorder (MDD) is a heritable psychiatric disorder whose biological basis remains poorly understood. This large-scale postmortem brain study identified extensive gene expression changes associated with genetic risk, highlighting disrupted glutamatergic signaling and synaptic vesicle function in MDD.

An overall burden of rare structural genomic variants has not been reported in bipolar disorder (BD), although there have been reports of cases with microduplication and microdeletion. Here, we present a genome-wide copy number variant (CNV) survey of 1001 cases and 1034 controls using the Affymetrix single nucleotide polymorphism (SNP) 6.0 SNP and CNV platform. Singleton deletions (deletions that appear only once in the dataset) more than 100 kb in length are present in 16.2% of BD cases in contrast to 12.3% of controls (permutation P =0.007). This effect was more pronounced for age at onset of mania ⩽18 years old. Our results strongly suggest that BD can result from the effects of multiple rare structural variants.

Distinguishing bipolar disorder (BP) from major depressive disorder (MDD) has important relevance for prognosis and treatment. Prior studies have identified clinical features that differ between these two diseases but have been limited by heterogeneity and lack of replication. We sought to identify depression-related features that distinguish BP from MDD in large samples with replication. Using a large, opportunistically ascertained collection of subjects with BP and MDD we selected 34 depression-related clinical features to test across the diagnostic categories in an initial discovery dataset consisting of 1228 subjects (386 BPI, 158 BPII and 684 MDD). Features significantly associated with BP were tested in an independent sample of 1000 BPI cases and 1000 MDD cases for classifying ability in receiver operating characteristic (ROC) analysis. Seven clinical features showed significant association with BPI compared with MDD: delusions, psychomotor retardation, incapacitation, greater number of mixed symptoms, greater number of episodes, shorter episode length, and a history of experiencing a high after depression treatment. ROC analyses of a model including these seven factors showed significant evidence for discrimination between BPI and MDD in an independent dataset (area under the curve = 0.83). Only two features (number of mixed symptoms, and feeling high after an antidepressant) showed an association with BPII versus MDD. Our study suggests that clinical features distinguishing depression in BPI versus MDD have important classification potential for clinical practice, and should also be incorporated as 'baseline' features in the evaluation of novel diagnostic biomarkers.

Long non-coding RNA Knowledgebase (lncRNAKB) is an integrated resource for exploring lncRNA biology in the context of tissue-specificity and disease association. A systematic integration of annotations from six independent databases resulted in 77,199 human lncRNA (224,286 transcripts). The user-friendly knowledgebase covers a comprehensive breadth and depth of lncRNA annotation. lncRNAKB is a compendium of expression patterns, derived from analysis of RNA-seq data in thousands of samples across 31 solid human normal tissues (GTEx). Thousands of co-expression modules identified via network analysis and pathway enrichment to delineate lncRNA function are also accessible. Millions of expression quantitative trait loci (cis-eQTL) computed using whole genome sequence genotype data (GTEx) can be downloaded at lncRNAKB that also includes tissue-specificity, phylogenetic conservation and coding potential scores. Tissue-specific lncRNA-trait associations encompassing 323 GWAS (UK Biobank) are also provided. LncRNAKB is accessible at http://www.lncrnakb.org/, and the data are freely available through Open Science Framework (10.17605/OSF.IO/RU4D2).Measurement(s)regulation of gene expression • sequence feature annotation • lnc_RNA • tissue-specific expression of lncRNA • Expression Quantitative Trait LocusTechnology Type(s)digital curation • computational modeling techniqueSample Characteristic - OrganismHomo sapiensMachine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12827597