Expressive

rs10261857 - LINC01392 - POLR2DP2

Magnitude 2.2 · 6 studies on file

Reported associations

  • Genome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways. - Nature genetics (2022) · Watanabe K, Jansen PR, Savage JE, Nandakumar P, Wang X, Hinds DA, Gelernter J, Levey DF, Polimanti R, Stein MB, Van Someren EJW, Smit AB, Posthuma D · PubMed 35835914

    Insomnia is a heritable, highly prevalent sleep disorder for which no sufficient treatment currently exists. Previous genome-wide association studies with up to 1.3 million subjects identified over 200 associated loci. This extreme polygenicity suggested that many more loci remain to be discovered. The current study almost doubled the sample size to 593,724 cases and 1,771,286 controls, thereby increasing statistical power, and identified 554 risk loci (including 364 novel loci). To capitalize on this large number of loci, we propose a novel strategy to prioritize genes using external biological resources and functional interactions between genes across risk loci. Of all 3,898 genes naively implicated from the risk loci, we prioritize 289 and find brain-tissue expression spec

  • The Australian Genetics of Depression Study: New Risk Loci and Dissecting Heterogeneity Between Subtypes. - Biological psychiatry (2022) · Mitchell BL, Campos AI, Whiteman DC, Olsen CM, Gordon SD, Walker AJ, Dean OM, Berk M, Hickie IB, Medland SE, Wray NR, Martin NG, Byrne EM · PubMed 34924174

    Major depressive disorder (MDD) is a common and highly heterogeneous psychiatric disorder, but little is known about the genetic characterization of this heterogeneity. Understanding the genetic etiology of MDD can be challenging because large sample sizes are needed for gene discovery-often achieved with a trade-off in the depth of phenotyping. The Australian Genetics of Depression Study is the largest stand-alone depression cohort with both genetic data and in-depth phenotyping and comprises a total of 15,792 participants of European ancestry, 92% of whom met diagnostic criteria for MDD. We leveraged the unique nature of this cohort to conduct a meta-analysis with the largest publicly available depression genome-wide association study to date and subsequently used polygenic scores to inv

  • Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference - Unknown journal (n.d.) · Unknown authors · PubMed 38177345

    ABSTRACT: 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 a

  • Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior - Unknown journal (n.d.) · Unknown authors · PubMed 31467194

    ABSTRACT: INTRODUCTION: Across human societies and in both sexes, some 2 to 10% of individuals report engaging in sex with same-sex partners, either exclusively or in addition to sex with opposite-sex partners. Twin and family studies have shown that same-sex sexual behavior is partly genetically influenced, but previous searches for the specific genes involved have been underpowered to detect effect sizes realistic for complex traits. RATIONALE: For the first time, new large-scale datasets afford sufficient statistical power to identify genetic variants associated with same-sex sexual behavior (ever versus never had a same-sex partner), estimate the proportion of variation in the trait accounted for by all variants in aggregate, estimate the genetic correlation of same-sex sexual behavior

  • Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use - Unknown journal (n.d.) · Unknown authors · PubMed 30643251

    ABSTRACT: Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders. They are heritable and etiologically related behaviors that have been resistant to gene discovery efforts. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco an

  • Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation - Unknown journal (n.d.) · Unknown authors · PubMed 38965376

    ABSTRACT: Data within biobanks capture broad yet detailed indices of human variation, but biobank-wide insights can be difficult to extract due to complexity and scale. Here, using large-scale factor analysis, we distill hundreds of variables (diagnoses, assessments and survey items) into 35 latent constructs, using data from unrelated individuals with predominantly estimated European genetic ancestry in UK Biobank. These factors recapitulate known disease classifications, disentangle elements of socioeconomic status, highlight the relevance of psychiatric constructs to health and improve measurement of pro-health behaviours. We go on to demonstrate the power of this approach to clarify genetic signal, enhance discovery and identify associations between underlying phenotypic structure and

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