Expressive

rs10789340 - LINC02796

Magnitude 2.0 · 8 studies on file

Reported associations

  • Shared genetics of asthma and mental health disorders: a large-scale genome-wide cross-trait analysis. - The European respiratory journal (2020) · Zhu Z, Zhu X, Liu CL, Shi H, Shen S, Yang Y, Hasegawa K, Camargo CA, Liang L · PubMed 31619474

    Epidemiological studies demonstrate an association between asthma and mental health disorders, although little is known about the shared genetics and causality of this association. Thus, we aimed to investigate shared genetics and the causal link between asthma and mental health disorders.We conducted a large-scale genome-wide cross-trait association study to investigate genetic overlap between asthma from the UK Biobank and eight mental health disorders from the Psychiatric Genomics Consortium: attention deficit hyperactivity disorder (ADHD), anxiety disorder (ANX), autism spectrum disorder, bipolar disorder, eating disorder, major depressive disorder (MDD), post-traumatic stress disorder and schizophrenia (sample size 9537-394 283).In the single-trait genome-wide association analysis,

  • Genome-wide analysis of insomnia in 1,331,010 individuals identifies new risk loci and functional pathways. - Nature genetics (2019) · Jansen PR, Watanabe K, Stringer S, Skene N, Bryois J, Hammerschlag AR, de Leeuw CA, Benjamins JS, Muñoz-Manchado AB, Nagel M, Savage JE, Tiemeier H, White T, Tung JY, Hinds DA, Vacic V, Wang X, Sullivan PF, van der Sluis S, Polderman TJC, Smit AB, Hjerling-Leffler J, Van Someren EJW, Posthuma D · PubMed 30804565

    Insomnia is the second most prevalent mental disorder, with no sufficient treatment available. Despite substantial heritability, insight into the associated genes and neurobiological pathways remains limited. Here, we use a large genetic association sample (n = 1,331,010) to detect novel loci and gain insight into the pathways, tissue and cell types involved in insomnia complaints. We identify 202 loci implicating 956 genes through positional, expression quantitative trait loci, and chromatin mapping. The meta-analysis explained 2.6% of the variance. We show gene set enrichments for the axonal part of neurons, cortical and subcortical tissues, and specific cell types, including striatal, hypothalamic, and claustrum neurons. We found considerable genetic correlations with psychiatric tr

  • The Genetic Architecture of Depression in Individuals of East Asian Ancestry - Unknown journal (n.d.) · Unknown authors · PubMed 34586374

    ABSTRACT: Key Points Question Are the genetic risk factors for depression the same in individuals of East Asian and European descent? Findings In this genome-wide association meta-analysis of depression in 194 548 individuals with East Asian ancestry, 2 novel genetic associations were identified, one of which is specific to individuals of East Asian descent living in East Asian countries. There was limited evidence for transferability with only 11% of depression loci previously identified in individuals of European descent reaching nominal significance levels in the individuals of East Asian descent. Meaning Caution is advised against generalizing findings about genetic risk factors for depression beyond the studied population. This genetic association study investigates the genetics of

  • Large-scale GWAS of food liking reveals genetic determinants and genetic correlations with distinct neurophysiological traits - Unknown journal (n.d.) · Unknown authors · PubMed 35585065

    ABSTRACT: We present the results of a GWAS of food liking conducted on 161,625 participants from the UK-Biobank. Liking was assessed over 139 specific foods using a 9-point scale. Genetic correlations coupled with structural equation modelling identified a multi-level hierarchical map of food-liking with three main dimensions: "Highly-palatable", "Acquired" and "Low-caloric". The Highly-palatable dimension is genetically uncorrelated from the other two, suggesting that independent processes underlie liking high reward foods. This is confirmed by genetic correlations with MRI brain traits which show with distinct associations. Comparison with the corresponding food consumption traits shows a high genetic correlation, while liking exhibits twice the heritability. GWAS analysis id

  • A multivariate genome-wide association study of psycho-cardiometabolic multimorbidity - Unknown journal (n.d.) · Unknown authors · PubMed 37390107

    ABSTRACT: Coronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree of multimorbidity, which may be explained by shared genetic influences. However, research exploring the presence of pleiotropic variants and genes common to CAD, T2D and depression is lacking. The present study aimed to identify genetic variants with effects on cross-trait liability to psycho-cardiometabolic diseases. We used genomic structural equation modelling to perform a multivariate genome-wide association study of multimorbidity (Neffective = 562,507), using summary statistics from univariate genome-wide association studies for CAD, T2D and major depression. CAD was moderately ge

  • Genome-wide association analyses identify distinct genetic architectures for early-onset and late-onset depression - Unknown journal (n.d.) · Unknown authors · PubMed 41233554

    ABSTRACT: Major depressive disorder (MDD) is a common and heterogeneous disorder of complex etiology. Studying more homogeneous groups stratified according to clinical characteristics, such as age of onset, can improve the identification of the underlying genetic causes and lead to more targeted treatment strategies. We leveraged Nordic biobanks with longitudinal health registries to investigate differences in the genetic architectures of early-onset (eoMDD; n = 46,708 cases) and late-onset (loMDD; n = 37,168 cases) MDD. We identified 12 genomic loci for eoMDD and two for loMDD. Overall, the two MDD subtypes correlated moderately (genetic correlation, rg = 0.58) and differed in their genetic correlations with related traits. These findings suggest that eoMDD and loMDD have part

  • Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways - Unknown journal (n.d.) · Unknown authors · PubMed 29662059

    ABSTRACT: Depression is a polygenic trait that causes extensive periods of disability. Previous genetic studies have identified common risk variants which have progressively increased in number with increasing sample sizes of the respective studies. Here, we conduct a genome-wide association study in 322,580 UK Biobank participants for three depression-related phenotypes: broad depression, probable major depressive disorder (MDD), and International Classification of Diseases (ICD, version 9 or 10)-coded MDD. We identify 17 independent loci that are significantly associated (P < 5 × 10−8) across the three phenotypes. The direction of effect of these loci is consistently replicated in an independent sample, with 14 loci likely representing novel findings. Gene sets are enriched in

  • Multi-trait analysis of genome-wide association summary statistics using MTAG - Unknown journal (n.d.) · Unknown authors · PubMed 29292387

    ABSTRACT: We introduce Multi-Trait Analysis of GWAS (MTAG), a method for joint analysis of summary statistics from GWASs of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (Neff = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). Compared to 32, 9, and 13 genome-wide significant loci in the single-trait GWASs (most of which are themselves novel), MTAG increases the number of loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase variance explained by polygenic scores by approximately 25%, matching theoretical expectations. FULL TEXT: [INTRO] INTRODUCTION [INTRO] The standard approach in genetic-association studi

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