Expressive

rs11039182 - MADD

Magnitude 4.5 · 7 studies on file

Reported associations

  • Meta-analysis of genome-wide association studies for neuroticism in 449,484 individuals identifies novel genetic loci and pathways. - Nature genetics (2019) · Nagel M, Jansen PR, Stringer S, Watanabe K, de Leeuw CA, Bryois J, Savage JE, Hammerschlag AR, Skene NG, Muñoz-Manchado AB, White T, Tiemeier H, Linnarsson S, Hjerling-Leffler J, Polderman TJC, Sullivan PF, van der Sluis S, Posthuma D · PubMed 29942085

    Neuroticism is an important risk factor for psychiatric traits, including depression , anxiety , and schizophrenia . At the time of analysis, previous genome-wide association studies (GWAS) reported 16 genomic loci associated to neuroticism . Here we conducted a large GWAS meta-analysis (n = 449,484) of neuroticism and identified 136 independent genome-wide significant loci (124 new at the time of analysis), which implicate 599 genes. Functional follow-up analyses showed enrichment in several brain regions and involvement of specific cell types, including dopaminergic neuroblasts (P = 3.49 × 10 ), medium spiny neurons (P = 4.23 × 10 ), and serotonergic neurons (P = 1.37 × 10 ). Gene set analyses implicated three specific pathways: neurogenesis (P = 4.43

  • Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function - Unknown journal (n.d.) · Unknown authors · PubMed 26831199

    ABSTRACT: Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across

  • JASS: command line and web interface for the joint analysis of GWAS results - Unknown journal (n.d.) · Unknown authors · PubMed 32002517

    ABSTRACT: Abstract Genome-wide association study (GWAS) has been the driving force for identifying association between genetic variants and human phenotypes. Thousands of GWAS summary statistics covering a broad range of human traits and diseases are now publicly available. These GWAS have proven their utility for a range of secondary analyses, including in particular the joint analysis of multiple phenotypes to identify new associated genetic variants. However, although several methods have been proposed, there are very few large-scale applications published so far because of challenges in implementing these methods on real data. Here, we present JASS (Joint Analysis of Summary Statistics), a polyvalent Python package that addresses this need. Our package incorporates recently developed j

  • Item-level analyses reveal genetic heterogeneity in neuroticism - Unknown journal (n.d.) · Unknown authors · PubMed 29500382

    ABSTRACT: Genome-wide association studies (GWAS) of psychological traits are generally conducted on (dichotomized) sums of items or symptoms (e.g., case-control status), and not on the individual items or symptoms themselves. We conduct large-scale GWAS on 12 neuroticism items and observe notable and replicable variation in genetic signal between items. Within samples, genetic correlations among the items range between 0.38 and 0.91 (mean rg = .63), indicating genetic heterogeneity in the full item set. Meta-analyzing the two samples, we identify 255 genome-wide significant independent genomic regions, of which 138 are item-specific. Genetic analyses and genetic correlations with 33 external traits support genetic differences between the items. Hierarchical clustering analysis identifi

  • Genetic contributions to two special factors of neuroticism are associated with affluence, higher intelligence, better health, and longer life - Unknown journal (n.d.) · Unknown authors · PubMed 30867560

    ABSTRACT: Higher scores on the personality trait of neuroticism, the tendency to experience negative emotions, are associated with worse mental and physical health. Studies examining links between neuroticism and health typically operationalize neuroticism by summing the items from a neuroticism scale. However, neuroticism is made up of multiple heterogeneous facets, each contributing to the effect of neuroticism as a whole. A recent study showed that a 12-item neuroticism scale described one broad trait of general neuroticism and two special factors, one characterizing the extent to which people worry and feel vulnerable, and the other characterizing the extent to which people are anxious and tense. This study also found that, although individuals who were higher on general neuroticism li

  • Distributed genetic effects of the corpus callosum subregions suggest links to neuropsychiatric disorders and related traits - Unknown journal (n.d.) · Unknown authors · PubMed 37612147

    ABSTRACT: Background: The corpus callosum (CC) is a brain structure with a high heritability and potential role in psychiatric disorders. However, the genetic architecture of the CC and the genetic link with psychiatric disorders remain largely unclear. We investigated the genetic architectures of the volume of the CC and its subregions and the genetic overlap with psychiatric disorders. Methods: We applied multivariate genome-wide association study (GWAS) to genetic and T1-weighted magnetic resonance imaging (MRI) data of 40,894 individuals from the UK Biobank, aiming to boost genetic discovery and to assess the pleiotropic effects across volumes of the five subregions of the CC (posterior, mid-posterior, central, mid-anterior and anterior) obtained by FreeSurfer 7.1. Multivariate GWAS wa

  • Pleiotropy informed adaptive association test of multiple traits using GWAS summary data - Unknown journal (n.d.) · Unknown authors · PubMed 31021400

    ABSTRACT: Summary: Genetic variants associated with disease outcomes can be used to develop personalized treatment. To reach this precision medicine goal, hundreds of large-scale genome-wide association studies (GWAS) have been conducted in the past decade to search for promising genetic variants associated with various traits. They have successfully identified tens of thousands of diseases related variants. However in total these identified variants explain only part of the variation for most complex traits. There remain many genetic variants with small effect sizes to be discovered, which calls for the development of (1) GWAS with more samples and more comprehensively genotyped variants, e.g., the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program is planning to conduct whole geno

Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.