Expressive

rs10809520 - LINC03131 - JKAMPP1

Magnitude 4.5 · 2 studies on file

Reported associations

  • 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

  • Genetic variants associated with subjective well-being, depressive symptoms and neuroticism identified through genome-wide analyses - Unknown journal (n.d.) · Unknown authors · PubMed 27089181

    ABSTRACT: We conducted genome-wide association studies of three phenotypes: subjective well-being (N = 298,420), depressive symptoms (N = 161,460), and neuroticism (N = 170,910). We identified three variants associated with subjective well-being, two with depressive symptoms, and eleven with neuroticism, including two inversion polymorphisms. The two depressive symptoms loci replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes strengthen the overall credibility of the findings, and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal/pancreas tissues are strongly enriched for association. FULL TEXT: [INTRO] Introduction [INTRO] Subjectiv

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