Expressive

rs10032297 - SLC7A11-AS1, LINC00616

Magnitude 2.2 · 2 studies on file

Reported associations

  • Multivariate genetic analysis of personality and cognitive traits reveals abundant pleiotropy. - Nature human behaviour (2023) · Hindley G, Shadrin AA, van der Meer D, Parker N, Cheng W, O'Connell KS, Bahrami S, Lin A, Karadag N, Holen B, Bjella T, Deary IJ, Davies G, Hill WD, Bressler J, Seshadri S, Fan CC, Ueland T, Djurovic S, Smeland OB, Frei O, Dale AM, Andreassen OA · PubMed 37365406

    Personality and cognitive function are heritable mental traits whose genetic foundations may be distributed across interconnected brain functions. Previous studies have typically treated these complex mental traits as distinct constructs. We applied the 'pleiotropy-informed' multivariate omnibus statistical test to genome-wide association studies of 35 measures of neuroticism and cognitive function from the UK Biobank (n = 336,993). We identified 431 significantly associated genetic loci with evidence of abundant shared genetic associations, across personality and cognitive function domains. Functional characterization implicated genes with significant tissue-specific expression in all tested brain tissues and brain-specific gene sets. We conditioned independent genome-wide association

  • Minimal phenotyping yields genome-wide association signals of low specificity for major depression - Unknown journal (n.d.) · Unknown authors · PubMed 32231276

    ABSTRACT: Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be

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