Expressive

rs12356045 - SORCS3 - LINC02627

Magnitude 2.2 · 3 studies on file

Reported associations

  • Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction - Unknown journal (n.d.) · Unknown authors · PubMed 34446935

    ABSTRACT: Behaviors and disorders related to self-regulation, such as substance use, antisocial behavior, and ADHD, are collectively referred to as externalizing and have shared genetic liability. We applied a multivariate approach that leverages genetic correlations among externalizing traits for genome-wide association analyses. By pooling data from ~1.5 million people, our approach is statistically more powerful than single-trait analyses and identifies more than 500 genetic loci. The loci were enriched for genes expressed in the brain and related to nervous system development. A polygenic score constructed from our results predicts a range of behavioral and medical outcomes that were not part of genome-wide analyses, including traits that until now lacked well-performing polygenic scor

  • Gene discovery and polygenic prediction from a 1.1-million-person GWAS of educational attainment - Unknown journal (n.d.) · Unknown authors · PubMed 30038396

    ABSTRACT: We conduct a large-scale genetic association analysis of educational attainment in a sample of ~1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of ~0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of

  • Genetic analyses identify widespread sex-differential participation bias - Unknown journal (n.d.) · Unknown authors · PubMed 33888908

    ABSTRACT: Genetic association results are often interpreted with the assumption that study participation does not affect downstream analyses. Understanding the genetic basis of participation bias is challenging as it requires genotypes of unseen individuals. Here we demonstrate that it is possible to estimate comparative biases by performing a genome-wide association study (GWAS) contrasting one subgroup versus another. For example, we show that sex exhibits artefactual autosomal heritability in the presence of sex-differential participation bias. By performing a GWAS of sex in ∼3.3 million males and females, we identify over 158 autosomal loci spuriously associated with sex and highlight complex traits underpinning differences in study participation between sexes. For example, the body

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