Expressive

rs12188716 - NR2F1-AS1

Magnitude 2.2 · 2 studies on file

Reported associations

  • 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

  • Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals - Unknown journal (n.d.) · Unknown authors · PubMed 35361970

    ABSTRACT: We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significan

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