Expressive

rs11876242 - RNU4-17P - MC4R

Magnitude 2.2 · 2 studies on file

Reported associations

  • Genetic architecture reconciles linkage and association studies of complex traits. - Nature genetics (2024) · Sidorenko J, Couvy-Duchesne B, Kemper KE, Moen GH, Bhatta L, Åsvold BO, Mägi R, Ani A, Wang R, Nolte IM, Gordon S, Hayward C, Campbell A, Benjamin DJ, Cesarini D, Evans DM, Goddard ME, Haley CS, Porteous D, Medland SE, Martin NG, Snieder H, Metspalu A, Hveem K, Brumpton B, Visscher PM, Yengo L · PubMed 39375568

    Linkage studies have successfully mapped loci underlying monogenic disorders, but mostly failed when applied to common diseases. Conversely, genome-wide association studies (GWASs) have identified replicable associations between thousands of SNPs and complex traits, yet capture less than half of the total heritability. In the present study we reconcile these two approaches by showing that linkage signals of height and body mass index (BMI) from 119,000 sibling pairs colocalize with GWAS-identified loci. Concordant with polygenicity, we observed the following: a genome-wide inflation of linkage test statistics; that GWAS results predict linkage signals; and that adjusting phenotypes for polygenic scores reduces linkage signals. Finally, we developed a method using recombination rate-stratif

  • Participation bias in the UK Biobank distorts genetic associations and downstream analyses - Unknown journal (n.d.) · Unknown authors · PubMed 37106081

    ABSTRACT: While volunteer-based studies such as the UK Biobank have become the cornerstone of genetic epidemiology, the participating individuals are rarely representative of their target population. To evaluate the impact of selective participation, here we derived UK Biobank participation probabilities on the basis of 14 variables harmonized across the UK Biobank and a representative sample. We then conducted weighted genome-wide association analyses on 19 traits. Comparing the output from weighted genome-wide association analyses (neffective = 94,643 to 102,215) with that from standard genome-wide association analyses (n = 263,464 to 283,749), we found that increasing representativeness led to changes in SNP effect sizes and identified novel SNP associations for 12 traits. While

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