rs12321621 - MYL2
Magnitude 2.2 · 2 studies on file
Reported associations
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Multi-trait GWAS for diverse ancestries: mapping the knowledge gap - Unknown journal (n.d.) · Unknown authors · PubMed 38627641
ABSTRACT: Background Approximately 95% of samples analyzed in univariate genome-wide association studies (GWAS) are of European ancestry. This bias toward European ancestry populations in association screening also exists for other analyses and methods that are often developed and tested on European ancestry only. However, existing data in non-European populations, which are often of modest sample size, could benefit from innovative approaches as recently illustrated in the context of polygenic risk scores. Methods Here, we extend and assess the potential limitations and gains of our multi-trait GWAS pipeline, JASS (Joint Analysis of Summary Statistics), for the analysis of non-European ancestries. To this end, we conducted the joint GWAS of 19 hematological traits and glycemic traits acro
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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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