Approximate conditional phenotype analysis based on genome wide association summary statistics
Year: 2021
Type: article
Abstract: Because single genetic variants may have pleiotropic effects, one trait can be a confounder in a genome-wide association study (GWAS) that aims to identify loci associated with another trait. A typical approach to address this issue is to perform an additional analysis adjusting for the confounder. However, obtaining conditional results can be time-consuming. We propose an approximate conditional phenotype analysis based on GWAS summary statistics, the covariance between outcome and confounder, and the variant minor allele frequency (MAF). GWAS summary statistics and MAF are taken from GWAS meta-analysis results while the traits covariance may be estimated by two strategies: (i) estimates from a subset of the phenotypic data; or (ii) estimates from published studies. We compare our two strategies with estimates using individual level data from the full GWAS sample (gold standard). A simulation study for both binary and continuous traits demonstrates that our approximate approach is accurate. We apply our method to the Framingham Heart Study (FHS) GWAS and to large-scale cardiometabolic GWAS results. We observed a high consistency of genetic effect size estimates between our method and individual level data analysis. Our approach leads to an efficient way to perform approximate conditional analysis using large-scale GWAS summary statistics.
Source: Scientific Reports
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $1,990
Awards: TOPMed Omics of Cardiovascular Disease in Diabetes, G1664136512, G1735617348, Precision Medicine in Ischemic Stroke and Atrial Fibrillation (PreMISe-AF), G2281899837, American Heart Association Tobacco Regulation and Addiction Center (A-TRAC), G278200998, G2952055171, G2953629384, G3405256882, AFGen Consortium: Atrial Fibrillation Genomics to Functional Analyses, G4976486911, G5164707915, Common Genetic Variation and Quantitative Diabetes Traits, Rare Sequence Variation and Diabetes Quantitative Traits, G6717867015, THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195, G8630864450, G8683204365, G8993135685, G9000079831, G9000124674, TOPMed Omics of Type 2 Diabetes and Quantitative Traits, IDENTIFICATION OF COMMON GENETIC VARIANTS FOR ATRIAL FIBRILLATION AND PR INTERVAL, Genomics of Cardiac Arrhythmias
OpenAlex ID: W3123374976