Siewert, K. M. | bioRxiv Science

bioRxiv2018

Bivariate GWAS scan identifies six novel loci associated with lipid levels and coronary artery disease

BackgroundPlasma lipid levels are heritable and genetically associated with risk of coronary artery disease (CAD). However, genome-wide association studies (GWAS) routinely analyze these traits independently of one another. Joint GWAS for two related phenotypes can lead to a higher-powered analysis to detect variants contributing to both traits.\n\nMethods and ResultsWe performed a bivariate GWAS to discover novel loci associated with heart disease, using a CAD Meta-Analysis (122,733 cases and 424,528 controls), and lipid traits, using data from the Global Lipid Genetics Consortium (188,577 subjects). We identified six previously unreported loci at genome-wide significance (P < 5 x 10-8), three which were associated with Triglycerides and CAD, two which were associated with LDL cholesterol and CAD, and one associated with Total Cholesterol and CAD. At several of our loci, the GWAS signals jointly localize with genetic variants associated with expression level changes for one or more neighboring genes, indicating that these loci may be affecting disease risk through regulatory activity.\n\nConclusionsWe discovered six novel variants individually associated with both lipids and coronary artery disease.

genomics↗

bioRxiv2017

Detecting Long-term Balancing Selection using Allele Frequency Correlation

Balancing selection occurs when multiple alleles are maintained in a population, which can result in their preservation over long evolutionary time periods. A characteristic signature of this long-term balancing selection is an excess number of intermediate frequency polymorphisms near the balanced variant. However, the expected distribution of allele frequencies at these loci has not been extensively detailed, and therefore existing summary statistic methods do not explicitly take it into account. Using simulations, we show that new mutations which arise in close proximity to a site targeted by balancing selection accumulate at frequencies nearly identical to that of the balanced allele. In order to scan the genome for balancing selection, we propose a new summary statistic, {beta}, which detects these clusters of alleles at similar frequencies. Simulation studies show that compared to existing summary statistics, our measure has improved power to detect balancing selection, and is reasonably powered in non-equilibrium demographic models or when recombination or mutation rate varies. We compute {beta} on 1000 Genomes Project data to identify lo ci potentially subjected to long-term balancing selection in humans. We report two balanced haplotypes - localized to the genes WFS1 and CADM2 - that are strongly linked to association signals for complex traits. Our approach is computationally efficient and applicable to species that lack appropriate outgroup sequences, allowing for well-powered analysis of selection in the wide variety of species for which population data are rapidly being generated.

evolutionary biology↗