Approaches to detect genetic effects that differ between two strata in genome-wide meta-analyses: Recommendations based on a systematic evaluation
Year: 2017
Type: article
Abstract: Genome-wide association meta-analyses (GWAMAs) conducted separately by two strata have identified differences in genetic effects between strata, such as sex-differences for body fat distribution. However, there are several approaches to identify such differences and an uncertainty which approach to use. Assuming the availability of stratified GWAMA results, we compare various approaches to identify between-strata differences in genetic effects. We evaluate type I error and power via simulations and analytical comparisons for different scenarios of strata designs and for different types of between-strata differences. For strata of equal size, we find that the genome-wide test for difference without any filtering is the best approach to detect stratum-specific genetic effects with opposite directions, while filtering for overall association followed by the difference test is best to identify effects that are predominant in one stratum. When there is no a priori hypothesis on the type of difference, a combination of both approaches can be recommended. Some approaches violate type I error control when conducted in the same data set. For strata of unequal size, the best approach depends on whether the genetic effect is predominant in the larger or in the smaller stratum. Based on real data from GIANT (>175 000 individuals), we exemplify the impact of the approaches on the detection of sex-differences for body fat distribution (identifying up to 10 loci). Our recommendations provide tangible guidelines for future GWAMAs that aim at identifying between-strata differences. A better understanding of such effects will help pinpoint the underlying mechanisms.
Source: PLoS ONE
Institutions: University of Regensburg, University of North Carolina at Chapel Hill, Boston University, Framingham Heart Study, Innsbruck Medical University, Universität Innsbruck, SIB Swiss Institute of Bioinformatics, Centre Hospitalier Universitaire Vaudois, Institute of Social and Preventive Medicine, University of Lausanne
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $1,592
Funders: National Science Foundation, Foundation for the National Institutes of Health, Deutscher Akademischer Austauschdienst, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Bundesministerium für Bildung und Forschung, Universität Regensburg, Fondation Leenaards, SystemsX.ch, Swiss Institute of Bioinformatics, National Institutes of Health, National Heart, Lung, and Blood Institute, National Institute of Diabetes and Digestive and Kidney Diseases
Awards: Identifizierung und Charakterisierung der genetischen Basis von altersbedingter Makuladegeneration unter spezieller Berücksichtigung von geschlechtsspezifischen Effekten, G214766520, G21957102, G2232381808, Genetic Architecture of Adiposity in Multiple Large Cohorts, Deciphering the missing heritability, Systems level understanding of the genetic architecture of complex human traits, G3584095272, Identifizierung und Charakterisierung der genetischen Basis von altersbedingter Makuladegeneration unter spezieller Berücksichtigung von geschlechtsspezifischen und anderen nicht-genetischen Effekten (2. Förderphase), G544591541, G896909551, Biological Insights from Genetic Investigation of ANthropometric Traits (GIANT) Across the Allelic Spectrum
OpenAlex ID: W2740317623