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Study Tracks GWAS Impacts of Genetic Architecture in Admixed Populations

In the American Journal of Human Genetics, investigators at the University of California, Los Angeles and elsewhere explore the genome-wide association effects of admixed ancestry. "In this work, we seek to understand the impact that estimated allelic effect-size heterogeneity by ancestry (HetLanc) has on the power of a GWAS in admixed populations," they explain, noting that the results suggest HetLanc and ancestry-related causal allele frequency differences "are the two most important factors when considering various methods for disease mapping in admixed populations." The team turned to admixed genotype and phenotype simulations — along with GWAS data spanning a dozen traits for more than 4,300 admixed UK Biobank participants with African and European ancestry — to analyze risk variant effect size differences stemming from ancestry-related allelic features using a model known as Tractor that accounts for HetLanc. "We find that in cases with small or absent levels of HetLanc, a standard GWAS is more powerful than Tractor in simulations of quantitative traits," the authors report, adding that "as CAF differentiation between ancestries increases, so does the improvement of power of a standard GWAS compared to Tractor." On the other hand, their results suggest Tractor "outperforms a standard GWAS" in situations marked by high HetLanc.