Project Summary/Abstract For this application, “Studying the Genetics of Aging, Behavioral, and Social Phenotypes in Diverse Populations,” we propose to develop tools to promote genetic research of aging, behavioral, and social phenotypes in diverse populations. These phenotypes have a number of unique characteristics (e.g., polygenicity, environmental mechanisms, and small effect sizes) which require special consideration when developing research tools. In brief, we propose to: • Develop the Genetic-Related-Matrix-Matched Association study (GRMMA) tool for performing genome-wide association studies (GWASs) in large, diverse data sets. Current GWAS methods require restricting samples into approximately homogeneous-ancestry samples, which is wasteful and has resulted in Eurocentric bias in genetics research. Using matching methods, GRMMA can use more of the available data in a way that both reduces bias and increases statistical power. We will employ computationally efficient strategies that allow us to implement GRMMA in large diverse sample such as the UK Biobank. We will make the GRMMA tool and tutorials publicly available through the online repository, Github. • Develop SBayes-Universal (SBayesU), an efficient new tool for producing polygenic scores (PGSs) by optimally combining GWAS summary statistics estimated in different populations. The key feature of SBayesU is that it uses a low-dimensional eigen decomposition of the linkage disequilibrium matrix. This permits SBayesU to model a much larger set of SNPs, to model SNP annotations, to account for imperfect cross-ancestry genetic correlation, to produce PGSs for populations that are not included among the sets of GWAS summary statistics, and to allow our algorithms to converge much more quickly and reliably. We will also make the SBayesU tool and tutorials publicly available. • We will apply the best available method for producing diverse-population PGSs (which we anticipate will be SBayesU) to a wide range of aging, behavioral, and social phenotypes, using existing cohorts and new genotyped data that becomes available during the grant period. We will make the polygenic scores we produce publicly available as part of the Social Science Genetic Association Consortium’s Polygenic Index Repository, which currently creates polygenic scores for 11 widely used datasets (but currently only for the European-ancestry individuals in those datasets). Each release of the Repository will be accompanied by documentation that clearly describes methods used and the underlying data.