Project Summary/Abstract This proposal is an R24 research network application. The Social Science Genetic Association Consortium (SSGAC) is a research network that provides a platform for large-scale, interdisciplinary collaborations on genome-wide association studies (GWASs) of behavioral, social, and other aging-related phenotypes. Summary statistics produced by the SSGAC are widely used in medical, epidemiological, and social-science research for studying biosocial science, health disparities, and aging-related topics, and for integrated analyses with omics including genome-wide methylation, gene expression, and brain imaging. The overarching goal of this proposal is to create and disseminate resources for the genomics and omics of behavioral and social phenotypes. The Specific Aims are: • Conduct genome-wide association studies (GWAS) of a wide range of behavioral, social, and other aging-related phenotypes in unprecedentedly large samples, using the most up-to-date methods to maximize power, and broadly disseminate the resulting summary statistics and PGIs. In addition to (standard) population-based GWAS (i.e., in samples of unrelated individuals) in samples with genetic ancestries similar to those of the 1000 Genomes subsample EUR, we will also disseminate results from family-based GWAS (i.e., controlling for parental genotypes, either measured or imputed from other genotypes relatives) and diverse-ancestry GWAS. Diverse-ancestry GWAS may be particularly useful for studying, and ultimately mitigating, health disparities across genetic ancestries. • Produce and disseminate materials for non-technical audiences that address appropriate interpretation of genomics research on behavioral and social phenotypes and its social and ethical implications. Building on the SSGAC’s practice of accompanying every major paper with Frequently Asked Questions (FAQs), we will convene a Community Advisory Panel to get public input on important questions that may be missed by FAQs to date. We will write general FAQs about the field as a whole, which can then be referenced by subsequent, briefer, paper-specific FAQs. We will create paper-specific FAQs that address the new and major issues raised by family-based and diverse-ancestry GWAS and PGIs and their potential uses and misuses. • Develop new methods for analysis of summary statistics and PGIs, prepare user-friendly software manuals, and make the software tools publicly available on a GitHub repository featuring a Q&A forum. We will also host and advertise monthly online methods/software seminars, taught by the developers of new methods. We will emphasize new methods that integrate the analysis of genomic summary statistics with other omics data.