Studying the Genetics of Aging, Behavioral, and Social Phenotypes in Diverse Populations-Supplement

PROJECT SUMMARY/ABSTRACT This proposal requests a Research Supplement to Promote Re-Entry into Health-Related Research Careers (NOT-OD-23-170) to support Dr. Jeffrey Swigert as he resumes his research career following a formal hiatus due to family caregiving responsibilities. This supplement will provide structured mentorship and research training to reintegrate Dr. Swigert into health-related genomics research while advancing the objectives of the parent R01 grant (R01 AG081518). The parent project focuses on developing novel statistical genetics tools to improve genetic research on aging, behavioral, and social phenotypes in heterogeneous populations. One such tool, Genetic-Relatedness-Matched Association (GRMA) studies, enables more powerful genome-wide association studies (GWAS) by leveraging distant relatives to enhance statistical precision while mitigating biases associated with traditional ancestry-based methods. This supplement will address a key limitation of GRMA by developing an improved method for estimating linkage disequilibrium (LD) structures in genetically heterogeneous populations. Standard LD matrices and scores, which are essential for downstream applications such as heritability estimation, genetic correlation, and polygenic index (PGI) construction, are currently incompatible with GRMA summary statistics. Dr. Swigert will formalize the theoretical framework for GRMA-based LD estimation, develop software tools to generate appropriate LD resources, and validate these tools using large-scale biobank data such as UK Biobank and All of Us. The results will be made publicly available, significantly expanding GRMA’s applicability and enabling broader adoption by the research community. To support Dr. Swigert’s long-term research independence, this supplement also includes a comprehensive re-entry plan with targeted mentorship, participation in key genomics and social science conferences, structured training in statistical genetics methodologies, and hands-on experience in grant writing, software development, and research leadership. By the conclusion of the supplement period, Dr. Swigert will be well- positioned to secure independent funding and contribute meaningfully to genomics research on health and aging. This proposal directly aligns with the goals of the NOSI by facilitating the re-entry of a highly qualified researcher into biomedical research while enhancing the impact of the parent grant’s innovations in statistical genetics.