Polygenic scores — summaries of the genomic contribution to risk and resilience for biomedical traits — are an emerging and promising approach for clinical risk assessment and personalized medicine. All communities do not currently benefit from insights gained via studies of polygenic scores because these groups have not been sufficiently characterized in this research. This must be addressed through recruitment as well as consideration of the effects of heterogeneity during analysis. For example, our preliminary data show striking dissociations in suicide risk as influenced by polygenic scores. Notably, these opposing associations are apparent only when sex-related effects are modeled, underscoring the imperative to parsing the heterogeneity of such associations by sex. These results suggest value in genomic research in understanding both innate risk and resilience related to sex. The promise of genomic research informed by sex depends on the ability to capture the variability within each sex (e.g., facial morphology, autism-related sex differences). This difficulty results in many studies not sufficiently accounting for sex differences in genetic research. We propose to close this gap by calibrating and genetically characterizing a novel and broadly disseminable method for studying key sex-related differences for genomic research and broader research applications. First, we will facilitate partnership between scientists and stakeholders, and improve communication in this field of research, by building on our established community partnerships with a purposively recruited stakeholder panel (N=50). Next, we will validate the stakeholder-refined method in a large sample (N=10,000) of genotyped neurotypical and neurodivergent adults. Finally, to demonstrate proof-of-principle for how sex contextualizes patterns of association with polygenic scores, we will measure key health outcomes (both mental and physical), in a large, genetically informed sample enriched for neurodiversity (e.g., autism). The proposed research will provide value by seeking a better understanding of how polygenic scores apply across the sexes.