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Pleiotropy is the phenomenon by which a genetic variant affects multiple independent traits. Human genetics studies have identified pervasive pleiotropy throughout the genome and multitrait genome-wide association studies are growing in scale, such that dissecting pleiotropy is an increasingly important step in linking disease-associated variants to specific mechanisms. Dissecting pleiotropy entails using one of several statistical approaches to define clusters of genetic associations reflecting biological processes that are distinct and shared across traits, which must then be validated with orthogonal datasets. In this Review, we outline the various approaches to pleiotropy dissection, describing exemplary applications throughout, and discuss the remaining challenges and limitations to elucidating the shared mechanisms of disease.