Genetic factor analysis for characterizing phenome-wide patterns of genetic pleiotropy.

Genetic factor analysis reveals 15 pleiotropic components underlying 22 risk factors for coronary artery disease and type 2 diabetes.

• Why it matters: Understanding shared genetic influences across traits helps clarify biological mechanisms and improves disease risk prediction, addressing limitations of existing methods.
• What they did: GFA automatically determines the number of factors, accounts for sample overlap, and captures non-orthogonal relationships, applied to 22 risk factors and blood cell phenotypes.
• The result: The approach successfully decomposes heritability into meaningful biological components and enhances precision in Mendelian randomization, emphasizing the importance of handling sample overlap.