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Complex Human Trait Clues Drawn From Statistical Model

In PLOS Genetics, a team from the University of Wisconsin at Madison and Stanford University describe a statistical framework dubbed "parental stratification of genetic effect components" (PARSEC) for analyzing complex trait architecture, including heritable contributors and genetic covariance related to shared environments such as family environments. "This framework enables us to partition both heritability and genetic covariance into direct and indirect pathways, and gain knowledge of how genetics and environment jointly contribute to complex traits as well as the correlation between trait pairs," the researchers write. When they applied PARSEC to five complex traits ranging from height, body mass index, or overall health to educational attainment or income in 12,571 UK Biobank families, for example, they saw "substantial involvement of indirect genetic components in shared genetic architecture across traits."