Abstract
While family studies are ideal to pinpoint strong genetic risk effects, genome-wide association studies in unrelated individuals are particularly successful in identifying moderate and small genetic risks for multifactorial diseases and disease-relevant quantitative parameters. Here, we present how the genetic risk for such variants is computed and what models are used to derive cumulative ...
Abstract
While family studies are ideal to pinpoint strong genetic risk effects, genome-wide association studies in unrelated individuals are particularly successful in identifying moderate and small genetic risks for multifactorial diseases and disease-relevant quantitative parameters. Here, we present how the genetic risk for such variants is computed and what models are used to derive cumulative genetic risk. Using the examples of obesity, diabetes, and age-related macular degeneration, we illustrate how these risks are computed and tackle the question of how big the small genetic risks are.
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