Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations

Combining a standard polygenic risk score (PRS) as a feature in a machine learning model increases the percentage variance explained for those traits, helping to account for non-linearities or interaction effects in genetics-based prediction models.