Utility of family history in disease prediction in the era of polygenic scores

Abstract

Clinicians have historically used family history and other risk prediction algorithms to guide patient care and preventive treatment such as statin therapeutics for coronary artery disease. As polygenic scores move towards clinical use, we have begun to consider the interplay of these scores with other predictors for optimal second generation risk prediction. Here, we assess the use of family history and polygenic scores as independent predictors of coronary artery disease and type 2 diabetes. We highlight considerations for use of family history as a predictor of these two diseases after evaluating their effectiveness in the Trondelag Health Study and the UK Biobank. From these, we advocate for collection of high resolution family history variables in biobanks for future prediction models.