PRS also can be used to predict continuous traits in the population like BMI, which is important as a risk factor for cardiometabolic traits. A recent large study showed that participants in the highest BMI PRS decile have a BMI that is 2.6 kg/m2 higher than those in the mid-quantile PRS—to put in context, this is half the width of the ‘overweight category’ of BMI (from 25 to 29.9 mg/m2)—and corresponds to 31% of individuals with a BMI > 40 (obesity class 3) [54]. Genetically dissected trajectories of BMI across the lifespan help us identify where genetic prediction starts to be relevant. BMI PRS is only minimally associated with birthweight; it has increasing prediction through childhood, and by age 18, the differences in BMI by PRS quartile are similar to that seen in adulthood [54]. Despite the significant polygenic prediction of BMI in the general population, it remains to be determined whether BMI PRS has clinical utility in high-risk populations. For example, a common adverse effect of antipsychotics or antidepressants is weight gain; however, we do not know whether this is determined or modified by the BMI PRS.
