One challenge of exploring the value of PRS within the clinical setting to predict the outcome, or determine the treatment, is that the sample sizes from case-only clinical studies with relevant phenotypic data related to the course of illness, treatment response, or adverse effects are substantially lower than those from case-control disease susceptibility studies. The latter requires minimal phenotypic information—a clinical diagnosis, or self-report—whilst determining prognosis or treatment outcome requires longitudinal follow-up across sustained periods of time. This is expensive and challenging to collect, and such studies often have much smaller sample sizes. Electronic health records (EHR) may provide longitudinal data, but ‘treatment response’ is often poorly recorded and needs to be captured laterally through prescription records. We highlight how applying PRS in treatment response may better facilitate clinical utility, as the genetic data will complement the clinician’s choice of treatment. We envisage that the role of PRS in informing treatment choices, for example, prioritising pharmaceutical or psychosocial interventions or providing quantitative information on the benefit to harm ratio for each treatment, rather than treat/not treat decisions, may be the low-hanging fruit where the clinical utility of PRS will become apparent.
