As conversations about personalized medicine make their way to the general public, it is important to recognize the need to include under-represented populations in genetic studies. Among other concerns, the inclusion of participants representing diverse ancestries in research is imperative to ensure equitable benefit from scientific discoveries for diverse populations, and to prevent further increase in health disparities. Relevant to these longer-term objectives, our findings provide essential basic information about polygenic risk score usage among diverse populations, summarized in four key points. First, polygenic scoring studies have primarily been conducted in European and East Asian ancestry populations. Second, the performance of polygenic scores in non-European populations is generally poorer than performance in European ancestry samples, particularly for African ancestry samples. Third, polygenic scores for complex genetic phenotypes depend critically on the methods used to construct scores. Fourth, appropriate data resources are lacking to address most questions about putative differences in polygenic scores across worldwide populations. The straightforward, albeit expensive and time-consuming, solution to improving polygenic score performance across diverse populations is to create well-powered GWAS data resources for many different
