Providing the best possible care for an individual means possessing a better understanding of the risks of developing disease. The goal is to have personalized answers when individuals need to know whether, for instance, preventive surgery makes sense, a given medicine is likely to be risky, or a certain diet should be recommended. According to an article in the September 9, 2021 issue of the journal Nature, information on genetic risk represents one promising approach to providing these answers. Genomic data, gathered across millions of individuals, have revealed thousands of DNA sequence variants associated with common diseases such as diabetes, heart disease, schizophrenia, and cancer. These clues to disease risk can be combined to generate ‘polygenic scores’ that provide a measure of the degree to which an individual genetically is predisposed to developing each such disease. A growing chorus of scientists and clinicians emphasize the value of such genetic profiling as an integral part of a personal medical record.
Alternatively, others argue that the clinical benefits have been massively overstated. This debate often fails to recognize that the challenge is not merely to improve understanding of genetic risk, but to capture more about the interwoven, multifaceted factors that play into disease risk. Perhaps a more pertinent argument would be that clinical medicine must learn to develop more-holistic measures of individual risk, both genetic and non-genetic, and to combine these with clinical data over time to deliver better care. Although current polygenic scores hold clinical promise, they come with several limitations. They leave out many sources of relevant data, and work best for the predominantly white, wealthy populations in which most genetic studies have been performed. The emphasis on genetic risk diverts attention away from non-genetic factors that might be equally important for disease risk and progression. Risk estimation on the basis of polygenic scores alone also fails to incorporate real-time measurements of clinical state that are especially important in diseases linked to aging. As a way of moving forward, researchers, funders, and industry need to embrace greater diversity in the design and implementation of studies, focusing not only on gender and ethnicity, but also on social, cultural, and economic factors that influence disease risk and access to health care.