Genomics and Precision Medicine: How Can Emerging Technologies Address Population Health Disparities? Join the Conversation.

November 13, 2017 by Wylie Burke, Professor Emeritus and former Chair, Department of Bioethics and Humanities, University of Washington, Charles Rotimi, Director, Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes for Health, Debbie Winn, Division of Cancer Control and Population Sciences, National Cancer Institute, Vence Bonham and Michael Hahn, National Human Genome Research Institute, National Institutes for Health, Muin J, Khoury, Office of Public Health Genomics, Centers for Disease Control and Prevention

different people standing on DNA in front of a world map

different people standing on DNA in front of a world map

Advances in genome sequencing, other “omic” technologies, and big data promise a new era of personalized medicine. However, there is an ongoing discussion how these new technologies can be used to understand and address existing population health disparities. On October 11, 2017, the Precision Medicine and Population Health Interest Group in the Division of Cancer Control and Population Sciences at the National Cancer Institute, the National Institutes for Health Genomics and Health Disparities Interest Group , and the CDC Office of Public Health Genomics co-sponsored a special one-hour online webinar that explored the intersection of genomics, precision medicine, and health disparities. Over 300 people virtually attended the webinar and engaged in a lively questions and answers session. (Watch the one-hour webinar online. Download the slide presentations for Dr. Rotimi[PDF 3.48 MB] and Dr. Burke[PDF 452 KB].)

Essentially, new genomic and other precision medicine technologies offer insights into some population variation in disease prevalence, but do not explain the systematic differences in health outcomes seen among different populations. Health disparities are due largely to differences in social and environmental factors (e.g. equitable access to healthy foods, education, employment, health care, and safe environments), resulting in poorer health outcomes, across many disease conditions throughout the lifespan. Genetic variation among populations can, however, account for some differences in disease prevalence. These differences will sometimes align with health disparity outcomes; but, sometimes not. For example, APOL1 gene variants contribute to increased kidney disease risk among African Americans, adding to social factors (such as, institutional racism, poverty, and barriers to high quality health care) that contribute to this health disparity. Conversely, African Americans have a lower prevalence of other diseases, such as melanoma and acute lymphoblastic leukemia, due to protective genetic factors. Yet, those who develop these diseases experience poorer survival due to social factors and differential access to healthcare.

In addition to offering some insights into disease prevalence, population genetic differences must be considered in developing genomic medicine. Pharmacogenomics provides an example of how prevalence of gene variants affecting drug response can differ among different populations. For instance, patients infected with hepatitis C virus are usually treated with peginterferon and ribavirin to prevent progressive hepatic fibrosis, cirrhosis, and hepatocellular carcinoma. Response to treatment varies considerably with about half of patients showing sustained virological response after the standard course of treatment. For unclear reasons, African Americans have been known to be less responsive to treatment, independent of other host and viral factors. Two recent genomic studies (here and here) provided insight into observed ethnic disparities in treatment response by identifying a genetic variant in the IL28B gene that is an important predictor of treatment response and spontaneous clearance in patients infected with hepatitis C virus. Notably, allele frequencies differ between ethnic groups, explaining the observed differences in response rates between European Americans (68%), African Americans (36%), and Asians (95%). Indeed, the IL28B genetic variant may explain at least half of the difference in response rates observed between European Americans and African Americans who received the same treatment. Effective use of pharmacogenetics to increase the safety and efficacy of drug treatment will require research in diverse populations to ensure accurate identification of all relevant variants. Yet, most genomic data currently available derive from European populations. Efforts to increase the diversity of populations participating in genomic research will help to prevent healthcare disparities in genomic medicine in the future.

It is important to realize that the tools of precision medicine and public health present complementary approaches to disease prevention and treatment in populations experiencing health-related disparities. As public health sciences begin to use more complex sources of data, better surveillance, and targeted implementation strategies (i.e., precision public health ), such studies may yield findings that could potentially improve our understanding of disease, and address subsets of the population that need available interventions the most. Ultimately, we will need both population approaches and individual precision interventions to improve overall population health and help reduce health disparities.

If you are interested in joining the conversation, please contribute your thoughts and feedback to the discussion on the role of genomics and precision medicine in health disparities. Submit your comments here.

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