Importance of genetic ancestry in pharmacogenomics for precision medicine.

Genetic ancestry refers to an individual's biogeographical origins inferred from correlated allele frequencies shared with individuals from similar ancestral regions. Understanding the complexities of genetic ancestry has proven beneficial in the field of pharmacogenomics (PGx), where personalized medication regimens are optimizing therapeutic outcomes while minimizing the risk of side effects. With the rise in the availability of electronic health records (EHR), population-specific genetic data can be integrated with clinical data using machine learning approaches to improve personalized treatment plans. Furthermore, multiomics data such as the transcriptome, methylome, proteome, and metabolome, paired with advances in machine learning methods, provide a more comprehensive approach to understanding genetic variation. The expansion of PGx studies in diverse populations can broaden the impact of precision medicine, particularly among underrepresented groups.VenkateshRasikaRDepartment of Genetics, University of Pennsylvania, Philadelphia, PA, USA.KeatKarlKDepartment of Genetics, University of Pennsylvania, Philadelphia, PA, USA.SalvatoreMaxwellMDepartment of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA.CindiZinhleZDepartment of Genetics, University of Pennsylvania, Philadelphia, PA, USA.HallMolly AMADepartment of Genetics, University of Pennsylvania, Philadelphia, PA, USA.RitchieMarylyn DMD0000-0002-1208-1720Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA.Division of Biomedical Informatics and AI, Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.engR01 AI077505AINIAID NIH HHSUnited StatesU24 HG013077HGNHGRI NIH HHSUnited StatesJournal ArticleReview20260207EnglandPharmacogenomics1008973501462-2416IMPrecision MedicinemethodstrendsHumansPharmacogeneticsmethodstrendsMachine LearningElectronic Health RecordsGene FrequencygeneticsGenetic VariationgeneticsPharmacogenomics (PGx) is the study of how a person’s genes affect their response to medicines. The information can help doctors choose the safest and most effective treatment for each patient. As PGx nears real-world clinical use, there is renewed concern about how genetic ancestry, a phenomenon by which people of similar ancestral geographic origins have shared genetic patterns, could impact how we use PGx. Since most human genetics studies have been conducted primarily on individuals who are genetically similar to European reference populations, there is significant concern that their findings do not generalize well to people with different ancestral backgrounds. In PGx, this can mean that genetic factors that influence drug outcomes in non-European populations could be absent from clinical guidelines or testing panels.The accuracy of newer genetic prediction methods that combine thousands of genetic variants, known as polygenic scores (PGS), is especially influenced by genetic ancestry. PGS derived from one ancestry group tend to predict health outcomes significantly worse in people who have less genetic similarity to the original population. Altogether, failing to account for ancestry in PGx has the potential to exacerbate health disparities. Fortunately, the increasing availability of large, diverse genetic datasets and new types of biological data along with artificial intelligence approaches show promise for addressing some of these risks.