Genetic risk scores for diabetes diagnosis and precision medicine Miriam S. Udler, Mark I McCarthy, Jose C. Florez, Anubha Mahajan Endocrine Reviews Endocrine Society Submitted: April 26, 2019 Accepted: July 08, 2019 First Online: July 19, 2019 Advance Articles are PDF versions of manuscripts that have been peer reviewed and accepted but not yet copyedited. The manuscripts are published online as soon as possible after acceptance and before the copyedited, typeset articles are published. They are posted "as is" (i.e., as submitted by the authors at the modification stage), and do not reflect editorial changes. No corrections/changes to the PDF manuscripts are accepted. Accordingly, there likely will be differences between the Advance Article manuscripts and the final, typeset articles. The manuscripts remain listed on the Advance Article page until the final, typeset articles are posted. At that point, the manuscripts are removed from the Advance Article page. DISCLAIMER: These manuscripts are provided "as is" without warranty of any kind, either express or particular purpose, or non-infringement. Changes will be made to these manuscripts before publication. Review and/or use or reliance on these materials is at the discretion and risk of the reader/user. In no event shall the Endocrine Society be liable for damages of any kind arising references to, products or publications do not imply endorsement of that product or publication. ADVANCE ARTICLE: Endocrine Reviews Downloaded from https://academic.oup.com/edrv/advance-article-abstract/doi/10.1210/er.2019-00088/5535575 by 81225740 user on 24 July 2019 ADVANCE ARTICLE Endocrine Reviews; Copyright 2019 DOI: 10.1210/er.2019-00088 1 Genetic risk scores for diabetes diagnosis and precision medicine Genetic risk scores for diabetes Miriam S. Udler1-4, Mark I McCarthy5-7, Jose C. Florez1-4, Anubha Mahajan6 1. Diabetes Unit, Massachusetts General Hospital, 50 Staniford St, Boston, MA 02114 2. Center for Genomic Medicine, Massachusetts General Hospital, Simches Research Building, 185 Cambridge St, Boston, MA 02114 3. Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, 415 Main St, Cambridge, MA 02142 4. Department of Medicine, Harvard Medical School, 25 Shattuck Street, Boston MA 02115 5. Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Old Road, Headington, Oxford, OX3 7LJ UK 6. Wellcome Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK 7. Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, OX3 9DU, UK ORCiD numbers: 0000-0003-3824-9162 Udler Miriam S. 0000-0002-4393-0510 McCarthy Mark I 0000-0002-1730-9325 Florez Jose C. 0000-0001-5585-3420 Mahajan Anubha Received 26 April 2019. Accepted 08 July 2019. ORCID identifiers Mark McCarthy ORCID: 0000-0002-4393-0510 Anubha Mahajan ORCID: 0000-0001-5585-3420 Jose Florez ORCID: 0000-0002-1730-9325 Miriam Udler ORCID: 0000-0003-3824-9162 Over the last decade, there have been substantial advances in the identification and characterization of DNA sequence variants associated with individual predisposition to type 1 ADVANCE ARTICLE: Endocrine Reviews Downloaded from https://academic.oup.com/edrv/advance-article-abstract/doi/10.1210/er.2019-00088/5535575 by 81225740 user on 24 July 2019 ADVANCE ARTICLE Endocrine Reviews; Copyright 2019 DOI: 10.1210/er.2019-00088 2 and type 2 diabetes. As well as providing insights into the molecular, cellular and physiological mechanisms involved in disease pathogenesis, these risk variants, when combined into a polygenic score, capture information on individual patterns of disease predisposition that have the potential to influence clinical management. In this review, we describe the various opportunities that polygenic scores provide: to predict diabetes risk, to support differential diagnosis, and to understand phenotypic and clinical heterogeneity. We also describe the challenges that will need to be overcome if this potential is to be fully realized. SEARCH STRATEGY The literature referenced in this article was selected for inclusion on the basis of the authors’ expertise in this area of research, based on a broader set of publications sourced from PubMed and other repositories using relevant search terms, including, but not limited to, “polygenic scores”, “risk scores”, “precision medicine”, “diabetes” and combinations thereof. ESSENTIAL POINTS • Over the last decade, there have been major advances in our understanding of the genetic basis of the most common subtypes of type 1 (T1D) and type 2 diabetes (T2D), with over 500 robust associations identified. • Although individual variants typically have only a modest effect on