medRxiv preprint doi: https://doi.org/10.1101/2021.07.12.21259837; this version posted July 16, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Harnessing the power of polygenic risk scores to predict type 2 diabetes and its subtypes in a high-risk population of British Pakistanis and Bangladeshis in a routine healthcare setting Authors Sam Hodgson*,1, Qin Qin Huang*,2, Neneh Sallah3,4, Genes & Health Research Team5, Chris J Griffiths6, William G Newman7, Richard C Trembath9, Thomas Lumbers3,4,10, Karoline Kuchenbaecker4,11, David A. van Heel5, Rohini Mathur12, Hilary Martin#,2 & Sarah Finer#,6,% * These authors contributed equally. # These authors contributed equally. % Corresponding author
[email protected] 1. Primary Care Research Centre, University of Southampton, UK 2. Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK 3. Institute of Health Informatics, University College London, London, UK 4. UCL Genetics Institute, University College London, London, UK 5. Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK 6. Institute for Population Health Sciences, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK 7. Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK 8. Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK 9.