@article{8e30fd9a3cf7485aa8d211ff95013599,
title = "Transferability of genetic loci and polygenic scores for cardiometabolic traits in British Pakistani and Bangladeshi individuals",
abstract = "Individuals with South Asian ancestry have a higher risk of heart disease than other groups but have been largely excluded from genetic research. Using data from 22,000 British Pakistani and Bangladeshi individuals with linked electronic health records from the Genes & Health cohort, we conducted genome-wide association studies of coronary artery disease and its key risk factors. Using power-adjusted transferability ratios, we found evidence for transferability for the majority of cardiometabolic loci powered to replicate. The performance of polygenic scores was high for lipids and blood pressure, but lower for BMI and coronary artery disease. Adding a polygenic score for coronary artery disease to clinical risk factors showed significant improvement in reclassification. In Mendelian randomisation using transferable loci as instruments, our findings were consistent with results in European-ancestry individuals. Taken together, trait-specific transferability of trait loci between populations is an important consideration with implications for risk prediction and causal inference.",
author = "Huang, {Qin Qin} and Neneh Sallah and Diana Dunca and Bhavi Trivedi and Hunt, {Karen A.} and Sam Hodgson and Lambert, {Samuel A.} and Elena Arciero and John Wright and Chris Griffiths and Trembath, {Richard C.} and Harry Hemingway and Michael Inouye and Sarah Finer and {van Heel}, {David A.} and Lumbers, {R. Thomas} and Martin, {Hilary C.} and Karoline Kuchenbaecker",
note = "Funding Information: We thank Social Action for Health, Centre of The Cell, members of our Community Advisory Group, and staff who have recruited and collected data from volunteers. We thank the NIHR National Biosample Centre (UK Biocentre), the Social Genetic & Developmental Psychiatry Centre (King{\textquoteright}s College London), Wellcome Sanger Institute, and Broad Institute for sample processing, genotyping, sequencing and variant annotation. We thank Barts Health NHS Trust, NHS Clinical Commissioning Groups (Hackney, Waltham Forest, Tower Hamlets, Newham), East London NHS Foundation Trust, Bradford Teaching Hospitals NHS Foundation Trust, and Public Health England (especially David Wyllie) for GDPR-compliant data sharing. We thank all members from the Genes & Health Research Team (full list in the Supplementary Information). We also thank Sally Hull and Martin Sharp from the primary care data team at QMUL for their help in estimating population prevalence of CAD. Most of all we thank all of the volunteers participating in Genes & Health. Genes & Health is/has recently been core-funded by Wellcome (WT102627, WT210561), the Medical Research Council (UK) (M009017), Higher Education Funding Council for England Catalyst, Barts Charity (845/1796), Health Data Research UK (for London substantive site), and research delivery support from the NHS National Institute for Health Research Clinical Research Network (North Thames). This research was funded in part by the Wellcome Trust Grant 206194 to the Wellcome Sanger Institute. This research was funded in part by the European Research Council (ERC) under the European Union{\textquoteright}s Horizon 2020 research and innovation programme (Grant agreement No. 948561). This work was supported by core funding from the: British Heart Foundation (RG/13/13/30194; RG/18/13/33946), BHF Cambridge Centre of Research Excellence (RE/13/6/30180), and NIHR Cambridge Biomedical Research Centre (BRC-1215-20014) [*The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care]. This work was also supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome. S.A.L. is supported by a Canadian Institutes of Health Research postdoctoral fellowship (MFE-171279). C.G. is supported by the National Institute for Health Research ARC North Thames. M.I. is supported by the Munz Chair of Cardiovascular Prediction and Prevention and the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). M.I. was also supported by the UK Economic and Social Research Council (ES/T013192/1). R.T.L. and N.S. are supported by the BigData@Heart Consortium funded by the Innovative Medicines Initiative-2 Joint Undertaking under grant agreement No. 116074. R.T.L. is additionally supported by the UCL British Heart Foundation Research Accelerator and has received support from a UK Research and Innovation Rutherford Fellowship hosted by Health Data Research UK (MR/S003754/1). For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Funding Information: We thank Social Action for Health, Centre of The Cell, members of our Community Advisory Group, and staff who have recruited and collected data from volunteers. We thank the NIHR National Biosample Centre (UK Biocentre), the Social Genetic & Developmental Psychiatry Centre (King{\textquoteright}s College London), Wellcome Sanger Institute, and Broad Institute for sample processing, genotyping, sequencing and variant annotation. We thank Barts Health NHS Trust, NHS Clinical Commissioning Groups (Hackney, Waltham Forest, Tower Hamlets, Newham), East London NHS Foundation Trust, Bradford Teaching Hospitals NHS Foundation Trust, and Public Health England (especially David Wyllie) for GDPR-compliant data sharing. We thank all members from the Genes & Health Research Team (full list in the Supplementary Information). We also thank Sally Hull and Martin Sharp from the primary care data team at QMUL for their help in estimating population prevalence of CAD. Most of all we thank all of the volunteers participating in Genes & Health. Genes & Health is/has recently been core-funded by Wellcome (WT102627, WT210561), the Medical Research Council (UK) (M009017), Higher Education Funding Council for England Catalyst, Barts Charity (845/1796), Health Data Research UK (for London substantive site), and research delivery support from the NHS National Institute for Health Research Clinical Research Network (North Thames). This research was funded in part by the Wellcome Trust Grant 206194 to the Wellcome Sanger Institute. This research was funded in part by the European Research Council (ERC) under the European Union{\textquoteright}s Horizon 2020 research and innovation programme (Grant agreement No. 948561). Publisher Copyright: {\textcopyright} 2022, Crown.",
year = "2022",
month = aug,
day = "9",
doi = "10.1038/s41467-022-32095-5",
language = "English",
volume = "13",
pages = "4664",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "Nature Publishing Group",
number = "1",
}