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Validity of European-centric cardiometabolic polygenic scores in multi-ancestry populations.
Topriceanu, Constantin-Cristian; Chaturvedi, Nish; Mathur, Rohini; Garfield, Victoria.
Afiliação
  • Topriceanu CC; Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, University College London, Gower Street, London, WC1E 6BT, UK. zchatop@ucl.ac.uk.
  • Chaturvedi N; MRC Unit for Lifelong Health and Ageing, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK. zchatop@ucl.ac.uk.
  • Mathur R; Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, University College London, Gower Street, London, WC1E 6BT, UK.
  • Garfield V; MRC Unit for Lifelong Health and Ageing, University College London, 1-19 Torrington Place, London, WC1E 7HB, UK.
Eur J Hum Genet ; 32(6): 697-707, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38182743
ABSTRACT
Polygenic scores (PGSs) provide an individual level estimate of genetic risk for any given disease. Since most PGSs have been derived from genome wide association studies (GWASs) conducted in populations of White European ancestry, their validity in other ancestry groups remains unconfirmed. This is especially relevant for cardiometabolic diseases which are known to disproportionately affect people of non-European ancestry. Thus, we aimed to evaluate the performance of PGSs for glycaemic traits (glycated haemoglobin, and type 1 and type 2 diabetes mellitus), cardiometabolic risk factors (body mass index, hypertension, high- and low-density lipoproteins, and total cholesterol and triglycerides) and cardiovascular diseases (including stroke and coronary artery disease) in people of White European, South Asian, and African Caribbean ethnicity in the UK Biobank. Whilst PGSs incorporated some GWAS data from multi-ethnic populations, the vast majority originated from White Europeans. For most outcomes, PGSs derived mostly from European populations had an overall better performance in White Europeans compared to South Asians and African Caribbeans. Thus, multi-ancestry GWAS data are needed to derive ancestry stratified PGSs to tackle health inequalities.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Herança Multifatorial / População Branca Tipo de estudo: Risk_factors_studies Limite: Female / Humans / Male / Middle aged País/Região como assunto: Europa Idioma: En Revista: Eur J Hum Genet / Eur. j. hum. genet / European journal of human genetics Assunto da revista: GENETICA MEDICA Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Herança Multifatorial / População Branca Tipo de estudo: Risk_factors_studies Limite: Female / Humans / Male / Middle aged País/Região como assunto: Europa Idioma: En Revista: Eur J Hum Genet / Eur. j. hum. genet / European journal of human genetics Assunto da revista: GENETICA MEDICA Ano de publicação: 2024 Tipo de documento: Article