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Abstract
Smoking is a leading risk factor for many of the top ten causes of death worldwide. Of the 1.3 billion smokers globally, 80% live in low- and middle-income countries, where the number of deaths due to tobacco use is expected to double in the next decade according to the World Health Organization. Genetic studies have helped to identify biological pathways for smoking behaviours, but have mostly focussed on individuals of European ancestry or living in either North America or Europe. We performed a genome-wide association study of two smoking behaviour traits in 10,558 men of African ancestry living in five African countries and the UK. Eight independent variants were associated with either smoking initiation or cessation at P-value < 5 × 10–6, four being monomorphic or rare in European populations. Gene prioritisation strategy highlighted five genes, including SEMA6D, previously described as associated with several smoking behaviour traits. These results confirm the importance of analysing underrepresented populations in genetic epidemiology, and the urgent need for larger genomic studies to boost discovery power to better understand smoking behaviours, as well as many other traits.
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Details
1 University of Leicester, Genetic Epidemiology Group, Department of Population Health Sciences, Leicester, UK (GRID:grid.9918.9) (ISNI:0000 0004 1936 8411)
2 Institut de Recherche en Sciences de La Santé, Clinical Research Unit of Nanoro, Nanoro, Burkina Faso (GRID:grid.457337.1) (ISNI:0000 0004 0564 0509); University of the Witwatersrand, Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, Johannesburg, South Africa (GRID:grid.11951.3d) (ISNI:0000 0004 1937 1135); University of the Witwatersrand, Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, Johannesburg, South Africa (GRID:grid.11951.3d) (ISNI:0000 0004 1937 1135)
3 Makerere University, Department of Immunology and Molecular Biology, College of Health Science, Kampala, Uganda (GRID:grid.11194.3c) (ISNI:0000 0004 0620 0548); National Biotechnology Development Agency CGRI/NABDA, H3Africa Bioinformatics Network (H3ABioNet) Node, Center for Genomics Research and Innovation (CGRI), Abuja, Nigeria (GRID:grid.11194.3c); MRC/UVRI LSHTM Uganda Research Unit, The African Computational Genomics (TACG) Research Group, Entebbe, Uganda (GRID:grid.415861.f) (ISNI:0000 0004 1790 6116)
4 University of the Witwatersrand, Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, Johannesburg, South Africa (GRID:grid.11951.3d) (ISNI:0000 0004 1937 1135)
5 University of Leicester, Genetic Epidemiology Group, Department of Population Health Sciences, Leicester, UK (GRID:grid.9918.9) (ISNI:0000 0004 1936 8411); Glenfield Hospital, National Institute for Health Research Leicester Respiratory Biomedical Research Centre, Leicester, UK (GRID:grid.412925.9) (ISNI:0000 0004 0400 6581)
6 University of the Witwatersrand, Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, Johannesburg, South Africa (GRID:grid.11951.3d) (ISNI:0000 0004 1937 1135); University of the Witwatersrand, Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, Johannesburg, South Africa (GRID:grid.11951.3d) (ISNI:0000 0004 1937 1135)
7 National Biotechnology Development Agency CGRI/NABDA, H3Africa Bioinformatics Network (H3ABioNet) Node, Center for Genomics Research and Innovation (CGRI), Abuja, Nigeria (GRID:grid.11951.3d); MRC/UVRI LSHTM Uganda Research Unit, The African Computational Genomics (TACG) Research Group, Entebbe, Uganda (GRID:grid.415861.f) (ISNI:0000 0004 1790 6116); London School of Hygiene and Tropical Medicine, Department of Non-Communicable Disease Epidemiology (NCDE), London, UK (GRID:grid.8991.9) (ISNI:0000 0004 0425 469X)