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Genetic loci implicated in meta-analysis of body shape in Africans.
Nakabuye, Mariam; Kamiza, Abram Bunya; Soremekun, Opeyemi; Machipisa, Tafadzwa; Cohen, Emmanuel; Pirie, Fraser; Nashiru, Oyekanmi; Young, Elizabeth; Sandhu, Manjinder S; Motala, Ayesha A; Chikowore, Tinashe; Fatumo, Segun.
Affiliation
  • Nakabuye M; The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene and Tropical Medicine (LSHTM), Entebbe, Uganda.
  • Kamiza AB; The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene and Tropical Medicine (LSHTM), Entebbe, Uganda; Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the
  • Soremekun O; The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene and Tropical Medicine (LSHTM), Entebbe, Uganda.
  • Machipisa T; Department of Medicine, University of Cape Town & Groote Schuur Hospital, Cape Town, South Africa; Population Health Research Institute (PHRI) & the Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, 1280 Main Street West, Hamilton ON
  • Cohen E; MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; CNRS, UMR 7206 « Eco-anthropologie ¼, Muséum National d'Histoire Naturelle, France.
  • Pirie F; Department of Diabetes and Endocrinology, University of KwaZulu-Natal, Durban, 4013 South Africa.
  • Nashiru O; H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria.
  • Young E; Omnigen Biodata Ltd, Cambridge, United Kingdom.
  • Sandhu MS; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom.
  • Motala AA; Department of Diabetes and Endocrinology, University of KwaZulu-Natal, Durban, 4013 South Africa.
  • Chikowore T; Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg,
  • Fatumo S; The African Computational Genomics (TACG) Research Group, Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Hygiene and Tropical Medicine (LSHTM), Entebbe, Uganda; H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NA
Nutr Metab Cardiovasc Dis ; 32(6): 1511-1518, 2022 06.
Article in En | MEDLINE | ID: mdl-35461751
BACKGROUND AND AIMS: Obesity is one of the leading causes of non-communicable diseases (NCD). Thus, NCD risk varies in obese individuals based on the location of their fat depots; while subcutaneous adiposity is protective, visceral adiposity increases NCD risk. Although, previously anthropometric traits have been used to quantify body shape in low-income settings, there is no consensus on how it should be assessed. Hence, there is a growing interest to evaluate body shape derived from the principal component analysis (PCA) of anthropometric traits; however, this is yet to be explored in individuals of African ancestry whose body shape is different from those of Europeans. We set out to capture body shape in its multidimensional structure and examine the association between genetic variants and body shape in individuals of African ancestry. METHOD AND RESULTS: We performed a genome-wide association study (GWAS) for body shape derived from PCA analysis of anthropometric traits in the Ugandan General Population Cohort (GPC, n = 6407) and the South African Zulu Cohort (SZC, n = 2595), followed by a GWAS meta-analysis to assess the genetic variants associated with body shape. We identified variants in FGF12, GRM8, TLX1NB and TRAP1 to be associated with body shape. These genes were different from the genes been associated with BMI, height, weight, WC and waist-hip ration in continental Africans. Notably, we also observed that a standard deviation change in body shape was associated with an increase in blood pressure and blood lipids. CONCLUSION: Variants associated with body shape, as a composite variable might be different for those of individual anthropometric traits. Larger studies are required to further explore these phenomena.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome-Wide Association Study / Noncommunicable Diseases Type of study: Diagnostic_studies / Prognostic_studies / Systematic_reviews Limits: Humans Language: En Journal: Nutr Metab Cardiovasc Dis Journal subject: ANGIOLOGIA / CARDIOLOGIA / CIENCIAS DA NUTRICAO / METABOLISMO Year: 2022 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genome-Wide Association Study / Noncommunicable Diseases Type of study: Diagnostic_studies / Prognostic_studies / Systematic_reviews Limits: Humans Language: En Journal: Nutr Metab Cardiovasc Dis Journal subject: ANGIOLOGIA / CARDIOLOGIA / CIENCIAS DA NUTRICAO / METABOLISMO Year: 2022 Document type: Article Affiliation country: Country of publication: