Faculty of Health Sciences

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Author: search.filters.author.Engelbert A. NonterahHas files: Yes

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    Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits
    (2022-05-11) Ananyo Choudhury; Jean-Tristan Brandenburg; Tinashe Chikowore; Dhriti Sengupta; Palwende Romuald Boua; Nigel J. Crowther; Godfred Agongo; Gershim Asik; F. Xavier Gómez-Olivé; Isaac Kisiangani; Eric Maimela; Matshane Masemola-Maphutha; Lisa K. Micklesfield; Engelbert A. Nonterah; Shane A. Norris; Hermann Sorgho; Halidou Tinto; Stephen Tollman; Sarah E. Graham; Cristen J. Willer; AWI-Gen study; H3Africa Consortium; Scott Hazelhurst; Michèle Ramsay
    Genetic associations for lipid traits have identified hundreds of variants with clear differences across European, Asian and African studies. Based on a sub-Saharan-African GWAS for lipid traits in the population cross-sectional AWI-Gen cohort (N = 10,603) we report a novel LDL-C association in the GATB region (P-value=1.56 × 10−8). Meta-analysis with four other African cohorts (N = 23,718) provides supporting evidence for the LDL-C association with the GATB/FHIP1A region and identifies a novel triglyceride association signal close to the FHIT gene (P-value =2.66 × 10−8). Our data enable fine-mapping of several well-known lipid-trait loci including LDLR, PMFBP1 and LPA. The transferability of signals detected in two large global studies (GLGC and PAGE) consistently improves with an increase in the size of the African replication cohort. Polygenic risk score analysis shows increased predictive accuracy for LDL-C levels with the narrowing of genetic distance between the discovery dataset and our cohort. Novel discovery is enhanced with the inclusion of African data.
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    Genomic and environmental risk factors for cardiometabolic diseases in Africa: methods used for Phase 1 of the AWI-Gen population cross-sectional study
    (2018-07-12) Stuart A. Al; Cassandra Soo; Godfred Agongo; Marianne Alberts; Lucas Amenga-Etego; Romuald P. Boua; Ananyo Choudhury; Nigel J. Crowther; Cornelius Depuur; F. Xavier GómezOlivé; Issa Guiraud; Tilahun N. Haregu; Scott Hazelhurst; Kathleen Kahn; Christopher Khayeka-Wandabwa; Catherine Kyobutung; Zané Lombard; Felistas Mashinya; Lisa Micklesfield; Shukri F. Mohamed; Freedom Mukomana; Seydou Nakanabo-Diallo; Hamtandi M. Natama; Nicholas Ngomi; Engelbert A. Nonterah; Shane A. Norris; Abraham R. Oduro; Athanase M. Somé; Hermann Sorgho; Paulina Tindana; Halidou Tinto; Stephen Tollman; Rhian Twine; Alisha Wade; Osman Sankoh; Michèle Ramsay
    There is an alarming tide of cardiovascular and metabolic disease (CMD) sweeping across Africa. This may be a result of an increasingly urbanized lifestyle characterized by the growing consumption of processed and calorie-dense food, combined with physical inactivity and more sedentary behaviour. While the link between lifestyle and public health has been extensively studied in Caucasian and African American populations, few studies have been conducted in Africa. This paper describes the detailed methods for Phase 1 of the AWI-Gen study that were used to capture phenotype data and assess the associated risk factors and end points for CMD in persons over the age of 40 years in sub-Saharan Africa (SSA). We developed a population-based cross-sectional study of disease burden and phenotype in Africans, across six centres in SSA. These centres are in West Africa (Nanoro, Burkina Faso, and Navrongo, Ghana), in East Africa (Nairobi, Kenya) and in South Africa (Agincourt, Dikgale and Soweto). A total of 10,702 individuals between the ages of 40 and 60 years were recruited into the study across the six centres, plus an additional 1021 participants over the age of 60 years from the Agincourt centre. We collected socio-demographic, anthropometric, medical history, diet, physical activity, fat distribution and alcohol/tobacco consumption data from participants. Blood samples were collected for disease-related biomarker assays, and genomic DNA extraction for genome-wide association studies. Urine samples were collected to assess kidney function. The study provides base-line data for the development of a series of cohorts with a second wave of data collection in Phase 2 of the study. These data will provide valuable insights into the genetic and environmental influences on CMD on the African continent