Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits

• Published in: Nature communications 2022-05, Vol.13 (1), p.2578-2578, Article 2578
• Main Authors: Choudhury, Ananyo, Brandenburg, Jean-Tristan, Chikowore, Tinashe, Sengupta, Dhriti, Boua, Palwende Romuald, Crowther, Nigel J., Agongo, Godfred, Asiki, Gershim, Gómez-Olivé, F. Xavier, Kisiangani, Isaac, Maimela, Eric, Masemola-Maphutha, Matshane, Micklesfield, Lisa K., Nonterah, Engelbert A., Norris, Shane A., Sorgho, Hermann, Tinto, Halidou, Tollman, Stephen, Graham, Sarah E., Willer, Cristen J., Hazelhurst, Scott, Ramsay, Michèle
• Format: Article
• Language: English
• Subjects: 45/43; 631/208/205/2138; 631/208/480; 692/499; 692/699/75; Africa South of the Sahara; African studies; Cholesterol, LDL - genetics; Cross-Sectional Studies; Datasets; FHIT protein; Gene mapping; Genetic distance; Genome-Wide Association Study; Humanities and Social Sciences; Humans; Lipids; Low density lipoprotein; Meta-analysis; multidisciplinary; Polygenic inheritance; Risk analysis; Science; Science (multidisciplinary); Triglycerides
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-022-30098-w

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. Genetic associations and polygenic scores for lipid traits have low transferability to African individuals. Here, the authors perform a large sub-Sarahan African lipid GWAS and find that larger datasets and better global representation in discovery GWAS help to bridge this gap.