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

Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits
Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits
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.
2041-1723
Choudhury, Ananyo
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Brandenburg, Jean-Tristan
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Chikowore, Tinashe
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Sengupta, Dhriti
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Boua, Palwende Romuald
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Crowther, Nigel J.
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Agongo, Godfred
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Asiki, Gershim
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Gomez-Olive, F. Xavier
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Kisiangani, Isaac
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Maimela, Eric
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Masemola-Maphutha, Matshane
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Micklesfield, Lisa K.
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Nonterah, Engelbert A.
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Norris, Shane A.
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Sorgho, Hermann
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Tinto, Halidou
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Tollman, Stephen
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Graham, Sarah E.
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Willer, Cristen J.
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Hazelhurst, Scott
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Ramsay, Michele
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AWI-Gen Study
H3Africa Consortium
Choudhury, Ananyo
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Brandenburg, Jean-Tristan
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Chikowore, Tinashe
b53b1cb9-8363-4e2c-9d62-dc3a8627a7b5
Sengupta, Dhriti
698f82dc-9f62-4ea1-b716-7ee02ebc53ab
Boua, Palwende Romuald
4b08fe0e-4c96-4f55-ac1f-9048a777ebcf
Crowther, Nigel J.
ca4aa5ba-4f92-4c4d-9736-1dcf303dee40
Agongo, Godfred
0d335cba-7025-45bb-bb5b-86c09c2ee944
Asiki, Gershim
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Gomez-Olive, F. Xavier
55cd5c65-ba41-43ae-b575-5b096e451c32
Kisiangani, Isaac
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Maimela, Eric
94078408-d83a-4a34-a8f0-3b6e2078687c
Masemola-Maphutha, Matshane
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Micklesfield, Lisa K.
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Nonterah, Engelbert A.
aacb7a34-ceef-4a9f-93b8-707a29db42c6
Norris, Shane A.
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Sorgho, Hermann
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Tinto, Halidou
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Tollman, Stephen
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Graham, Sarah E.
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Willer, Cristen J.
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Hazelhurst, Scott
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Ramsay, Michele
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Choudhury, Ananyo, Brandenburg, Jean-Tristan, Chikowore, Tinashe, Sengupta, Dhriti, Boua, Palwende Romuald, Crowther, Nigel J., Agongo, Godfred, Asiki, Gershim, Gomez-Olive, 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. and Willer, Cristen J. , AWI-Gen Study and H3Africa Consortium (2022) Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits. Nature Communications, 13, [2578]. (doi:10.1038/S41467-022-30098-W).

Record type: Article

Abstract

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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Submitted date: 21 July 2021
Accepted/In Press date: 18 April 2022
Published date: 11 May 2022

Identifiers

Local EPrints ID: 504430
URI: http://eprints.soton.ac.uk/id/eprint/504430
ISSN: 2041-1723
PURE UUID: e375b425-15e4-4a17-83bf-3383abb7ee3e
ORCID for Shane A. Norris: ORCID iD orcid.org/0000-0001-7124-3788

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Date deposited: 09 Sep 2025 17:21
Last modified: 11 Sep 2025 03:09

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Contributors

Author: Ananyo Choudhury
Author: Jean-Tristan Brandenburg
Author: Tinashe Chikowore
Author: Dhriti Sengupta
Author: Palwende Romuald Boua
Author: Nigel J. Crowther
Author: Godfred Agongo
Author: Gershim Asiki
Author: F. Xavier Gomez-Olive
Author: Isaac Kisiangani
Author: Eric Maimela
Author: Matshane Masemola-Maphutha
Author: Lisa K. Micklesfield
Author: Engelbert A. Nonterah
Author: Shane A. Norris ORCID iD
Author: Hermann Sorgho
Author: Halidou Tinto
Author: Stephen Tollman
Author: Sarah E. Graham
Author: Cristen J. Willer
Author: Scott Hazelhurst
Author: Michele Ramsay
Corporate Author: AWI-Gen Study
Corporate Author: H3Africa Consortium

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