Multi-trait discovery and fine-mapping of lipid loci in 125,000 individuals of African ancestry

Abram Bunya Kamiza; Sounkou M Touré; Feng Zhou; Opeyemi Soremekun; Cheickna Cissé; Mamadou Wélé; Aboubacrine M Touré; Oyekanmi Nashiru; Manuel Corpas; Moffat Nyirenda; Amelia Crampin; Jeffrey Shaffer; Seydou Doumbia; Eleftheria Zeggini; Andrew P Morris; Jennifer L Asimit; Tinashe Chikowore; Segun Fatumo

doi:10.1038/s41467-023-41271-0

Multi-trait discovery and fine-mapping of lipid loci in 125,000 individuals of African ancestry

Nat Commun. 2023 Sep 5;14(1):5403. doi: 10.1038/s41467-023-41271-0.

Authors

Abram Bunya Kamiza^#^{1

2

3}, Sounkou M Touré^#^{1

4}, Feng Zhou^#⁵, Opeyemi Soremekun¹, Cheickna Cissé^{4

6}, Mamadou Wélé^{2

6}, Aboubacrine M Touré⁶, Oyekanmi Nashiru⁷, Manuel Corpas⁸, Moffat Nyirenda⁹, Amelia Crampin², Jeffrey Shaffer¹⁰, Seydou Doumbia^{4

11}, Eleftheria Zeggini^{12

13}, Andrew P Morris¹⁴, Jennifer L Asimit⁵, Tinashe Chikowore^{3

15

16

17}, Segun Fatumo^{18

19

20

21}

Affiliations

¹ The African Computational Genomic (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda.
² Malawi Epidemiology and Intervention Research Unit, Lilongwe, Malawi.
³ Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
⁴ African Center of Excellence in Bioinformatics, University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali.
⁵ MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
⁶ Faculty of Sciences and Techniques, University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali.
⁷ H3Africa Bioinformatics Network (H3ABioNet) Node, Center for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria.
⁸ School of Life sciences, University of Westminster, London, UK.
⁹ Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe, Uganda.
¹⁰ Department of Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA.
¹¹ Faculty of Medicine and Odonto-stomatology, University of Sciences, Techniques and Technologies of Bamako, Bamako, Mali.
¹² Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
¹³ TUM School of Medicine, Translational Genomics, Technical University of Munich and Klinikum Rechts der Isar, Munich, Germany.
¹⁴ Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, University of Manchester, Manchester, UK.
¹⁵ Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
¹⁶ Harvard Medical School, Boston, MA, USA.
¹⁷ MRC/Wits Developmental Pathways for Health Research Unit, Department of Pediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
¹⁸ The African Computational Genomic (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda. segun.fatumo@lshtm.ac.uk.
¹⁹ H3Africa Bioinformatics Network (H3ABioNet) Node, Center for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria. segun.fatumo@lshtm.ac.uk.
²⁰ Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany. segun.fatumo@lshtm.ac.uk.
²¹ Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK. segun.fatumo@lshtm.ac.uk.

^# Contributed equally.

Abstract

Most genome-wide association studies (GWAS) for lipid traits focus on the separate analysis of lipid traits. Moreover, there are limited GWASs evaluating the genetic variants associated with multiple lipid traits in African ancestry. To further identify and localize loci with pleiotropic effects on lipid traits, we conducted a genome-wide meta-analysis, multi-trait analysis of GWAS (MTAG), and multi-trait fine-mapping (flashfm) in 125,000 individuals of African ancestry. Our meta-analysis and MTAG identified four and 14 novel loci associated with lipid traits, respectively. flashfm yielded an 18% mean reduction in the 99% credible set size compared to single-trait fine-mapping with JAM. Moreover, we identified more genetic variants with a posterior probability of causality >0.9 with flashfm than with JAM. In conclusion, we identified additional novel loci associated with lipid traits, and flashfm reduced the 99% credible set size to identify causal genetic variants associated with multiple lipid traits in African ancestry.

Publication types

Meta-Analysis
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural

MeSH terms

Black People
Genome-Wide Association Study*
Humans
Lipids* / genetics
Phenotype

Substances

Lipids

Abstract

Publication types

MeSH terms

Substances

Grants and funding