Meta-analysis of African ancestry genome-wide association studies identified novel locus and validates multiple loci associated with kidney function

BMC Genomics

Research

Daudi Jjingo¹  Bernard S. Bagaya²  Robert Kalyesubula³  Tafadzwa Machipisa⁴  Tinashe Chikowore⁵  Christopher Kintu⁶  Richard Mayanja⁷  Opeyemi Soremekun⁸  Segun Fatumo⁹ 

[1] African Center of Excellence in Bioinformatics (ACE-B), Makerere University, 10101, Kampala, Uganda;Department of Computer Science, College of Computing, Makerere University, Kampala, Uganda;Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda;Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda;MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda;Department of Medicine, University of Cape Town & Groote Schuur Hospital, Cape Town, South Africa;MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa;Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa;Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA;Harvard Medical School, Boston, MA, USA;The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda;Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda;The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda;Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda;MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda;The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda;MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda;The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda;MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda;Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK;

关键词: GWAS;    Africa;    Kidney function;    Fine mapping;    eGFR;   

DOI  :  10.1186/s12864-023-09601-0

 received in 2023-02-11, accepted in 2023-08-17,  发布年份 2023

来源: Springer

【 摘 要 】

Despite recent efforts to increase diversity in genome-wide association studies (GWASs), most loci currently associated with kidney function are still limited to European ancestry due to the underlying sample selection bias in available GWASs. We set out to identify susceptibility loci associated with estimated glomerular filtration rate (eGFRcrea) in 80027 individuals of African-ancestry from the UK Biobank (UKBB), Million Veteran Program (MVP), and Chronic Kidney Disease genetics (CKDGen) consortia.We identified 8 lead SNPs, 7 of which were previously associated with eGFR in other populations. We identified one novel variant, rs77408001 which is an intronic variant mapped to the ELN gene. We validated three previously reported loci at GATM-SPATA5L1, SLC15A5 and AGPAT3. Fine-mapping analysis identified variants rs77121243 and rs201602445 as having a 99.9% posterior probability of being causal. Our results warrant designing bigger studies within individuals of African ancestry to gain new insights into the pathogenesis of Chronic Kidney Disease (CKD), and identify genomic variants unique to this ancestry that may influence renal function and disease.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

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