Genome-wide association study identifying novel risk variants associated with glycaemic traits in the continental African AWI-Gen cohort

Abstract

Aims/hypothesis

Glycaemic traits such as high fasting glucose levels and insulin resistance are positively associated with the risk of type 2 diabetes and other cardiometabolic diseases. Genetic association studies have identified hundreds of associations for each glycaemic trait, yet very few studies have involved continental African populations. We report the results of genome-wide association studies (GWASs) in a pan-African cohort for four glycaemic traits, namely fasting glucose, fasting insulin, insulin resistance (HOMA-IR) and beta cell function (HOMA-B), which are quantitative variables that affect the risk of developing type 2 diabetes.

Methods

GWASs for the four traits were conducted in approximately 10,000 individuals from the Africa Wits-INDEPTH Partnership for Genomics Studies (AWI-Gen) cohort, with participants from Burkina Faso, Ghana, Kenya and South Africa. Association testing was performed using linear mixed models implemented in BOLT-LMM, with age, sex, BMI and principal components as covariates. Replication, fine mapping and functional annotation were performed using standard approaches.

Results

We identified a novel signal (rs574173815) in the intron of the ankyrin repeat domain 33B (ANKRD33B) gene associated with fasting glucose, and a novel signal (rs114029796) in the intronic region of the WD repeat domain 7 (WDR7) gene associated with fasting insulin. SNPs in WDR7 have been shown to be associated with type 2 diabetes. A variant (rs74806991) in the intron of ADAM metallopeptidase with thrombospondin type 1 motif 16 (ADAMTS16) and another variant (rs6506934) in the β-1,4-galactosyltransferase 6 gene (B4GALT6) are associated with HOMA-IR. Both ADAMTS16 and B4GALT6 are implicated in the development of type 2 diabetes. In addition, our study replicated several well-established fasting glucose signals in the GCK-YTK6, SLC2A2 and THORLNC gene regions.

Conclusions/interpretation

Our findings highlight the importance of performing GWASs for glycaemic traits in under-represented populations, especially continental African populations, to discover novel associated variants and broaden our knowledge of the genetic aetiology of glycaemic traits. The limited replication of well-known signals in this study hints at the possibility of a unique genetic architecture of these traits in African populations.

Data availability

The dataset used in this study is available in the European Genome–Phenome Archive (EGA) database (https://ega-archive.org/) under study accession code EGAS00001002482. The phenotype dataset accession code is EGAD00001006425 and the genotype dataset accession code is EGAD00010001996. The availability of these datasets is subject to controlled access by the Data and Biospecimen Access Committee of the H3Africa Consortium. GWAS summary statistics are accessible through the NHGRI-EBI GWAS Catalog (https://www.ebi.ac.uk/gwas/).

Graphical Abstract