| Title: | Genome-wide association study of type 2 diabetes in Africa |
| Journal: | Diabetologia |
| Published: | 2 May 2019 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/31049640/ |
| DOI: | https://doi.org/10.1007/s00125-019-4880-7 |
| URL: | https://link.springer.com/content/pdf/10.1007/s00125-019-4880-7.pdf |
Publication 8833
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Abstract
Aims/hypothesisGenome-wide association studies (GWAS) for type 2 diabetes have uncovered >400 risk loci, primarily in populations of European and Asian ancestry. Here, we aimed to discover additional type 2 diabetes risk loci (including African-specific variants) and fine-map association signals by performing genetic analysis in African populations.MethodsWe conducted two type 2 diabetes genome-wide association studies in 4347 Africans from South Africa, Nigeria, Ghana and Kenya and meta-analysed both studies together. Likely causal variants were identified using fine-mapping approaches.ResultsThe most significantly associated variants mapped to the widely replicated type 2 diabetes risk locus near TCF7L2 (p = 5.3 × 10−13). Fine-mapping of the TCF7L2 locus suggested one type 2 diabetes association signal shared between Europeans and Africans (indexed by rs7903146) and a distinct African-specific signal (indexed by rs17746147). We also detected one novel signal, rs73284431, near AGMO (p = 5.2 × 10−9, minor allele frequency [MAF] = 0.095; monomorphic in most non-African populations), distinct from previously reported signals in the region. In analyses focused on 100 published type 2 diabetes risk loci, we identified 21 with shared causal variants in African and non-African populations.Conclusions/interpretationThese results demonstrate the value of performing GWAS in Africans, provide a resource to larger consortia for further discovery and fine-mapping and indicate that additional large-scale efforts in Africa are warranted to gain further insight in to the genetic architecture of type 2 diabetes.</p>
17 Authors
- Ji Chen
- Meng Sun
- Adebowale Adeyemo
- Fraser Pirie
- Tommy Carstensen
- Cristina Pomilla
- Ayo P. Doumatey
- Guanjie Chen
- Elizabeth H. Young
- Manjinder Sandhu
- Andrew P. Morris
- Inês Barroso
- Mark I. McCarthy
- Anubha Mahajan
- Eleanor Wheeler
- Charles N. Rotimi
- Ayesha A. Motala
1 Application
| Application ID | Title |
|---|---|
| 9161 | Type 2 diabetes: using genetic discovery to drive biological inference and translational opportunities. |
Enabling scientific discoveries that improve human health