Genetic analyses of diverse populations improves discovery for complex traits
- PMID: 31217584
- PMCID: PMC6785182
- DOI: 10.1038/s41586-019-1310-4
Genetic analyses of diverse populations improves discovery for complex traits
Abstract
Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions13-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.
Figures
![Extended Data Fig. 1 |](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/6785182/bin/nihms-1050617-f0004.gif)
![Extended Data Fig. 2 |](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/6785182/bin/nihms-1050617-f0005.gif)
![Fig. 1 |](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/6785182/bin/nihms-1050617-f0001.gif)
![Fig. 2 |](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/6785182/bin/nihms-1050617-f0002.gif)
![Fig. 3 |](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/6785182/bin/nihms-1050617-f0003.gif)
Comment in
-
Making the case for more inclusive GWAS.Nat Rev Genet. 2019 Sep;20(9):500-501. doi: 10.1038/s41576-019-0160-0. Nat Rev Genet. 2019. PMID: 31292566 No abstract available.
Similar articles
-
Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics.BMC Genomics. 2020 Mar 14;21(1):228. doi: 10.1186/s12864-020-6626-9. BMC Genomics. 2020. PMID: 32171239 Free PMC article.
-
Genome-wide Association Identifies Novel Etiological Insights Associated with Parkinson's Disease in African and African Admixed Populations.medRxiv [Preprint]. 2023 May 7:2023.05.05.23289529. doi: 10.1101/2023.05.05.23289529. medRxiv. 2023. Update in: Lancet Neurol. 2023 Nov;22(11):1015-1025. doi: 10.1016/S1474-4422(23)00283-1. PMID: 37398408 Free PMC article. Updated. Preprint.
-
Multi-trait GWAS for diverse ancestries: mapping the knowledge gap.BMC Genomics. 2024 Apr 17;25(1):375. doi: 10.1186/s12864-024-10293-3. BMC Genomics. 2024. PMID: 38627641 Free PMC article.
-
Genome-Wide Association Studies of Cancer in Diverse Populations.Cancer Epidemiol Biomarkers Prev. 2018 Apr;27(4):405-417. doi: 10.1158/1055-9965.EPI-17-0169. Epub 2017 Jun 21. Cancer Epidemiol Biomarkers Prev. 2018. PMID: 28637795 Free PMC article. Review.
-
Genetics of Obesity in Diverse Populations.Curr Diab Rep. 2018 Nov 19;18(12):145. doi: 10.1007/s11892-018-1107-0. Curr Diab Rep. 2018. PMID: 30456705 Free PMC article. Review.
Cited by
-
Polygenic risk score portability for common diseases across genetically diverse populations.Hum Genomics. 2024 Sep 2;18(1):93. doi: 10.1186/s40246-024-00664-y. Hum Genomics. 2024. PMID: 39218908 Free PMC article.
-
Rare coding variant analysis for human diseases across biobanks and ancestries.Nat Genet. 2024 Aug 29. doi: 10.1038/s41588-024-01894-5. Online ahead of print. Nat Genet. 2024. PMID: 39210047
-
Forensic height estimation using polygenic score in Korean population.Mol Genet Genomics. 2024 Aug 9;299(1):78. doi: 10.1007/s00438-024-02172-z. Mol Genet Genomics. 2024. PMID: 39120737
-
The interaction of genetics and physical activity in the pathogenesis of metabolic dysfunction associated liver disease.Sci Rep. 2024 Aug 1;14(1):17817. doi: 10.1038/s41598-024-68271-4. Sci Rep. 2024. PMID: 39090170 Free PMC article.
-
A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data.Sci Rep. 2024 Aug 1;14(1):17851. doi: 10.1038/s41598-024-68541-1. Sci Rep. 2024. PMID: 39090161 Free PMC article.
References
-
- Need AC & Goldstein DB Next generation disparities in human genomics: concerns and remedies. Trends Genet. 25, 489–494 (2009). - PubMed
Publication types
MeSH terms
Grants and funding
- U01 HG007419/HG/NHGRI NIH HHS/United States
- HHSN268201100004I/HL/NHLBI NIH HHS/United States
- P01 GM099568/GM/NIGMS NIH HHS/United States
- T32 HL129982/HL/NHLBI NIH HHS/United States
- N01HC65233/HL/NHLBI NIH HHS/United States
- R01 DK101855/DK/NIDDK NIH HHS/United States
- T32 HD049311/HD/NICHD NIH HHS/United States
- U01 HG009080/HG/NHGRI NIH HHS/United States
- T32 HG000044/HG/NHGRI NIH HHS/United States
- T32 HD007168/HD/NICHD NIH HHS/United States
- HHSN268201100004C/WH/WHI NIH HHS/United States
- R01 CA082659/CA/NCI NIH HHS/United States
- U01 HG007417/HG/NHGRI NIH HHS/United States
- HHSN268201100001I/HL/NHLBI NIH HHS/United States
- K99 HL130580/HL/NHLBI NIH HHS/United States
- U01 HG007416/HG/NHGRI NIH HHS/United States
- R01 HG009974/HG/NHGRI NIH HHS/United States
- KL2 TR001109/TR/NCATS NIH HHS/United States
- HHSN268201100046C/HL/NHLBI NIH HHS/United States
- R00 HL130580/HL/NHLBI NIH HHS/United States
- L60 MD008384/MD/NIMHD NIH HHS/United States
- R25 CA094880/CA/NCI NIH HHS/United States
- N01HC65236/HL/NHLBI NIH HHS/United States
- L30 HG009840/HG/NHGRI NIH HHS/United States
- HHSN268201100003C/WH/WHI NIH HHS/United States
- U01 HG007376/HG/NHGRI NIH HHS/United States
- N01HC65235/HL/NHLBI NIH HHS/United States
- U01 AI090905/AI/NIAID NIH HHS/United States
- S10 OD018522/OD/NIH HHS/United States
- N01HC65234/HL/NHLBI NIH HHS/United States
- HHSN268201200008C/HL/NHLBI NIH HHS/United States
- R01 GM047845/GM/NIGMS NIH HHS/United States
- N01HC65237/HL/NHLBI NIH HHS/United States
- HHSN271201100004C/AG/NIA NIH HHS/United States
- HHSN268201100002C/WH/WHI NIH HHS/United States
- R01 HL104608/HL/NHLBI NIH HHS/United States
- S10 OD020069/OD/NIH HHS/United States
- HHSN268201100003I/HL/NHLBI NIH HHS/United States
- HHSN268201100002I/HL/NHLBI NIH HHS/United States
- P01 CA142538/CA/NCI NIH HHS/United States
- KL2 TR000421/TR/NCATS NIH HHS/United States
- P2C HD050924/HD/NICHD NIH HHS/United States
- T32 HL007055/HL/NHLBI NIH HHS/United States
- HHSN268201200008I/HL/NHLBI NIH HHS/United States
- P30 CA071789/CA/NCI NIH HHS/United States
- U01 HG007397/HG/NHGRI NIH HHS/United States
- U01 CA164973/CA/NCI NIH HHS/United States
- HHSN268201100001C/WH/WHI NIH HHS/United States
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical