The Future of Genomic Studies Must Be Globally Representative: Perspectives from PAGE

Overview

Journal Annu Rev Genomics Hum Genet

Publisher Annual Reviews

Specialty Genetics

Date 2019 Apr 13

PMID 30978304

Citations 25

Authors

Stephanie A Bien

Genevieve L Wojcik

Chani J Hodonsky

Christopher R Gignoux

Iona Cheng

Tara C Matise

Ulrike Peters

Eimear E Kenny

Kari E North

Affiliations

Soon will be listed here.

Abstract

The past decade has seen a technological revolution in human genetics that has empowered population-level investigations into genetic associations with phenotypes. Although these discoveries rely on genetic variation across individuals, association studies have overwhelmingly been performed in populations of European descent. In this review, we describe limitations faced by single-population studies and provide an overview of strategies to improve global representation in existing data sets and future human genomics research via diversity-focused, multiethnic studies. We highlight the successes of individual studies and meta-analysis consortia that have provided unique knowledge. Additionally, we outline the approach taken by the Population Architecture Using Genomics and Epidemiology (PAGE) study to develop best practices for performing genetic epidemiology in multiethnic contexts. Finally, we discuss how limiting investigations to single populations impairs findings in the clinical domain for both rare-variant identification and genetic risk prediction.

Citing Articles

Genetic Diversity Landscape in African Population: A Review of Implications for Personalized and Precision Medicine.

Sibomana O Pharmgenomics Pers Med. 2024; 17:487-496.

PMID: 39555236 PMC: 11566596. DOI: 10.2147/PGPM.S485452.

Advancements in genetic research by the Hispanic Community Health Study/Study of Latinos: A 10-year retrospective review.

Rao H, Weiss M, Moon J, Perreira K, Daviglus M, Kaplan R HGG Adv. 2024; 6(1):100376.

PMID: 39473183 PMC: 11754138. DOI: 10.1016/j.xhgg.2024.100376.

Mapping Epigenetic Gene Variant Dynamics: Comparative Analysis of Frequency, Functional Impact and Trait Associations in African and European Populations.

Sinkala M, Retshabile G, Mpangase P, Bamba S, Goita M, Nembaware V medRxiv. 2024; .

PMID: 39185519 PMC: 11343269. DOI: 10.1101/2024.08.11.24311816.

Optimizing clinico-genomic disease prediction across ancestries: a machine learning strategy with Pareto improvement.

Gao Y, Cui Y Genome Med. 2024; 16(1):76.

PMID: 38835075 PMC: 11149372. DOI: 10.1186/s13073-024-01345-0.

Building a vertically integrated genomic learning health system: The biobank at the Colorado Center for Personalized Medicine.

Wiley L, Shortt J, Roberts E, Lowery J, Kudron E, Lin M Am J Hum Genet. 2024; 111(1):11-23.

PMID: 38181729 PMC: 10806731. DOI: 10.1016/j.ajhg.2023.12.001.

References

Nadkarni G, Gignoux C, Sorokin E, Daya M, Rahman R, Barnes K . Worldwide Frequencies of APOL1 Renal Risk Variants. N Engl J Med. 2018; 379(26):2571-2572. PMC: 6482949. DOI: 10.1056/NEJMc1800748. View

Conomos M, Reiner A, Weir B, Thornton T . Model-free Estimation of Recent Genetic Relatedness. Am J Hum Genet. 2016; 98(1):127-48. PMC: 4716688. DOI: 10.1016/j.ajhg.2015.11.022. View

Gong J, Schumacher F, Lim U, Hindorff L, Haessler J, Buyske S . Fine Mapping and Identification of BMI Loci in African Americans. Am J Hum Genet. 2013; 93(4):661-71. PMC: 3791273. DOI: 10.1016/j.ajhg.2013.08.012. View

Battle A, Mostafavi S, Zhu X, Potash J, Weissman M, McCormick C . Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals. Genome Res. 2013; 24(1):14-24. PMC: 3875855. DOI: 10.1101/gr.155192.113. View

Price A, Patterson N, Plenge R, Weinblatt M, Shadick N, Reich D . Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006; 38(8):904-9. DOI: 10.1038/ng1847. View

Bien S, Wojcik G, Zubair N, Gignoux C, Martin A, Kocarnik J . Strategies for Enriching Variant Coverage in Candidate Disease Loci on a Multiethnic Genotyping Array. PLoS One. 2016; 11(12):e0167758. PMC: 5156387. DOI: 10.1371/journal.pone.0167758. View

Maples B, Gravel S, Kenny E, Bustamante C . RFMix: a discriminative modeling approach for rapid and robust local-ancestry inference. Am J Hum Genet. 2013; 93(2):278-88. PMC: 3738819. DOI: 10.1016/j.ajhg.2013.06.020. View

Visscher P, Brown M, McCarthy M, Yang J . Five years of GWAS discovery. Am J Hum Genet. 2012; 90(1):7-24. PMC: 3257326. DOI: 10.1016/j.ajhg.2011.11.029. View

Gusev A, Ko A, Shi H, Bhatia G, Chung W, Penninx B . Integrative approaches for large-scale transcriptome-wide association studies. Nat Genet. 2016; 48(3):245-52. PMC: 4767558. DOI: 10.1038/ng.3506. View

10.

Conomos M, Miller M, Thornton T . Robust inference of population structure for ancestry prediction and correction of stratification in the presence of relatedness. Genet Epidemiol. 2015; 39(4):276-93. PMC: 4836868. DOI: 10.1002/gepi.21896. View

11.

Genovese G, Friedman D, Ross M, Lecordier L, Uzureau P, Freedman B . Association of trypanolytic ApoL1 variants with kidney disease in African Americans. Science. 2010; 329(5993):841-5. PMC: 2980843. DOI: 10.1126/science.1193032. View

12.

Zhang Y, Qi G, Park J, Chatterjee N . Estimation of complex effect-size distributions using summary-level statistics from genome-wide association studies across 32 complex traits. Nat Genet. 2018; 50(9):1318-1326. DOI: 10.1038/s41588-018-0193-x. View

13.

Bustamante C, Burchard E, De La Vega F . Genomics for the world. Nature. 2011; 475(7355):163-5. PMC: 3708540. DOI: 10.1038/475163a. View

14.

. The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators. Am J Epidemiol. 1989; 129(4):687-702. View

15.

Sempos C, Bild D, Manolio T . Overview of the Jackson Heart Study: a study of cardiovascular diseases in African American men and women. Am J Med Sci. 1999; 317(3):142-6. DOI: 10.1097/00000441-199903000-00002. View

16.

McCarthy S, Das S, Kretzschmar W, Delaneau O, Wood A, Teumer A . A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet. 2016; 48(10):1279-83. PMC: 5388176. DOI: 10.1038/ng.3643. View

17.

Zhang L, Buzkova P, Wassel C, Roman M, North K, Crawford D . Lack of associations of ten candidate coronary heart disease risk genetic variants and subclinical atherosclerosis in four US populations: the Population Architecture using Genomics and Epidemiology (PAGE) study. Atherosclerosis. 2013; 228(2):390-9. PMC: 3717342. DOI: 10.1016/j.atherosclerosis.2013.02.038. View

18.

Gurdasani D, Carstensen T, Tekola-Ayele F, Pagani L, Tachmazidou I, Hatzikotoulas K . The African Genome Variation Project shapes medical genetics in Africa. Nature. 2014; 517(7534):327-32. PMC: 4297536. DOI: 10.1038/nature13997. View

19.

Morris A, Voight B, Teslovich T, Ferreira T, V Segre A, Steinthorsdottir V . Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012; 44(9):981-90. PMC: 3442244. DOI: 10.1038/ng.2383. View

20.

Avery C, Wassel C, Richard M, Highland H, Bien S, Zubair N . Fine mapping of QT interval regions in global populations refines previously identified QT interval loci and identifies signals unique to African and Hispanic descent populations. Heart Rhythm. 2016; 14(4):572-580. PMC: 5448160. DOI: 10.1016/j.hrthm.2016.12.021. View