Genetic analyses of diverse populations improves discovery for complex traits
Open accessAbstract
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 ancestry 1-3. 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-specific 4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations 11,12. 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 conditions 13-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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The field lacks adequate genetic data on determinants of A1C in diverse populations.
“There is an emerging understanding of the genetic determinants of A1C (21), but the fi eld lacks adequate genetic data in diverse populations (26,27).”
From 2. Diagnosis and Classification of Diabetes: <i>Standards of Care in Diabetes—2024</i> (2024) · cites this paper as [27]
Increasing sample size, improved access to trans-ethnic data, and more representative imputation reference panels provide a path to improved resolution of causal variants and clues to molecular mechanisms.
“Increasing sample size, improved access to trans-ethnic data, and more representative imputation reference panels3 provide a path to improved resolution of the causal variants59 and clues to the molecular mechanisms through which they operate.”
From A brief history of human disease genetics (2020) · cites this paper as [59]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
A New Equation to Estimate Glomerular Filtration Rate
Levey, A. S., Stevens, L. A., Schmid, C. H., Zhang, Y. (., Castro, A. F., Feldman, H. I., Kusek, J. W., Eggers, P., Van Lente, F., Greene, T., et al. (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-150-9-200905050-00006 · Cited by 25,603 · see citing works
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247 · see citing works
Self-citationSecond-generation PLINK: rising to the challenge of larger and richer datasets
Chang, C. C., Chow, C. C., Tellier, L. C., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015) · Gigascience · doi:10.1186/s13742-015-0047-8 · Cited by 12,709 · see citing works
METAL: fast and efficient meta-analysis of genomewide association scans
Willer, C. J., Li, Y., & Abecasis, G. R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq340 · Cited by 5,205 · see citing works
Self-citationA New Initiative on Precision Medicine
Collins, F. S., & Varmus, H. (2015) · New England Journal of Medicine · doi:10.1056/nejmp1500523 · Cited by 5,202 · see citing works
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534 · see citing works
Self-citationHowie, B. N., Donnelly, P., & Marchini, J. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000529 · Cited by 3,928 · see citing works
Khera, A. V., Chaffin, M., Aragam, K. G., Haas, M. E., Roselli, C., Choi, S. H., Natarajan, P., Lander, E. S., Lubitz, S. A., Ellinor, P. T., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0183-z · Cited by 2,953 · see citing works
National Center for Biotechnology Information
Gressner, A. M., & Arndt, T. (2019) · Springer Reference Medizin · doi:10.1007/978-3-662-48986-4_301184 · Cited by 2,610 · see citing works
Design of the Women’s Health Initiative Clinical Trial and Observational Study
The Women’s Health Initiative Study Group (1998) · Controlled Clinical Trials · doi:10.1016/s0197-2456(97)00078-0 · Cited by 2,580 · see citing works
A high-performance computing toolset for relatedness and principal component analysis of SNP data
Zheng, X., Levine, D., Shen, J., Gogarten, S. M., Laurie, C. C., & Weir, B. S. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts606 · Cited by 2,541 · see citing works
Self-citation23andMe Research Team, Lee, J. J., COGENT (Cognitive Genomics Consortium), Social Science Genetic Association Consortium, Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Nguyen-Viet, T. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0147-3 · Cited by 2,470 · see citing works
The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog)
MacArthur, J., Bowler, E., Cerezo, M., Gil, L., Hall, P., Hastings, E., Junkins, H., McMahon, A., Milano, A., Morales, J., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1133 · Cited by 2,161 · see citing works
Self-citationGenomics is failing on diversity
Popejoy, A. B., & Fullerton, S. M. (2016) · Nature · doi:10.1038/538161a · Cited by 1,924 · see citing works
The Electronic Medical Records and Genomics (eMERGE) Consortium, Wood, A. R., The MIGen Consortium, The PAGE Consortium, Study, T. L. C., Esko, T., Yang, J., Vedantam, S., Pers, T. H., Gustafsson, S., et al. (2014) · Nature Genetics · doi:10.1038/ng.3097 · Cited by 1,853 · see citing works
Self-citationA linear complexity phasing method for thousands of genomes
Delaneau, O., Marchini, J., & Zagury, J.-F. (2012) · Nature Methods · doi:10.1038/nmeth.1785 · Cited by 1,850 · see citing works
HLA-B*5701 Screening for Hypersensitivity to Abacavir
Mallal, S. A., Phillips, E. J., Carosi, G., Molina, J., Workman, C., Tomažič, J., Jägel-Guedes, E., Rugină, S., Козырев, О. А., Cid, J. F., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa0706135 · Cited by 1,834 · see citing works
Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations
Martin, A. R., Gignoux, C. R., Walters, R. K., Wojcik, G. L., Neale, B. M., Gravel, S., Daly, M. J., Bustamante, C. D., & Kenny, E. E. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.03.004 · Cited by 1,391 · see citing works
Self-citationA Multiethnic Cohort in Hawaii and Los Angeles: Baseline Characteristics
Kolonel, L. N., Henderson, B. E., Hankin, J. H., Nomura, A. M. Y., Wilkens, L. R., Pike, M. C., Stram, D. O., Monroe, K. R., Earle, M. E., & Nagamine, F. S. (2000) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a010213 · Cited by 1,024 · see citing works
Self-citationA Human Genome Diversity Cell Line Panel
Cann, H. M., de Toma, C., Cazes, L., Legrand, M.-F., Morel, V., Piouffre, L., Bodmer, J. G., Bodmer, W. F., Bonné, B., Cambon‐Thomsen, A., et al. (2002) · Science · doi:10.1126/science.296.5566.261b · Cited by 997 · see citing works
FINEMAP: efficient variable selection using summary data from genome-wide association studies
Benner, C., Spencer, C. C. A., Havulinna, A. S., Salomaa, V., Ripatti, S., & Pirinen, M. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw018 · Cited by 815 · see citing works
Immune self-reactivity triggered by drug-modified HLA-peptide repertoire
Illing, P. T., Vivian, J. P., Dudek, N. L., Kostenko, L., Chen, Z., Bharadwaj, M., Miles, J. J., Kjer‐Nielsen, L., Gras, S., Williamson, N. A., et al. (2012) · Nature · doi:10.1038/nature11147 · Cited by 694 · see citing works
Demographic history and rare allele sharing among human populations
Gravel, S., Henn, B. M., Gutenkunst, R. N., Indap, A. R., Marth, G., Clark, A. G., Yu, F., Gibbs, R. A., The 1000 Genomes Project, Bustamante, C. D., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1019276108 · Cited by 625 · see citing works
Self-citationBustamante, C. D., Vega, F. M. D. L., & Burchard, E. G. (2011) · Nature · doi:10.1038/475163a · Cited by 601 · see citing works
Self-citationClines, Clusters, and the Effect of Study Design on the Inference of Human Population Structure
Rosenberg, N. A., Mahajan, S., Ramachandran, S., Zhao, C., Pritchard, J. K., & Feldman, M. W. (2005) · PLoS Genetics · doi:10.1371/journal.pgen.0010070 · Cited by 570 · see citing works
Shim, H., Chasman, D. I., Smith, J. D., Mora, S., Ridker, P. M., Nickerson, D. A., Krauss, R. M., & Stephens, M. (2015) · PLoS ONE · doi:10.1371/journal.pone.0120758 · Cited by 552 · see citing works
Hunter-gatherer genomic diversity suggests a southern African origin for modern humans
Henn, B. M., Gignoux, C. R., Jobin, M., Granka, J. M., Macpherson, J. M., Kidd, J. M., Rodríguez-Botigué, L., Ramachandran, S., Hon, L., Brisbin, A., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1017511108 · Cited by 502 · see citing works
Self-citationSeveral common variants modulate heart rate, PR interval and QRS duration
Hólm, H., Gudbjartsson, D., Arnar, D., Thorleifsson, G., Thorgeirsson, G., Stefánsdóttir, H., Gudjonsson, S. A., Jónasdóttir, Á., Mathiesen, E., Njølstad, I., et al. (2010) · Nature Genetics · doi:10.1038/ng.511 · Cited by 441 · see citing works
Colby, S. L., & Ortman, J. M. (2015) · Cited by 435 · see citing works
A common Greenlandic TBC1D4 variant confers muscle insulin resistance and type 2 diabetes
Moltke, I., Grarup, N., Jørgensen, M. E., Bjerregaard, P., Treebak, J. T., Fumagalli, M., Korneliussen, T. S., Andersen, M. A., Nielsen, T. S., Krarup, N. T., et al. (2014) · Nature · doi:10.1038/nature13425 · Cited by 418 · see citing works
Conomos, M. P., Miller, M. B., & Thornton, T. A. (2015) · Genetic Epidemiology · doi:10.1002/gepi.21896 · Cited by 416 · see citing works
Self-citationNext generation disparities in human genomics: concerns and remedies
Need, A. C., & Goldstein, D. B. (2009) · Trends in Genetics · doi:10.1016/j.tig.2009.09.012 · Cited by 398 · see citing works
Model-free Estimation of Recent Genetic Relatedness
Conomos, M. P., Reiner, A. P., Weir, B. S., & Thornton, T. A. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.11.022 · Cited by 397 · see citing works
Self-citationThe (in)famous GWAS P-value threshold revisited and updated for low-frequency variants
Fadista, J., Manning, A. K., Florez, J. C., & Groop, L. (2016) · European Journal of Human Genetics · doi:10.1038/ejhg.2015.269 · Cited by 357 · see citing works
Conomos, M. P., Laurie, C. A., Stilp, A. M., Gogarten, S. M., McHugh, C. P., Nelson, S. C., Sofer, T., Fernández-Rhodes, L., Justice, A. E., Graff, M., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.12.001 · Cited by 336 · see citing works
Self-citationAssociation of a Low-Frequency Variant in <i>HNF1A</i> With Type 2 Diabetes in a Latino Population
Estrada, K., Aukrust, I., Bjørkhaug, L., Burtt, N. P., Mercader, J. M., García-Ortiz, H., Huerta-Chagoya, A., Moreno-Macías, H., Walford, G., Flannick, J., et al. (2014) · JAMA · doi:10.1001/jama.2014.6511 · Cited by 259 · see citing works
Self-citationCarlson, C. S., Matise, T. C., North, K. E., Haiman, C. A., Fesinmeyer, M. D., Buyske, S. G., Schumacher, F. R., Peters, U., Franceschini, N., Ritchie, M. D., et al. (2013) · PLoS Biology · doi:10.1371/journal.pbio.1001661 · Cited by 258 · see citing works
Self-citationLiao, Y., Bang, D., Cosgrove, S., Dulin, R., Harris, Z., Taylor, A., White, S., Yatabe, G., Liburd, L., & Giles, W. (2011) · Digital Repository at the University of Maryland · doi:10.13016/0ydt-rppb · Cited by 222 · see citing works
On the relative efficiency of using summary statistics versus individual-level data in meta-analysis
Lin, D. Y., & Zeng, D. (2010) · Biometrika · doi:10.1093/biomet/asq006 · Cited by 186 · see citing works
Self-citationGuðmundsson, J., Sulem, P., Gudbjartsson, D. F., Másson, G., Agnarsson, B. A., Benediktsdóttir, K. R., Sigurðsson, Á., Magnússon, Ó. Þ., Gudjonsson, S. A., Magnúsdóttir, D. N., et al. (2012) · Nature Genetics · doi:10.1038/ng.2437 · Cited by 183 · see citing works
Association of Sickle Cell Trait With Hemoglobin A<sub>1c</sub> in African Americans
Lacy, M. E., Wellenius, G. A., Sumner, A. E., Correa, A., Carnethon, M. R., Liem, R. I., Wilson, J. G., Sacks, D. B., Jacobs, D. R., Carson, A. P., et al. (2017) · JAMA · doi:10.1001/jama.2016.21035 · Cited by 141 · see citing works
Self-citationProstate Cancer Susceptibility in Men of African Ancestry at 8q24
Han, Y., Rand, K. A., Hazelett, D. J., Ingles, S. A., Kittles, R. A., Strom, S. S., Rybicki, B. A., Nemesure, B. B., Isaacs, W. B., Stanford, J. L., et al. (2016) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djv431 · Cited by 130 · see citing works
Self-citationMelanesian Blond Hair Is Caused by an Amino Acid Change in TYRP1
Kenny, E. E., Timpson, N. J., Sikora, M., Yee, M., Moreno‐Estrada, A., Eng, C. S., Huntsman, S., Burchard, E. G., Stoneking, M., Bustamante, C. D., et al. (2012) · Science · doi:10.1126/science.1217849 · Cited by 126 · see citing works
Self-citationEffects of Hemoglobin C and S Traits on Glycohemoglobin Measurements by Eleven Methods
Roberts, W. L., Safar-Pour, S., De, B. K., Rohlfing, C. L., Weykamp, C. W., & Little, R. R. (2005) · Clinical Chemistry · doi:10.1373/clinchem.2004.047142 · Cited by 103 · see citing works
Bien, S. A., Wojcik, G. L., Zubair, N., Gignoux, C. R., Martin, A. R., Kocarnik, J., Martin, L. W., Buyske, S. G., Haessler, J., Walker, R. W., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0167758 · Cited by 97 · see citing works
Self-citationLin, D.-Y., Tao, R., Kalsbeek, W. D., Zeng, D., Gonzalez, F., Fernández‐Rhodes, L., Graff, M., Koch, G. G., North, K. E., & HEISS, G. M. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.11.005 · Cited by 82 · see citing works
Self-citationEffects of Hemoglobin C and S Traits on the Results of 14 Commercial Glycated Hemoglobin Assays
Mongia, S. K., Little, R. R., Rohlfing, C. L., Hanson, S., Roberts, R. F., Owen, W. E., D’Costa, M., Reyes, C., Luzzi, V. I., & Roberts, W. L. (2008) · American Journal of Clinical Pathology · doi:10.1309/1yu0d34vjknucgt1 · Cited by 68 · see citing works
Effects of hemoglobin C, D, E, and S traits on measurements of HbA1c by six methods
Lin, C.-N., Emery, T. J., Little, R. R., Hanson, S. E., Rohlfing, C. L., Jaisson, S., Gillery, P., & Roberts, W. L. (2012) · Clinica Chimica Acta · doi:10.1016/j.cca.2011.12.019 · Cited by 68 · see citing works
Manning, A. K., Highland, H. M., Gasser, J. A., Sim, X., Tukiainen, T., Fontanillas, P., Grarup, N., Rivas, M. A., Mahajan, A., Locke, A. E., et al. (2017) · Diabetes · doi:10.2337/db16-1329 · Cited by 56 · see citing works
Self-citationThe Role of Local Ancestry Adjustment in Association Studies Using Admixed Populations
Zhang, J.-Q., & Stram, D. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21835 · Cited by 48 · see citing works
Self-citationWojcik, G. L., Fuchsberger, C., Taliun, D., Welch, R., Martin, A. R., Shringarpure, S., Carlson, C. S., Abecasis, G. R., Kang, H. M., Boehnke, M., et al. (2018) · G3 Genes Genomes Genetics · doi:10.1534/g3.118.200502 · Cited by 42 · see citing works
Self-citationTierney, J. F., Stewart, L. A., Clarke, M. J., & on behalf of the Cochrane Individual Participant Data Meta‐analysis Methods Group (2019) · doi:10.1002/9781119536604.ch26 · Cited by 37 · see citing works
Pharmacogenomic implications of the evolutionary history of infectious diseases in Africa
Baker, J. L., Shriner, D., Bentley, A. R., & Rotimi, C. N. (2016) · The Pharmacogenomics Journal · doi:10.1038/tpj.2016.78 · Cited by 26 · see citing works
A Genome-Wide Association Study Of Bronchodilator Response
Himes, B. E., Wu, A. C., Lasky-Su, J. A., et al. (2012) · doi:10.1164/ajrccm-conference.2012.185.1_meetingabstracts.a2512 · Cited by 3 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
2. Diagnosis and Classification of Diabetes: <i>Standards of Care in Diabetes—2024</i>
American Diabetes Association Professional Practice Committee, ElSayed, N. A., Aleppo, G., Bannuru, R. R., Bruemmer, D., Collins, B. S., Ekhlaspour, L., Gaglia, J. L., Hilliard, M. E., Johnson, E. L., et al. (2024) · Diabetes Care · doi:10.2337/dc24-s002 · Cited by 2,086 · see citing works
2. Diagnosis and classification of diabetes: standards of care in diabetes-2025
American Diabetes Association Professional Practice Committee, ElSayed, N. A., McCoy, R. G., Aleppo, G., Balapattabi, K., Beverly, E. A., Briggs Early, K., Bruemmer, D., Ebekozien, O., Echouffo-Tcheugui, J. B., et al. (2025) · Diabetes Care · doi:10.2337/dc25-s002 · Cited by 1,393 · see citing works
The genetics of obesity: From discovery to biology
Loos, R. J. F., & Yeo, G. S. H. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-021-00414-z · Cited by 1,291 · see citing works
Self-citationAnalysis of polygenic risk score usage and performance in diverse human populations
Duncan, L., Shen, H., Gelaye, B., Meijsen, J., Ressler, K., Feldman, M., Peterson, R., & Domingue, B. (2019) · Nature Communications · doi:10.1038/s41467-019-11112-0 · Cited by 1,038 · see citing works
“(6) Random error in the estimation of GWAS betas”
BackgroundThe power of genetic diversity in genome-wide association studies of lipids
Graham, S. E., Clarke, S. L., Wu, K.-H. H., Kanoni, S., Zajac, G. J. M., Ramdas, S., Surakka, I., Ntalla, I., Vedantam, S., Winkler, T. W., et al. (2021) · Nature · doi:10.1038/s41586-021-04064-3 · Cited by 972 · see citing works
Self-citationGenomic data in the all of us research program
The All of Us Research Program Genomics Investigators, Manuscript Writing Group, Bick, A. G., Metcalf, G. A., Mayo, K. R., Lichtenstein, L., Rura, S., Carroll, R. J., Musick, A., Linder, J. E., et al. (2024) · Nature · doi:10.1038/s41586-023-06957-x · Cited by 829 · see citing works
Self-citationA brief history of human disease genetics
Claussnitzer, M., Cho, J. H., Collins, R., Cox, N. J., Dermitzakis, E. T., Hurles, M. E., Kathiresan, S., Kenny, E. E., Lindgren, C. M., MacArthur, D. G., et al. (2020) · Nature · doi:10.1038/s41586-019-1879-7 · Cited by 697 · see citing works
Self-citationImproving polygenic prediction in ancestrally diverse populations
Ruan, Y., Lin, Y.-F., Feng, Y.-C. A., Chen, C.-Y., Lam, M., Guo, Z., Initiatives, S. G. A., Ahn, Y. M., Akiyama, K., Arai, M., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01054-7 · Cited by 707 · see citing works
“Alternatively, independent analysis can be performed on each discovery GWAS and resulting PRS can be linearly combined 21 , but this approach does not make full use of the genetic overlap between populations.”
Chen, M.-H., Raffield, L. M., Mousas, A., Sakaue, S., Huffman, J. E., Moscati, A., Trivedi, B., Jiang, T., Akbari, P., Vuckovic, D., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.045 · Cited by 661 · see citing works
Ishigaki, K., Akiyama, M., Kanai, M., Takahashi, A., Kawakami, E., Sugishita, H., Sakaue, S., Matoba, N., Low, S.-K., Okada, Y., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0640-3 · Cited by 508 · see citing works
Update on NAFLD genetics: From new variants to the clinic
Trépo, E., & Valenti, L. (2020) · Journal of Hepatology · doi:10.1016/j.jhep.2020.02.020 · Cited by 393 · see citing works
A meta-analysis of genome-wide association studies identifies multiple longevity genes
Deelen, J., Evans, D. S., Arking, D. E., Tesi, N., Nygaard, M., Liu, X., Wojczynski, M. K., Biggs, M. L., van der Spek, A., Atzmon, G., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11558-2 · Cited by 370 · see citing works
Precision medicine in the era of artificial intelligence: implications in chronic disease management
Subramanian, M., Wojtusciszyn, A., Favre, L., Boughorbel, S., Shan, J., Letaief, K. B., Pitteloud, N., & Chouchane, L. (2020) · Journal of Translational Medicine · doi:10.1186/s12967-020-02658-5 · Cited by 362 · see citing works
Robertson, C. C., Inshaw, J. R. J., Onengut-Gumuscu, S., Chen, W.-M., Santa Cruz, D. F., Yang, H., Cutler, A. J., Crouch, D. J. M., Farber, E., Bridges, S. L., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00880-5 · Cited by 302 · see citing works
Native American gene flow into Polynesia predating Easter Island settlement
Ioannidis, A. G., Blanco-Portillo, J., Sandoval, K., Hagelberg, E., Miquel-Poblete, J. F., Moreno-Mayar, J. V., Rodríguez-Rodríguez, J. E., Quinto-Cortés, C. D., Auckland, K., Parks, T., et al. (2020) · Nature · doi:10.1038/s41586-020-2487-2 · Cited by 196 · see citing works
Self-citationEnsuring that biomedical AI benefits diverse populations
Zou, J., & Schiebinger, L. (2021) · EBioMedicine · doi:10.1016/j.ebiom.2021.103358 · Cited by 124 · see citing works
Cai, Y., Cai, Y.-Q., Tang, L.-Y., Wang, Y.-H., Gong, M., Jing, T.-C., Li, H.-J., Li-Ling, J., Hu, W., Yin, Z., et al. (2024) · BMC Medicine · doi:10.1186/s12916-024-03273-7 · Cited by 122 · see citing works
Privé, F. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac348 · Cited by 33 · see citing works
Genetics of child aggression, a systematic review
Koyama, E., Kant, T., Takata, A., Kennedy, J. L., & Zai, C. C. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-02870-7 · Cited by 33 · see citing works
Liang, J., Cade, B. E., He, K. Y., Wang, H., Lee, J., Sofer, T., Williams, S., Li, R., Chen, H., Gottlieb, D. J., et al. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.10.002 · Cited by 21 · see citing works
Self-citationImplicit bias of encoded variables: frameworks for addressing structured bias in EHR–GWAS data
Dueñas, H. R., Seah, C., Johnson, J. S., & Huckins, L. M. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddaa192 · Cited by 31 · see citing works
Self-citationActkins, K. V., Singh, K., Hucks, D., Velez Edwards, D. R., Aldrich, M., Cha, J., Wellons, M., & Davis, L. K. (2021) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgaa675 · Cited by 27 · see citing works
Advancing Understanding of Inequities in Rare Disease Genomics
Serrano, J. G., O'Leary, M., VanNoy, G. E., Mangilog, B. E., Holm, I. A., Fraiman, Y. S., Rehm, H. L., O'Donnell-Luria, A., & Wojcik, M. H. (2023) · Clinical Therapeutics · doi:10.1016/j.clinthera.2023.06.010 · Cited by 25 · see citing works
- Authors
- Wojcik, G. L., Graff, M., Nishimura, K. K., Tao, R., Haessler, J., Gignoux, C. R., Highland, H. M., Patel, Y. M., Sorokin, E. P., Avery, C. L., Belbin, G. M., Bien, S. A., Cheng, I., Cullina, S., Hodonsky, C. J., Hu, Y., Huckins, L. M., Jeff, J., Justice, A. E., Kocarnik, J. M., Lim, U., Lin, B. M., Lu, Y., Nelson, S. C., Park, S.-S. L., Poisner, H., Preuss, M. H., Richard, M. A., Schurmann, C., Setiawan, V. W., Sockell, A., Vahi, K., Verbanck, M., Vishnu, A., Walker, R. W., Young, K. L., Zubair, N., Acuña-Alonso, V., Ambite, J. L., Barnes, K. C., Boerwinkle, E., Bottinger, E. P., Bustamante, C. D., Caberto, C., Canizales-Quinteros, S., Conomos, M. P., Deelman, E., Do, R., Doheny, K., Fernández-Rhodes, L., Fornage, M., Hailu, B., Heiss, G., Henn, B. M., Hindorff, L. A., Jackson, R. D., Laurie, C. A., Laurie, C. C., Li, Y., Lin, D.-Y., Moreno-Estrada, A., Nadkarni, G., Norman, P. J., Pooler, L. C., Reiner, A. P., Romm, J., Sabatti, C., Sandoval, K., Sheng, X., Stahl, E. A., Stram, D. O., Thornton, T. A., Wassel, C. L., Wilkens, L. R., Winkler, C. A., Yoneyama, S., Buyske, S., Haiman, C. A., Kooperberg, C., Le Marchand, L., Loos, R. J. F., Matise, T. C., North, K. E., Peters, U., Kenny, E. E., & Carlson, C. S.
- Affiliations
- Stanford University (US)
- University of North Carolina at Chapel Hill (US)
- Fred Hutch Cancer Center (US)
- Vanderbilt University Medical Center (US)
- University of Colorado Anschutz (US)
- University of Southern California (US)
- Icahn School of Medicine at Mount Sinai (US)
- University of California, San Francisco (US)
- University of Hawaii Cancer Center (US)
- University of Washington (US)
- Brown Foundation (US)
- Hasso Plattner Institute (DE)
- The University of Texas Health Science Center at Houston (US)
- Johns Hopkins University (US)
- National Institutes of Health (US)
- University of California, Davis (US)
- The Ohio State University Wexner Medical Center (US)
- Cancer Prevention Institute of California (US)
- University of Vermont (US)
- Frederick National Laboratory for Cancer Research (US)
- Rutgers, The State University of New Jersey (US)
- Corresponding author
- Kenny, Eimear E.
- Carlson, Christopher S.
- ORCID
- Wojcik, Genevieve L.
- Graff, Mariaelisa
- Nishimura, Katherine K.
- Tao, Ran
- Gignoux, Christopher R.
- Highland, Heather M.
- Patel, Yesha M.
- Sorokin, Elena P.
- Avery, Christy L.
- Belbin, Gillian M.
- Bien, Stephanie A.
- Cheng, Iona
- Hodonsky, Chani J.
- Hu, Yao
- Huckins, Laura M.
- Justice, Anne E.
- Kocarnik, Jonathan M.
- Lim, Unhee
- Lin, Bridget M.
- Lu, Yingchang
- Nelson, Sarah C.
- Poisner, Hannah
- Preuss, Michael H.
- Richard, Melissa A.
- Schurmann, Claudia
- Setiawan, Veronica W.
- Sockell, Alexandra
- Vahi, Karan
- Verbanck, Marie
- Vishnu, Abhishek
- Walker, Ryan W.
- Young, Kristin L.
- Barnes, Kathleen C.
- Boerwinkle, Eric
- Bustamante, Carlos D.
- Conomos, Matthew P.
- Deelman, Ewa
- Do, Ron
- Doheny, Kimberly
- Fornage, Myriam
- Heiss, Gerardo
- Henn, Brenna M.
- Hindorff, Lucia A.
- Jackson, Rebecca D.
- Laurie, Cecelia A.
- Laurie, Cathy C.
- Li, Yuqing
- Nadkarni, Girish
- Norman, Paul J.
- Pooler, Loreall C.
- Sabatti, Chiara
- Sandoval, Karla
- Sheng, Xin
- Stahl, Eli A.
- Stram, Daniel O.
- Thornton, Timothy A.
- Wassel, Christina L.
- Wilkens, Lynne R.
- Winkler, Cheryl A.
- Buyske, Steven
- Haiman, Christopher A.
- Kooperberg, Charles
- Loos, Ruth J. F.
- Matise, Tara C.
- North, Kari E.
- Peters, Ulrike
- Kenny, Eimear E.
- Carlson, Christopher S.
- Venue
- Nature
- Published
- 2019-06
- Volume
- 570
- Issue
- 7762
- Pages
- 514-518
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC6785182
- OpenAlex
- W2952013316
- Cited by
- 1,033
- References
- 54
- Citations by year
- 2026: 94 · 2025: 134 · 2024: 166 · 2023: 163 · 2022: 162 · 2021: 157 · 2020: 117 · 2019: 38 · 2018: 2
- FWCI
- 71.48
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Rutgers University Community Repository (Rutgers University) (submittedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- UNC Libraries
- Funders
- National Institutes of Health (2r24hd050924-06, n01hc65235-13-0-1, n01hc65234-5-0-0, n01hc65237-14-0-1, HHSN268201100004C, n01hc65236-16-0-1, n01hc65233-9-0-0, HHSN268201100001C, HHSN268201100002C, KL2TR001109, KL2TR000421, HHSN268201100003C)
- National Institute on Aging (HHSN-271-2011-00004C,)
- National Heart, Lung, and Blood Institute (N01 HC065235, HHSN2682011-00001I, R01HL104608, HHSN2682011-00002I, N01 HC065237, N01 HC065234, HHSN268201200008I, HHSN2682011‐00004I, HHSN268201200008C, N01 HC065236, HHSN268201100046C, N01 HC065233, HHSN2682011-00003I, K99HL130580, T32HL007055)
- National Human Genome Research Institute (U01HG007416, U01HG007417, K22HG000044, U01HG007397, U01HG007419, U01HG009080, U01HG007376, T32HG000044)
- National Cancer Institute (R01CA082659, P01CA142538, R25CA094880, U01CA164973)
- National Institute of General Medical Sciences (P01GM099568, R01GM047845)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK101855)
- National Center for Advancing Translational Sciences
- National Institute on Minority Health and Health Disparities (L60 MD008384)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R24 HD-050924, P2CHD050924, T32HD007168, T32HD049311)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Race, Genetics, and Society
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Keywords
- multi-ethnic population, admixed populations, non-European ancestry, complex traits, PAGE study, fine mapping, rare variants, genetic discovery, health disparities, precision medicine
- MeSH terms
- Health Equity, Black or African American, Body Height, Female, Genetics, Medical, Hispanic or Latino, Humans, Male, Minority Groups, United States, Cohort Studies, Women's Health, Multifactorial Inheritance, Black People, Asian People, Health Status Disparities, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
