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Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations

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Peterson, Roseann E., Kuchenbaecker, Karoline, Walters, Raymond K., Chen, Chia-Yen, Popejoy, Alice B., Periyasamy, Sathish, Lam, Max, Iyegbe, Conrad, Strawbridge, Rona J., Brick, Leslie, Carey, Caitlin E., Martin, Alicia R., Meyers, Jacquelyn L., Su, Jinni, Chen, Junfang, Edwards, Alexis C., Kalungi, Allan, Koen, Nastassja, Majara, Lerato, Schwarz, Emanuel, Smoller, Jordan W., Stahl, Eli A., Sullivan, Patrick F., Vassos, Evangelos, Mowry, Bryan, Prieto, Miguel L., Cuellar-Barboza, Alfredo, Bigdeli, Tim B., Edenberg, Howard J., Huang, Hailiang, Duncan, Laramie E.·2019·Cell

DOI 10.1016/j.cell.2019.08.051PMC PMC6939869

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Abstract

Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.

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Pasanen, A., Karjalainen, M. K., FinnGen, Zhang, G., Tiensuu, H., Haapalainen, A. M., Ojaniemi, M., Feenstra, B., Jacobsson, B., Palotie, A. V., et al. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010982 · Cited by 31
Common and rare variants associated with cardiometabolic traits across 98,622 whole-genome sequences in the All of Us research program
Wang, X., Ryu, J. H., Kim, J., Ramirez, A. H., Mayo, K., Condon, H. R., Vaitinadin, N. S., Lucila Ohno-machado, A., Talavera, G. A., Ellinor, P. T., et al. (2023) · Journal of Human Genetics · doi:10.1038/s10038-023-01147-z · Cited by 14
A Genetic Map of the Modern Urban Society of Amsterdam
Ferwerda, B., Abdellaoui, A., Nieuwdorp, M., & Zwinderman, A. H. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.727269 · Cited by 13
“GWAS datasets with varying ethnicities can be analyzed in two ways, namely, by analyzing the entire cohort at once or by meta-analysis summarizing the results of analyses per ethnicity (Peterson et al., 2019;Wojcik et al., 2019).”
Method
Age varying polygenic effects on alcohol use in African Americans and European Americans from adolescence to adulthood
Elam, K. K., Ha, T., Neale, Z. E., Alıev, F., Dick, D. M., & Lemery‐Chalfant, K. (2021) · Scientific Reports · doi:10.1038/s41598-021-01923-x · Cited by 11
Epicardial Adipose Tissue: The Genetics Behind an Emerging Cardiovascular Risk Marker
Sousa, J., Mendonça, M., Serrão, M., Borges, S., Henriques, E., Freitas, S., Tentem, M., Santos, M., Freitas, P., Ferreira, A., et al. (2021) · Clinical Medicine Insights: Cardiology · doi:10.1177/11795468211029244 · Cited by 11
Cannabis Use in College: Genetic Predispositions, Peers, and Activity Participation
Thomas, N., Salvatore, J., Gillespie, N., Aliev, F., Ksinan, A., & Dick, D. (2020) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2020.108489 · Cited by 11
Editorial: Polygenic scores in child and adolescent psychiatry – strengths, weaknesses, opportunities and threats
Ronald, A. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13246 · Cited by 17
“This situation is currently being corrected through major projects and methodological advances (Peterson et al., 2019).”
Background
Polygenic risk scores: Navigating the future of precision medicine through economic, ethical, and scientific advancements
Nguyen, H. H. K., Le, H. M., Thang, L. Q., Ngan, D. T. Q., Thoi, N. T., Phuong, N., Hoang, D. M., & Huynh, C. D. (2025) · iScience · doi:10.1016/j.isci.2025.114375 · Cited by 10
“34 Commercial testing is expanding fast with both clinical and direct-to-consumer (DTC) services 35 ; but reimbursement and cost-effectiveness remain unresolved.”
From clock to clock: Therapeutic target discovery for aging and age-related diseases
Chen, J., Leung, G. H. D., Leung, H., Ustiugova, A. S., Shneyderman, A., Korzinkin, M., Gennert, D. G., Pun, F. W., Aliper, A. M., Ren, F., et al. (2025) · Ageing Research Reviews · doi:10.1016/j.arr.2025.102871 · Cited by 10
Self-citation
Bioaerosols and Airway Diseases: Mechanisms of Epithelial Dysfunction, Immune Activation, and Strategies for Exposure Mitigation
Nabipur, L., Mouawad, M., & Agrawal, D. K. (2025) · Archives of Internal Medicine Research · doi:10.26502/aimr.0210 · Cited by 10
“However, populations with a high disease burden, such as those of African ancestry, have been underrepresented, prompting efforts to increase genetic research in diverse populations [98–100].”
New Genomics Discoveries Across the Bipolar Disorder Spectrum Implicate Neurobiological and Developmental Pathways
O’Connell, K. S., Adolfsson, R., Andlauer, T. F. M., Bauer, M., Baune, B. T., Biernacka, J. M., Carpiniello, B., Cichon, S., Craddock, N. J., Barboza, A. B. C., et al. (2025) · Biological Psychiatry · doi:10.1016/j.biopsych.2025.05.020 · Cited by 12
Self-citation
Translation of genome-wide association study: from genomic signals to biological insights
Bruner, W. S., & Grant, S. F. A. (2024) · Frontiers in Genetics · doi:10.3389/fgene.2024.1375481 · Cited by 10
The frequency of the ACE I/D polymorphism in South America: a systematic review and meta-analysis
Trevisano, R. G., Apaza, H. M., Teani, T. D. J., Silvino, V. O., Ferreira, C. P., dos Santos, M. A. P., Braga, P. L. G., & de Almeida, S. S. (2024) · Molecular and Cellular Biochemistry · doi:10.1007/s11010-023-04923-9 · Cited by 12
A Developmentally-Informative Genome-wide Association Study of Alcohol Use Frequency
Thomas, N., Gillespie, N. A., Chan, G., Edenberg, H. J., Kamarajan, C., Kuo, S. I., Miller, A. P., Nürnberger, J. I., Tischfield, J. A., Dick, D. M., et al. (2023) · Behavior Genetics · doi:10.1007/s10519-023-10170-x · Cited by 8
“It is a critical priority to extend genetic analyses to a broader range of ancestry groups (Peterson et al. 2019).”
Self-citation
Bridging the gap: returning genetic results to indigenous communities in Latin America
Arango-Isaza, E., Aninao, M. J., Campbell, R., Martínez, F. I., Shimizu, K. K., & Barbieri, C. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1304974 · Cited by 10
Polygenic risk score for problematic alcohol use predicts heavy drinking and alcohol use disorder symptoms in young adulthood after accounting for adolescent alcohol use and parental alcohol use disorder
Wang, F. L., Hicks, B. M., Zhou, H., Kranzler, H. R., Gelernter, J. E., & Zucker, R. A. (2023) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2023.109909 · Cited by 12
Dual-systems models of the genetic architecture of impulsive personality traits: Neurogenetic evidence of distinct but related factors
Miller, A. P., & Gizer, I. (2023) · medRxiv · doi:10.1101/2023.02.10.23285725 · Cited by 10
“Crucially, non-European ancestry groups are extremely underrepresented in extant GWAS studies (Mills & Rahal, 2019, 2020), and addressing this limitation is of dire importance for leveling health disparities across groups (Peterson et al., 2019).”
Background
The estimation of environmental and genetic parental influences
Balbona, J. V., Kim, Y., & Keller, M. C. (2022) · Development and Psychopathology · doi:10.1017/s0954579422000761 · Cited by 17
“…accuracy greatly suffers when applied in non-European samples – a problem that limits their applicability in clinical and research settings, and one that researchers are working to mitigate through the recruitment of larger and more diverse GWAS samples (Martin et al., 2019; Peterson et al., 2019).”
Diverse ancestry whole-genome sequencing association study identifies TBX5 and PTK7 as susceptibility genes for posterior urethral valves
Chan, M., Sadeghi‐Alavijeh, O., Lopes, F. M., Hilger, A. C., Stanescu, H. C., Voinescu, C., Beaman, G. M., Newman, W. G., Zaniew, M., Weber, S., et al. (2022) · eLife · doi:10.7554/elife.74777 · Cited by 23
“74777 10 of 32 examining rarer variants and non- European populations for which imputation performance may be limiting (Höglund et al., 2019; Peterson et al., 2019).”
Background
Using Polygenic Hazard Scores to Predict Age at Onset of Alzheimer’s Disease in Nordic Populations
Motazedi, E., Cheng, W., Thomassen, J. Q., Frei, O., Rongve, A., Athanasiu, L., Bahrami, S., Shadrin, A. A., Ulstein, I. D., Stordal, E., et al. (2022) · Journal of Alzheimer s Disease · doi:10.3233/jad-220174 · Cited by 12
Additive genetic effects in interacting species jointly determine the outcome of caterpillar herbivory
Gompert, Z., Saley, T. C., Philbin, C. S., Yoon, S. A., Perry, E., Sneck, M. E., Harrison, J. G., Buerkle, C. A., Fordyce, J. A., Nice, C. C., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2206052119 · Cited by 10
Investigating the Genetic Profile of the Amyotrophic Lateral Sclerosis/Frontotemporal Dementia (ALS-FTD) Continuum in Patients of Diverse Race, Ethnicity and Ancestry
Mesaros, M., Lenz, S., Lim, W., Brown, J., Drury, L. J., & Roggenbuck, J. (2021) · Genes · doi:10.3390/genes13010076 · Cited by 11
“Such findings are often attributed to the lack of adequate representation of diverse REA groups in population databases [31,45].”
Background
Ancestral diversity is limited in published T cell receptor sequencing studies
Huang, Y.-N., Peng, K., Popejoy, A. B., Hu, J., Nowicki, T., Gold, S. M., Quintana-Murci, L., Fuentes-Guajardo, M., Shugay, M., Greiff, V., et al. (2021) · Immunity · doi:10.1016/j.immuni.2021.09.015 · Cited by 10
Self-citation
Polygenic risk for major depression is associated with lifetime suicide attempt in US soldiers independent of personal and parental history of major depression
Stein, M. B., Jain, S., Campbell‐Sills, L., Ware, E. B., Choi, K. W., He, F., Ge, T., Gelernter, J. E., Smoller, J. W., Kessler, R. C., et al. (2021) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32868 · Cited by 10
“Last, our analyses focused solely on individuals of European ancestry (Peterson et al., 2019), given the known limitations of extending PRS from European to other ancestral groups.”
BackgroundMethodSelf-citation
Behavior genetics research on personality: Moving beyond traits to examine characteristic adaptations
Nguyen, P. L. L., Syed, M., & McGue, M. K. (2021) · Social and Personality Psychology Compass · doi:10.1111/spc3.12628 · Cited by 14
Phenotype Risk Scores: moving beyond ‘cases’ and ‘controls’ to classify psychiatric disease in hospital-based biobanksPreprint
Lebovitch, D. S., Johnson, J., Duenas, H. R., & Huckins, L. M. (2021) · medRxiv · doi:10.1101/2021.01.25.21249615 · Cited by 6
Multi-ancestry sequencing-based genome-wide association study of C-reactive protein in 513,273 genomes
Li, H., Zhao, J., Dai, J., You, D., Zhao, Y., Christiani, D. C., Chen, F., & Shen, S. (2025) · Nature Communications · doi:10.1038/s41467-025-59155-w · Cited by 8
Evolution, genetic diversity, and health
Palma-Martínez, M. J., Posadas‐García, Y. S., Shaukat, A., López-Ángeles, B. E., & Sohail, M. (2025) · Nature Medicine · doi:10.1038/s41591-025-03558-1 · Cited by 13
Shattering the monolith: burden of gastrointestinal cancer in Asian Americans, Native Hawaiians, and Pacific Islanders in the United States
Yoon, J. Y., Shah, S. C., Lin, J. J., Kim, M. K., Itzkowitz, S. H., & Wang, C. P. (2024) · The Lancet Regional Health - Americas · doi:10.1016/j.lana.2024.100954 · Cited by 5
“72,73 Additionally, robust instruments that assess risk factors, dietary practices, and health beliefs/behaviours must be developed, culturally tailored, and validated across ethnic groups.”
Reproductive options and genetic testing for patients with an inherited cardiac disease
Verdonschot, J. A. J., Paulussen, A. D. C., Lakdawala, N. K., de Die-Smulders, C. E. M., Ware, J. S., & Ingles, J. (2024) · Nature Reviews Cardiology · doi:10.1038/s41569-024-01073-3 · Cited by 12
“The limitations of genomics for individuals from ancestry groups that have been poorly represented in research and population reference databases have been well described, including for inherited cardiac diseases 51–54 .”
Low-frequency and rare genetic variants associated with rheumatoid arthritis risk
Kronzer, V. L., Sparks, J. A., Raychaudhuri, S., & Cerhan, J. R. (2024) · Nature Reviews Rheumatology · doi:10.1038/s41584-024-01096-7 · Cited by 14
Attention-mediated genetic influences on psychotic symptomatology in adolescence
Chang, S. E., Hughes, D., Zhu, J., Hyat, M., Salone, S. D., Goodman, Z. T., Roffman, J. L., Karcher, N. R., Hernandez, L. M., Forsyth, J. K., et al. (2024) · Nature Mental Health · doi:10.1038/s44220-024-00338-7 · Cited by 9
“ABCD subjects were assigned a population label if their predicted probability of a given ancestry membership was greater than 0.9, per recommendations for diverse samples 115 .”
Influential
Alcohol Use Disorder Polygenic Risk Scores and Trajectories of Early Adolescent Externalizing Behaviors: Examining the Role of Parenting and Family Conflict in the Racially/Ethnically Diverse ABCD Sample
Trevino, A. D., Jamil, B., Su, J., Alıev, F., Elam, K. K., & Lemery‐Chalfant, K. (2023) · Behavior Genetics · doi:10.1007/s10519-023-10155-w · Cited by 10
Self-citation
Circulating epigenomic biomarkers correspond with kidney disease susceptibility in high-risk populations with type 2 diabetes mellitus.
Khurana, I., Howard, N. J., Maxwell, S., Preez, A. D., Kaipananickal, H., Breen, J. M., Buckberry, S., Okabe, J., Al-Hasani, K., Nakasatien, S., et al. (2023) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2023.110918 · Cited by 9
Correlates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder
Bigdeli, T., Barr, P. B., Rajeevan, N., Graham, D. P., Li, Y.-L., Meyers, J., Gorman, B., Peterson, R. E., Sayward, F., Radhakrishnan, K., et al. (2023) · medRxiv · doi:10.1101/2023.03.06.23286866 · Cited by 9
“This general strategy has been shown to be robust to population stratification(13, 27, 28).”
Self-citation
The Promise and Peril of Genetics
Dick, D. M. (2022) · Current Directions in Psychological Science · doi:10.1177/09637214221112041 · Cited by 7
Genome-wide association study meta-analysis of suicide attempt identifies twelve genome-wide significant loci and implicates genetic risks for specific health factorsPreprint
Docherty, A. R., Mullins, N., Ashley‐Koch, A. E., Qin, X., Coleman, J. R. I., Shabalin, A. A., Kang, J., Murnyak, B., Wendt, F. R., Adams, M. J., et al. (2022) · medRxiv · doi:10.1101/2022.07.03.22277199 · Cited by 7
It’s time to incorporate diversity into our basic science and disease models
Horwitz, R., Riley, E. A. U., Millan, M. T., & Gunawardane, R. N. (2021) · Nature Cell Biology · doi:10.1038/s41556-021-00803-w · Cited by 10
Genotype–environment correlation by intervention effects underlying middle childhood peer rejection and associations with adolescent marijuana use
Elam, K. K., Clifford, S., Ruof, A., Shaw, D. S., Wilson, M. N., & Lemery‐Chalfant, K. (2020) · Development and Psychopathology · doi:10.1017/s0954579420001066 · Cited by 20
“As GWAS data grow in diversity, it is similarly important to align racial/ethnic groups in GWAS and PRS samples, one approach being the use of multiethnic PRS (Márquez-Luna, Loh, & Price, 2017; Peterson et al., 2019).”
Method
An Update on the Role of Common Genetic Variation Underlying Substance Use Disorders
Johnson, E. C., Chang, Y., & Arpana Agrawal, A. (2020) · Current Genetic Medicine Reports · doi:10.1007/s40142-020-00184-w · Cited by 9
Efficient and accurate framework for genome-wide gene-environment interaction analysis in large-scale biobanks
Ma, Y., Zhao, Y., Zhang, J., & Bi, W. (2025) · Nature Communications · doi:10.1038/s41467-025-57887-3 · Cited by 10
“This issue is particularly critical in large-scale biobank data analyses, in which the inclusion of diverse ancestries or admixed populations is common 31 – 33 .”
Genetic architectures of childhood maltreatment and causal influence of childhood maltreatment on health outcomes in adulthood
Chen, T., Chen, C., Liu, C.-Y., Lee, J., Ganna, A., Feng, Y. A., & Lin, K. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-02928-y · Cited by 11
“We excluded samples of non-European ancestry to minimize bias from population strati ﬁ cation [22], and we also excluded population outliers in samples of European ancestry by conducting three rounds of in-sample PCA.”
Self-citation
Characterizing features affecting local ancestry inference performance in admixed populations
Mauer, J., Shah, N. N., Maihofer, A. X., Zai, C. C. H., Belangero, S. I., Nievergelt, C. M., Santoro, M. L., & Atkinson, E. G. (2025) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2024.12.005 · Cited by 15
Amygdala connectivity is associated with withdrawn/depressed behavior in a large sample of children from the Adolescent Brain Cognitive Development (ABCD) Study®
Thomas, E., Juliano, A., Owens, M. M., Cupertino, R. B., Mackey, S., Hermosillo, R. J. M., Miranda-Domínguez, Ó., Conan, G., Ahmed, M., Fair, D. A., et al. (2024) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2024.111877 · Cited by 9
“…polygenic risk scores derived from predominantly European samples predict individual risk with higher accuracy in Europeans than in non-Europeans (Hoggart et al., 2023a; Li & Keating, 2014; Martin et al. 2017; Peterson et al., 2019; Ruan et al., 2022; Weissbrod et al., 2022; Wojcik et al., 2019).”
An ensemble penalized regression method for multi-ancestry polygenic risk prediction
Zhang, J., Zhan, J., Jin, J., Ma, C., Zhao, R., O’Connell, J., Jiang, Y., Koelsch, B. L., Zhang, H., & Chatterjee, N. (2024) · Nature Communications · doi:10.1038/s41467-024-47357-7 · Cited by 54
Genome-Wide Association Studies of 3 Distinct Recovery Phenotypes in Mild Ischemic Stroke
Aldridge, C., Braun, R. G., Lohse, K. R., de Havenon, A., Cole, J. W., Cramer, S. C., Lindgren, A. G., Keene, K. L., Hsu, F., & Worrall, B. B. (2024) · Neurology · doi:10.1212/wnl.0000000000208011 · Cited by 11
Trans-ancestry polygenic models for the prediction of LDL blood levels: an analysis of the United Kingdom Biobank and Taiwan Biobank
Hassanin, E., Lee, K.-H., Hsieh, T.-C., Aldisi, R., Lee, Y.-L., Bobbili, D., Krawitz, P., May, P., Chen, C.-Y., & Maj, C. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1286561 · Cited by 8
Self-citation
Genome‐wide association study of tuberculosis in the western Chinese Han and Tibetan population
Bai, H., Song, M., Lei, S., Jiao, L., Hu, X. L., Wu, T., Song, J., Liu, T., Peng, W., Zhao, Z., et al. (2023) · MedComm · doi:10.1002/mco2.250 · Cited by 13
Evolutionary Landscape of SOX Genes to Inform Genotype-to-Phenotype Relationships
Underwood, A. C., Rasicci, D. T., Hinds, D., Mitchell, J. T., Zieba, J. K., Mills, J., Arnold, N. E., Cook, T. W., Moustaqil, M. D., Gambin, Y., et al. (2023) · Genes · doi:10.3390/genes14010222 · Cited by 9
Novel Functional Genomics Approaches Bridging Neuroscience and Psychiatry
Restrepo-Lozano, J. M., Flores, C., & Silveira, P. P. (2022) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2022.07.005 · Cited by 7
“This is especially true when the ancestry of the target sample does not match the population of the original GWAS (57,58).”
Background
How Neanderthals Became White: The Introgression of Race into Contemporary Human Evolutionary Genetics
Weasel, L. H. (2022) · The American Naturalist · doi:10.1086/720130 · Cited by 10
“…of European-origin samples inGWASs has led to bias due to genetic drift when applied to a wider range of populations (Martin et al. 2017a), which has implications not just for the integrity of the science but also for clinical practice and public health (Hindorff et al. 2018; Peterson et al. 2019).”
Background
Recommendations on the use and reporting of race, ethnicity, and ancestry in genetic research: experiences from the NHLBI Trans-Omics for Precision Medicine (TOPMed) programPreprint
Khan, A. T., Gogarten, S., McHugh, C. P., Stilp, A., Sofer, T., Bowers, M., Wong, Q., Cupples, L., Hidalgo, B. A., Johnson, A. D., et al. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.07858 · Cited by 8
Penalized linear mixed models for structured genetic data
Reisetter, A. C., & Breheny, P. J. (2021) · Genetic Epidemiology · doi:10.1002/gepi.22384 · Cited by 7
Why most Principal Component Analyses (PCA) in population genetic studies are wrongPreprint
Elhaik, E. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.11.439381 · Cited by 9
“…and controls (e.g., Luca et al. 2008; Genovese et al. 2010; Willis et al. 2014; Mobuchon et al. 2017) as well as outliers (samples or data) (Moorjani et al. 2011; van’t Hof et al. 2016), assess SNP effects (Price et al. 2006), and calculate population structure covariates (Peterson et al. 2019).”
BackgroundMethod
The Contribution of Genetics and Epigenetics to Our Understanding of Health Disparities in Rheumatic Diseases
Lanata, C. M., Blazer, A., & Criswell, L. A. (2020) · Rheumatic Disease Clinics of North America · doi:10.1016/j.rdc.2020.09.005 · Cited by 10
Tractor: A framework allowing for improved inclusion of admixed individuals in large-scale association studies
Atkinson, E., Maihofer, A., Kanai, M., Martin, A. R., Karczewski, K., Santoro, M. L., Ulirsch, J., Kamatani, Y., Okada, Y., Finucane, H., et al. (2020) · bioRxiv · doi:10.1101/2020.05.17.100727 · Cited by 8
Self-citation
TwinsMX: Uncovering the Basis of Health and Disease in the Mexican Population
Leon-Apodaca, A. V., Chiu-Han, E., Ortega-Mora, I., Román-López, T. V., Caballero-Sánchez, U., Aldana-Assad, O., Campos, A. I., Cuéllar-Partida, G., Ruiz‐Contreras, A. E., Alcauter, S., et al. (2019) · Twin Research and Human Genetics · doi:10.1017/thg.2019.112 · Cited by 7
“…result in inequitable access to the benefits of precision medicine, exacerbating existing disease and healthcare disparities (Martin et al., 2019; Peterson et al., 2019; Wojcik et al., 2019) The heritability of a trait, that is, the amount of variance of the trait that can be attributed to…”
Indirect paths from genetics to education
Schork, A. J., Peterson, R. E., Dahl, A., Cai, N., & Kendler, K. S. (2022) · Nature Genetics · doi:10.1038/s41588-021-00999-5 · Cited by 7
Self-citation
Associations Between a Genetic Liability Toward Externalizing and Behavioral Outcomes Spanning Toddlerhood Through Early Adulthood in Five Developmental Cohorts
Choi, M., Poore, H. E., Brislin, S. J., Barr, P. B., Alıev, F., Zellers, S. M., Saunders, G., Salvatore, J. E., Vrieze, S. I., Harden, K. P., et al. (2025) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2025.04.010 · Cited by 9
“Given that PGS have poor portability when applied to target samples with different genetic ancestry than the original GWAS sample 25 (eg, using a PGS developed in a European ancestry sample to an African ancestry sample), we chose to restrict our analyses.”
Psychiatric neuroimaging at a crossroads: Insights from psychiatric genetics
Dall’Aglio, L., Urbina-Johanson, S., Mallard, T. T., Lamballais, S., Delaney, S., Smoller, J. W., Muetzel, R. L., & Tiemeier, H. W. (2024) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2024.101443 · Cited by 8
“Notable examples are outlined in the literature (Peterson et al., 2019), and include the modeling of population-specific LD patterns, stratified or cross-ancestral meta-analyses, and methods to account for admixture, i.e., when the genome reflects more than one ancestry (Clyde, 2021).”
BackgroundSelf-citation
Characterizing features affecting local ancestry inference performance in admixed populations
Honorato-Mauer, J., Shah, N. N., Maihofer, A., Zai, C., Belangero, S., Nievergelt, C., Santoro, M. L., & Atkinson, E. G. (2024) · bioRxiv · doi:10.1101/2024.08.26.609770 · Cited by 7
“As large-scale efforts begin to focus more heavily on admixed groups, there is an unmet need for the design of well-suited pipelines to appropriately study these underrepresented populations 7 .”
Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project
Huider, F., Milaneschi, Y., Hottenga, J., Bot, M., Rietman, M. L., Kok, A. A. L., Galesloot, T. E., Hart, L. M. ‘., Rutters, F., Blom, M. T., et al. (2024) · Twin Research and Human Genetics · doi:10.1017/thg.2024.4 · Cited by 5
“One of the future goals of our project is to include individuals from all ancestral backgrounds, as analytical approaches to include these are currently actively being studied and developed (e.g., see Peterson et al., 2019).”
Evaluation of imputation performance of multiple reference panels in a Pakistani population
Xu, J.-Y., Liu, D.-J., Hassan, A., Genovese, G., Cote, A., Fennessy, B., Cheng, E., Charney, A., Knowles, J. A., Ayub, M., et al. (2023) · medRxiv · doi:10.1101/2023.12.22.23300448 · Cited by 7
Self-citation
Individual Trajectories of Depressive Symptoms Within Racially-Ethnically Diverse Youth: Associations with Polygenic Risk for Depression and Substance Use Intent and Perceived Harm
Elam, K. K., Su, J., Kutzner, J., & Trevino, A. D. (2023) · Behavior Genetics · doi:10.1007/s10519-023-10167-6 · Cited by 7
“These findings further highlight the need for increasing representation of LX and other minority populations in GWAS studies (e.g., Giannakopoulou et al. 2021; Peterson et al. 2019).”
Self-citation
Gene-by-Sex Interactions: Genome-Wide Association Study Reveals Five SNPs Associated with Obesity and Overweight in a Male Population
Kyrgiafini, M.-A., Sarafidou, T., Giannoulis, T., Chatziparasidou, A., Christoforidis, N., & Mamuris, Z. (2023) · Genes · doi:10.3390/genes14040799 · Cited by 10
“Genetic heterogeneity can affect the ability to detect associations between genotypes and phenotypes of interest [52] and, especially in obesity, ethnicity differences have been reported due to genetic background [53,54].”
Background
Cross-ancestry genetic architecture and prediction for cholesterol traits
Momin, M. M., Zhou, X., Hyppönen, E., Benyamin, B., & Lee, S. (2024) · Human Genetics · doi:10.1007/s00439-024-02660-7 · Cited by 6
“Some genes are functionally homogeneous across ances-tries while the other genes may not be (Lam et al. 2019; Marigorta and Navarro 2013; Peterson et al. 2019).”
Impact of cross-ancestry genetic architecture on GWAS in admixed populations
Mester, R., Hou, K., Ding, Y., Meeks, G. L., Burch, K. S., Bhattacharya, A., Henn, B., & Pasaniuc, B. (2023) · bioRxiv · doi:10.1101/2023.01.20.524946 · Cited by 7
“However, the success of admixture mapping indicates that the possibility of losing power due to over-correction for local ancestry stratification is serious 17,21 .”
Gene burden analysis identifies genes associated with increased risk and severity of adult-onset hearing loss in a diverse hospital-based cohort
Hui, D., Mehrabi, S., Quimby, A., Chen, T., Chen, S., Park, J., Li, B.-L., Ruckenstein, M., Rader, D., Ritchie, M., et al. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010584 · Cited by 7
A Method for Bridging Population-Specific Genotypes to Detect Gene Modules Associated with Alzheimer’s Disease
Dai, Y., Jia, P., Zhao, Z., & Gottlieb, A. (2022) · Cells · doi:10.3390/cells11142219 · Cited by 5
“However, it is now widely acknowledged that broadening the diversity of studied populations will improve the effectiveness of GWAS [7] with an especially noticeable difference between African and non-African populations [8].”
Background
Brain-derived neurotrophic factor Val66Met and neuropsychological functioning after early childhood traumatic brain injury
Treble‐Barna, A., Wade, S. L., Pilipenko, V. V., Martin, L. J., Yeates, K. O., Taylor, H. G., & Kurowski, B. G. (2022) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617722000194 · Cited by 9
“Results of analyses were similar when including only participants of European ancestry; therefore, both ancestral groups were retained to preserve power and to be more inclusive of diverse populations (Peterson et al., 2019).”

Authors: Peterson, R. E., Kuchenbaecker, K., Walters, R. K., Chen, C.-Y., Popejoy, A. B., Periyasamy, S., Lam, M., Iyegbe, C., Strawbridge, R. J., Brick, L., Carey, C. E., Martin, A. R., Meyers, J. L., Su, J., Chen, J., Edwards, A. C., Kalungi, A., Koen, N., Majara, L., Schwarz, E., Smoller, J. W., Stahl, E. A., Sullivan, P. F., Vassos, E., Mowry, B., Prieto, M. L., Cuellar-Barboza, A., Bigdeli, T. B., Edenberg, H. J., Huang, H., & Duncan, L. E.
Affiliations: Virginia Commonwealth University (US)
University College London (GB)
Broad Institute (US)
Stanford Medicine (US)
The University of Queensland (AU)
King's College London (GB)
Karolinska Institutet (SE)
Brown University (US)
SUNY Downstate Health Sciences University (US)
Arizona State University (US)
Heidelberg University (DE)
Massachusetts General Hospital (US)
Icahn School of Medicine at Mount Sinai (US)
University of North Carolina at Chapel Hill (US)
Mayo Clinic (US)
Indiana University School of Medicine (US)
Corresponding author: Peterson, Roseann E.
ORCID: Peterson, Roseann E.
Kuchenbaecker, Karoline
Walters, Raymond K.
Chen, Chia-Yen
Popejoy, Alice B.
Periyasamy, Sathish
Lam, Max
Iyegbe, Conrad
Strawbridge, Rona J.
Brick, Leslie
Carey, Caitlin E.
Martin, Alicia R.
Meyers, Jacquelyn L.
Su, Jinni
Chen, Junfang
Edwards, Alexis C.
Kalungi, Allan
Koen, Nastassja
Majara, Lerato
Schwarz, Emanuel
Smoller, Jordan W.
Stahl, Eli A.
Sullivan, Patrick F.
Vassos, Evangelos
Mowry, Bryan
Prieto, Miguel L.
Bigdeli, Tim B.
Edenberg, Howard J.
Huang, Hailiang
Duncan, Laramie E.
Venue: Cell
Publisher: Elsevier BV
Published: 2019-10
Volume: 179
Issue: 3
Pages: 589-603
ISSN: 0092-8674 (ISSN-L)
DOI: 10.1016/j.cell.2019.08.051
PMC: PMC6939869
OpenAlex: W2970480306
Cited by: 797
References: 89
Citations by year: 2026: 110 · 2025: 134 · 2024: 153 · 2023: 158 · 2022: 117 · 2021: 82 · 2020: 41 · 2019: 2
FWCI: 8.08
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: other-oa
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (vor, 382 d)
Locations: Cell (publishedVersion, other-oa)
PubMed (publishedVersion)
ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
PubMed Central (acceptedVersion)
UCL Discovery (University College London) (submittedVersion)
eScholarship (California Digital Library) (submittedVersion)
Research Portal (King's College London) (submittedVersion)
SUNY Digital Repository Support (State University of New York System) (submittedVersion, cc-by-nc-nd)
IUScholarWorks (Indiana University) (submittedVersion)
Funders: Vetenskapsrådet (D0886501)
UK Research and Innovation (MR/S003061/1, K99MH117229)
National Alliance for Research on Schizophrenia and Depression (22604)
National Institutes of Health (K01 MH113848, MH109532, MH109536, MH109539, U01 MH109528, MH109501, MH109514, MH109499)
European Commission
Horizon 2020
Royal Irish Academy (610307)
Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University
Wellcome Trust (212360/Z/18/Z, 5U01MH109539)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Social Sciences › Anthropology › Race, Genetics, and Society
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
Keywords: genome-wide association study, population diversity, admixed populations, genetic ancestry, genetic architecture, methodological considerations, underrepresented groups, genetic research ethics
MeSH terms: Data Accuracy, Human Genetics, Genetics, Population, Humans, Pedigree, Genetic Variation, Genome-Wide Association Study, Genotyping Techniques

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Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations

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