Cited by 797Genetic Associations and EpidemiologyRace, Genetics, and SocietyForensic and Genetic Research

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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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Akgün, B., & Rajabli, F. (2026) · Current Protocols · doi:10.1002/cpz1.70321 · Cited by 2
The current state of polygenic scores for the development of lung cancer: a systematic review and validation in UK Biobank
Galal, B., Dennis, J., Antoniou, A., & Harrison, H. (2026) · British Journal of Cancer · doi:10.1038/s41416-025-03330-9 · Cited by 2
Ethnic Discrimination Moderates Genetic Influences on Adolescent Internalizing and Externalizing Psychopathology
Su, J., Trevino, A. D., Jamil, B., Lemery‐Chalfant, K., Elam, K. K., & Causadías, J. M. (2025) · Behavior Genetics · doi:10.1007/s10519-025-10247-9 · Cited by 2
“limiting our understanding of G×E processes underlying the development of psychopathology among racially/ethni - cally marginalized populations (e.g., Black, Latinx, Asian American, multiracial) in the United States (Hagenbeek et al. 2023; Peterson et al. 2019).”
Self-citation
ACTN3 c.1729C>T Polymorphism Might Not Be a Standalone Factor in Non-contact Musculoskeletal Injury: A Systematic Review and Meta-analysis.
Varillas-Delgado, D., Villaoslada, E., & Clavaín, L. (2025) · Sports Medicine · doi:10.1007/s40279-025-02368-2 · Cited by 2
Plasma Protein Fluctuation Trajectories Over 15 Years Before Rheumatoid Arthritis Onset
Sun, C., Wang, J.-C., She, W., Lv, W.-H., Wei, S.-Y., Chen, H.-Y., Tao, J.-X., Yuan, L.-N., Zou, Y.-P., Li, R.-L., et al. (2025) · Immunology · doi:10.1111/imm.70066 · Cited by 2
The Promise of Genetics in Alcohol Use Disorders and the Problems of Phenotype, Polygenetic Architecture, Ancestry, and Comorbidity
Ehlers, C. L., & Peng, Q. (2025) · American Journal of Psychiatry · doi:10.1176/appi.ajp.20250909 · Cited by 2
Engaging migrants and immigrants in genetics research
Valdez-Aguilar, M., Conklin, J., & Abebe, D. (2025) · Nature Genetics · doi:10.1038/s41588-025-02373-1 · Cited by 2
“The diversity of genome-wide association studies is typically measured by the proportion of participants from different ancestral backgrounds, using reference panels such as the 1000 Genomes Project or self-reported ethnicity 27–30 .”
Mendelian randomization in a multi-ancestry world: reflections and practical advice
Mason, A. M., Zuber, V., Hemani, G., Raffetti, E., Xu, Y., Chong, A., Woolf, B., Allara, E., Gill, D., Soremekun, O. S., et al. (2025) · doi:10.48550/arxiv.2510.17554 · Cited by 2
Associations between epilepsy-related polygenic risk and brain morphology in childhood
Ngo, A., Liu, L., Larivière, S., Kebets, V., Fett, S., Weber, C. F., Royer, J., Yu, E., Rodríguez‐Cruces, R., Zhang, Z., et al. (2025) · Brain · doi:10.1093/brain/awaf259 · Cited by 5
“99 Replication of imaging-genetic effects, particularly using a GWAS that includes larger and more diverse cohorts—ideally with inclusion criteria that specifically define TLE-HS—could enhance the reliability and generalizability of imaging-genetic effects.”
Evocative effects of children's education‐associated genetics on maternal parenting: results from the Norwegian mother, father and child cohort study
Austerberry, C., Zayats, T., Ronald, A., Corfield, E. C., Smajlagić, D., Havdahl, A., Andreassen, O. A., Magnus, P. M., Njølstad, P. R., Bekkhus, M., et al. (2025) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.70025 · Cited by 6
Putting the patient at the centre: a call for research involvement of nurses, midwives and allied health professionals working in genomics
Cowley, L., Henriques, S., Roberts, J., Monje‐Garcia, L., Nolan, J., Lubasch, K., Theobald, R., Greer, R., Fennell, N., Clarkson, A., et al. (2025) · BMJ Open · doi:10.1136/bmjopen-2024-086962 · Cited by 2
Utilising genomic association data for causal inference in anorexia nervosa
Adams, D. M., & Cairns, M. J. (2025) · Mammalian Genome · doi:10.1007/s00335-025-10150-y · Cited by 2
“A large issue prevalent through many GWAS analyses is the lack of non-European cohorts (Peterson et al. 2019 ).”
Responses of Sitobion avenae (Hemiptera: Aphididae) to water-deficit stress on drought-resistant wheat cultivars
Khoso, A. G., Li, D., Yang, Y., Li, Y., & Liu, D. (2025) · Journal of Economic Entomology · doi:10.1093/jee/toaf091 · Cited by 3
Phenome-wide Mendelian randomization identifying circulating proteins for cardiovascular traits in populations of African ancestryPreprint
Selber‐Hnatiw, S., Trajanoska, K., Pelletier, J., Su, C., McClelland, P., Taliun, D., Yoshiji, S., Mooser, V., Bhérer, C., & Zhou, S. (2025) · medRxiv · doi:10.1101/2025.06.10.25329388 · Cited by 1
Utilization of polygenic risk scores in drug development protocols.
Pressly, M. A., Schuck, R. N., Mummaneni, P., Roman, Y., & Pacanowski, M. (2025) · Pharmacogenomics (London) · doi:10.1080/14622416.2025.2489916 · Cited by 2
Psychiatric Polygenic Risk Scores and Week-by-Week Symptomatic Status in Youth with Bipolar Disorder: An Exploratory Study
Jiang, X., Zai, C. C. H., Merranko, J. A., Young, L. T., Birmaher, B. B., & Goldstein, B. I. (2025) · Journal of Child and Adolescent Psychopharmacology · doi:10.1089/cap.2024.0130 · Cited by 1
“Given that ancestry is an important factor in genetic structure, it is important to undertake GWAS in the ancestral populations to which the ﬁ ndings would be applied (Martin et al., 2019; Peterson et al., 2019; Wray et al., 2021).”
Diversifying Psychiatric Genomics
Giusti‐Rodríguez, P., Okewole, N., Jain, S., Montalvo‐Ortiz, J. L., & Peterson, R. E. (2025) · Psychiatric Clinics of North America · doi:10.1016/j.psc.2025.01.003 · Cited by 4
Self-citation
Trans-ancestry Genome-Wide Analyses in UK Biobank Yield Novel Risk Loci for Major DepressionPreprint
Singh, M., Chatzinakos, C., Barr, P. B., Gentry, A. E., Bigdeli, T. B., Webb, B. T., & Peterson, R. E. (2025) · medRxiv · doi:10.1101/2025.02.22.25322721 · Cited by 4
“For the ancestry-stratified meta-analysis 21 ( Fig.”
InfluentialSelf-citation
IL-1 signaling enrichment in inflammatory skin disease loci with higher-risk allele frequencies in African ancestryPreprint
Tsoi, L., Dong, Y., Patrick, M. T., Sarkar, M., Zhang, H.-H., Bogle, R., Zhang, Z., Dand, N., Paulsen, M., Ljungman, M., et al. (2025) · Research Square · doi:10.21203/rs.3.rs-5724270/v1 · Cited by 2
“Recent GWAS have underscored the genetic factors in�uencing these ISDs; however, the predominance of European ancestry cohorts limit their generalizability 26,31,34 .”
Polygenic Risk Scores: Coming to Your Operating Room?
Kovacheva, V., & Saxena, R. (2024) · Anesthesiology · doi:10.1097/aln.0000000000005240 · Cited by 2
Identifying key genes in COPD risk via multiple population data integration and gene prioritization
Zainab, A., Anzawa, H., & Kinoshita, K. (2024) · PLoS ONE · doi:10.1371/journal.pone.0305803 · Cited by 2
“Post-GWAS functional analysis is critical for interpreting identified loci, as evolutionary forces create differences in allele frequencies and LD patterns among populations [57].”
Background
Novel risk loci for COVID-19 hospitalization among admixed American populationsPreprint
Diz-de-Almeida, S., Cruz, R., Luchessi, A., Lorenzo-Salazar, J., de Heredia, M. L., Quintela, I., González-Montelongo, R., Silbiger, V. N., Porras, M., Castano, J. A. T., et al. (2024) · eLife · doi:10.7554/elife.93666 · Cited by 2
A comprehensive framework for trans-ancestry pathway analysis using GWAS summary data from diverse populations
Fu, S., Wheeler, W., Wang, X., Hua, X., Godbole, D., Duan, J., Zhu, B., Deng, L., Qin, F., Zhang, H., et al. (2024) · PLoS Genetics · doi:10.1371/journal.pgen.1011322 · Cited by 3
Using Pre-training and Interaction Modeling for ancestry-specific disease prediction in UK Biobank
Menestrel, T. L., Craig, E., Tibshirani, R., Hastie, T., & Rivas, M. A. (2024) · arXiv.org · doi:10.48550/arxiv.2404.17626 · Cited by 2
“Yet, these studies have predominantly focused on individuals of European descent, leading to under-representation of non-European ancestry in genomic databases [5,6], despite ancestry being a crucial factor in disease susceptibility [7].”
Discovering mechanisms of human genetic variation and controlling cell states at scale
Frenkel, M. P. C., & Raman, S. (2024) · Trends in Genetics · doi:10.1016/j.tig.2024.03.010 · Cited by 2
Brain eQTLs of European, African American, and Asian ancestry improve interpretation of schizophrenia GWAS
Chen, Y., Liu, S., Ren, Z., Wang, F., Jiang, Y., Dai, R.-J., Duan, F., Han, C., Ning, Z.-L., Xia, Y., et al. (2024) · medRxiv · doi:10.1101/2024.02.13.24301833 · Cited by 2
“Past brain eQTL studies primarily focused on European (EUR) ancestry 2–6 .”
BackgroundSelf-citation
Worldwide distribution of genetic factors related to severity of COVID-19 infection
Esteban, M. E., Pino, D., Romero‐Lorca, A., Novillo, A., Gaibar, M., Riancho, J. A., Rojas‐Martínez, A., Flores, C., Lapunzina, P. D., Carracedo, Á., et al. (2024) · Annals of Human Biology · doi:10.1080/03014460.2024.2366248 · Cited by 2
“…and limited predictive power, the use of polygenic risk scores (PRSs) – the joint consideration of genotypes and genetic effects across the entire genome (Choi et al. 2020) – can provide additional useful insights, contingent on the aforementioned conservation of LD patterns (Peterson et al. 2019).”
Genetic Influences on Alcohol Sensitivity: a Critical Review
Yeung, E. W., Herchenroeder, L., Webster, H., Albright, A. B., & Gizer, I. R. (2023) · Current Addiction Reports · doi:10.1007/s40429-023-00530-2 · Cited by 2
Identification of Novel Loci and Cross-Disorder Pleiotropy Through Multi-Ancestry Genome-Wide Analysis of Alcohol Use Disorder in Over One Million Individuals
Icick, R., Shadrin, A., Holen, B., Karadag, N., Parker, N., O'Connell, K., Frei, O., Bahrami, S., Høegh, M., Lagerberg, T., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-3755915/v1 · Cited by 2
Self-citation
Evaluation of genomic factors and early childhood stimulation on intelligence in children from a Brazilian birth cohort: The primary role of independent factors
Sánchez-Luquez, K., Carpena, M. X., Karam, S. D. M., Martins‐Silva, T., Barros, F. C., Oliveira, I. O., Santos, I. S., Barros, A. J. D., Matijasevich, A., & Tovo‐Rodrigues, L. (2023) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2023.110932 · Cited by 4
Opioid trail: Tracking contributions to opioid use disorder from host genetics to the gut microbiome
Duffy, E. P., Bachtell, R. K., & Ehringer, M. A. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105487 · Cited by 4
Assessing the associations between known genetic variants and substance use in people with HIV in the United States
Haas, C., Jordahl, K. M., Nance, R., Whitney, B., Wang, L., Delaney, J., Ruderman, S., Jia, T., Mathews, W. C., Saag, M., et al. (2023) · PLoS ONE · doi:10.1371/journal.pone.0292068 · Cited by 2
Trans-ancestry polygenic models for the prediction of LDL blood levels: An analysis of the UK Biobank and Taiwan BiobankPreprint
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) · medRxiv · doi:10.1101/2023.08.03.23293320 · Cited by 2
Self-citation
Genetic liability for gastrointestinal inflammation disorders and association with gastrointestinal symptoms in children with and without autism
Morrill, V. N., Benke, K. S., Brinton, J. T., Soke, G. N., Schieve, L. A., Fields, V. L., Farzadegan, H., Holingue, C., Newschaffer, C. J., Reynolds, A., et al. (2023) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32952 · Cited by 2
“Efforts are underway to include more diverse samples in future GWAS (Mahajan et al., 2022; Peterson et al., 2019).”
Background
Genetic Associations with Dynamic Placental Proteins Identify Causal Biomarkers for Hypertension in PregnancyPreprint
Yan, Q., Blue, N., Truong, B., Zhang, Y., Guerrero, R. F., Liu, N.-J., Honigberg, M., Parry, S., McNeil, R., Mercer, B., et al. (2023) · medRxiv · doi:10.1101/2023.05.25.23290460 · Cited by 2
Population Genetics and Human Health in the Genomic Era
Assyuhada, M. G. S. N., Zulkafli, Z., Noor, N. H. M., Pati, S., Kari, Z. A., Dawood, M., Chambers, G. K., & Edinur, H. A. (2023) · Journal of King Saud University: Science · doi:10.1016/j.jksus.2023.102593 · Cited by 2
Meta-analysis of gestational duration and spontaneous preterm birth identifies new maternal risk lociPreprint
Pasanen, A., Karjalainen, M., FinnGen, Zhang, G., Tiensuu, H., Haapalainen, A., Ojaniemi, M., Feenstra, B., Jacobsson, B., Palotie, A., et al. (2022) · medRxiv · doi:10.1101/2022.10.31.22281753 · Cited by 2
A Prism Vote method for individualized risk prediction of traits in genotype data of Multi-population
Xia, X., Sun, R., Zhang, Y., Wei, Y., Li, Q., Chong, K. C., Wu, W. K. K., Zee, B. C.-Y., Tang, H., & Wang, M. H. (2022) · PLoS Genetics · doi:10.1371/journal.pgen.1010443 · Cited by 4
“Developing statistical methods for cross-population disease prediction is crucial for improving the genetic risk profiling, precision medicine interventions, and reducing health disparities [9].”
Method
Partial Identification of the Average Causal Effect in Multiple Study Populations: The Challenge of Combining Mendelian Randomization Studies
Diemer, E. W., Zuccolo, L., & Swanson, S. A. (2022) · Epidemiology · doi:10.1097/ede.0000000000001526 · Cited by 4
The Role of Polygenic Susceptibility on Air Pollution-Associated Asthma between German and Japanese Elderly Women
Kress, S., Hara, A., Wigmann, C., Sato, T. K., Suzuki, K., Pham, K.-O., Zhao, Q., Areal, A. T., Tajima, A., Schwender, H. R., et al. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19169869 · Cited by 3
“We followed recent recommendations to use ethnic-specific genotyping arrays [12,36,38] and to analyze the G × E effects between different ethnic groups using PRS.”
BackgroundMethodResultInfluential
Asymptotic tests for Hardy–Weinberg equilibrium in hexaploids
Wang, J., Feng, L., Mu, S., Dong, A., Gan, J.-W., Wen, Z.-Y., Meng, J., Li, M., Wu, R.-L., & Sun, L.-D. (2022) · Horticulture Research · doi:10.1093/hr/uhac104 · Cited by 2
“Polyploidy has been thought to be a driving force for evolution and speciation, especially in higher plants [1– 4], but the genetic mechanisms underlying its evolution have not been fully understood [5].”
BackgroundMethod
The contribution of genetic risk to the comorbidity of depression and anxiety: a multi-site electronic health records studyPreprint
Coombes, B., Landi, I., Choi, K., Singh, K., Fennessy, B., Gao, Y.-N., Jenkins, G., Batzler, A., Pendegraft, R., Núñez, N., et al. (2022) · medRxiv · doi:10.1101/2022.04.11.22273720 · Cited by 2
Self-citation
Genome-wide study on 72,298 Korean individuals in Korean biobank data for 76 traits identifies hundreds of novel loci
Nam, K., Kim, J., & Lee, S. (2022) · medRxiv · doi:10.1101/2022.02.23.22271389 · Cited by 2
Polygenic risk prediction based on singular value decomposition with applications to alcohol use disorder
Yang, J. J., Luo, X., Trucco, E. M., & Buu, A. (2022) · BMC Bioinformatics · doi:10.1186/s12859-022-04566-5 · Cited by 5
“To deal with this issue, the PRS approach proposes an additive model to summarize the marginal effects of many variants to quantify genetic influences on a particular phenotype [4].”
Method
Cooperative studies Program (CSP) #572: A study of serious mental illness in veterans as a pathway to personalized medicine in schizophrenia and bipolar illness
Harvey, P. D., Bigdeli, T. B., Fanous, A. H., Li, Y., Rajeevan, N., Sayward, F. G., Radhakrishnan, K., Huang, G. D., & Aslan, M. (2021) · Personalized Medicine in Psychiatry · doi:10.1016/j.pmip.2021.100078 · Cited by 3
Self-citation
Genetic Architecture of Bipolar Disorder in Individuals of Han Chinese and European Ancestries
Mullins, N., & Huang, H. (2020) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2020.3639 · Cited by 3
Self-citation
Four Actionable Bottlenecks and Potential Solutions to Translating Psychiatric Genetics Research: An Expert Review
Bourdon, J. L., Davies, R. A., & Long, E. C. (2020) · Public Health Genomics · doi:10.1159/000510832 · Cited by 2
Characterizing features of the genetic architecture underlying autism from a multi-ancestry perspective
de Aquino, M. M., Xu, C. Y., Engchuan, W., Trost, B., Zhou, X., Miwa, B., Salazar, N. B., Iglar, J., Thiruvahindrapuram, B., Wallich, L., et al. (2026) · Molecular Psychiatry · doi:10.1038/s41380-026-03886-9 · Cited by 2
Clinical Utility of Trio Exome Sequencing in Rwandan Children With Autism Spectrum Disorder
Hakizimana, O., Hitayezu, J., Uyisenga, J. P., Dukuze, N., Akimana, M. V., Mizero, L., Bampire, C., Mudenge, C., Butoto, X. K., Helou, L., et al. (2026) · Molecular Genetics & Genomic Medicine · doi:10.1002/mgg3.70294 · Cited by 1
“Despite harboring the greatest human genetic diversity, African populations remain markedly underrepresented in global genomic reference databases (Martin et al. 2018; Peterson et al. 2019).”
Genetic variants and the risk of renal impairment in decompensated cirrhosis: a multi-ancestry genome-wide association study
Sanchez, L. O., Clãria, J., Galvanin, C., Aguilar, F., Layese, R., Serra, M., Jiménez-Gracia, L., Nieto, P., Castven, D., Fraňková, S., et al. (2026) · The Lancet. Gastroenterology & hepatology · doi:10.1016/s2468-1253(26)00217-7
plinkQC : an integrated tool for ancestry inference, sample selection, and quality control in population genetics
Syed, M., Walter, C., & Meyer, H. V. (2026) · Bioinformatics · doi:10.1093/bioinformatics/btag612 · Cited by 3
“For cohorts composed of multiple ances-tries, PCs can be used to define and divide cohorts into ancestry-specific subgroups for independent analyses and potential meta-analyses (Price et al. 2006, Peterson et al. 2019).”
Genome-wide association analyses of borderline personality disorder identify 11 loci and highlight shared risk with mental and somatic disorders
Streit, F., Awasthi, S., Hall, A. S. M., Braun, A., Niarchou, M., Marouli, E., Babajide, O., Frank, J., Zillich, L., Callies, C., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02654-3 · Cited by 14
“Furthermore, expanding the analyses to non-European ancestries is necessary to improve our understanding of the underlying genetic architecture and to facilitate the generalizability of the results 84,85 .”
Self-citation
Global Landscape of Publicly Available Human Oral Microbiome Data
Chen, X., Jamieson, L., Weyrich, L. S., & Nath, S. (2026) · Journal of Dental Research · doi:10.1177/00220345261456612 · Cited by 1
An OLD DOG teaching us new tricks in ageing biology
Carvalho, O. M. D. S., Abukwaik, A., Sultan, O., Koizia, L., & Harris, B. H. L. (2026) · The Journal of frailty & aging · doi:10.1016/j.tjfa.2026.100181 · Cited by 1
A comprehensive overview of the biological foundations of ADHD
Folego-Temoteo, I., Lima, Y. C., Grevet, E. H., Vidor, M. V., Tavares, M. E., da Silva, B. S., Bau, C. H. D., & Rovaris, D. L. (2026) · Bioscience Reports · doi:10.1042/bsr20254061 · Cited by 1
Placental biology links genetic, epigenetic, ancestral, and social determinants to maternal–fetal health inequities
Schuch, V., Mukherjee, I., de Carvalho, A. R. N., Olanrewaju, R. A., Davis, J., Thomas, S., Chakraborty, R., & Johnson, E. L. (2026) · Frontiers in Reproductive Health · doi:10.3389/frph.2026.1783837 · Cited by 1
“Large maternal GWAS meta-analyses of preeclampsia and gestational hypertension (109) illustrate the distinction between “multi-ancestry” labeling and balanced representation.”
Leveraging Machine Learning to Predict Warfarin Sensitivity in the Puerto Rican Population: A Pharmacogenomic Approach
Martínez-Jiménez, J. E., Ortega-Lampón, Y., Cedres-Rivera, D., Heredia-Negrón, F., Roche-Lima, A., & Duconge, J. (2026) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph23030337 · Cited by 1
“Most pharmacogenomic studies, including genome-wide association studies (GWAS), have been conducted predominantly in individuals of European ancestry, [9,19–21] with more than 87% of participants in many genomic datasets of European descent and fewer than 2% Hispanic/Latino individuals [22].”
Gene-drug interactions identify genomic loci that enhance statin effectiveness in lowering LDL cholesterolPreprint
Verhulst, B., Harris, J., Adams, A. M., Benstock, S. E., Tong, C. W.-C., Case, A. J., & Hettema, J. M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.04.703692 · Cited by 1
“Second, existing non-European sample sizes in the UKB do not provide sufficient power for genome-wide analyses 54,55 .”
Maternal and fetal genetic predispositions to insulin deficiency and resistance affect fetal growth through distinct pathways
Yu, G., Tam, C., Shi, M., Hughes, A. E., Huang, C., Deng, Y., Weedon, M. N., Lim, C. K. P., Wang, C.-C., Chan, J. C. N., et al. (2026) · Diabetologia · doi:10.1007/s00125-026-06669-7 · Cited by 1
“We calculated the corrected birthweight [28] Before imputation, we performed genetic ancestry inference on all individuals in each ethnic group following the recommended pipeline from Peterson et al [30] (for details, see ESM Methods and ESM Figs 1, 2).”
The double-edged sword: A critical review of foundational medical datasets for AI benchmarks, biases, and the future of equitable healthcare
Ramadan, R. Α., Madi, N. K. M., Fageeri, S. O., Yousif, K. A., Al-Daweri, M. S., & Rajhi, W. K. H. A. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.132919 · Cited by 5
Searching for local associations while controlling the false discovery rate
Gablenz, P., Sesia, M., Sun, T.-S., & Sabatti, C. (2026) · Journal of the American Statistical Association · doi:10.1080/01621459.2026.2616856 · Cited by 1
Cross‐Ancestry Polygenic Prediction: Comparing Methods and Assessing Transferability Across Traits
Momin, M. M., Zhou, X., Ahmed, M., Hyppönen, E., Benyamin, B., & Lee, S. H. (2026) · Genetic Epidemiology · doi:10.1002/gepi.70029 · Cited by 2
“The majority of GWASs to date have been conducted in individuals of European descent (Hindorff et al. 2018; Peterson et al. 2019), and there are many genetic studies to show that the accuracy of PGSs based on European training data is lower when applied to non‐European populations (Martin et al.…”
Genome-wide association study of tolerance to acute hypoxia in the olive flounder (Paralichthys olivaceus) using individual blood cortisol levels as a physiological phenotype.
Dilshan, M. A. H., Kim, G., Omeka, W., Liyanage, D., Udayantha, H., Rodrigo, D., Ganepola, G., Hanchapola, H. A. C. R., Kodagoda, Y. K., Gong, P., et al. (2025) · Gene · doi:10.1016/j.gene.2025.149952 · Cited by 1
From Normal Variation in Sleep to Clinical Sleep Disorders: Genetic Insights from Over One Million IndividualsPreprint
Kunorozva, L., Valliere, J., Chen, C., Maher, M., Tchio, C. I. M., Burns, A. C., Zhang, Y., Strausz, S. J., FinnGen, Winkelman, J. W., et al. (2025) · medRxiv · doi:10.1101/2025.11.21.25340447 · Cited by 1
Self-citation
The lack of ESR1 ethnic diversity evidence and its implications for breast cancer personalized treatment
Manóchio, C., Faleiros, H., Vieira, J. F., Oliveira-Ferreira, A., Nomelini, R. S., & Rodrigues-Soares, F. (2025) · Drug Metabolism and Personalized Therapy · doi:10.1515/dmpt-2025-0067 · Cited by 1
“However, no association between ESR1 genotypes and adverse events was observed in studies with heterogeneous populations [28], likely re ﬂ ecting population structure and the predominance of homogeneous samples in pharmacogenetic studies [29].”
Multi-Omics Advances in Major Depressive Disorder for Molecular Insights, Biomarker Discovery, and Therapeutic Development
Elasbali, A. M., Adnan, M., Ali, A. S., Shamsi, A., & Hassan, M. I. (2025) · Aging and Disease · doi:10.14336/ad.2025.1075 · Cited by 2
“This has remedied the historical limitations of GWAS, typically constrained to European samples, by incorporating underrepresented populations to reveal population-specific variants [45].”
SPAmix: a scalable, accurate, and universal analysis framework for large-scale genetic association studies in admixed populations
Ma, Y., Xu, H., Li, Y., Kim, H., Xu, L.-L., Miao, L., Xu, P., Mao, F., Zhou, S., Zhou, W., et al. (2025) · Genome biology · doi:10.1186/s13059-025-03827-9 · Cited by 2
“Population stratification is a significant confounder in GWAS, and large biobanks may include a considerable number of individuals from heterogeneous ancestries, such as those in admixed populations [21–23].”
Examining polygenic scores for depression, depressive symptoms from childhood to adolescence, and adolescent substance use in a diverse sample: The moderating impact of a family-centered intervention
Elam, K. K., Shaw, D., Westling, E., Brown-Iannuzzi, J. L., & Lemery-Chalfant, K. (2025) · Development and Psychopathology · doi:10.1017/s0954579425100709 · Cited by 1
“Rather statistical models are typically computed within each ancestral group without cross-comparison (Peterson et al., 2019).”
Influential
Ten years of exome sequencing and reanalysis among racial, ethnic, and ancestral groups: The importance of equitable reanalysis access
Giles, A., Zayhowski, K., Ruderman, M., Rañola, J. M. O., VanNoy, G. E., & Towne, M. C. (2025) · Genetics in Medicine · doi:10.1016/j.gim.2025.101576 · Cited by 2

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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