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Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations
Open accessAbstract
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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“Previous studies have found that population diversity may improve fine-mapping resolution38,39”
From Shared genetic architectures of educational attainment in East Asian and European populations (2024) · cites this paper as [39]
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“Available genomic studies have focused mainly on European descent, accounting for approximately 79% of all GWAS participants, while the overall European population comprises about 16% of the total global population (Martin et al., 2019; Peterson et al., 2019).”
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“Finally, as noted in many of the reviews as well as in the PGC review in Cell (Peterson et al., 2019), we urgently require larger samples from individuals of non-European ancestry.”
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Self-citationFrom variants to mechanisms: Neurogenomics in the post-GWAS era
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Self-citationThe Impact of Ancestry on Genome-Wide Association Studies
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“Furthermore, expanding the analyses to non-European ancestries is necessary to improve the understanding of the underlying genetic architecture and to facilitate the generalizability of the results 85,86 .”
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“…Consortium, NIH’s All of Us Research Program), new platforms for genotyping DNA from diverse groups, and new methods for analyzing GWAS data across ancestral groups and within groups of mixed genetic ancestry (e.g., Hispanic and/or Latine participants; Atkinson et al., 2021; Peterson et al., 2019).”
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“This general strategy has been shown to be robust to population strati fi cation [14, 30, 31].”
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“13 Biobanking and genetic research activities in LMICs are limited.”
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“1 The post-GWAS era and possible implementations of GWAS results in psoriasis. increase in the forthcoming years is expected to identify additional shared and population-speci fi c loci implicated in psoriasis pathogenesis, fostered by the development of multi-ancestry strategies [26].”
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“Thus, low power due to the underlying sampling bias towards European ancestry individuals in most global consortia is still eminent [18, 19].”
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“…genetics, with transferability of European‐centric GWAS findings to other populations impacted by many factors (e.g., linkage disequilibrium, allele frequencies, genetic architecture); however, there is growing effort to increase diversity in large‐scale genomics discovery (Peterson et al., 2019).”
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“Consistent with previous studies 50–52 , we find that the PRS we derived from GWAS on European-ancestry cohorts generally had poorer portability to non-European cohorts.”
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“However, emerging trans-ancestry methods are increasingly available and should be applied to be as inclusive as possible (see Table 1) (Peterson et al., 2019).”
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“For heterogeneous multi-ancestry samples, joint mixed-model methods might be the optimal approach [34].”
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Gene-Environment Effects on Female FertilityPreprint
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“Finally, expanding the analysis to populations of non-European descent will allow us to ascertain the generalizability of our results to other ethnic groups (Peterson et al., 2019).”
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“Population-specific genetic architectures can influence genetic associations, potentially limiting the direct transferability of genetic findings across ancestries [50, 51].”
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“While inappropriately conducted MR analysis can lead to spurious heterogeneity in causal ef-82 fects across ancestries, genuine heterogeneity does exist due to differences in environmental and cultural factors, such as dietary habits, climate, and lifestyle (Peterson et al., 2019).”
Andreu-Bernabeu, Á., González‐Peñas, J., Perdiguero, A. M., Bernardo, M., Mezquida, G., Amoretti, S., Bobes, J., Sáiz, P. A., García‐Portilla, M. P., Sanjuán, J., et al. (2025) · The British Journal of Psychiatry · doi:10.1192/bjp.2025.100 · Cited by 5
“50 Future models should also incorporate a wider range of risk factors, focusing on critical time windows and the complexities of subjective, long-lasting experiences.”
Methodological opportunities in genomic data analysis to advance health equity
Lehmann, B., Bräuninger, L., Cho, Y., Falck, F., Jayadeva, S., Katell, M. A., Nguyen, T., Perini, A., Tallman, S., Mackintosh, M. E., et al. (2025) · Nature Reviews Genetics · doi:10.1038/s41576-025-00839-w · Cited by 7
“In a diverse sample, applying these metrics without accounting for population structure may lead to variants and samples being incorrectly flagged as errors or outliers, particularly from under-represented groups 23 .”
Genome‐Wide Association Study Reveals Genetic Architecture of Common Epilepsies
Thakran, S., Guin, D., Singh, P., Uppili, B., Ramachandran, S., Kushwaha, S. S., & Kukreti, R. (2025) · Clinical Genetics · doi:10.1111/cge.14710 · Cited by 5
Icick, R., Shadrin, A. A., Holen, B., Karadag, N., Parker, N., O’Connell, K. S., Frei, O., Bahrami, S., Høegh, M. C., Lagerberg, T. V., et al. (2025) · Nature Mental Health · doi:10.1038/s44220-024-00353-8 · Cited by 6
“Likewise, including samples from multiple ancestries by meta-analysis may improve GWAS ability to detect and infer causality and biological relevance of associated genetic variants 14 —including for AUD 6,7 .”
Self-citationHorwitz, T. B., Zorina-Lichtenwalter, K., Gustavson, D. E., Grotzinger, A. D., & Stallings, M. C. (2024) · Behavior Genetics · doi:10.1007/s10519-024-10188-9 · Cited by 4
“…were comprised of individuals of European ancestry, as different genetic ancestry groups may have different patterns of linkage disequilibrium and allele frequencies (Peterson et al. 2019) and analyses looking at non-European ancestry groups are under-powered for some of the indicators of interest.”
Friligkou, E., Løkhammer, S., Cabrera‐Mendoza, B., Shen, J., He, J., Deiana, G. A., Zanoaga, M. D., Asgel, Z., Pilcher, A., Lascio, L. D., et al. (2024) · medRxiv · doi:10.1101/2024.02.14.24302836 · Cited by 8
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“Lastly, 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.”
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“In addition to disease-related variants, different racial and ethnic groups may have distinct genetic variations that influence disease susceptibility and treatment responses [54].”
BackgroundLife is pain: Fibromyalgia as a nexus of multiple liability distributions
Moscati, A., Faucon, A. B., Arnaiz, C., Lönn, S. L., Sundquist, J., Sundquist, K., Belbin, G. M., Nadkarni, G. N., Cho, J. H., Loos, R. J. F., et al. (2023) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32949 · Cited by 4
“…predicting the same trait, in samples from distinct continental populations as the genetic distance between the discovery and test populations reduces accuracy in the polygenic associations (Peterson et al., 2019), and can also unpredictably produce biases in any direction (Martin et al., 2017).”
BackgroundOsman, W. M., Mousa, M., Albreiki, M. S., Baalfaqih, Z., Daggag, H., Hill, C., McKnight, A. J., Maxwell, A. P., & AlSafar, H. S. (2023) · Scientific Reports · doi:10.1038/s41598-023-31701-w · Cited by 6
Genetic nurture in educational attainment
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Polygenic scores for psychiatric disorders in a diverse postmortem brain tissue cohort
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“The most critical consideration for use of the polygenic scores is ancestry given that polygenic scores are oftentimes highly correlated with ancestry, and therefore spurious findings may be generated if ancestry is not adjusted for correctly in analyses [36].”
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“Despite concerted efforts (such as through policy initiatives by the NIH), this underrepresentation continues to widen [2, 39, 40].”
BackgroundThe molecular genetic landscape of human brain size variation
Seidlitz, J., Mallard, T., Vogel, J., Lee, Y., Warrier, V., Ball, G., Hansson, O., Hernandez, L., Mandal, A., Wagstyl, K., et al. (2022) · bioRxiv · doi:10.1101/2022.11.03.514996 · Cited by 5
Self-citationBountress, K. E., Bustamante, D., de Viteri, S. S., Chatzinakos, C., Sheerin, C. M., Daskalakis, N. P., Edenberg, H. J., Peterson, R. E., Webb, B. T., Meyers, J., et al. (2022) · Psychological Medicine · doi:10.1017/s0033291722002999 · Cited by 7
“…whether findings are consistent between those of European Ancestry (EA) and African Ancestry (AA) individuals – the latter of which is particularly important given the lack of diversity in genomic studies (Bentley, Callier, & Rotimi, 2017; Peterson et al., 2019; Sirugo, Williams, & Tishkoff, 2019).”
Self-citationThoughtful Phenotype Definitions Empower Participants and Power Studies
Huckins, L. M. (2022) · Complex Psychiatry · doi:10.1159/000527022 · Cited by 3
Rare schizophrenia risk variant burden is conserved in diverse human populationsPreprint
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“Studies of mental illness have contributed to this disparity with almost exclusive European GWAS cohorts despite roughly equal prevalence of psychiatric disorders worldwide 17 .”
BackgroundSelf-citationCoto-Vílchez, C., Martínez-Magaña, J. J., Mora-Villalobos, L., Valerio, D., Genis-Mendoza, A. D., Silverman, J. M., Nicolini, H., Raventós, H., & Chavarria-Soley, G. (2021) · CNS Spectrums · doi:10.1017/s109285292100105x · Cited by 5
“Besides, there is increasing recognition of the value of studying ancestrally diverse populations, and Latin American populations have been historically underrepresented in large-scale genomic and epigenomic studies.(74,75)”
BackgroundPerspective on Beyond Statistical Significance: Finding Meaningful Effects
Edenberg, H. J. (2021) · Complex Psychiatry · doi:10.1159/000517237 · Cited by 7
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Multi-ancestry GWAS of age-related hearing loss identifies 140 loci and key cellular mechanisms
Shi, L., He, H., Li, J., Gai, K., Li, W., Zhao, Y., Yuan, H., & Wu, Y. (2026) · Nature Communications · doi:10.1038/s41467-026-69894-z · Cited by 3
Ancestral diversity in complex disease genetics: from discovery to translation
Kuchenbaecker, K. B., & Navoly, G. (2026) · Nature Reviews Genetics · doi:10.1038/s41576-025-00921-3 · Cited by 6
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“Previous research shows that the effectiveness and reliability of PGS are primarily influenced by the statistical power and sample size of the discovery GWAS, as well as the ancestral similarities between the target and discovery samples (Martin et al., 2019; Peterson et al., 2019).”
Self-citationSyed, M., Walter, C., & Meyer, H. V. (2025) · bioRxiv · doi:10.1101/2025.11.25.690541 · Cited by 4
“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).”
Bucheeri, S., Alcibahy, Y., Bucheeri, Y., Bucheeri, S., Alhermi, A., & Butler, A. E. (2025) · Cells · doi:10.3390/cells14221769 · Cited by 8
“In addition, ethnic diversity remains underrepresented, with most data derived from East Asian and European populations [92–94].”
Rivier, C., Xu, L.-Q., Clocchiatti-Tuozzo, S., Zhao, H.-Y., Ohno-Machado, L., Hafler, D., Falcone, G., & Longbrake, E. (2025) · Multiple Sclerosis · doi:10.1177/13524585251377607 · Cited by 4
“8 This raises the possibility that there is less applicability and accuracy of GRS in individuals of non-Euro-pean ancestries, potentially leading to disparities in disease prediction and prevention efforts.”
Echoes of Inequity: A Critical Examination of the Past, Present, and Future of Cardiac Health Equity
Awoyemi, T., Mutebi, C., Youmans, Q. R., Okwuosa, I. S., Yancy, C. W., & Ositelu, K. C. (2025) · Current Cardiology Reports · doi:10.1007/s11886-025-02275-y · Cited by 6
“There have been over 250 loci linked to CAD identified through genome-wide association studies (GWAS), with more being discovered using multi-ancestry GWAS uncovering novel loci in diverse populations [79, 80].”
Obesity-related brain atrophy is independent of Alzheimer's disease protein pathways
Morys, F., Liu, L., Senkevich, K. A., Gan‐Or, Z., & Dagher, A. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251359680 · Cited by 3
“82,83 Prior to exclusions, our sample included only 2.6% percent of individuals of other ethnicities, which was not enough to conduct desired, disag-gregated analyses.”
InfluentialPoudel, A., Phogat, S., Roy, J., Saini, M. R., Shivaprasad, K., Madhavan, J., Chinnusamy, V., Vinod, K. K., Sevanthi, A., & Mandal, P. (2025) · Zeitschrift für Induktive Abstammungs- und Vererbungslehre · doi:10.1007/s00438-025-02249-3 · Cited by 4
“Diversity of the association panel is very important for the success of a GWAS study (Peterson et al. 2019).”
Lo, Y.-C., Tian, H., Chan, T. F., Jeon, S., Alatorre, K., Dinh, B. L., Maskarinec, G., Taparra, K., Nakatsuka, N. J., Yu, M., et al. (2025) · Communications Biology · doi:10.1038/s42003-025-08050-7 · Cited by 4
“However, available GWAS data are heavily biased towards European-ancestry individuals 13,14 , posing a challenge for PGS due to its poor transferability between populations.”
Self-citationMeena, D., Huang, J. V., Zare, M., Hasbani, N. R., Boua, P. R., Mustafa, R., van der Laan, S. W., Xu, H., Terry, J. G., Bis, J. C., et al. (2025) · medRxiv · doi:10.1101/2025.04.11.25325582 · Cited by 3
“Second, the identification of 12 additional loci associated with cIMT from the multi-ancestry meta-analysis emphasises the importance of aggregating GWAS results from diverse populations to increase sample size and statistical power which is in line with previous research 19 .”
Striving Towards Equity in Cardiovascular Genomics Research
Vélez, J. A. J., Anderson, N., Datcher, I., Foster, C., Jackson, P., & Hidalgo, B. (2025) · Current Atherosclerosis Reports · doi:10.1007/s11883-025-01277-z · Cited by 4
“However, the patient population for GWAS studies consists of 78–91% of patients from European ancestry, lacking an inclusive representation of underrepresented communities [7–9].”
Kuang, A., Hivert, M., Hayes, M. G., Lowe, W. L., & Scholtens, D. M. (2025) · BMC Genomics · doi:10.1186/s12864-025-11229-1 · Cited by 6
Descriptor: Synthetic Genomic Dataset With Diverse Ancestry (SynGen6)
Wang, X., Min, S., & Vaidya, J. S. (2024) · IEEE data descriptions. · doi:10.1109/ieeedata.2024.3505852 · Cited by 2
Ramirez-Diaz, A. M., Díaz‐Zuluaga, A. M., Stroud, R. E., Vreeker, A., Bitta, M. A., Ivankovic, F., Wootton, O., Whiteman, C., Mountcastle, H., Jha, S. C., et al. (2024) · medRxiv · doi:10.1101/2024.10.02.24314732 · Cited by 3
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Improving genetic risk modeling of dementia from real-world data in underrepresented populations
Fu, M., Valiente‐Banuet, L., Wadhwa, S. S., UCLA Precision Health Data Discovery Repository Working Group, UCLA Precision Health ATLAS Working Group, Paşaniuc, B., Vossel, K. A., & Chang, T. S. (2024) · Communications Biology · doi:10.1038/s42003-024-06742-0 · Cited by 4
Step, K., Sima, C. A. A. N., Mata, I. F., & Bardien, S. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2024.1380860 · Cited by 8
Genetic Researchers’ Use of and Interest in Research With Diverse Ancestral Groups
Jaffe, K., Greene, A. K., Chen, L., Ryan, K. A., Krenz, C. D., Roberts, J. S., Zikmund‐Fisher, B. J., McGuire, A. L., Thomas, J. D., Marsh, E. E., et al. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.6805 · Cited by 6
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Improving genetic risk modeling of dementia from real-world data in underrepresented populations
Fu, M.-Z., Valiente-Banuet, L., Wadhwa, S. S., Pasaniuc, B., Vossel, K., & Chang, T. S. (2024) · medRxiv · doi:10.1101/2024.02.05.24302355 · Cited by 4
Progress and Implications from Genetic Studies of Bipolar Disorder
Kong, L., Chen, Y., Shen, Y., Zhang, D., Chen, W., Lai, J., & Hu, S. (2024) · Neuroscience Bulletin · doi:10.1007/s12264-023-01169-9 · Cited by 6
“…with abnormalities in nodal network measures in structures within the limbic system, especially the left hippocampus, the bilateral isthmus of the cingulate [113, 114], the corpus callosum [115], and the lateral occipital cortex [116], but the exact genetic mechanisms remain to be elucidated.”
Functional genomics and small molecules in mitochondrial neurodevelopmental disorders
Calame, D. G., & Emrick, L. (2024) · Neurotherapeutics · doi:10.1016/j.neurot.2024.e00316 · Cited by 11
“As common variant studies have concentrated in Europe and the United States due to global inequities, remaining common variant studies must concentrate on the Global South and other understudied populations [110].”
BackgroundKe, M.-H., Bao, B., Ke, Z., Ma, W., Guo, J., Zhang, L., Wen, H., Ma, L.-R., Fan, G., & Liu, B. (2023) · Endocrine · doi:10.1007/s12020-023-03653-8 · Cited by 4
“This provides a more robust and reliable dataset for MR analysis due to the larger sample size and reduced heterogeneity [47].”
Bebo, A., Jarmul, J. A., Pletcher, M., Hasbani, N. R., Couper, D., Nambi, V., Ballantyne, C., Fornage, M., Morrison, A., Avery, C., et al. (2023) · PLoS ONE · doi:10.1371/journal.pone.0285259 · Cited by 4
Human Genetic Variation in F3 and Its Impact on Tissue Factor–Dependent Disease
Park, J. K., Brake, M. A., & Schulman, S. (2023) · Seminars in Thrombosis and Hemostasis · doi:10.1055/s-0043-1769079 · Cited by 5
“71”
Kim, D., Song, J., Mancuso, N., Mangul, S., Ahn, C. W., Jang, W., & Jang, W. (2024) · Arthritis Research & Therapy · doi:10.1186/s13075-024-03280-2 · Cited by 7
“This creates a critical gap in our understanding of complex traits across diverse populations [138].”
BackgroundGenetic variants associated with post-traumatic stress symptoms in patients with gynecologic cancer
Johnson, A. M., Teoh, D. G. K., Jewett, P. I., Darst, B. F., Mattson, J. N., Hoffmann, C., Brown, K., Makaram, A., Keller, C., Blaes, A. H., et al. (2023) · Gynecologic Oncology · doi:10.1016/j.ygyno.2023.01.006 · Cited by 6
Understanding Anhedonia from a Genomic Perspective
Bondy, E., & Bogdan, R. (2022) · Current topics in behavioral neurosciences · doi:10.1007/7854_2021_293 · Cited by 9
Genetic and Social-Environmental Influences on Substance Use and Disorders
Meyers, J. L., & Salvatore, J. E. (2021) · Psychiatric Annals · doi:10.3928/00485713-20210311-02 · Cited by 4
Self-citationBrick, L. A. D., Benca‐Bachman, C. E., Bertin, L., Martin, K. P., Risner, V., & Palmer, R. H. C. (2021) · Addiction · doi:10.1111/add.15476 · Cited by 4
Self-citationGeographic patterns of human allele frequency variation: a variant-centric perspective
Biddanda, A., Rice, D. P., & Novembre, J. (2020) · bioRxiv · doi:10.1101/2020.07.01.182311 · Cited by 4
“Most importantly, future applications of the approach will ideally use datasets that include a greater sampling of the world’s genetic diversity (Bustamante, Burchard, and De la Vega 2011; Popejoy and Fullerton 2016; Martin et al. 2017; Peterson et al. 2019).”
BackgroundACLY and CKD: A Mendelian Randomization Analysis
Mohammadi‐Shemirani, P., Chong, M., Perrot, N., Pigeyre, M., Steinberg, G. R., Paré, G., Krepinsky, J. C., & Lanktree, M. B. (2022) · Kidney International Reports · doi:10.1016/j.ekir.2022.04.013 · Cited by 9
“The eQTLGen, CKDGen, and UK Biobank data available are primarily of White European ancestry, and improving the ancestral diversity of genomic studies is a recognized ethical and scientific imperative.(31) We tested variants associated with ACLY expression in the blood, which is likely an imperfect proxy for ACLY expre…”
Hollowell, A., Gui, A., Wigdor, E. M., MORGAN, M., Hannigan, L. J., Corfield, E. C., Pool, R., Bruins, S., Ask, H., Middeldorp, C. M., et al. (2026) · Nature Human Behaviour · doi:10.1038/s41562-026-02486-5 · Cited by 3
“Past GWAS have mostly been conducted in European-ancestry samples due to data availability 95 .”
A comparison of deep multiomics profiles across ethnicity, geography, and age
Bararpour, N., Cao, J. Z., Wu, Y., Gupta, S., Hoopmann, M. R., Qin, R., Midha, M. K., Mireault, M., Juanes‐Velasco, P., Hanson, C. R., et al. (2026) · Cell · doi:10.1016/j.cell.2026.04.032 · Cited by 3
Su, H., Wang, T., & Chen, C. (2026) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2026.1797221 · Cited by 3
“…of non-European populations in current datasets raises additional concern that AI systems may perform unevenly across demographic groups, thereby exacerbating existing inequities in precision oncology (Carter et al., 2020; Murdoch, 2021; Peterson et al., 2019; Martin et al., 2019).”
Self-citationYang, Y., & Zhu, X. (2026) · Genome biology · doi:10.1186/s13059-026-04051-9 · Cited by 2
“While improperly conducted MR analyses may yield spurious heterogeneity in causal effects across ancestries, genuine heterogeneity can also arise from environmental and cultural differences, such as diet, climate, and lifestyle [23].”
Black EquaLity in OCD NeuroGenomics ( BELONG ): Study Protocol
Williams, I. J., Márquez., D. Y. P., Lopez-Lengowski, K., Bommiasamy, M., Onyeka, O. “., Underwood, S. J., Avery, J. E., Gluckman, J., Pichardo, T., Chandler, R., et al. (2026) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmgb.70002 · Cited by 3
“Most large-scale genomic discoveries are heavily biased toward individuals of European ancestry (EUR), despite the fact that EUR populations only make up 16% of the global population, potentially exacerbating existing health disparities (Martin et al. 2019; Peterson et al. 2019).”
Changes in polygenic burden for psychiatric disorders across two decades of birth cohorts
Lousdal, M. L., LaBianca, S., Agerbo, E., Albiñana, C., Vilhjálmsson, B. J., McGrath, J. J., Schork, A. J., & Plana‐Ripoll, O. (2025) · Nature Mental Health · doi:10.1038/s44220-025-00478-4 · Cited by 2
“As PGSs have lower prediction accuracy in other ancestries, large diverse discovery cohorts are needed to fully characterize PGS changes over time 30,31 .”
Shen, X., Toenders, Y. J., Han, L. K. M., Weihs, A., Alexander, N., Andlauer, T. F. M., Brosch, K., Forstner, A. J., Grotegerd, D., Hahn, T., et al. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-03136-4 · Cited by 8
Genetic and epigenetic landscape of erectile dysfunction: a comprehensive review
Ajayi, A. F., Olateju, B. S., Aremu, T. V., Ayodele, A. H., & Akano, O. P. (2025) · Gene · doi:10.1016/j.gene.2025.149716 · Cited by 3
Utility of Germline, Somatic and ctDNA Testing in Adults With Cancer
DeBortoli, E., McGahan, E., Yanes, T., Berkman, J. L., Aoude, L. G., Smit, A. K., Gokoolparsadh, A., Hermes, A., Newett, L., Bourke, M., et al. (2025) · Cancer Medicine · doi:10.1002/cam4.71080 · Cited by 4
“Of note, not all populations are well represented in clinical databases, which compromises the sensitivity of identifying and actioning genomic cancer variants in diverse ancestral groups [165, 166].”
SNP associations in the L-citrulline metabolic pathway and vascular aging in the Japanese population
Nogimura, D., Moriyasu, K., Ishida, S., Kohda, M., Yazawa, T., & Morita, M. (2025) · PLoS ONE · doi:10.1371/journal.pone.0323778 · Cited by 3
“Because GWAS results are not always replicated in other populations or races [55], future validation in different populations and races is needed to better ensure the association between the identified SNPs and the symptoms related to vascular aging toward generalizing applicability.”
Onyenobi, E., Zhong, M., Soremekun, O. S., Kamiza, A. B., Boua, P. R., Chikowore, T., Fatumo, S., Choudhury, A., Hazelhurst, S., Adebamowo, C., et al. (2025) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.124.005048 · Cited by 3
“16 Continental African populations not only encompass a rich genetic diversity, 17 but also experience distinct environmental and social factors that vary widely across regions in Africa.”
Metadata
- 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)
- 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
- 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
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 ›
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