Abstract
The long delay before genomic technologies become available in low- and middle-income countries is a concern from both scientific and ethical standpoints. Polygenic risk scores (PRSs), a relatively recent advance in genomics, could have a substantial impact on promoting health by improving disease risk prediction and guiding preventive strategies. However, clinical use of PRSs in their current forms might widen global health disparities, as their portability to diverse groups is limited. This Perspective highlights the need for global collaboration to develop and implement PRSs that perform equitably across the world. Such collaboration requires capacity building and the generation of new data in low-resource settings, the sharing of harmonized genotype and phenotype data securely across borders, novel population genetics and statistical methods to improve PRS performance, and thoughtful clinical implementation in diverse settings. All this needs to occur while considering the ethical, legal and social implications, with support from regulatory and funding agencies and policymakers.
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References
Vollset, S. E. et al. Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021. Lancet 403, 2204–2256 (2024).
Kullo, I. J. et al. Polygenic scores in biomedical research. Nat. Rev. Genet. 23, 524–532 (2022).
Wang, Y. et al. Challenges and opportunities for developing more generalizable polygenic risk scores. Annu. Rev. Biomed. Data Sci. 5, 293–320 (2022).
Baynam, G. et al. Advancing diagnosis and research for rare genetic diseases in Indigenous peoples. Nat. Genet. 56, 189–193 (2024).
Philippakis, A. A. et al. The Matchmaker Exchange: a platform for rare disease gene discovery. Hum. Mutat. 36, 915–921 (2015).
Rehm, H. L. et al. GA4GH: international policies and standards for data sharing across genomic research and healthcare. Cell Genom. 1, 100029 (2021).
Zhou, W. et al. Global Biobank Meta-analysis Initiative: powering genetic discovery across human disease. Cell Genom. 2, 100192 (2022).
Skantharajah, N. et al. Equity, diversity, and inclusion at the Global Alliance for Genomics and Health. Cell Genom. 3, 100386 (2023).
Yusuf, S. et al. Polypill with or without aspirin in persons without cardiovascular disease. N. Engl. J. Med. 384, 216–228 (2021).
Manolio, T. A. et al. Genes, environment and the value of prospective cohort studies. Nat. Rev. Genet. 7, 812–820 (2006).
Chen, Z. et al. China Kadoorie Biobank of 0.5 million people: survey methods, baseline characteristics and long-term follow-up. Int. J. Epidemiol. 40, 1652–1666 (2011).
Tapia-Conyer, R. et al. Cohort profile: the Mexico City Prospective Study. Int. J. Epidemiol. 35, 243–249 (2006).
Collins, R. et al. Global priorities for large-scale biomarker-based prospective cohorts. Cell Genom. 2, 100141 (2022).
Mayo, K. R. et al. The All of Us Data and Research Center: creating a secure, scalable, and sustainable ecosystem for biomedical research. Annu. Rev. Biomed. Data Sci. 6, 443–464 (2023).
Manolio, T. A. Using the data we have: improving diversity in genomic research. Am. J. Hum. Genet. 105, 233–236 (2019).
Finer, S. et al. Cohort profile: East London Genes & Health (ELGH), a community-based population genomics and health study in British Bangladeshi and British Pakistani people. Int. J. Epidemiol. 49, 20–21i (2019).
Wonkam, A. & Adeyemo, A. Leveraging our common African origins to understand human evolution and health. Cell Genom. 3, 100278 (2023).
Wonkam, A. Sequence three million genomes across Africa. Nature 590, 209–211 (2021).
Fatumo, S. et al. Promoting the genomic revolution in Africa through the Nigerian 100K Genome Project. Nat. Genet. 54, 531–536 (2022).
Adebamowo, C. A. et al. Polygenic risk scores for CARDINAL study. Nat. Genet. 54, 527–530 (2022).
Ramsay, M. et al. H3Africa AWI-Gen Collaborative Centre: a resource to study the interplay between genomic and environmental risk factors for cardiometabolic diseases in four sub-Saharan African countries. Glob. Health Epidemiol. Genom. 1, e20 (2016).
World Health Organization Advisory Committee on Health and Research. Accelerating Access to Genomics for Global Health: Promotion, Implementation, Collaboration, and Ethical, Legal, and Social Issues: a Report of the WHO Science Council (World Health Organization: 2022).
Smith, J. The next 20 years of human genomics must be more equitable and more open. Nature 590, 183–184 (2021).
Norland, K. et al. Associations of self-reported race, polygenic risk, and social determinants of health with coronary heart disease. J. Am. Coll. Cardiol. (in the press).
Buniello, A. et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 47, D1005–D1012 (2019).
Thelwall, M. et al. Is useful research data usually shared? An investigation of genome-wide association study summary statistics. PLoS ONE 15, e0229578 (2020).
Lambert, S. A. et al. The Polygenic Score Catalog as an open database for reproducibility and systematic evaluation. Nat. Genet. 53, 420–425 (2021).
Schatz, M. C. et al. Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space. Cell Genom. 2, 100085 (2022).
Page, A. et al. A federated ecosystem for sharing genomic, clinical data. Science 352, 1278–1280 (2016).
Evans, J. P. et al. The National Institutes of Health Patient-Reported Outcomes Measurement Information System (PROMIS): a view from the UK. Patient Relat. Outcome Meas. 9, 345–352 (2018).
Pan, H. et al. Using PhenX measures to identify opportunities for cross-study analysis. Hum. Mutat. 33, 849–857 (2012).
Khalifa, A. et al. Interoperable genetic lab test reports: mapping key data elements to HL7 FHIR specifications and professional reporting guidelines. J. Am. Med. Inform. Assoc. 28, 2617–2625 (2021).
National Academies of Sciences, Engineering, and Medicine; Division of Behavioral and Social Sciences and Education; Health and Medicine Division; Committee on Population; Board on Health Sciences Policy; Committee on the Use of Race, Ethnicity, and Ancestry as Population Descriptors in Genomics Research. Using Population Descriptors in Genetics and Genomics Research: a New Framework for an Evolving Field (National Academies, 2023).
Wand, H. et al. Improving reporting standards for polygenic scores in risk prediction studies. Nature 591, 211–219 (2021).
Wilkinson, M. D. et al. The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016).
Kachuri, L. et al. Principles and methods for polygenic risk scores (PRS) across global populations. Nat. Rev. Genet. 25, 8–25 (2024).
Norland, K. et al. A linear weighted combination of polygenic scores for a broad range of traits improves prediction of coronary heart disease. Eur. J. Hum. Genet. 32, 209–214 (2024).
Schaid, D. J. et al. From genome-wide associations to candidate causal variants by statistical fine-mapping. Nat. Rev. Genet. 19, 491–504 (2018).
Zhang, B. C., Biddanda, A., Gunnarsson, Á. F., Cooper, F. & Palamara, P. F. Biobank-scale inference of ancestral recombination graphs enables genealogical analysis of complex traits. Nat. Genet. 55, 768–776 (2023).
Marnetto, D. et al. Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals. Nat. Commun. 11, 1628 (2020).
Ruan, Y. et al. Improving polygenic prediction in ancestrally diverse populations. Nat. Genet. 54, 573–580 (2022).
Kowalski, M. H. et al. Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations. PLoS Genet. 15, e1008500 (2019).
Koenig, Z. et al. A harmonized public resource of deeply sequenced diverse human genomes. Genome Res. 34, 796–809 (2024).
Sherman, R. M. et al. Assembly of a pan-genome from deep sequencing of 910 humans of African descent. Nat. Genet. 51, 30–35 (2019).
Wang, T. et al. The Human Pangenome Project: a global resource to map genomic diversity. Nature 604, 437–446 (2022).
Mostafavi, H. et al. Variable prediction accuracy of polygenic scores within an ancestry group. eLife 9, e48376 (2020).
Kamiza, A. B. et al. Transferability of genetic risk scores in African populations. Nat. Med. 28, 1163–1166 (2022).
Zhang, J. Y. Commoning genomic solidarity to improve global health equality. Cell Genom. 3, 100405 (2023).
Moreau, Y. Crack down on genomic surveillance. Nature 576, 36–38 (2019).
Yanes, T. et al. Future implications of polygenic risk scores for life insurance underwriting. NPJ Genom. Med. 9, 25 (2024).
Lemke, A. A. et al. Addressing underrepresentation in genomics research through community engagement. Am. J. Hum. Genet. 109, 1563–1571 (2022).
Linder, J. E. et al. Returning integrated genomic risk and clinical recommendations: the eMERGE study. Genet. Med. 25, 100006 (2023).
Manolio, T. A. et al. The International Hundred Thousand Plus Cohort Consortium: integrating large-scale cohorts to address global scientific challenges. Lancet Digit. Health 2, e567–e568 (2020).
Riba, M. et al. The 1+Million Genomes Minimal Dataset for Cancer. Nat. Genet. 56, 733–736 (2024).
Jackson, C. S. et al. Facing our history—building an equitable future. Am. J. Hum. Genet. 110, 377–395 (2023).
Fatumo, S. et al. Uganda Genome Resource: a rich research database for genomic studies of communicable and non-communicable diseases in Africa. Cell Genom. 2, 100209 (2022).
Elmonem, M. A. et al. The Egypt Genome Project. Nat. Genet. 56, 1035–1037 (2024).
Mbarek, H. et al. Qatar genome: insights on genomics from the Middle East. Hum. Mutat. 43, 499–510 (2022).
Saleheen, D. et al. Human knockouts and phenotypic analysis in a cohort with a high rate of consanguinity. Nature 544, 235–239 (2017).
GenomeAsia100K Consortium. The GenomeAsia 100K Project enables genetic discoveries across Asia. Nature 576, 106–111 (2019).
Nagai, A. et al. Overview of the BioBank Japan Project: study design and profile. J. Epidemiol. 27, S2–S8 (2017).
Walters, R. G. et al. Genotyping and population characteristics of the China Kadoorie Biobank. Cell Genom. 3, 100361 (2023).
Feng, Y.-C. A. et al. Taiwan Biobank: a rich biomedical research database of the Taiwanese population. Cell Genom. 2, 100197 (2022).
Nam, K. et al. Genome-wide study on 72,298 individuals in Korean biobank data for 76 traits. Cell Genom. 2, 100189 (2022).
Sohail, M. et al. Mexican Biobank advances population and medical genomics of diverse ancestries. Nature 622, 775–783 (2023).
Manolio, T. A. et al. Global implementation of genomic medicine: we are not alone. Sci. Transl. Med. 7, 290ps13 (2015).
Wang, Y. et al. Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts. Cell Genom. 3, 100241 (2023).
Polygenic Risk Score Task Force of the International Common Disease Alliance. Responsible use of polygenic risk scores in the clinic: potential benefits, risks and gaps. Nat. Med. 27, 1876–1884 (2021).
Acknowledgements
I.J.K. is supported by the Mayo Center for Individualized Medicine and by the following grants from the US NHGRI: U01 HG11710 (the PRIMED Consortium), U01 HG06379 (the eMERGE Network) and U24 HG09650 (the ClinGen Consortium). I thank investigators in the eMERGE, PRIMED and ClinGen consortia for many helpful discussions and T. Manolio, H. Rehm and S. Gogarten for reading a draft of the manuscript and providing feedback.
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Kullo, I.J. Promoting equity in polygenic risk assessment through global collaboration. Nat Genet 56, 1780–1787 (2024). https://doi.org/10.1038/s41588-024-01843-2
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DOI: https://doi.org/10.1038/s41588-024-01843-2