PRIMED investigators are innovating new polygenic risk score (PRS) methods and models to improve prediction of key traits across diverse, global populations. PRIMED is also developing new approaches to incorporate genetic ancestry and flexible population descriptors. Select contributions and publications below, see PRIMED publications and pre-prints for a complete list. See the ASHG 2024 PRIMED flyer (PDF) for these and other highlights.
Perspectives on the field of PRS methods and development
Kachuri L, Chatterjee N, Hirbo J, Schaid DJ, Martin I, Kullo IJ, Kenny EE, Pasaniuc B; Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium Methods Working Group; Witte JS, Ge T. Principles and methods for transferring polygenic risk scores across global populations. Nat Rev Genet. 2024 Jan;25(1):8-25. doi: 10.1038/s41576-023-00637-2. Epub 2023 Aug 24. PMID: 37620596; PMCID: PMC10961971.
Kullo IJ, Conomos MP, Nelson SC, Adebamowo SN, Choudhury A, Conti D, Fullerton SM, Gogarten SM, Heavner B, Hornsby WE, Kenny EE, Khan A, Khera AV, Li Y, Martin I, Mercader JM, Ng M, Raffield LM, Reiner A, Rowley R, Schaid D, Stilp A, Wiley K, Wilson R, Witte JS, Natarajan P; Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium. The PRIMED Consortium: Reducing disparities in polygenic risk assessment. Am J Hum Genet. 2024 Nov 14:S0002-9297(24)00379-3. doi: 10.1016/j.ajhg.2024.10.010. Epub ahead of print. PMID: 39561770.
Kullo IJ, Lewis CM, Inouye M, Martin AR, Ripatti S, Chatterjee N. Polygenic scores in biomedical research. Nat Rev Genet. 2022 Sep;23(9):524-532. doi: 10.1038/s41576-022-00470-z. Epub 2022 Mar 30. PMID: 35354965; PMCID: PMC9391275.
Adebamowo CA, Adeyemo A, Ashaye A, Akpa OM, Chikowore T, Choudhury A, Fakim YJ, Fatumo S, Hanchard N, Hauser M, Mitchell B, Mulder N, Ofori-Acquah SF, Owolabi M, Ramsay M, Tayo B, VasanthKumar AB, Zhang Y, Adebamowo SN. Polygenic risk scores for CARDINAL study. Nat Genet. 2022 May;54(5):527-530. doi: 10.1038/s41588-022-01074-3. PMID: 35513726; PMCID: PMC9907721.
PRS methods & software to improve prediction across diverse and admixed populations
Truong B, Hull LE, Ruan Y, Huang QQ, Hornsby W, Martin H, van Heel DA, Wang Y, Martin AR, Lee SH, Natarajan P. Integrative polygenic risk score improves the prediction accuracy of complex traits and diseases. Cell Genom. 2024 Apr 10;4(4):100523. doi: 10.1016/j.xgen.2024.100523. Epub 2024 Mar 19. PMID: 38508198; PMCID: PMC11019356.
Sun Q, Rowland BT, Chen J, Mikhaylova AV, Avery C, Peters U, Lundin J, Matise T, Buyske S, Tao R, Mathias RA, Reiner AP, Auer PL, Cox NJ, Kooperberg C, Thornton TA, Raffield LM, Li Y. Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI. Nat Commun. 2024 Feb 3;15(1):1016. doi: 10.1038/s41467-024-45135-z. PMID: 38310129; PMCID: PMC10838303.
Zhang J, Zhan J, Jin J, Ma C, Zhao R, O'Connell J, Jiang Y; 23andMe Research Team; Koelsch BL, Zhang H, Chatterjee N. An ensemble penalized regression method for multi-ancestry polygenic risk prediction. Nat Commun. 2024 Apr 15;15(1):3238. doi: 10.1038/s41467-024-47357-7. PMID: 38622117; PMCID: PMC11271575.
Ruan Y, Lin YF, Feng YA, Chen CY, Lam M, Guo Z; Stanley Global Asia Initiatives; He L, Sawa A, Martin AR, Qin S, Huang H, Ge T. Improving polygenic prediction in ancestrally diverse populations. Nat Genet. 2022 May;54(5):573-580. doi: 10.1038/s41588-022-01054-7. Epub 2022 May 5. Erratum in: Nat Genet. 2022 Aug;54(8):1259. doi: 10.1038/s41588-022-01144-6. PMID: 35513724; PMCID: PMC9117455.
PRS models for key traits to reduce health inequities
Smith JL, Tcheandjieu C, Dikilitas O, Iyer K, Miyazawa K, Hilliard A, Lynch J, Rotter JI, Chen YI, Sheu WH, Chang KM, Kanoni S, Tsao PS, Ito K, Kosel M, Clarke SL, Schaid DJ, Assimes TL, Kullo IJ. Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization. Circ Genom Precis Med. 2024 Jun;17(3):e004272. doi: 10.1161/CIRCGEN.123.004272. Epub 2024 Feb 21. PMID: 38380516; PMCID: PMC11372723.
Wang A, Shen J, Rodriguez AA, Saunders EJ, Chen F, Janivara R, Darst BF, Sheng X, Xu Y, Chou AJ, Benlloch S, Dadaev T, Brook MN, Plym A, Sahimi A, Hoffman TJ, Takahashi A, Matsuda K, Momozawa Y…Haiman CA. Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants. Nat Genet. 2023 Dec;55(12):2065-2074. doi: 10.1038/s41588-023-01534-4. Epub 2023 Nov 9. PMID: 37945903; PMCID: PMC10841479.
Adebamowo SN, Adeyemo A, Adebayo A, Achara P, Alabi B, Bakare RA, Famooto AO, Obende K, Offiong R, Olaniyan O, Ologun S, Rotimi C; ACCME Research Group as part of the H3Africa Consortium; Adebamowo CA. Genome, HLA and polygenic risk score analyses for prevalent and persistent cervical human papillomavirus (HPV) infections. Eur J Hum Genet. 2024 Jun;32(6):708-716. doi: 10.1038/s41431-023-01521-7. Epub 2024 Jan 10. PMID: 38200081; PMCID: PMC11153215.
Patel AP, Wang M, Ruan Y, Koyama S, Clarke SL, Yang X, Tcheandjieu C, Agrawal S, Fahed AC, Ellinor PT; Genes & Health Research Team; the Million Veteran Program; Tsao PS, Sun YV, Cho K, Wilson PWF, Assimes TL, van Heel DA, Butterworth AS, Aragam KG, Natarajan P, Khera AV. A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease. Nat Med. 2023 Jul;29(7):1793-1803. doi: 10.1038/s41591-023-02429-x. Epub 2023 Jul 6. PMID: 37414900; PMCID: PMC10353935.
Huerta-Chagoya A, Schroeder P, Mandla R, Deutsch AJ, Zhu W, Petty L, Yi X, Cole JB, Udler MS, Dornbos P, Porneala B, DiCorpo D, Liu CT, Li JH, Szczerbiński L, Kaur V, Kim J, Lu Y, Martin A…Mercader JM. The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes. Diabetologia. 2023 Jul;66(7):1273-1288. doi: 10.1007/s00125-023-05912-9. Epub 2023 May 6. PMID: 37148359; PMCID: PMC10244266.
PRIMED is conducting federated analyses in diverse biobanks to develop new PRS models and approaches and test their performance. Initial efforts focus on ensemble PRS models using the PRSMix method.
PRS models to improve biomarker accuracy
Mandla R, Schroeder PH, Florez JC, Mercader JM, Leong A. Hemoglobin A1c Genetics and Disparities in Risk of Diabetic Retinopathy in Individuals of Genetically Inferred African American/African British and European Ancestries. Diabetes Care. 2024 Oct 1;47(10):1731-1739. doi: 10.2337/dc23-1691. PMID: 39042486; PMCID: PMC11417273.
Kachuri L, Hoffmann TJ, Jiang Y, Berndt SI, Shelley JP, Schaffer KR, Machiela MJ, Freedman ND, Huang WY, Li SA, Easterlin R, Goodman PJ, Till C, Thompson I, Lilja H, Van Den Eeden SK, Chanock SJ, Haiman CA, Conti DV, Klein RJ, Mosley JD, Graff RE, Witte JS. Genetically adjusted PSA levels for prostate cancer screening. Nat Med. 2023 Jun;29(6):1412-1423. doi: 10.1038/s41591-023-02277-9. Epub 2023 Jun 1. PMID: 37264206; PMCID: PMC10287565.
Environmental and social determinants to refine risk estimation
Cromer SJ, Lakhani CM, Mercader JM, Majarian TD, Schroeder P, Cole JB, Florez JC, Patel CJ, Manning AK, Burnett-Bowie SM, Merino J, Udler MS. Association and Interaction of Genetics and Area-Level Socioeconomic Factors on the Prevalence of Type 2 Diabetes and Obesity. Diabetes Care. 2023 May 1;46(5):944-952. doi: 10.2337/dc22-1954. PMID: 36787958; PMCID: PMC10154653.
Archambault AN, Jeon J, Lin Y, Thomas M, Harrison TA, Bishop DT, Brenner H, Casey G, Chan AT, Chang-Claude J, Figueiredo JC, Gallinger S, Gruber SB, Gunter MJ, Guo F, Hoffmeister M, Jenkins MA, Keku TO, Le Marchand L…Peters U, Hayes RB. Risk Stratification for Early-Onset Colorectal Cancer Using a Combination of Genetic and Environmental Risk Scores: An International Multi-Center Study. J Natl Cancer Inst. 2022 Apr 11;114(4):528-539. doi: 10.1093/jnci/djac003. PMID: 35026030; PMCID: PMC9002285.
Cho SMJ, Koyama S, Honigberg MC, Surakka I, Haidermota S, Ganesh S, Patel AP, Bhattacharya R, Lee H, Kim HC, Natarajan P. Genetic, sociodemographic, lifestyle, and clinical risk factors of recurrent coronary artery disease events: a population-based cohort study. Eur Heart J. 2023 Sep 21;44(36):3456-3465. doi: 10.1093/eurheartj/ehad380. PMID: 37350734; PMCID: PMC10516626.
PRIMED is developing a conceptual framework to integrate PRS and social determinants of health in risk prediction models for diverse groups.
Innovative approaches to representing and using diversity in PRS
Ding Y, Hou K, Xu Z, Pimplaskar A, Petter E, Boulier K, Privé F, Vilhjálmsson BJ, Olde Loohuis LM, Pasaniuc B. Polygenic scoring accuracy varies across the genetic ancestry continuum. Nature. 2023 Jun;618(7966):774-781. doi: 10.1038/s41586-023-06079-4. Epub 2023 May 17. PMID: 37198491; PMCID: PMC10284707.
Hou K, Ding Y, Xu Z, Wu Y, Bhattacharya A, Mester R, Belbin GM, Buyske S, Conti DV, Darst BF, Fornage M, Gignoux C, Guo X, Haiman C, Kenny EE, Kim M, Kooperberg C, Lange L, Manichaikul A…Pasaniuc B. Causal effects on complex traits are similar for common variants across segments of different continental ancestries within admixed individuals. Nat Genet. 2023 Apr;55(4):549-558. doi: 10.1038/s41588-023-01338-6. Epub 2023 Mar 20. PMID: 36941441; PMCID: PMC11120833.
PRIMED has developed a data model that systematically organizes and retains detailed population descriptor data, providing flexibility for downstream analyses and adhering to NASEM recommendations on distinguishing descriptors (axes of measurement) from labels (measured values); see ASHG 2024 abstract.
Social and ethical considerations to responsibly develop and implement PRS
PRIMED is collecting use cases of common applications of PRS in research and healthcare to highlight best practices and practical concerns, with added emphasis on the conceptualization and use of ancestry and on downstream clinical implementation.
PRIMED is collaborating with the eMERGE network on a manuscript that addresses the considerations and concerns of PRS development and implementation, drawing from the experiences of both consortia.
Cloud-based approach to collaboratively share and analyze data on the AnVIL platform
Hou K, Gogarten S, Kim J, Hua X, Dias JA, Sun Q, Wang Y, Tan T; Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium Methods Working Group; Atkinson EG, Martin A, Shortt J, Hirbo J, Li Y, Pasaniuc B, Zhang H. Admix-kit: an integrated toolkit and pipeline for genetic analyses of admixed populations. Bioinformatics. 2024 Mar 29;40(4):btae148. doi: 10.1093/bioinformatics/btae148. PMID: 38490256; PMCID: PMC10980565.
Analysis workflows developed as part of PRIMED are made available to the research community in the PRIMED Dockstore Organization.
PRIMED investigators are implementing PRS methods in analysis workflows and benchmarking PRS model performance across datasets shared in the cloud on AnVIL.
The Data Sharing Working Group is preparing a manuscript describing the design and rationale of data sharing policies and procedures in the Consortium, as well as making recommendations for future research and policy-making.