IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-45135-z.html
   My bibliography  Save this article

Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI

Author

Listed:
  • Quan Sun

    (University of North Carolina at Chapel Hill)

  • Bryce T. Rowland

    (University of North Carolina at Chapel Hill)

  • Jiawen Chen

    (University of North Carolina at Chapel Hill)

  • Anna V. Mikhaylova

    (University of Washington)

  • Christy Avery

    (University of North Carolina at Chapel Hill)

  • Ulrike Peters

    (Fred Hutchinson Cancer Center)

  • Jessica Lundin

    (Fred Hutchinson Cancer Center)

  • Tara Matise

    (Rutgers University)

  • Steve Buyske

    (Rutgers University)

  • Ran Tao

    (Vanderbilt University Medical Center
    Vanderbilt University Medical Center)

  • Rasika A. Mathias

    (Johns Hopkins University)

  • Alexander P. Reiner

    (University of Washington)

  • Paul L. Auer

    (and Cancer Center, Medical College of Wisconsin)

  • Nancy J. Cox

    (Vanderbilt University Medical Center
    Vanderbilt University Medical Center)

  • Charles Kooperberg

    (Fred Hutchinson Cancer Center)

  • Timothy A. Thornton

    (University of Washington)

  • Laura M. Raffield

    (University of North Carolina at Chapel Hill)

  • Yun Li

    (University of North Carolina at Chapel Hill
    University of North Carolina at Chapel Hill)

Abstract

Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for different segments of their genomes. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals. GAUDI explicitly models ancestry-differential effects while borrowing information across segments with shared ancestry in admixed genomes. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses for traits with associated variants exhibiting ancestral-differential effects. Leveraging data from the Women’s Health Initiative study, we show that GAUDI improves PRS prediction of white blood cell count and C-reactive protein in African Americans by > 64% compared to alternative methods, and even outperforms PRS-CSx with large European GWAS for some scenarios. We believe GAUDI will be a valuable tool to mitigate disparities in PRS performance in admixed individuals.

Suggested Citation

  • Quan Sun & Bryce T. Rowland & Jiawen Chen & Anna V. Mikhaylova & Christy Avery & Ulrike Peters & Jessica Lundin & Tara Matise & Steve Buyske & Ran Tao & Rasika A. Mathias & Alexander P. Reiner & Paul , 2024. "Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45135-z
    DOI: 10.1038/s41467-024-45135-z
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-45135-z
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-024-45135-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Saredo Said & Raha Pazoki & Ville Karhunen & Urmo Võsa & Symen Ligthart & Barbara Bodinier & Fotios Koskeridis & Paul Welsh & Behrooz Z. Alizadeh & Daniel I. Chasman & Naveed Sattar & Marc Chadeau-Hya, 2022. "Genetic analysis of over half a million people characterises C-reactive protein loci," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Genevieve L. Wojcik & Mariaelisa Graff & Katherine K. Nishimura & Ran Tao & Jeffrey Haessler & Christopher R. Gignoux & Heather M. Highland & Yesha M. Patel & Elena P. Sorokin & Christy L. Avery & Gil, 2019. "Genetic analyses of diverse populations improves discovery for complex traits," Nature, Nature, vol. 570(7762), pages 514-518, June.
    3. Davide Marnetto & Katri Pärna & Kristi Läll & Ludovica Molinaro & Francesco Montinaro & Toomas Haller & Mait Metspalu & Reedik Mägi & Krista Fischer & Luca Pagani, 2020. "Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    4. Robert Tibshirani & Michael Saunders & Saharon Rosset & Ji Zhu & Keith Knight, 2005. "Sparsity and smoothness via the fused lasso," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(1), pages 91-108, February.
    5. Konrad J. Karczewski & Laurent C. Francioli & Grace Tiao & Beryl B. Cummings & Jessica Alföldi & Qingbo Wang & Ryan L. Collins & Kristen M. Laricchia & Andrea Ganna & Daniel P. Birnbaum & Laura D. Gau, 2020. "The mutational constraint spectrum quantified from variation in 141,456 humans," Nature, Nature, vol. 581(7809), pages 434-443, May.
    6. Daniel Taliun & Daniel N. Harris & Michael D. Kessler & Jedidiah Carlson & Zachary A. Szpiech & Raul Torres & Sarah A. Gagliano Taliun & André Corvelo & Stephanie M. Gogarten & Hyun Min Kang & Achille, 2021. "Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program," Nature, Nature, vol. 590(7845), pages 290-299, February.
    7. Jiacheng Miao & Hanmin Guo & Gefei Song & Zijie Zhao & Lin Hou & Qiongshi Lu, 2023. "Quantifying portable genetic effects and improving cross-ancestry genetic prediction with GWAS summary statistics," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zihuai He & Linxi Liu & Michael E. Belloy & Yann Guen & Aaron Sossin & Xiaoxia Liu & Xinran Qi & Shiyang Ma & Prashnna K. Gyawali & Tony Wyss-Coray & Hua Tang & Chiara Sabatti & Emmanuel Candès & Mich, 2022. "GhostKnockoff inference empowers identification of putative causal variants in genome-wide association studies," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    2. Ananyo Choudhury & Jean-Tristan Brandenburg & Tinashe Chikowore & Dhriti Sengupta & Palwende Romuald Boua & Nigel J. Crowther & Godfred Agongo & Gershim Asiki & F. Xavier Gómez-Olivé & Isaac Kisiangan, 2022. "Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    3. Shaan Khurshid & Julieta Lazarte & James P. Pirruccello & Lu-Chen Weng & Seung Hoan Choi & Amelia W. Hall & Xin Wang & Samuel F. Friedman & Victor Nauffal & Kiran J. Biddinger & Krishna G. Aragam & Pu, 2023. "Clinical and genetic associations of deep learning-derived cardiac magnetic resonance-based left ventricular mass," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    4. Jingning Zhang & Jianan Zhan & Jin Jin & Cheng Ma & Ruzhang Zhao & Jared O’Connell & Yunxuan Jiang & Bertram L. Koelsch & Haoyu Zhang & Nilanjan Chatterjee, 2024. "An ensemble penalized regression method for multi-ancestry polygenic risk prediction," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    5. Dmitrii Usoltsev & Nikita Kolosov & Oxana Rotar & Alexander Loboda & Maria Boyarinova & Ekaterina Moguchaya & Ekaterina Kolesova & Anastasia Erina & Kristina Tolkunova & Valeriia Rezapova & Ivan Molot, 2024. "Complex trait susceptibilities and population diversity in a sample of 4,145 Russians," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    6. Alexandra Barry & Michelle T. McNulty & Xiaoyuan Jia & Yask Gupta & Hanna Debiec & Yang Luo & China Nagano & Tomoko Horinouchi & Seulgi Jung & Manuela Colucci & Dina F. Ahram & Adele Mitrotti & Aditi , 2023. "Multi-population genome-wide association study implicates immune and non-immune factors in pediatric steroid-sensitive nephrotic syndrome," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    7. Manon Baudic & Hiroshige Murata & Fernanda M. Bosada & Uirá Souto Melo & Takanori Aizawa & Pierre Lindenbaum & Lieve E. Maarel & Amaury Guedon & Estelle Baron & Enora Fremy & Adrien Foucal & Taisuke I, 2024. "TAD boundary deletion causes PITX2-related cardiac electrical and structural defects," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    8. Tutz, Gerhard & Pößnecker, Wolfgang & Uhlmann, Lorenz, 2015. "Variable selection in general multinomial logit models," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 207-222.
    9. Mkhadri, Abdallah & Ouhourane, Mohamed, 2013. "An extended variable inclusion and shrinkage algorithm for correlated variables," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 631-644.
    10. Vincent Michaud & Eulalie Lasseaux & David J. Green & Dave T. Gerrard & Claudio Plaisant & Tomas Fitzgerald & Ewan Birney & Benoît Arveiler & Graeme C. Black & Panagiotis I. Sergouniotis, 2022. "The contribution of common regulatory and protein-coding TYR variants to the genetic architecture of albinism," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    11. Natalie DeForest & Yuqi Wang & Zhiyi Zhu & Jacqueline S. Dron & Ryan Koesterer & Pradeep Natarajan & Jason Flannick & Tiffany Amariuta & Gina M. Peloso & Amit R. Majithia, 2024. "Genome-wide discovery and integrative genomic characterization of insulin resistance loci using serum triglycerides to HDL-cholesterol ratio as a proxy," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    12. Sean A. Misek & Aaron Fultineer & Jeremie Kalfon & Javad Noorbakhsh & Isabella Boyle & Priyanka Roy & Joshua Dempster & Lia Petronio & Katherine Huang & Alham Saadat & Thomas Green & Adam Brown & John, 2024. "Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    13. Katrina G. Claw & Casey R. Dorr & Erica L. Woodahl, 2024. "Implementing community-engaged pharmacogenomics in Indigenous communities," Nature Communications, Nature, vol. 15(1), pages 1-5, December.
    14. Jian Guo & Elizaveta Levina & George Michailidis & Ji Zhu, 2010. "Pairwise Variable Selection for High-Dimensional Model-Based Clustering," Biometrics, The International Biometric Society, vol. 66(3), pages 793-804, September.
    15. Lu Tang & Ling Zhou & Peter X. K. Song, 2019. "Fusion learning algorithm to combine partially heterogeneous Cox models," Computational Statistics, Springer, vol. 34(1), pages 395-414, March.
    16. Yash Pershad & Taralynn Mack & Hannah Poisner & Yasminka A. Jakubek & Adrienne M. Stilp & Braxton D. Mitchell & Joshua P. Lewis & Eric Boerwinkle & Ruth J. F. Loos & Nathalie Chami & Zhe Wang & Kathle, 2024. "Determinants of mosaic chromosomal alteration fitness," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    17. Molly C. Klanderman & Kathryn B. Newhart & Tzahi Y. Cath & Amanda S. Hering, 2020. "Fault isolation for a complex decentralized waste water treatment facility," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 931-951, August.
    18. Alexendar R. Perez & Laura Sala & Richard K. Perez & Joana A. Vidigal, 2021. "CSC software corrects off-target mediated gRNA depletion in CRISPR-Cas9 essentiality screens," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    19. Tomáš Plíhal, 2021. "Scheduled macroeconomic news announcements and Forex volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1379-1397, December.
    20. Elena V. Feofanova & Michael R. Brown & Taryn Alkis & Astrid M. Manuel & Xihao Li & Usman A. Tahir & Zilin Li & Kevin M. Mendez & Rachel S. Kelly & Qibin Qi & Han Chen & Martin G. Larson & Rozenn N. L, 2023. "Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations," Nature Communications, Nature, vol. 14(1), pages 1-12, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45135-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.