IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-46663-4.html
   My bibliography  Save this article

Data-driven identification of predictive risk biomarkers for subgroups of osteoarthritis using interpretable machine learning

Author

Listed:
  • Rikke Linnemann Nielsen

    (Novo Nordisk Research Centre Oxford)

  • Thomas Monfeuga

    (Novo Nordisk Research Centre Oxford)

  • Robert R. Kitchen

    (Novo Nordisk Research Centre Oxford)

  • Line Egerod

    (Novo Nordisk Research Centre Oxford)

  • Luis G. Leal

    (Novo Nordisk Research Centre Oxford)

  • August Thomas Hjortshøj Schreyer

    (Novo Nordisk Research Centre Oxford)

  • Frederik Steensgaard Gade

    (Novo Nordisk A/S)

  • Carol Sun

    (Novo Nordisk Research Centre Oxford)

  • Marianne Helenius

    (Technical University of Denmark)

  • Lotte Simonsen

    (Novo Nordisk A/S)

  • Marianne Willert

    (Novo Nordisk A/S)

  • Abd A. Tahrani

    (Novo Nordisk A/S)

  • Zahra McVey

    (Novo Nordisk Research Centre Oxford)

  • Ramneek Gupta

    (Novo Nordisk Research Centre Oxford)

Abstract

Osteoarthritis (OA) is increasing in prevalence and has a severe impact on patients’ lives. However, our understanding of biomarkers driving OA risk remains limited. We developed a model predicting the five-year risk of OA diagnosis, integrating retrospective clinical, lifestyle and biomarker data from the UK Biobank (19,120 patients with OA, ROC-AUC: 0.72, 95%CI (0.71–0.73)). Higher age, BMI and prescription of non-steroidal anti-inflammatory drugs contributed most to increased OA risk prediction ahead of diagnosis. We identified 14 subgroups of OA risk profiles. These subgroups were validated in an independent set of patients evaluating the 11-year OA risk, with 88% of patients being uniquely assigned to one of the 14 subgroups. Individual OA risk profiles were characterised by personalised biomarkers. Omics integration demonstrated the predictive importance of key OA genes and pathways (e.g., GDF5 and TGF-β signalling) and OA-specific biomarkers (e.g., CRTAC1 and COL9A1). In summary, this work identifies opportunities for personalised OA prevention and insights into its underlying pathogenesis.

Suggested Citation

  • Rikke Linnemann Nielsen & Thomas Monfeuga & Robert R. Kitchen & Line Egerod & Luis G. Leal & August Thomas Hjortshøj Schreyer & Frederik Steensgaard Gade & Carol Sun & Marianne Helenius & Lotte Simons, 2024. "Data-driven identification of predictive risk biomarkers for subgroups of osteoarthritis using interpretable machine learning," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-46663-4
    DOI: 10.1038/s41467-024-46663-4
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-46663-4
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-024-46663-4?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. Heli Julkunen & Anna Cichońska & Mika Tiainen & Harri Koskela & Kristian Nybo & Valtteri Mäkelä & Jussi Nokso-Koivisto & Kati Kristiansson & Markus Perola & Veikko Salomaa & Pekka Jousilahti & Annamar, 2023. "Atlas of plasma NMR biomarkers for health and disease in 118,461 individuals from the UK Biobank," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Benjamin B. Sun & Joshua Chiou & Matthew Traylor & Christian Benner & Yi-Hsiang Hsu & Tom G. Richardson & Praveen Surendran & Anubha Mahajan & Chloe Robins & Steven G. Vasquez-Grinnell & Liping Hou & , 2023. "Plasma proteomic associations with genetics and health in the UK Biobank," Nature, Nature, vol. 622(7982), pages 329-338, October.
    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. 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.
    2. Zhening Liu & Hangkai Huang & Jiarong Xie & Yingying Xu & Chengfu Xu, 2024. "Circulating fatty acids and risk of hepatocellular carcinoma and chronic liver disease mortality in the UK Biobank," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    3. Shiyu Zhang & Zheng Wang & Yijing Wang & Yixiao Zhu & Qiao Zhou & Xingxing Jian & Guihu Zhao & Jian Qiu & Kun Xia & Beisha Tang & Julian Mutz & Jinchen Li & Bin Li, 2024. "A metabolomic profile of biological aging in 250,341 individuals from the UK Biobank," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    4. Naman S. Shetty & Mokshad Gaonkar & Nirav Patel & Akhil Pampana & Nehal Vekariya & Peng Li & Garima Arora & Pankaj Arora, 2024. "Determinants of transthyretin levels and their association with adverse clinical outcomes among UK Biobank participants," Nature Communications, Nature, vol. 15(1), pages 1-7, December.
    5. Abolfazl Doostparast Torshizi & Dongnhu T. Truong & Liping Hou & Bart Smets & Christopher D. Whelan & Shuwei Li, 2024. "Proteogenomic network analysis reveals dysregulated mechanisms and potential mediators in Parkinson’s disease," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    6. Jia You & Yu Guo & Yi Zhang & Ju-Jiao Kang & Lin-Bo Wang & Jian-Feng Feng & Wei Cheng & Jin-Tai Yu, 2023. "Plasma proteomic profiles predict individual future health risk," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    7. Javier Botey-Bataller & Hedwig D. Vrijmoeth & Jeanine Ursinus & Bart-Jan Kullberg & Cees C. Wijngaard & Hadewych Hofstede & Ahmed Alaswad & Manoj K. Gupta & Lennart M. Roesner & Jochen Huehn & Thomas , 2024. "A comprehensive genetic map of cytokine responses in Lyme borreliosis," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    8. Anders Mälarstig & Felix Grassmann & Leo Dahl & Marios Dimitriou & Dianna McLeod & Marike Gabrielson & Karl Smith-Byrne & Cecilia E. Thomas & Tzu-Hsuan Huang & Simon K. G. Forsberg & Per Eriksson & Mi, 2023. "Evaluation of circulating plasma proteins in breast cancer using Mendelian randomisation," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    9. Chirag Krishna & Joshua Chiou & Saori Sakaue & Joyce B. Kang & Stephen M. Christensen & Isac Lee & Melis Atalar Aksit & Hye In Kim & David Schack & Soumya Raychaudhuri & Daniel Ziemek & Xinli Hu, 2024. "The influence of HLA genetic variation on plasma protein expression," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    10. Yan Zhao & Changchun Ma & Rongzhi Cai & Lijing Xin & Yongsheng Li & Lixin Ke & Wei Ye & Ting Ouyang & Jiahao Liang & Renhua Wu & Yan Lin, 2024. "NMR and MS reveal characteristic metabolome atlas and optimize esophageal squamous cell carcinoma early detection," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    11. Shaopeng Yang & Zhuoting Zhu & Shida Chen & Yixiong Yuan & Mingguang He & Wei Wang, 2023. "Metabolic fingerprinting on retinal pigment epithelium thickness for individualized risk stratification of type 2 diabetes mellitus," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    12. Karsten Suhre & Guhan Ram Venkataraman & Harendra Guturu & Anna Halama & Nisha Stephan & Gaurav Thareja & Hina Sarwath & Khatereh Motamedchaboki & Margaret K. R. Donovan & Asim Siddiqui & Serafim Batz, 2024. "Nanoparticle enrichment mass-spectrometry proteomics identifies protein-altering variants for precise pQTL mapping," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    13. Keren Papier & Joshua R. Atkins & Tammy Y. N. Tong & Kezia Gaitskell & Trishna Desai & Chibuzor F. Ogamba & Mahboubeh Parsaeian & Gillian K. Reeves & Ian G. Mills & Tim J. Key & Karl Smith-Byrne & Rut, 2024. "Identifying proteomic risk factors for cancer using prospective and exome analyses of 1463 circulating proteins and risk of 19 cancers in the UK Biobank," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    14. Robert F. Hillary & Danni A. Gadd & Zhana Kuncheva & Tasos Mangelis & Tinchi Lin & Kyle Ferber & Helen McLaughlin & Heiko Runz & Riccardo E. Marioni & Christopher N. Foley & Benjamin B. Sun, 2024. "Systematic discovery of gene-environment interactions underlying the human plasma proteome in UK Biobank," Nature Communications, Nature, vol. 15(1), pages 1-13, 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_s41467-024-46663-4. 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.