IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v16y2025i1d10.1038_s41467-025-58724-3.html
   My bibliography  Save this article

UKB-MDRMF: a multi-disease risk and multimorbidity framework based on UK biobank data

Author

Listed:
  • Yukang Jiang

    (University of North Carolina at Chapel Hill)

  • Bingxin Zhao

    (University of Pennsylvania)

  • Xiaopu Wang

    (University of Science and Technology of China)

  • Borui Tang

    (University of North Carolina at Chapel Hill)

  • Huiyang Peng

    (University of Science and Technology of China)

  • Zidan Luo

    (University of Science and Technology of China)

  • Yue Shen

    (University of Science and Technology of China)

  • Zheng Wang

    (Alibaba Group)

  • Zhiwen Jiang

    (University of North Carolina at Chapel Hill)

  • Jie Wang

    (University of Science and Technology of China)

  • Jieping Ye

    (Alibaba Group)

  • Xueqin Wang

    (University of Science and Technology of China)

  • Hongtu Zhu

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

Abstract

The rapid accumulation of biomedical cohort data presents opportunities to explore disease mechanisms, risk factors, and prognostic markers. However, current research often has a narrow focus, limiting the exploration of risk factors and inter-disease correlations. Additionally, fragmented processes and time constraints can hinder comprehensive analysis of the disease landscape. Our work addresses these challenges by integrating multimodal data from the UK Biobank, including basic, lifestyle, measurement, environment, genetic, and imaging data. We propose UKB-MDRMF, a comprehensive framework for predicting and assessing health risks across 1560 diseases. Unlike single disease models, UKB-MDRMF incorporates multimorbidity mechanisms, resulting in superior predictive accuracy, with all disease types showing improved performance in risk assessment. By jointly predicting and assessing multiple diseases, UKB-MDRMF uncovers shared and distinctive connections among risk factors and diseases, offering a broader perspective on health and multimorbidity mechanisms.

Suggested Citation

  • Yukang Jiang & Bingxin Zhao & Xiaopu Wang & Borui Tang & Huiyang Peng & Zidan Luo & Yue Shen & Zheng Wang & Zhiwen Jiang & Jie Wang & Jieping Ye & Xueqin Wang & Hongtu Zhu, 2025. "UKB-MDRMF: a multi-disease risk and multimorbidity framework based on UK biobank data," Nature Communications, Nature, vol. 16(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-58724-3
    DOI: 10.1038/s41467-025-58724-3
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-025-58724-3
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-025-58724-3?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. Jean-Pierre Després & Isabelle Lemieux, 2006. "Abdominal obesity and metabolic syndrome," Nature, Nature, vol. 444(7121), pages 881-887, December.
    2. Yukang Jiang & Bingxin Zhao & Xiaopu Wang & Borui Tang & Huiyang Peng & Zidan Luo & Yue Shen & Zheng Wang & Zhiwen Jiang & Jie Wang & Jieping Ye & Xueqin Wang & Hongtu Zhu, 2025. "UKB-MDRMF: a multi-disease risk and multimorbidity framework based on UK biobank data," Nature Communications, Nature, vol. 16(1), pages 1-16, December.
    3. Cathie Sudlow & John Gallacher & Naomi Allen & Valerie Beral & Paul Burton & John Danesh & Paul Downey & Paul Elliott & Jane Green & Martin Landray & Bette Liu & Paul Matthews & Giok Ong & Jill Pell &, 2015. "UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age," PLOS Medicine, Public Library of Science, vol. 12(3), pages 1-10, March.
    4. Ahmed M Alaa & Thomas Bolton & Emanuele Di Angelantonio & James H F Rudd & Mihaela van der Schaar, 2019. "Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-17, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yukang Jiang & Bingxin Zhao & Xiaopu Wang & Borui Tang & Huiyang Peng & Zidan Luo & Yue Shen & Zheng Wang & Zhiwen Jiang & Jie Wang & Jieping Ye & Xueqin Wang & Hongtu Zhu, 2025. "UKB-MDRMF: a multi-disease risk and multimorbidity framework based on UK biobank data," Nature Communications, Nature, vol. 16(1), pages 1-16, December.

    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. Hsin-Han Chen & Hui-Ling Chen & Yi-Tien Lin & Chaou-Wen Lin & Chien-Chang Ho & Hsueh-Yi Lin & Po-Fu Lee, 2020. "The Associations between Functional Fitness Test Performance and Abdominal Obesity in Healthy Elderly People: Results from the National Physical Fitness Examination Survey in Taiwan," IJERPH, MDPI, vol. 18(1), pages 1-14, December.
    2. William R Scott & Weihua Zhang & Marie Loh & Sian-Tsung Tan & Benjamin Lehne & Uzma Afzal & Juan Peralta & Richa Saxena & Sarju Ralhan & Gurpreet S Wander & Kiymet Bozaoglu & Dharambir K Sanghera & Pa, 2016. "Investigation of Genetic Variation Underlying Central Obesity amongst South Asians," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-17, May.
    3. Dionysios V Chartoumpekis & Apostolos Zaravinos & Panos G Ziros & Ralitsa P Iskrenova & Agathoklis I Psyrogiannis & Venetsana E Kyriazopoulou & Ioannis G Habeos, 2012. "Differential Expression of MicroRNAs in Adipose Tissue after Long-Term High-Fat Diet-Induced Obesity in Mice," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-13, April.
    4. Jujiao Kang & Yue-Ting Deng & Bang-Sheng Wu & Wei-Shi Liu & Ze-Yu Li & Shitong Xiang & Liu Yang & Jia You & Xiaohong Gong & Tianye Jia & Jin-Tai Yu & Wei Cheng & Jianfeng Feng, 2024. "Whole exome sequencing analysis identifies genes for alcohol consumption," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    5. Leslie A. Smith & James A. Cahill & Ji-Hyun Lee & Kiley Graim, 2025. "Equitable machine learning counteracts ancestral bias in precision medicine," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
    6. Sofia I I Kring & Claus Holst & Esther Zimmermann & Tine Jess & Tina Berentzen & Søren Toubro & Torben Hansen & Arne Astrup & Oluf Pedersen & Thorkild I A Sørensen, 2008. "FTO Gene Associated Fatness in Relation to Body Fat Distribution and Metabolic Traits throughout a Broad Range of Fatness," PLOS ONE, Public Library of Science, vol. 3(8), pages 1-7, August.
    7. Samvida S. Venkatesh & Habib Ganjgahi & Duncan S. Palmer & Kayesha Coley & Gregorio V. Linchangco & Qin Hui & Peter Wilson & Yuk-Lam Ho & Kelly Cho & Kadri Arumäe & Laura B. L. Wittemans & Christoffer, 2024. "Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    8. Katharina Ruettger & Stacy A. Clemes & Yu-Ling Chen & Charlotte L. Edwardson & Amber Guest & Nicholas D. Gilson & Laura J. Gray & Vicki Johnson & Nicola J. Paine & Aron P. Sherry & Mohsen Sayyah & Jac, 2022. "Drivers with and without Obesity Respond Differently to a Multi-Component Health Intervention in Heavy Goods Vehicle Drivers," IJERPH, MDPI, vol. 19(23), pages 1-12, November.
    9. Shih-Chang Chen & Chaou-Wen Lin & Po-Fu Lee & Hui-Ling Chen & Chien-Chang Ho, 2021. "Anthropometric Characteristics in Taiwanese Adults: Age and Gender Differences," IJERPH, MDPI, vol. 18(14), pages 1-13, July.
    10. Ashley Beckett & Jake Riley Scott & Angel Marie Chater & Louise Ferrandino & Jeffrey William Frederick Aldous, 2023. "The Prevalence of Metabolic Syndrome and Its Components in Firefighters: A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 20(19), pages 1-14, September.
    11. Vincenzo Sicari & Irene Maria Grazia Custureri & Rosa Tundis & Monica Rosa Loizzo, 2023. "Comparison of Physicochemical Characteristics and Bioactivity of Olive Oil Mill Wastewaters from Traditional and Water-Saving ARA-Controlled Three-Phase Decanter," Sustainability, MDPI, vol. 15(5), pages 1-11, February.
    12. Shamim Shaikh Mohiuddin, 2019. "A Mini Review on Diagnostic Criteria of Metabolic Syndrome Associated with Chronic Obesity in Children and Adolescent," Current Research in Diabetes & Obesity Journal, Juniper Publishers Inc., vol. 9(3), pages 72-77, January.
    13. Shelda Sajeev & Stephanie Champion & Alline Beleigoli & Derek Chew & Richard L. Reed & Dianna J. Magliano & Jonathan E. Shaw & Roger L. Milne & Sarah Appleton & Tiffany K. Gill & Anthony Maeder, 2021. "Predicting Australian Adults at High Risk of Cardiovascular Disease Mortality Using Standard Risk Factors and Machine Learning," IJERPH, MDPI, vol. 18(6), pages 1-14, March.
    14. Yuji Yamamoto & Yuya Shirai & Kyuto Sonehara & Shinichi Namba & Takafumi Ojima & Kenichi Yamamoto & Ryuya Edahiro & Ken Suzuki & Akinori Kanai & Yoshiya Oda & Yutaka Suzuki & Takayuki Morisaki & Akira, 2025. "Dissecting cross-population polygenic heterogeneity across respiratory and cardiometabolic diseases," Nature Communications, Nature, vol. 16(1), pages 1-18, December.
    15. Po-Fu Lee & Chien-Chang Ho & Nai-Wen Kan & Ding-Peng Yeh & Yun-Chi Chang & Yu-Jui Li & Ching-Yu Tseng & Xin-Yu Hsieh & Chih-Hui Chiu, 2020. "The Association between Physical Fitness Performance and Abdominal Obesity Risk among Taiwanese Adults: A Cross-Sectional Study," IJERPH, MDPI, vol. 17(5), pages 1-10, March.
    16. Koichiro Irie & Tatsuo Yamamoto & Tetsuji Azuma & Komei Iwai & Takatoshi Yonenaga & Takaaki Tomofuji, 2023. "Association between Periodontal Condition and Fat Distribution in Japanese Adults: A Cross-Sectional Study Using Check-Up Data," IJERPH, MDPI, vol. 20(3), pages 1-10, January.
    17. Sung-Kwan Oh & A-Ra Cho & Yu-Jin Kwon & Hye-Sun Lee & Ji-Won Lee, 2018. "Derivation and validation of a new visceral adiposity index for predicting visceral obesity and cardiometabolic risk in a Korean population," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-14, September.
    18. Michał Konwerski & Marek Postuła & Marzena Barczuk-Falęcka & Anna Czajkowska & Anna Mróz & Katarzyna Witek & Wawrzyniec Bakalarski & Aleksandra Gąsecka & Łukasz A. Małek & Tomasz Mazurek, 2021. "Epicardial Adipose Tissue and Cardiovascular Risk Assessment in Ultra-Marathon Runners: A Pilot Study," IJERPH, MDPI, vol. 18(6), pages 1-9, March.
    19. Dongfang You & Yaqian Wu & Mengyi Lu & Fang Shao & Yingdan Tang & Sisi Liu & Liya Liu & Zewei Zhou & Ruyang Zhang & Sipeng Shen & Theis Lange & Hongyang Xu & Hongxia Ma & Yongmei Yin & Hongbing Shen &, 2025. "A genome-wide cross-trait analysis characterizes the shared genetic architecture between lung and gastrointestinal diseases," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    20. Antonio Paoli & Andrea Casolo & Matteo Saoncella & Carlo Bertaggia & Marco Fantin & Antonino Bianco & Giuseppe Marcolin & Tatiana Moro, 2021. "Effect of an Endurance and Strength Mixed Circuit Training on Regional Fat Thickness: The Quest for the “Spot Reduction”," IJERPH, MDPI, vol. 18(7), pages 1-10, April.

    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:16:y:2025:i:1:d:10.1038_s41467-025-58724-3. 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.