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

Yukang Jiang, Bingxin Zhao, Xiaopu Wang, Borui Tang, Huiyang Peng, Zidan Luo, Yue Shen, Zheng Wang, Zhiwen Jiang, Jie Wang, Jieping Ye (), Xueqin Wang () and Hongtu Zhu ()
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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

Nature Communications, 2025, vol. 16, issue 1, 1-16

Abstract: 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.

Date: 2025
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DOI: 10.1038/s41467-025-58724-3

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