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

IF 15.7 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Nature Communications Pub Date : 2025-04-22 DOI:10.1038/s41467-025-58724-3
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
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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.

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UKB-MDRMF:基于英国生物银行数据的多疾病风险和多病症框架
生物医学队列数据的快速积累为探索疾病机制、危险因素和预后标志物提供了机会。然而,目前的研究往往侧重点狭窄,限制了对危险因素和疾病间相关性的探索。此外,支离破碎的过程和时间限制可能阻碍对疾病状况的全面分析。我们的工作通过整合来自英国生物银行的多模式数据来解决这些挑战,包括基础、生活方式、测量、环境、遗传和成像数据。我们提出UKB-MDRMF,一个预测和评估1560种疾病健康风险的综合框架。与单一疾病模型不同,UKB-MDRMF结合了多发病机制,导致更高的预测准确性,所有疾病类型在风险评估中都表现出更好的表现。通过联合预测和评估多种疾病,UKB-MDRMF揭示了风险因素和疾病之间的共同和独特联系,为健康和多病机制提供了更广阔的视角。
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来源期刊
Nature Communications
Nature Communications Biological Science Disciplines-
CiteScore
24.90
自引率
2.40%
发文量
6928
审稿时长
3.7 months
期刊介绍: Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.
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