Machine learning-assisted optimization of dietary intervention against dementia risk.

Journal: Nature human behaviour
Published Date:

Abstract

A healthy diet has been associated with a reduced risk of dementia. Here we devised a Machine learning-assisted Optimizing Dietary intERvention against demeNtia risk (MODERN) diet based on data from 185,012 UK Biobank participants, 1,987 of whom developed all-cause dementia over 10 years. We first identified 25 food groups associated with dementia in a food-wide association analysis. Second, we ranked their importance using machine learning and prioritized eight groups (for example, green leafy vegetables, berries and citrus fruits). Finally, we established and externally validated a MODERN score (0-7), which showed stronger associations with lower risk of dementia-related outcomes (hazard ratio comparing highest versus lowest tertiles: 0.64, 95% CI: 0.43-0.93) than the a priori-defined MIND diet (0.75, 0.61-0.92). Across 63 health-related outcomes, the MODERN diet showed particularly significant associations with mental/behavioural disorders. Multimodal neuroimaging, metabolomics, inflammation and proteomics analyses revealed potential pathways and further support the potential of MODERN diet for dementia prevention.

Authors

  • Si-Jia Chen
    Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • Hui Chen
    Xiangyang Central HospitalAffiliated Hospital of Hubei University of Arts and Science Xiangyang 441000 China.
  • Jia You
  • Shi-Dong Chen
    Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • Yan Fu
    School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300350, PR China. Electronic address: fuyan@tju.edu.cn.
  • Wei Zhang
    The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Liyan Huang
    Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.
  • Jian-Feng Feng
    Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
  • Xiang Gao
    Department of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.
  • Wei Cheng
    Department of Dental Implantology, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China.
  • Changzheng Yuan
    School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, China.
  • Jin-Tai Yu
    Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China. jintai_yu@fudan.edu.cn.

Keywords

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