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机器学习辅助优化针对痴呆风险的饮食干预

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

作者信息

Chen Si-Jia, Chen Hui, You Jia, Chen Shi-Dong, Fu Yan, Zhang Wei, Huang Liyan, Feng Jian-Feng, Gao Xiang, Cheng Wei, Yuan Changzheng, Yu Jin-Tai

机构信息

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.

School of Public Health, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

出版信息

Nat Hum Behav. 2025 Jul 2. doi: 10.1038/s41562-025-02255-w.

DOI:10.1038/s41562-025-02255-w
PMID:40603580
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.

摘要

健康饮食与降低患痴呆症的风险有关。在此,我们基于来自185,012名英国生物银行参与者的数据,设计了一种机器学习辅助的优化饮食干预以降低痴呆风险(MODERN)饮食,其中1,987人在10年内患上了全因性痴呆症。我们首先在全食物关联分析中确定了25种与痴呆症相关的食物组。其次,我们使用机器学习对它们的重要性进行排序,并将八组食物(例如绿叶蔬菜、浆果和柑橘类水果)列为优先。最后,我们建立并在外部验证了一个MODERN评分(0 - 7),与先验定义的MIND饮食相比,该评分与较低的痴呆相关结局风险显示出更强的关联(最高三分位数与最低三分位数相比的风险比:0.64,95%置信区间:0.43 - 0.93)(0.75,0.61 - 0.92)。在63项与健康相关的结局中,MODERN饮食与精神/行为障碍显示出特别显著的关联。多模态神经影像学、代谢组学、炎症和蛋白质组学分析揭示了潜在途径,并进一步支持了MODERN饮食预防痴呆的潜力。

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Machine learning-assisted optimization of dietary intervention against dementia risk.机器学习辅助优化针对痴呆风险的饮食干预
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本文引用的文献

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Plasma proteomic profiles predict future dementia in healthy adults.血浆蛋白质组谱可预测健康成年人的未来痴呆症。
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Association of biological age with health outcomes and its modifiable factors.生物年龄与健康结果及其可调节因素的关联。
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Associations of sugar-sweetened, artificially sweetened, and naturally sweet juices with Alzheimer's disease: a prospective cohort study.含糖饮料、人工甜味饮料和天然甜味饮料与阿尔茨海默病的关联:一项前瞻性队列研究。
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Association of the Mediterranean Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay (MIND) Diet With the Risk of Dementia.地中海饮食防治高血压干预神经退行性延迟(MIND)饮食与痴呆风险的关联。
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