生物医学工程研究2025，Vol.44Issue(3)：170-177,8.DOI:10.19529/j.cnki.1672-6278.2025.03.05
基于机器学习的阿尔茨海默病非靶向代谢组学研究
Study on non-targeted metabolomics of Alzheimer's disease based on machine learning
章浩伟 1李晓乐 1张添桂 1刘颖1
作者信息
- 1. 上海理工大学 健康科学与工程学院,上海 200093
- 折叠
摘要
Abstract
To explore the relationships between metabolic disturbances in patients with Alzheimer's disease(AD)and different stages of the disease,and to study the potential of plasma in the prevention,diagnosis and treatment of AD,we employed three ma-chine learning methods to establish classification models for plasma and cerebrospinal fluid at different stages of the disease respective-ly,and conducted enrichment pathway analysis by screening relevant features as differential metabolites.The results indicated that ab-normalities in amino acid metabolism,lipid metabolism,energy metabolism and mitochondrial function were found in both body fluids of the patients,and these abnormalities occurred in the early stage of mild cognitive impairment.This research not only investigates the potential of plasma in the diagnosis of AD,but also explores the pathogenesis of different stages of AD from a metabolic perspective.关键词
机器学习/阿尔茨海默病/轻度认知障碍/代谢组学/血浆/脑脊液Key words
Machine learning/Alzheimer's disease/Mild cognitive impairment/Metabolomics/Plasma/Cerebrospinal fluid分类
医药卫生引用本文复制引用
章浩伟,李晓乐,张添桂,刘颖..基于机器学习的阿尔茨海默病非靶向代谢组学研究[J].生物医学工程研究,2025,44(3):170-177,8.
