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预测代谢网络揭示了阿尔茨海默病精准医学中性别和 APOE 基因型特异性的代谢特征和驱动因素。

Predictive metabolic networks reveal sex- and APOE genotype-specific metabolic signatures and drivers for precision medicine in Alzheimer's disease.

机构信息

Department of Neurology, University of Arizona, Tucson, Arizona, USA.

The Center for Innovation in Brain Science, University of Arizona, Tucson, Arizona, USA.

出版信息

Alzheimers Dement. 2023 Feb;19(2):518-531. doi: 10.1002/alz.12675. Epub 2022 Apr 28.

Abstract

INTRODUCTION

Late-onset Alzheimer's disease (LOAD) is a complex neurodegenerative disease characterized by multiple progressive stages, glucose metabolic dysregulation, Alzheimer's disease (AD) pathology, and inexorable cognitive decline. Discovery of metabolic profiles unique to sex, apolipoprotein E (APOE) genotype, and stage of disease progression could provide critical insights for personalized LOAD medicine.

METHODS

Sex- and APOE-specific metabolic networks were constructed based on changes in 127 metabolites of 656 serum samples from the Alzheimer's Disease Neuroimaging Initiative cohort.

RESULTS

Application of an advanced analytical platform identified metabolic drivers and signatures clustered with sex and/or APOE ɛ4, establishing patient-specific biomarkers predictive of disease state that significantly associated with cognitive function. Presence of the APOE ɛ4 shifts metabolic signatures to a phosphatidylcholine-focused profile overriding sex-specific differences in serum metabolites of AD patients.

DISCUSSION

These findings provide an initial but critical step in developing a diagnostic platform for personalized medicine by integrating metabolomic profiling and cognitive assessments to identify targeted precision therapeutics for AD patient subgroups through computational network modeling.

摘要

简介

迟发性阿尔茨海默病(LOAD)是一种复杂的神经退行性疾病,其特征是多个进行性阶段、葡萄糖代谢失调、阿尔茨海默病(AD)病理和不可避免的认知能力下降。发现性别、载脂蛋白 E(APOE)基因型和疾病进展阶段特有的代谢特征,可为个性化 LOAD 医学提供关键见解。

方法

基于阿尔茨海默病神经影像学倡议队列中 656 个血清样本中 127 种代谢物的变化,构建了性别和 APOE 特异性代谢网络。

结果

应用先进的分析平台,确定了与性别和/或 APOE ɛ4 聚类的代谢驱动因素和特征,建立了预测疾病状态的患者特异性生物标志物,这些标志物与认知功能显著相关。APOE ɛ4 的存在将代谢特征转移到以磷脂酰胆碱为重点的特征,从而忽略了 AD 患者血清代谢物中性别特异性的差异。

讨论

这些发现通过整合代谢组学分析和认知评估,为个性化医学开发诊断平台提供了初步但关键的一步,通过计算网络建模,为 AD 患者亚组确定靶向精准治疗药物。

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