Multi-omics analysis reveals the key factors involved in the severity of the Alzheimer's disease.

ABSTRACT: Alzheimer's disease (AD) is a debilitating neurodegenerative disorder with a global impact, yet its pathogenesis remains poorly understood. While age, metabolic abnormalities, and accumulation of neurotoxic substances are potential risk factors for AD, their effects are confounded by other factors. To address this challenge, we first utilized multi-omics data from 87 well phenotyped AD patients and generated plasma proteomics and metabolomics data, as well as gut and saliva metagenomics data to investigate the molecular-level alterations accounting the host-microbiome interactions. Second, we analyzed individual omics data and identified the key parameters involved in the severity of the dementia in AD patients. Next, we employed Artificial Intelligence (AI) based models to predict AD seve

SUBMITTER: Meng L 

PROVIDER: S-EPMC11448018 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature