Exploration of mitochondrial autophagy related genes in the diagnosis model construction and molecular marker mining of Alzheimer's disease based on multi-omics integration.

Abstract

Key features of Alzheimer's disease include neuronal loss, accumulation of beta-amyloid plaques, and formation of neurofibrillary tangles. These changes are due in part to abnormal protein metabolism, particularly the accumulation of amyloid beta. Mitochondria are the energy production centers within cells and are also the main source of oxidative stress. In AD, mitochondrial function is impaired, leading to increased oxidative stress and the production of more reactive oxidative substances, further damaging cells. Mitophagy is an important mechanism for maintaining mitochondrial health, helping to clear damaged mitochondria, prevent the spread of oxidative stress, and reduce abnormal protein aggregation. To this end, this article conducts an integrated analysis based on DNA methylation and transcriptome data of AD. After taking the intersection of the genes where the differential methylation sites are located and the differential genes, machine learning methods were used to build an AD diagnostic model. This article screened five diagnostic genes ATG12, CSNK2A2, CSNK2B, MFN1 and PGAM5 and conducted experimental verification. The diagnostic genes discovered and the diagnostic model constructed in this article can provide reference for the development of clinical diagnostic models for AD.