Mult-omics Approach-Based Autophagy Pathway Analysis in Alzheimer’s Disease

Abstract

Abstract Autophagy, as an important cellular protective mechanism, is closely associated with the occurrence and progression of neurode- generative diseases such as Alzheimer’s disease. However, the specific mechanisms underlying autophagy in neurodegenerative diseases remain unclear, and there are still many unknowns regarding its detailed regulation and involvement mechanisms. In this study, we aimed to use a multi-omics bioinformatics approach to integrate large-scale transcriptomic data and identify a series of autophagy key genes, namely CDKN2A, CXCR4, and IFNG, whose expression levels significantly differ between disease pa- tients and normal controls. Additionally, single-cell omics data will be supplemented to further investigate these findings. Our goal is to provide important clues for unraveling the pathogenesis of Alzheimer’s disease and potentially identify novel targets for future therapeutics and diagnostics. Furthermore, by incorporating Mendelian randomization analysis, we will explore the causal relationships between vascular inflammation, depression, and mood fluctuations with Alzheimer’s disease to provide insights into the associations among these related diseases and offer a theoretical basis and clinical application value for their treatment and prevention.