Exploring the inverse association of glioblastoma multiforme and Alzheimer's disease via bioinformatics analysis

Glioblastoma multiforme (GBM) and Alzheimer's disease (AD) are two major diseases in the nervous system with a similar peak age of onset, which has the typical characteristics of high cost, difficult treatment, and poor prognosis. Epidemiological studies and a few molecular biological studies have hinted at an opposite relationship between AD and GBM. However, there are few studies on their reverse relationship, and the regulatory mechanism is still unclear, indicating that further systematic research is urgently needed. Our study firstly employs advanced bioinformatics methods to explore the inverse relationship between them and find various target drugs. We obtained the gene expression dataset from public databases (GEO, TCGA, and GTEx). Then, we identified 122 differentially expressed genes (DEGs) of AD and GBM. Four significant gene modules were identified through protein-protein interaction (PPI) and module construction, and 13 hub genes were found using cytoHubba. We constructed co-expression networks and found various target drugs through these hub genes. Functional enrichment analysis revealed that the AMPK pathway, cell cycle, and cellular senescence play important roles in AD and GBM. Our study may provide a potential direction for studying the opposite molecular mechanism of AD and GBM in the future.