Bioinformatics-Based Analysis of Circadian Rhythm Regulation Mechanisms in Alzheimer's Disease

Background: There is a close association between Alzheimer's disease (AD) and circadian rhythms, and neuroinflammatory-related pathways are associated with both interactions. Objective: To reveal the relationship between circadian rhythm (CR) and AD at the level of genes, pathways, and molecular functions through bioinformatics. Methods: We analyzed the differential genes between AD and control groups in GSE122063 and found the important gene modules; obtained CR-related genes from GeenCard database; used Venn 2.1 database to obtain the intersection of genes of AD important modules with CR-related genes; and used STRING database and Cytoscape 3.7.1 to construct the gene protein-protein interaction network. The MCODE plugin was used to screen pivotal genes and analyze their differential expression. We trranslated with www.DeepL.com/Translator (free version) to obtain transcriptional regulatory relationships from the TRRUST database and construct a hub gene-transcription factor relationship network. Results: A total of 42 common genes were screened from AD and CR genes, mainly involving signaling pathways such as neuroactive ligand-receptor interactions. A total of 10 pivotal genes were screened from the common genes of CR and AD, which were statistically significant in the comparison of AD and control groups (p < 0.001), and ROC analysis showed that all these pivotal genes had good diagnostic significance. A total of 36 TFs of pivotal genes were obtained. Conclusion: We identified AD- and CR-related signaling pathways and 10 hub genes and found strong associations between these related genes and biological processes such as inflammation.

Automated summary

This study used bioinformatics to reveal the relationship between circadian rhythm and Alzheimer's disease at the genetic level. The results showed a strong association between circadian rhythm and Alzheimer's disease, as well as identified important genes and signaling pathways related to inflammation.