Common biomarkers of Alzheimer disease and postoperative delirium.

Alzheimer disease (AD) and Postoperative delirium (POD) may share a common mechanism, but their shared genes and potential novel therapeutic targets remains unknown. We selected datasets GSE48350, GSE4226, and GSE16759 containing AD and control samples from the GEO database for AD model development, and use the GSE63061 dataset for AD model validation. The GSE163943 dataset containing PODs and controls was used to identify common genes. Differentially expressed genes (DEGs) associated with POD and AD respectively, as well as common DEGs between 2 diseases were analyzed. Shared DEGs were assessed using gene ontology and KEGG enrichment and PPI interaction networks. Machine learning algorithms, nomogram and decision tree analyses were used to interpret top 5 genes and visualize the models. 259 DEGs in POD with 148 being up-regulated and 111 down-regulated, and 199 DEGs in AD with 25 up-regulated and 174 down-regulated were found, of which 23 were common to POD and AD. Gene ontology analysis indicated that DEGs were primarily concentrated in 9 distinct biological processes, while KEGG results revealed 3 major metabolic pathways. Five hub genes emerged as potential diagnostic biomarkers for both diseases, Bruton tyrosine kinase (BTK), NCF2, CRH, FCGR3A, and SERPINA3. The LASSO model determined that the 23 common genes could serve as biomarkers for both POD and AD patients, and the Random Forest model is the the most suitable model. POD or AD decision trees showed BTK and NCF2 were sufficient to distinguish between POD or AD patients and healthy controls. BTK and NCF2 were identified common biomarkers of POD and AD. Further investigations are required to verify correlations between gene expression levels and pathological characteristics.