The application of weighted gene co-expression network analysis in identifying key modules and hub genes associated with disease status in Alzheimer's disease.

Abstract

Alzheimer's disease (AD) is the most common neurodegenerative condition that affects more than 15 million individuals globally. However, a predictive molecular biomarker to distinguish the different stages of AD patients is still lacking. A weighted gene co-expression network analysis (WGCNA) was employed to systematically identify the co-expressed gene modules and hub genes connected with AD development based on a microarray dataset (GSE1297) from the Gene Expression Omnibus (GEO) database. An independent validation cohort, GSE28146, was utilized to assess the diagnostic efficiency for distinguishing the different stages of AD. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) and western blotting analysis were applied to examine the mRNA and protein level of GRIK1, respectively, in AD mice established with the expression of mutant amyloid precursor protein and wild type mice. The morphology of neurons was investigated using phalloidin staining. We identified 16 co-expressed genes modules, with the pink module showing significant association with all three disease statuses [neurofibrillary tangle (NFT), BRAAK, and mini-mental state examination (MMSE)]. Enrichment analysis specified that these modules were enriched in phosphatidylinositol 3-kinase (PI3K) signaling and ion transmembrane transport. The validation cohort GSE28146 confirmed that six hub genes in the pink module could distinguish severe and non-severe AD patients [area under the curve (AUC) >0.7]. These hub genes might act as a biomarker and help to differentiate diverse pathological stages for AD patients. Finally, one of the hubs, GRIK1, was validated by an animal AD model. The mRNA and protein level of GRIK1 in the AD hippocampus was increased compared with the control group (NC) hippocampus. Phalloidin staining showed that dendritic length of the GRIK1 pCDNA3.1 group was shorter than that of the NC group. In summary, we systematically recognized co-expressed gene modules and genes related to AD stages, which gave insight into the fundamental mechanisms of AD progression and revealed some probable targets for the treatment of AD.