Abstract
Background: Neurodegenerative diseases, such as Alzheimer's disease patients (AD), Huntington's disease (HD) and Parkinson’s disease (PD), are common causes of morbidity, mortality, and cognitive impairment in older adults.
Objective: We aimed to understand the transcriptome characteristics of the cortex of neurodegenerative diseases and to provide an insight into the target genes of differently expressed microRNAs in the occurrence and development of neurodegenerative diseases.
Methods: The Limma package of R software was used to analyze GSE33000, GSE157239, GSE64977 and GSE72962 datasets to identify the differentially expressed genes (DEGs) and microRNAs in the cortex of neurodegenerative diseases. Bioinformatics methods, such as GO enrichment analysis, KEGG enrichment analysis and gene interaction network analysis, were used to explore the biological functions of DEGs. Weighted gene co-expression network analysis (WGCNA) was used to cluster DEGs into modules. RNA22, miRDB, miRNet 2.0 and TargetScan7 databases were performed to predict the target genes of microRNAs.
Results: Among 310 Alzheimer's disease (AD) patients, 157 Huntington's disease (HD) patients and 157 non-demented control (Con) individuals, 214 co-DEGs were identified. Those co-DEGs were filtered into 2 different interaction network complexes, representing immune-related genes and synapserelated genes. The WGCNA results identified five modules: yellow, blue, green, turquoise, and brown. Most of the co-DEGs were clustered into the turquoise module and blue module, which respectively regulated synapse-related function and immune-related function. In addition, human microRNA-4433 (hsa-miR-4443), which targets 18 co-DEGs, was the only 1 co-up-regulated microRNA identified in the cortex of neurodegenerative diseases.
Conclusion: 214 DEGs and 5 modules regulate the immune-related and synapse-related function of the cortex in neurodegenerative diseases. Hsa-miR-4443 targets 18 co-DEGs and may be a potential molecular mechanism in neurodegenerative diseases' occurrence and development.
Keywords: neurodegenerative diseases, differentially expressed genes, bioinformatics analysis, weighted gene co-expression network analysis, differentially expressed microRNA, risk factor
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