Weighted Gene Co-Expression Network Analysis Reveals Key Genes and Potential Drugs in Abdominal Aortic Aneurysm.
Ke-Jia KanFeng GuoLei ZhuPrama PallaviMartin SiglMichael KeesePublished in: Biomedicines (2021)
Abdominal aortic aneurysm (AAA) is a prevalent aortic disease that causes high mortality due to asymptomatic gradual expansion and sudden rupture. The underlying molecular mechanisms and effective pharmaceutical therapy for preventing AAA progression have not been fully identified. In this study, we identified the key modules and hub genes involved in AAA growth from the GSE17901 dataset in the Gene Expression Omnibus (GEO) database through the weighted gene co-expression network analysis (WGCNA). Key genes were further selected and validated in the mouse dataset (GSE12591) and human datasets (GSE7084, GSE47472, and GSE57691). Finally, we predicted drug candidates targeting key genes using the Drug-Gene Interaction database. Overall, we identified key modules enriched in the mitotic cell cycle, GTPase activity, and several metabolic processes. Seven key genes (CCR5, ADCY5, ADCY3, ACACB, LPIN1, ACSL1, UCP3) related to AAA progression were identified. A total of 35 drugs/compounds targeting the key genes were predicted, which may have the potential to prevent AAA progression.
Keyphrases
- network analysis
- genome wide
- genome wide identification
- cell cycle
- abdominal aortic aneurysm
- bioinformatics analysis
- gene expression
- dna methylation
- genome wide analysis
- copy number
- poor prognosis
- type diabetes
- cell proliferation
- emergency department
- endothelial cells
- magnetic resonance
- risk factors
- aortic valve
- drug induced
- cardiovascular events
- binding protein
- pulmonary hypertension
- dendritic cells
- computed tomography
- pulmonary artery
- long non coding rna
- coronary artery disease
- climate change
- pulmonary arterial hypertension
- regulatory t cells