Atherosclerosis biomarkers via mitochondrial permeability transition necrosis gene analysis
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Background
Atherosclerosis (AS) is a major cause for cardiovascular disease, and mitochondrial permeability transition driven necrosis (MPTDN) is often associated with cardiovascular disease. To investigate the role of MPTDN-associated genes (MPTDNGs) in AS is the aim of this study.
Methods
GSE100927 and GSE66360 datasets, along with MPTDNGs were included in this study. Employing differential expression analysis, weighted gene co-expression network analysis (WGCNA), machine learning algorithms, and the integration of receiver operating characteristic (ROC) analysis with expression profiling, this study identified biomarkers. Subsequent analyses included functional analysis and immune infiltration analysis, the prediction of targeted drugs, and the molecular docking. Eventually, the expression of biomarkers was clinically validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR).
Results
Colony stimulating factor 1 receptor (CSF1R), tumor necrosis factor (TNF) and integrin alpha M (ITGAM) were identified as biomarkers, all exhibiting up-regulated expression in AS samples. The ROC analysis showed that their Area Under Curve (AUC) values were all greater than 0.9, which indicated that they were good at distinguishing between AS and control samples. Gene set enrichment analysis (GSEA) enrichment results showed that biomarkers positively regulated lysosome, leishmania infection and so on. Interestingly, immune infiltration analysis showed that both differential immune cells (CD4 memory resting T cells and M0 Macrophages) and differential immune gene sets (naturalKiller cell cytotoxicity and transforming growth factor-b (TGFb) family member receptor) were strongly correlated with ITGAM.The drugs were predicted, and the molecular docking illustrated that a robust binding interaction was found between CSF1R and EDICOTINIB, with a binding energy of - 8.93 kcal/mol. Lastly, the expression validation results obtained through RT-qPCR demonstrated that CSF1R exhibited up-regulation in AS samples when compared to normal samples, while TNF and ITGAM showed less significant differences between AS and normal.
Conclusion
CSF1R, TNF and ITGAM were identified as biomarkers in AS, which provided a basis and reference for the study of MPTDNGs in AS.
