Constructing differential co-expression network to predict key pathways for myocardial infarction

New thoughts are warranted to develop efficient diagnosis and optimal therapeutics to combat unstable angina (UA)/myocardial infarction (MI). Therefore, the gene data of patients with UA or MI were used in this study to identify the optimal pathways which can provide comprehensive information for UA/MI development. Differentially expressed genes (DEGs) between UA and MI were detected using LIMMA package, and pathway enrichment analysis was conducted for the DEGs, based on the DAVID tool, to detect the significant pathways. Then, differential co-expression network (DCN) and sub-DCN for the DEGs were constructed. Subsequently, informative pathways were extracted using guilt-by-association (GBA) principle relying on the area under the curve (AUC), and the pathway categories with AUC >0.8 were defined as the informative pathways. Finally, we selected the optimal pathways based on the traditional pathway analysis and the sub-DCN-based-GBA pathway prediction method. A total of 203 and 266 DEGs were identified from the expression profile of blood of MI samples comparing with UAs in the time-point 1 and time-point 2 groups. Moreover, 7 and 10 informative pathway terms were identified based on AUC>0.8. Significantly, cytokine-cytokine receptor interaction, as well as MAPK signaling pathway were the common optimal pathways in the two groups. Calcium signaling pathway was unique to the whole blood of patients with acute coronary syndrome (ACS) taken at 30 days post-ACS. In conclusion, the optimal pathways (MAPK signaling pathway, cytokine-cytokine receptor interaction, and calcium signaling pathway) might play important roles in the progression of UA/MI.