Analysis of multi-factor regulated network and different clusters in hypertrophic obstructive cardiomyopathy

Abstract We herein explored the regulatory network between lncRNA, miRNAs, mRNAs, and TFs in the HOCM and divided HOCM samples into different clusters to identify key genes and regulatory factors. The four gene sets from GEO, GENE and OMIM databases were integrated and WGCNA network was used to obtain two modules and 32 core genes. Through online database, miRNA-lncRNA, miRNA-mRNA, and TF-mRNA interaction pairs were obtained to screen the regulatory factors, and finally a multi-factor regulatory network was obtained. The first 7 regulatory factors were obtained as the core regulatory factors. The unsupervised clustering method was used to divide HOCM samples into 4 clusters. As a result, four genes including COMP, FMOD, AEBP1 and SULF1 showed significant expression in different clusters. Finally, we got 4 genes are considered as important biomarkers for different progressive stages or prognosis of HOCM. These might assist in discovering molecular mechanisms of HOCM in the future.