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

Xianyu Qin, Lei Huang, Shaoxian Chen, Pengju Wen, Sichengg Chen, Min Wu, Yueheng Wu
2020 unpublished
Background Hypertrophic obstructive cardiomyopathy (HOCM) is a kind of hypertrophic cardiomyopathy (HCM) with more severe symptoms. 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 that are involved in the process of HOCM. Methods Differentially expressed genes and online associated genes were integrated as a candidate gene set. WGCNA method was used to
more » ... d was used to obtain key modules and genes related to HOCM. Subsequently, core genes were used to construct a multi-factor regulatory network and divided HOCM into different clusters. Lastly, the key regulatory factors and significant genes were identified in different clusters. Results 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 that interact with the co-expressed key genes (N = 32), and finally a multi-factor regulatory network with 175 interaction pairs was obtained. The first 7 regulatory factors were obtained as the core regulatory factors, which included the lncRNAs (XIST, MALAT1, H19), TFs (SPI1 and SP1) and miRNAs (hsa-miR-29b-39 and has-miR-29a-3p). Finally, 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. Conclusion Bioinformatics method was used to obtain the molecular regulatory lncRNA-miRNA-mRNA and TF network and classified HOCM samples into different clusters. Finally, 32 co-expressed key genes that are of great significance for HOCM typing and 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.
doi:10.21203/ fatcat:bal4mqqsrnaizpznx7tyy3rk2q