Systematic Identification And Analysis Of Dysregulated MiRNA-TF Feed-Forward Loops In Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy(HCM)is one of the common hereditary cardiovascular diseases,and the pathogenesis is unknown,with a prevalence of 0.2%in the general population.It can occur at various stages of age and the ratio of male to female is roughly 3:2.Studies have shown that hypertrophic cardiomyopathy is the leading cause of sudden cardiac death(SCD)in young people under 35,especially athletes.With the development of clinical medicine and life sciences,the research on hypertrophic cardiomyopathy has achieved some results,as well as some genes related to hypertrophic cardiomyopathy have been identified,but the molecular mechanism study of the occurrence and development about hypertrophic cardiomyopathy is still not comprehensive,currently.In many biological processes,miRNA and transcription factor(TF)act as two key gene regulatory factors,involving many important cellular processes,including cell differentiation,proliferation and apoptosis.MiRNA is a type of single-stranded small-molecule non-codingRNA with a length of 18-25 nucleotides found in recent years.It is processed from the transcription precursor of the stem-loop structure.miRNA mainly degrades the target gene mRNA or inhibiting its translation through completely or incompletely matching the target gene 3’UTR,and thereby regulates the expression of the target gene at the post-transcription level and participates in the regulation of individual development,apoptosis,proliferation,differentiation and other life activities.Transcription factor is a kind of protein molecule that can specifically bind to a specific sequence upstream of the 5’ end of a gene,and it regulates gene transcription at the transcription level.Thereby it ensuring that the target gene is expressed at a specific intensity in a specific time and space.Previous studies have shown that miRNA and transcription factor can synergistically regulate the same target gene,and they can regulate each other,thereby forming feed-forward loops(FFLs).The miRNA-TF feed-forward loops has been reported to play an important role in mammalian gene regulatory networks,therefore,the dysregulation of the miRNA-TF feed-forward loops will lead to the occurrence and development of diseases.At present,the cooperative regulation mechanism between miRNA and transcription factor in hypertrophic cardiomyopathy has not been systematically studied.The aims of this study are exploring the three issues: Firstly,developing a novel bioinformatics algorithm to identify the dysregulated miRNA-TF feed-forward loops in hypertrophic cardiomyopathy.Secondly,systematically analyzing the dysregulated miRNA-TF feed-forward loops in hypertrophic cardiomyopathy,and exploring the co-regulatory mode between miRNA and transcription factor.Thirdly,further identifying the potential diagnostic markers of hypertrophic cardiomyopathy based on the miRNA-TF feed-forward loops identified.In this study,we firstly systematically integrated the paired miRNA and gene expression profile data of hypertrophic cardiomyopathy-related samples,and experimentally confirmed the interactions data between miRNA and target gene,as well as transcription factor and target gene.Then we proposed a novel bioinformatics algorithm to identify the dysregulated miRNA-TF feed-forward loops in hypertrophic cardiomyopathy.At the same time,we compared the method in this study with existing methods from multiple aspects to show the effectiveness and reliability of the method our method.Furthermore,based on the identified the dysregulated miRNA-TF feed-forward loops in hypertrophic cardiomyopathy,we constructed a dysregulated miRNA-TF regulatory network,performed topology analysis and functional analysis of the network,and explored the synergistic regulation patterns between miRNAs and transcription factors in hypertrophic cardiomyopathy.Finally,we applied the support vector machine(SVM)classification model and five-fold cross-validation to key molecules in the network,and identified potential diagnostic markers for hypertrophic cardiomyopathy.Based on the sample-paired miRNA and gene expression profile data and the interactions between the molecules,we proposed a new method to identify dysregulated miRNA-TF feed-forward loops in hypertrophic cardiomyopathy.In hypertrophic cardiomyopathy,we identified 316 significantly dysregulated miRNA-TF feed-forward loops,which consist of 118 miRNAs,102 genes,and 53 transcription factors.We have confirmed that these feed-forward loops are closely related to hypertrophic cardiomyopathy at the levels of significantly differently expressed genes,known hypertrophic cardiomyopathy-related molecules,and significantly enriched KEGG pathway.At the same time,we compared the method in this study with existing methods,the results show that the miRNA-TF feed-forward loops obtained in this study has more hypertrophic cardiomyopathy-related molecules,more significantly differentially expressed molecules,and enriched more hypertrophic cardiomyopathy-associated KEGG sub-pathways.Secondly,based on the identified miRNA-TF feed-forward loops,we constructed a dysregulated miRNA-TF regulatory network in hypertrophic cardiomyopathy,and systematically analyzed the network’s topological properties from a global perspective.We found that the miRNA-TF regulatory network had biological network characteristics.At the same time,it was found that the miRNA-TF feed-forward loop composed of hsa-miR-17-5p,FASN and STAT3 may play an important role in hypertrophic cardiomyopathy.Finally,we identified two sets of potential diagnostic markers for hypertrophic cardiomyopathy,one set consisting of three transcription factors(CEBPB,HIF1 A and STAT3),and the other set consisting of four miRNAs(hsa-miR-155-5p,hsa-miR-17-5p,hsa-miR-20a-5p and hsa-miR-181a-5p).At the same time,we verified the biomarkers in an independent test set,and the results showed that the potential diagnostic markers of hypertrophic cardiomyopathy we identified have good classification performance.We proposed a new and reliable bioinformatics method for identifying dysregulated miRNA-TF feed-forward loops in hypertrophic cardiomyopathy,and this method can be extended to the research of other disease-related miRNA-TF feed-forward loops.We systematically studied the synergistic regulation mode of miRNAs and transcription factors in hypertrophic cardiomyopathy,and simultaneously identified two groups of potential diagnostic markers of hypertrophic cardiomyopathy with high diagnostic efficacy.In conclusion,our results will provide new ideas and directions for further research on the molecular mechanism,diagnosis and treatment of hypertrophic cardiomyopathy.