Screening Of Key Factors For Hypertension Based On Gene Chip Data

Hypertension is one of the most widespread diseases in the world and also is the leading cause of cardiovascular death,which seriously threatens human health.The characteristics of high disability,high morbidity,high mortality and low awareness,low control rate,low treatment rate,and low aging trend have made hypertension the focus of the researcher.Gene chip data is often used in screening drug targets,medical diagnosis,revealing the mechanism of disease occurrence,gene functions,etc.Exploring the mechanism of disease through gene chip data is the current research focus in the life sciences community.Therefore,mining the key factors associated with hypertension based on gene chip data,which is of great value and scientific significance for early prevention and accurate treatment of hypertension.With the continuous development of gene chip technology and the reduction of sequencing costs,a large amount of biological data has been generated,which brings opportunities but challenges for biological data mining research.At present,the major problems in the key factor research field of hypertension: the etiology of hypertension is complex,and the mechanism that causes it is unclear;the key factors of hypertension have not been fully identified.Therefore,more research methods are needed to screen the key factors that affect the occurrence of hypertension.This paper has innovated in the following areas:(1)Based on the samples from control and disease groups of hypertension gene expression profile data,combining the weighted gene co-expression network(WGCNA)analysis method with hypertensive diseases.We constructed a hypertensive gene co-expression network,and proposed a new method of hierarchical fusion screening hub base.Then,19 hub nodes of the hypertensive gene expression network are determined,which correspond to key(hub)genes(RPL21,RPS28,FURIN,etc.)playing vital roles in hypertension and have been confirmed by biological/medical research.(2)The screening rules of single nucleotide polymorphism(SNPs)association analysis were constructed,and SNPs sites that were significantly related to hypertension were effectively screened out.We visualized the results so that key site information can be displayed more intuitively.In the paper,we took the GSE75360 dataset in the Gene Experssion Omnibus(GEO)as example,and found two key gene modules(lightcyan module and greenyellow module)that are negatively related to hypertension.In these two key modules,nine key genes related to ribosomal proteins that may regulate hypertension and ten key genes related to various enzymes that may regulate hypertension were screened,and four key genes have been reported to be associated with blood pressure.We took some data obtained from laboratory sequencing as an example,five key SNPs loci that may affect the occurrence of hypertension.Among them,the genes located at three loci have been shown to be related to hypertension.It shows that the method in the paper can excavate the key factors of hypertension with biological significance,which is of great significance for the prevention and treatment of hypertension.