Bioinformatic Analysis of Key Genes in Cardiotoxic Compound Induced Long QT Interval
17 Pages Posted: 12 Apr 2019More...
Background: Long QT (LQT) syndrome is an inherited disease with various triggering factors. The present study investigated the genetic role in medication induced LQT by conducting integrated bioinformatics analysis.
Methods: The gene expression dataset of GSE59927 and GSE59905 were downloaded from the Gene Expression Omnibus (GEO) database. LQT associated medications with genetic informations were identified by crossing reference the list of cardiotoxic compounds in GSE dataset with the list of drugs with known risk of LQT. Common differentially expressed genes (DEGs) were extracted and compared with target genes of cardiac tissue specific microRNA. The overlapped mRNA were considered as tissue specific DEGs and employed to construct the regulatory network with microRNAs. The PPI network was built to identify the key genes.
Findings: A total of 15 cardiac tissue specific DEGs in 14 different medications were identified and substantially enriched in the pathways of 'Calcium signaling pathway, Mucin type O-Glycan biosynthesis, Primary bile acid biosynthesis'. With the PPI network, 'Nrcam, Dlgap1, Gnal' were identified as key genes.
Interpretation: The identification of key genes and related pathways in the present study provided genetic insight into the acquired LQT syndrome and may facilitate therapeutic individualization.
Funding Statement: The authors state: "No funding was received."
Declaration of Interests: The authors declare that they have no competing interests, and all authors confirm its accuracy.
Ethics Approval Statement: The analyses were based on previously published studies. Thus no ethical approval was required.
Keywords: Prolong QT interval, Bioinformatic analysis, Sudden cardiac death, Acquired LQT, Cardiotoxic compound, Torsades de pointes
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