Web‐based transcriptome analysis determines a sixteen‐gene signature and associated drugs on hearing loss patients: A bioinformatics approach

BACKGROUND: Hearing loss is becoming more and more general. It may occur at all age and affect the language learning ability of children and trigger serious social problems. METHODS: The hearing loss differentially expressed genes (HL‐DEGs) were recognized through a comparison with healthy subjects. The Gene Ontology (GO) analysis was executed by DAVID. The reactome analysis of HL‐DEGs was performed by Clue‐GO. Next, we used STRING, an online website, to identify crucial protein‐protein interactions among HL‐DEGs. Cytoscape software was employed to construct a protein‐protein interaction network. MCODE, a plug‐in of the Cytoscape software, was used for module analysis. Finally, we used DGIdb database to ascertain the targeted drugs for MCODE genes. RESULTS: Four hundred four HL‐DEGs were identified, among which the most up‐regulated 10 genes were AL008707.1, SDR42E1P5, BX005040.1, AL671883.2, MT1XP1, AC016957.1, U2AF1L5, XIST, DAAM2, and ADAMTS2, and the most down‐regulated 10 genes were ALOX15, PRSS33, IL5RA, SMPD3, IGHV1‐2, IGLV3‐9, RHOXF1P1, CACNG6, MYOM2, and RSAD2. Through STRING database and MCODE analysis, we finally got 16 MCODE genes. These genes can be regarded as hearing loss related genes. Through biological analysis, it is found that these genes are enriched in pathways related to apoptosis such as tumor necrosis factor. Among them, MMP8, LTF, ORM2, FOLR3, and TCN1 have corresponding targeted drugs. Foremost, MCODE genes should be investigated for its usefulness as a new biomarker for diagnosis and treatment. CONCLUSION: In summary, our study produced a sixteen‐gene signature and associated drugs that could be diagnosis and treatment of hearing loss patients.