CC BY 4.0 · Glob Med Genet 2023; 10(04): 357-369
DOI: 10.1055/s-0043-1777069
Original Article

Study on Screening Core Biomarkers of Noise and Drug-Induced Hearing Loss Based on Transcriptomics

Xin Qiu
1   Department of Otolaryngology-Head & Neck Surgery, The Sixth Medical Center of PLA General Hospital, National Clinical Research Center for Otolaryngologic Diseases, State Key Lab of Hearing Science, Ministry of Education, Beijing Key Lab of Hearing Impairment Prevention and Treatment Beijing, Beijing, People's Republic of China
,
Qing-Qing Jiang
1   Department of Otolaryngology-Head & Neck Surgery, The Sixth Medical Center of PLA General Hospital, National Clinical Research Center for Otolaryngologic Diseases, State Key Lab of Hearing Science, Ministry of Education, Beijing Key Lab of Hearing Impairment Prevention and Treatment Beijing, Beijing, People's Republic of China
,
Wei-Wei Guo
1   Department of Otolaryngology-Head & Neck Surgery, The Sixth Medical Center of PLA General Hospital, National Clinical Research Center for Otolaryngologic Diseases, State Key Lab of Hearing Science, Ministry of Education, Beijing Key Lab of Hearing Impairment Prevention and Treatment Beijing, Beijing, People's Republic of China
,
Ning Yu
1   Department of Otolaryngology-Head & Neck Surgery, The Sixth Medical Center of PLA General Hospital, National Clinical Research Center for Otolaryngologic Diseases, State Key Lab of Hearing Science, Ministry of Education, Beijing Key Lab of Hearing Impairment Prevention and Treatment Beijing, Beijing, People's Republic of China
,
Shi-ming Yang
1   Department of Otolaryngology-Head & Neck Surgery, The Sixth Medical Center of PLA General Hospital, National Clinical Research Center for Otolaryngologic Diseases, State Key Lab of Hearing Science, Ministry of Education, Beijing Key Lab of Hearing Impairment Prevention and Treatment Beijing, Beijing, People's Republic of China
› Author Affiliations
Funding This research was supported by National Key R&D Program of China (2020YFC2004001), National Key R&D Program of China (2020YFC2005203), NSFC (81470700), Project supported by the Funds for International Cooperation and Exchange of the National Natural Science Foundation of China (81820108009), and Beijing Natural Science Foundation (7222185).

Abstract

Background Noise and drug-induced hearing loss (HL) is becoming more and more serious, but the integration and analysis based on transcriptomics and proteomics are lacking. On the one hand, this study aims to integrate existing public transcriptomic data on noise and gentamicin-induced HL. On the other hand, the study aims to establish the gentamicin and noise-induced HL model of guinea pigs, then to perform the transcriptomic and proteomic analyses. Through comprehensive analysis of the above data, we aim to screen, predict, and preliminarily verify biomarkers closely related to HL.

Material and Methods We screened the Gene Expression Omnibus database to obtain transcriptome data expression profiles of HL caused by noise and gentamicin, then constructed the guinea pig HL model and perform the transcriptomic and proteomic analyses. Differential expression and enrichment analysis were performed on public and self-sequenced data, and common differentially expressed genes (DEGs) and signaling pathways were obtained. Finally, we used proteomic data to screen for common differential proteins and validate common differential expression genes for HL.

Results By integrating the public data set with self-constructed model data set, we eventually obtained two core biomarkers of HL, which were RSAD2 and matrix metalloproteinase-3 (MMP3). Their main function is to regulate the development of sense organ in the inner ear and they are mainly involved in mitogen-activated protein kinase and phosphoinositol-3 kinase/protein kinase B signaling pathways. Finally, by integrating the proteomic data of the self-constructed model, we also found differential expression of MMP3 protein. This also preliminarily and partially verified the above-mentioned core biomarkers.

Conclusion and Significance In this study, public database and transcriptomic data of self-constructed model were integrated, and we screened out two core genes and various signal pathways of HL through differential analysis, enrichment analysis, and other analysis methods. Then, we preliminarily validated the MMP3 by proteomic analysis of self-constructed model. This study pointed out the direction for further laboratory verification of key biomarkers of HL, which is of great significance for revealing the core pathogenic mechanism of HL.

Ethics Approval and Consent to Participate

Our studies did not involve human participants, human data, or human tissues.


Consent for Publication

Written informed consent for publication was obtained from all participants.


Authors' Contributions

All authors contributed to the article and approved the submitted version.




Publication History

Article published online:
04 December 2023

© 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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