Analysis and identification of mitochondrial DNA associated with age-related hearing loss

Analysis and identification of mitochondrial DNA associated with age-related hearing loss | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysis and identification of mitochondrial DNA associated with age-related hearing loss Tianyu ma, Xiaoyun Zeng, Mengting Liu, Shijia Xu, Yuyao Wang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4465565/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Mar, 2025 Read the published version in BMC Genomics → Version 1 posted 11 You are reading this latest preprint version Abstract Background To explore the mitochondrial genes that play a key role in the occurrence and development of age-related hearing loss(ARHL), provide a basis for the study of the mechanism of ARHL. Results A total of 503 differentially expressed genes (DEGs) were detected in the GSE49543 dataset,233 genes were up-regulated and 270 genes were down-regulated. There are a total of 1140 genes in the mitochondrial gene bank and 28 DE-MFRGS related to ARHL. These genes are mainly involved in mitochondrial respiratory chain complex assembly, small molecule catabolism, NADH dehydrogenase complex assembly, organic acid catabolism, precursor metabolites and energy production, and mitochondrial span Membrane transport, metabolic processes of active oxygen species. Then, the three key genes were identified by Cytoscape software :Aco2,Bcs1l and Ndufs1. Immunofluorescence and Western blot experiments confirmed that the protein content of three key genes in aging cochlear hair cells decreased. Conclusion We employed bioinformatics analysis to screen 503 differentially expressed genes and identified three key genes associated with ARHL. Subsequently, we conducted in vitro experiments to validate their significance, thereby providing a valuable reference for further elucidating the role of mitochondrial function in the pathogenesis and progression of ARHL. ARHL mtDNA Mitochondrial homeostasis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Age-related hearing loss (ARHL) is a degenerative condition affecting the cochlea and vestibule, commonly associated with aging ( 1 ), It is characterized by progressive and irreversible bilateral symmetrical sensorineural hearing impairment. Deafness can result in diminished social functioning, heightened risk of dementia, anxiety, and depression among older individuals, significantly jeopardizing their physical and mental well-being while imposing a substantial burden on both families and society( 2 , 3 )。Due to the unknown etiology of ARHL, treatment primarily relies on hearing aids as there are currently no effective preventive or therapeutic measures available. Recent research advancements have suggested that mitochondrial homeostasis imbalance may be implicated in the development of ARHL( 4 )。 The homeostasis of mitochondria in cells is achieved through division and fusion, ensuring the normal functioning of mitochondria, which primarily relies on mitochondrial DNA ( 5 )。Within cells, mitochondria play a crucial role in regulating oxidative metabolism and serve as the primary source of Reactive Oxygen Species (ROS). Mitochondrial dysfunction serves as an indicator of cellular aging. Excessive ROS production during cellular aging results in the loss of mitochondrial membrane potential, an increase in mitochondrial mass, alterations to the mitochondrial respiratory complex, release of cytochrome C, reduction in mitochondrial transcription factor A levels, and an accumulation of fragmented mitochondrial DNA. These events ultimately lead to impaired mitochondrial function and subsequent activation of the apoptotic pathway within mitochondria,which lead to cell senescence and death ( 6 , 7 )。Among these factors influencing ROS production or deficiency regulation lies mitochondrial DNA - a pivotal target for excessive ROS ( 8 , 9 )。Mutations and deletions within mitochondrial DNA can induce apoptosis and contribute to age-related diseases ( 10 )。To date, over 150 mtDNA deletions associated with various diseases have been identified through the Mitomap database dedicated to studying the human mitochondrial genome ( http://www.mitomap.org ) ( 11 )。 Currently, there is no definitive conclusion regarding the alterations and impacts of mitochondrial DNA in the onset and progression of ARHL. However, the significant role of mitochondrial DNA in cellular aging has compelled researchers to give it due attention. In this study, we employed bioinformatics methods to investigate the pivotal mitochondrial DNA factors influencing ARHL. Our findings indicate that ACO2, BCS1L, and Ndufs1 are key mitochondrial genes associated with ARHL, which were further validated through in vitro experiments. Materials and methods Collection and acquisition of gene chip data Access the GEO public database ( https://www.ncbi.nlm.nih.gov/geo/ ) ( 12 )and download the GSE49543 dataset of gene chip raw data for research purposes. The GSE49543 dataset comprises gene sequencing data from the cochlea of 40 presbycusis mice, obtained using the GPL339 platform (MOE430A) Affymetrix array. The GEO2R online tool was utilized to standardize the microarray data from the GSE49543 dataset, and a total of 13661 differentially expressed genes (ARHL-DEGs) were identified using ggplot2 package analysis with a significance threshold of P < 0.05. For further investigation, we downloaded Mouse MitoCarta3.0 from Broad Institute's MitoCarta 3.0 database - an inventory of mammalian mitochondrial proteins and pathways that includes a list of 1,136 human and 1,140 mouse protein-coding genes localized on mitochondria( 13 ). This database provides information on submitochondrial localization, pathway annotation, and assigns genes to 149 mitochondrial terms. Validation of key genes The accuracy of key genes identified from the GSE49543 dataset was validated using the GEO database. R software (version 4.1.3; https://www.r-project.org/ ) is a programming language utilized for statistical analysis, graphical visualization, and reporting purposes. The data set was normalized using the "limma" package of R software, and Wilcoxon tests were employed (* p < 0.05 and ** p < 0.01). The ggplot2 data package was utilized to standardize the microarray data from the GSE49543 dataset, resulting in the identification of differential genes. Subsequently, we employed Sangerbox, a web-based platform for clinical health analysis ( http://vip.sangerbox.com)(14) , to generate a volcano plot. Differential expression analysis of mitochondria-related genes The intersection genes between the identified differentially expressed genes and mitochondrial genes were selected. A Venn diagram was generated using the "VennDiagram package" in R software to visually represent the number of differentially expressed genes (DE-MFRGS) associated with senior-onset deafness. GO analysis Gene Ontology (GO) is an internationally recognized standard classification system for gene function. GO analysis, a bioinformatics method available at https://geneontology.org/ , involves categorizing genes or proteins based on their biological functions through the analysis of biological data( 15 , 16 ). This provides a crucial theoretical framework for conducting research in biology. GO comprises three ontologies that describe the molecular function (MF), biological process (BP), and cellular component (CC) of a gene. The fundamental unit of GO is a gene set or term, which refers to a group of genes with similar biological processes and metabolic pathways located within the same signaling pathway. Each term corresponds to an attribute representing either a functional category or cell localization. KEGG analysis KEGG analysis, the Kyoto Encyclopedia of Genes and Genomes, was established in 1995 by the Kanehisa Laboratory of the Bioinformatics Center at Kyoto University, Japan( 17 ). It is widely recognized as one of the most extensively utilized biological information databases worldwide. KEGG ( https://www.genome.jp/kegg/ ) serves as a comprehensive resource for exploring advanced features and understanding biological systems such as cells, organisms, and ecological systems. It particularly focuses on molecular-level information derived from large-scale datasets generated through genome sequencing and other high-throughput experimental technologies. GSEA Gene Set Enrichment Analysis (GSEA) is a computational method utilized to determine whether a predefined set of genes exhibits a statistically significant and consistent difference between two biological states( 18 ). The "clusterProfiler package" in the R language was employed for linking the gene set of GO functional terms and KEGG Pathway in GSEA analysis, while converting the gene expression profile into an expression matrix for GSEA analysis. Metascape ( http://metascape.org/gp/index.html#/main/step1 ) is a web tool that offers gene enrichment analysis, protein interaction network analysis, and other functionalities. This website integrates over 40 gene functional annotation databases and also provides various visualizations( 19 ). Construction of PPI network and identification of hub gene The Protein-Protein Interaction Networks (PPI) were constructed using the STRING online database ( https://cn.string-db.org/)(20) . Through the utilization of Cytoscape ( https://www.statistical-analysis.top/Cytoscape)(21, 22) , a software for biological network analysis and visualization, we performed an analysis on CytoHubba MCC to identify the top 10 genes in the PPI network, which were determined as key genes: Fdx1, Mrpl24 Mtif2, Arg2, Aco2 Ndufs1, Bcs1l, Ndufaf5, Nsun2, Sdhaf1. Cell line In this experiment, the mouse cochlea hair cell immortal HEI-OC1 cell line, purchased from Ubigene Company, was cultured in Dulbecco's modified Eagle's culture medium (DMEM) (Gibco, USA) under humid conditions with 5% CO2 at 37℃. The culture medium was supplemented with 10% fetal bovine serum (FBS) (ExCell, CHINA) and 100 U/ml penicillin/streptomycin (Gibco, USA). To induce aging in the cells, they were treated with D-galactose (Solebol, China) at a concentration of 30mg/ml for 72 hours. Western blot HEI-OC1 cells were lysed with RIPA buffer containing PMSF and protease inhibitor, and the protein concentration was determined using the BCA method. 20 µg of protein were separated by 12% SDS-PAGE and transferred onto a PVDF membrane, followed by overnight incubation with specific primary antibodies at 4℃. Immunoreactive bands were detected using chemiluminescence. Antibodies used included anti-ACO2 (proteintech, China), anti-BCS1L (proteintech, China), anti-NDUSF1 (proteintech, China), and anti-GAPDH (proteintech, China). Immunofluorescence The cells were seeded onto small glass slides and subsequently subjected to the corresponding treatments. After fixation with 4% PFA for 30 minutes, permeabilization was achieved by incubating the cells with 0.5% Triton X-100 for 30 minutes. Subsequently, blocking was performed using 5% BSA for 1 hour. The cells were then incubated overnight at 4℃ with the primary antibody specific to their target protein. On the following day, fluorescently labeled secondary antibodies and DAPI were applied to stain the nuclei of the cells. Finally, immunofluorescence analysis was conducted under a fluorescence microscope. Results A total of 503 differentially expressed genes associated with ARHL were identified A total of 503 differentially expressed genes (ARHL-DEGs) were identified using the R language package "limma (v3.48.3)"(Fig. 2). 233 genes exhibited upregulation with a conditional logFC > 0 threshold, while 270 genes showed downregulation with a logFC < 0 threshold. Through the enrichment analysis of differentially expressed genes, it was determined that these genes were associated with mitochondrial function. The clusterProfiler software package was utilized to analyze the differential gene expression in ARHL, resulting in 659 significant GO terms and 35 KEGG pathways (p < 0.05). The identified biological processes primarily encompassed mitochondrial respiratory chain complex assembly, small molecule catabolism process, NADH dehydrogenase complex assembly, organic acid catabolism process, generation of precursor metabolites and energy, mitochondrial transmembrane transport, and reactive oxygen species metabolic process(Table 1). Cellular components included integral component of mitochondrial membrane, mitochondrial matrix, extracellular exosomes, integral component of organelle membrane, extracellular vesicle(Table 2༉. Molecular functions comprised iron-sulfur cluster binding, metal cluster binding mRNA methyltransferase activity ,2-sulfur cluster binding, tRNA methyltransferase activity, carboxylic ester hydrolase activity,and lyase activity(Table 3). KEGG pathway analysis revealed involvement in Biosynthesis of amino acids, biosynthesis of unsaturated fatty acids, peroxisome,carbon metabolism,and primary bile acid biosynthesis(Table 4). Table 1. GO analysis: Biological Processes (Top 10） Table 2. GO analysis: Cellular Components (Top 10） Table 3. GO analysis: Molecular Function (Top 10) Table 4. KEGG enrichment pathway analysis (Top 10) A total of 28 mitochondrial genes were differentially expressed We observed a strong association between gene enrichment results and mitochondria, thus we integrated these 503 differential genes with mitochondrial genes to identify the differentially expressed genes related to mitochondria. A total of 28 differentially expressed mitochondrial genes (DE-MFRGS) associated with ARHL were analyzed using Venn mapping software package (1.7.1) (Fig. 3A). The Metascape tool was utilized to perform enrichment analysis on these 28 differentially expressed mitochondrial genes, using the following criteria: Min Overlap ≤ 3, P Value Cutoff ≤ 0.01, and Min Enrichment ≤ 1.5. The results were visualized in a bar chart. We observed that NDUFS1, FDX1, ACO2, ALDH2, NDUFAF5, HSD17B4 and AASS were significantly enriched in iron-sulfur cluster binding at the molecular function. Additionally, ALDH2, ACOT7 and ABHD10 exhibited enrichment in catalytic activity, acting on a tRNA. METTL8, NSUN2, NDUFAF5 and GARS1 showed enrichment in carboxylic ester hydrolase activity while CLYBL, ACO2 and HSD17B4 demonstrated enrichment in lyase activity (Fig. 3B). In terms of biological processes, GTP2, ARG2, AASS, HSD17B4, AcoT7, ALDH2, NUDT5 and GARS1 are involved in small molecule catabolic process. NDUFAF5, NDUFS1, BCS1L, SLC25A33, SDHAF1 and RHOT1 contribute to the assembly of mitochondrial respiratory chain complex assembly. ACOT7,HSD17B4,AASS ,NDUFS1 ,NUDT5,GARS1 and CKMT1B play a role in mitochondrial gene expression. SLC25A33,SFXN1,SFXN4 and RHOT participate in nucleotide metabolism. ALDH2 ,FDX1 ,ACO2,and NDUFS participate in the electron transport chain; METTL8 ,NSUN2,GARS,and NDUFAF5 are involved tRNA metabolism (Fig. 3C). In terms of cell components, SDHAF1 MRPL24, NDUFS1, ARG2, GARS1, GPT2, FDX1, ABHD10, AASS, ALDH2, AC02 participated in the composition of mitochondrial membrane. NDUFS1, MRPL24, BCS1L, SLC25A33, SFXN1, NDUFAF5, CKMT1B, SFXN4, RHOT1 SLC30A9 participate in the formation of mitochondrial matrix(Fig. 3D). KEGG analysis showed that ALDH2, CKMT1B and ARG2 were involved in the metabolic pathways of arginine and proline. ARG2, AC02 and GPT2 participate in the metabolic pathway of amino acids (Fig. 3E). Three crucial mitochondrial genes were identified A network diagram depicting protein interactions of differentially expressed mitochondrial genes was constructed using the STRING database. Subsequently, a network clustering module comprising 28 nodes and 17 edges was obtained (Fig. 4A). Next, Cytoscape's CytoHubba MCC software plugin was employed for analysis, leading to the identification of ten top hub genes: Fdx1, Mrpl24, Mtif2, Arg2, Aco2, Ndufs1, Bcs1l, Ndufaf5, Nsun2, and Sdhaf1. Notably among them are Aco2, Bcs1l and Ndufs1 which occupy central positions within the module and serve as hub genes associated with ARHL (Fig. 4B). Furthermore,the expression levels of these three hub genes exhibit significant downregulation in ARHL. The expression of Aco2, Bcs1l and Ndufs1 decreased in senescent hair cells In order to validate the conclusion derived from the aforementioned analysis, we conducted cell experiments to corroborate it. Specifically, we performed in vitro experiments using the hair cell immortal cell line HEI-OC1 and exposed the cells to D-galactose at a concentration of 30mg/ml for 72 hours to simulate senescent hair cells. Subsequently, we assessed the levels of three hub genes through immunofluorescence and Western blot techniques. Our findings revealed a significant downregulation in the expression levels of Aco2, Bcs1l, and Ndufs1 in aging hair cells compared to the control group(Fig. 5). Discussion According to previous speculation,age-related hearing loss is primarily attributed to the degeneration of Stira vascularis (SV), which plays a crucial role in maintaining the electrical potential of the inner ear and facilitating the conversion of mechanical signals into electrical signals in the cochlea. ( 23 )。Recent research has identified that cochlear hair cells (HC) are pivotal in determining ARHL. In their autopsy study involving 120 cadaver patients, Liberman et al. observed a significant correlation between hair cell loss and the extent of hearing damage, while stira vascularis were found to be unrelated to hearing damage levels. This groundbreaking study provided novel insights into the key component responsible for ARHL within human cochlea( 24 ). Cochlear hair cells are highly energy-consuming cells, primarily relying on the oxidative phosphorylation process of mitochondria for their energy source( 4 , 25 ).Mitochondria in hair cells maintain homeostasis through division and fusion, thereby ensuring normal mitochondrial function. In hair cells, mitochondria play a crucial role in regulating oxidative metabolism and generating Reactive Oxygen Species (ROS). The aging of hair cells is characterized by the accumulation of oxidative damage caused by ROS buildup, with mitochondria being the primary site of ROS-induced cellular damage ( 26 , 27 ). Additionally, mitochondria are involved in various other processes such as signaling, cell differentiation, and regulation of the cell cycle and growth ( 28 ). During the aging process of cochlear hair cells, disturbances in mitochondrial homeostasis lead to mitochondrial dysfunction (MD), resulting in alterations in intracellular REDOX levels and subsequent cell death( 29 , 30 ). The human mitochondrial genome is a circular, double-stranded, supercoiled molecule with one to several thousand copies per cell consisting of 16,569 bases ( 31 )。Although mitochondrial genes are also protected by proteins, their protective effect is significantly weaker than that of nuclear DNA, rendering them more susceptible to external genotoxic substances ( 32 )。Accumulation of ROS in hair cells also induces mutations in the mitochondrial genome, leading to damage in mitochondrial DNA. Mutation and deletion of mitochondrial mtDNA play a crucial role in hair cell senescence. Markaryan et al. discovered that cochlear tissues from elderly humans exhibited deficiency in 4977-bp mitochondria and and the probability of deficiency would increase with age ( 33 )。Enhanced protection of mitochondrial DNA could be beneficial. Jun Li et al. utilized the DNA methylation inhibitor 5-azacytidine to reduce the methylation level of SOD2, thereby decreasing oxidative stress and copy number variations (CNVs) of mtDNA4834 mutations while inhibiting H2O2-induced apoptosis in hair cells ( 34 )。Subsequently, more studies have confirmed the close association between mutation and deletion of mtDNA with age-related hearing loss (ARHL), suggesting an increased risk for ARHL due to its mutation ( 35 )。 A total of 503 DEGs were identified. KEGG pathway enrichment analysis revealed significant enrichment of DEGs in the oxidative phosphorylation signaling pathway, amino acid anabolic signaling pathway, ribosome signaling pathway, peroxisome signaling pathway, and other pathways associated with mitochondrial function. These findings suggest that alterations in these signaling pathways may contribute to mitochondrial dysfunction and subsequently induce ARHL. Following GO functional enrichment analysis of DEGs, Tables present the top ten entries for each of the three Go ontologies. BP primarily encompasses processes related to mitochondrial transmembrane transport, metabolic processes involving reactive oxygen species, assembly of mitochondrial respiratory chain complexes and genes expression within mitochondria, NADH dehydrogenase complex assembly, precursor metabolite and energy production as well as organic acid decomposition and small molecule metabolism. CC involves the formation of components such as mitochondrial membranes, mitochondrial matrixes, myelin sheaths, extracellular exosomes as well as complete components found in other organelle membranes including extracellular vesicles and organelles. MM molecules are involved in activities such as binding to 2- and 4-ferric sulfur clusters or metal clusters; mRNA/tRNA methyltransferase activity; catalytic activity; carboxylic ester hydrolase activity. In light of the strong correlation observed between these differential genes and mitochondrial function, we performed an intersection analysis with mitochondrial DNA to identify differentially expressed mitochondrial DNA associated with age-related hearing loss. Among them, Aco2, Bcs1l, and Ndufs1 emerged as three key hub genes closely linked to mitochondrial function. Mitochondrial aconitase 2 (ACO2) belongs to the iron-sulfur cluster hydratase family. Upon binding to the enzyme structure, the active iron-sulfur cluster catalyzes citric acid reversibly into isocitrate in the TCA cycle and facilitates dehydration and rehydration reactions ( 36 ). Aco2 is an indispensable enzyme in the tricarboxylic acid cycle, playing a crucial role in coordinating mitochondrial and autophagy functions for energy metabolism within cellular mitochondrial respiratory chain. ACO2 significantly contributes to cellular energy metabolism, maintenance of iron homeostasis, resistance against oxidative stress, as well as preservation of mitochondrial DNA (mtDNA) integrity ( 37 ). Research has indicated that mutations in the ACO2 gene may be associated with premature aging ( 38 ). Furthermore, studies have demonstrated that ACO2 impacts neuronal function and survival during aging process, potentially contributing to Alzheimer's disease onset ( 39 ).Targeting ACO2 for enhancing energy metabolism could serve as a promising therapeutic strategy for Parkinson's disease and other neurodegenerative disorders( 40 )。Currently, there are extensive reports on the involvement of ACO2 mutations in energy metabolism issues and progression of neurodegenerative diseases such as optic atrophy, microcephaly, intellectual impairment cognitive decline hypotonia spastic paraplegia( 41 – 43 ). As a chaperone and translocation enzyme in the inner mitochondrial membrane, the BCS1L protein plays a crucial role in promoting the final folding and assembly of respiratory complex III by facilitating the insertion of the Rieske iron-sulfur subunit into the complex( 44 ). The functional structure of BCS1L consists of three distinct domains: (a) N-terminal domain comprising three special parts - transmembrane domain (TMD), mitochondrial targeting sequence (MTS), and input auxiliary sequence (IAS); (b) BSC1L-specific domain; and (c) C-terminal AAA-ATPase domain. The interactions between TMD/MTS and BCS1L assist in anchoring proteins within the mitochondrial matrix for subsequent transport ( 45 , 46 )。Mutations in BCS1L are commonly associated with defects in human mitochondrial complex III ( 47 ), where mutated BCS1L protein disrupts complex III assembly, reduces mitochondrial electron transport chain activity, impairs ATP synthesis, and increases reactive oxygen species production( 48 ), thereby causing damage to cellular components that accelerates aging. In addition to various diseases such as sensorineural hearing loss (Bjornstad syndrome) and severe multisystem organ failure (Complex III deficiency and GRACILE syndrome), mutations in BCS1L also lead to features related to central nervous system dysfunction including movement disorders, seizures, and clinical manifestations resembling Leigh's encephalopathy( 49 ). Furthermore, BCS1L is involved in regulating mitochondrial autophagy; its dysfunction affects damaged mitochondria clearance leading to dysfunctional organelle accumulation which can contribute to cell senescence ( 44 ). NADH:ubiquinone oxidoreductase core subunit S1 (NDUFS1) is the largest subunit within mitochondrial complex I, responsible for catalyzing the initial step of respiratory nicotinamide adenine dinucleotide (NADH) oxidation in mitochondria. It plays a pivotal role in maintaining the stability and functionality of mitochondrial complex I ( 50 ).Deletion or mutation of NDUFS1 results in reduced levels and catalytic activity of mitochondrial complex I, disrupting NADH homeostasis and impeding electron transfer within the respiratory chain. Consequently, this leads to substantial intracellular reactive oxygen species (ROS) production( 51 ),impaired mitochondrial function, and ultimately accelerates cellular aging processes. Furthermore, deficiency in NDUFS1 causes loss of mitochondrial complex I, contributing to Leigh encephalopathy ( 52 ). Additionally, studies have suggested that mutations in Ndufs1 may be associated with Parkinson's disease and can serve as diagnostic markers for its detection( 53 ). A Danish cohort study has also demonstrated that NDUFS1 reflects physical conditions among elderly individuals by correlating with grip strength and walking speed( 54 ). Conclusion In summary, this study identified 503 differentially expressed genes in age-related hearing loss using bioinformatics tools. Among them, 28 differentially expressed mtDNA were further associated with the mitochondrial function database. Subsequently, three hub genes (Aco2, Bcs1l, and Ndufs1) involved in mitochondrial function injury were discovered. The expression of these three genes was found to be decreased in the hair cells of ARHL. Investigating the role of ACO2, BCS1L, and NDUFS1 in the ARHL process is crucial for understanding its mechanism and developing related therapeutic approaches. The integrity of mitochondrial function and disruption of homeostasis are important mechanisms underlying hair cell senescence and play a significant role in the occurrence and progression of age-related hearing loss. This study provides valuable insights into the pathogenesis of ARHL and offers an important target for understanding its pathogenesis as well as developing treatment strategies. Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials The datasets generated and/or analysed during the current study are available in the GEO public database (https://www.ncbi.nlm.nih.gov/geo/) and Mouse MitoCarta 3.0 database (https://personal.broadinstitute.org/scalvo/MitoCarta3.0/mouse.mitocarta3.0.html). The data that support the findings of this study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests Funding Tianyu Ma receives the Heilongjiang Provincial Nature Foundation(YQ2022H013) and Innovation Program of the First Hospital of Harbin Medical University. Mengting Liu receives funding from Postdoctoral Program in Heilongjiang Province (LBH-Z23220) and Innovation Program of Harbin Medical University. Tianhong Zhang receives funding from Key Research and Development program of Heilongjiang Province (2023ZX06C07) . Authors’ Contribution Tianhong Zhang is the corresponding author, and she contributes to the conception of the study. Tianyu Ma contributes to design. Xiaoyun Zeng complete the bioinformatics analysis. Mengting Liu, Shijia Xu contribute to the experiment in vitro. Yuyao Wang and Qilong Wu contribute to data analysis and interpretation. 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Impaired energy metabolism in a Drosophila model of mitochondrial aconitase deficiency. Biochem Biophys Res Commun. 2013;433(1):145–50. Beinert H, Kennedy MC. Aconitase, a two-faced protein: enzyme and iron regulatory factor. Faseb j. 1993;7(15):1442–9. Poon HF, Shepherd HM, Reed TT, Calabrese V, Stella AM, Pennisi G, et al. Proteomics analysis provides insight into caloric restriction mediated oxidation and expression of brain proteins associated with age-related impaired cellular processes: Mitochondrial dysfunction, glutamate dysregulation and impaired protein synthesis. Neurobiol Aging. 2006;27(7):1020–34. Mangialasche F, Baglioni M, Cecchetti R, Kivipelto M, Ruggiero C, Piobbico D, et al. Lymphocytic mitochondrial aconitase activity is reduced in Alzheimer's disease and mild cognitive impairment. J Alzheimers Dis. 2015;44(2):649–60. Zhu J, Xu F, Lai H, Yuan H, Li XY, Hu J, et al. 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Cellular pathophysiological consequences of BCS1L mutations in mitochondrial complex III enzyme deficiency. Hum Mutat. 2010;31(8):930–41. Baker RA, Priestley JRC, Wilstermann AM, Reese KJ, Mark PR. Clinical spectrum of BCS1L Mitopathies and their underlying structural relationships. Am J Med Genet A. 2019;179(3):373–80. Stan T, Brix J, Schneider-Mergener J, Pfanner N, Neupert W, Rapaport D. Mitochondrial protein import: recognition of internal import signals of BCS1 by the TOM complex. Mol Cell Biol. 2003;23(7):2239–50. Brischigliaro M, Frigo E, Corrà S, De Pittà C, Szabò I, Zeviani M, et al. Modelling of BCS1L-related human mitochondrial disease in Drosophila melanogaster. J Mol Med (Berl). 2021;99(10):1471–85. Hinson JT, Fantin VR, Schönberger J, Breivik N, Siem G, McDonough B, et al. Missense mutations in the BCS1L gene as a cause of the Björnstad syndrome. N Engl J Med. 2007;356(8):809–19. Hikmat O, Isohanni P, Keshavan N, Ferla MP, Fassone E, Abbott MA, et al. Expanding the phenotypic spectrum of BCS1L-related mitochondrial disease. Ann Clin Transl Neurol. 2021;8(11):2155–65. Hirst J. Mitochondrial complex I. Annu Rev Biochem. 2013;82:551–75. Hoefs SJ, Skjeldal OH, Rodenburg RJ, Nedregaard B, van Kaauwen EP, Spiekerkötter U, et al. Novel mutations in the NDUFS1 gene cause low residual activities in human complex I deficiencies. Mol Genet Metab. 2010;100(3):251–6. Tuppen HA, Hogan VE, He L, Blakely EL, Worgan L, Al-Dosary M, et al. The p.M292T NDUFS2 mutation causes complex I-deficient Leigh syndrome in multiple families. Brain. 2010;133(10):2952–63. Chi J, Xie Q, Jia J, Liu X, Sun J, Deng Y, et al. Integrated Analysis and Identification of Novel Biomarkers in Parkinson's Disease. Front Aging Neurosci. 2018;10:178. Dato S, Soerensen M, Lagani V, Montesanto A, Passarino G, Christensen K, et al. Contribution of genetic polymorphisms on functional status at very old age: a gene-based analysis of 38 genes (311 SNPs) in the oxidative stress pathway. Exp Gerontol. 2014;52:23–9. Additional Declarations No competing interests reported. Supplementary Files supFigure1.jpg supFigure2.jpg supFigure3.jpg supFigure4.jpg supplementaryFigurelegend.docx Cite Share Download PDF Status: Published Journal Publication published 05 Mar, 2025 Read the published version in BMC Genomics → Version 1 posted Editorial decision: Revision requested 09 Dec, 2024 Reviewers agreed at journal 04 Dec, 2024 Reviews received at journal 03 Dec, 2024 Reviewers agreed at journal 01 Dec, 2024 Reviews received at journal 11 Jun, 2024 Reviewers agreed at journal 02 Jun, 2024 Reviewers invited by journal 01 Jun, 2024 Editor invited by journal 31 May, 2024 Submission checks completed at journal 27 May, 2024 Editor assigned by journal 27 May, 2024 First submitted to journal 23 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4465565","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":309516184,"identity":"97e9f402-2bee-4b10-b4ee-869b0b547d25","order_by":0,"name":"Tianyu ma","email":"","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Tianyu","middleName":"","lastName":"ma","suffix":""},{"id":309516185,"identity":"a9d0ad38-1af8-4aab-afa0-bbfc7b9db2ed","order_by":1,"name":"Xiaoyun Zeng","email":"","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyun","middleName":"","lastName":"Zeng","suffix":""},{"id":309516186,"identity":"a79f3a92-efc9-4e20-867a-09eccea9ce37","order_by":2,"name":"Mengting Liu","email":"","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mengting","middleName":"","lastName":"Liu","suffix":""},{"id":309516187,"identity":"0a85a894-89d6-4ab4-960c-b2ef9f59cdaf","order_by":3,"name":"Shijia Xu","email":"","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shijia","middleName":"","lastName":"Xu","suffix":""},{"id":309516188,"identity":"e89c40db-0731-45d3-ae2b-38918ee58897","order_by":4,"name":"Yuyao Wang","email":"","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuyao","middleName":"","lastName":"Wang","suffix":""},{"id":309516189,"identity":"b4a78be3-3b29-4218-a4fa-5b8472a3718f","order_by":5,"name":"Qilong Wu","email":"","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qilong","middleName":"","lastName":"Wu","suffix":""},{"id":309516190,"identity":"3dc628e4-620f-45d8-a299-51bf2df33a0e","order_by":6,"name":"Tianhong Zhang#","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwUlEQVRIiWNgGAWjYFACHuYHH//YyLGxNx8gUgcbD5vhzIY0Yz6eYwlEa2GQ5m04lDhPIkeBOB3y83sPGM7ccSC9jSGHgeFHxTbCWhjb+BIefDxzJ7eN4ewBxp4ztwlrYWbjMTCcwfYst42xL4GZsY0ILWxALdI8bIfT2Zh5DIjTwgPSwtt2OAGklzgtEmw5ZoYzzqQZtvGwJRwkyi/yzWeMH3yosJGXn//44IMfFURoQQEHSFQ/CkbBKBgFowAXAACZUjmOnhY+NAAAAABJRU5ErkJggg==","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":true,"prefix":"","firstName":"Tianhong","middleName":"","lastName":"Zhang#","suffix":""}],"badges":[],"createdAt":"2024-05-23 08:55:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4465565/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4465565/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12864-025-11287-5","type":"published","date":"2025-03-05T15:58:21+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57945548,"identity":"752dfe63-34d5-477f-a38a-cae6d20ecca1","added_by":"auto","created_at":"2024-06-07 19:41:57","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51926,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of multi-step analysis based on bioinformatics data\u003c/p\u003e","description":"","filename":"Figure1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4465565/v1/e959e69ee669388ef3838f34.jpeg"},{"id":57945274,"identity":"3498029c-2d2a-42fd-9d3b-e688fa159c2b","added_by":"auto","created_at":"2024-06-07 19:33:57","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":74453,"visible":true,"origin":"","legend":"\u003cp\u003eDifferentially expressed genes in ARHL .Volcano map of differentially expressed genes in ARHL obtained through database analysis.\u003c/p\u003e","description":"","filename":"figure2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4465565/v1/1fb33ce31a1e242623eccfbe.jpeg"},{"id":57945276,"identity":"65994c32-73c2-475b-a7a0-10f8f3f4b62a","added_by":"auto","created_at":"2024-06-07 19:33:57","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":99721,"visible":true,"origin":"","legend":"\u003cp\u003e28 differentially expressed mitochondrial genes were found. A. The differentially expressed genes in ARHL interacted with mitochondrial genes, resulting in the identification of 28 differentially expressed mitochondrial genes. B-D, GO analysis was performed on the differentially expressed mitochondrial genes, leading to the enrichment results of molecular functions, biological processes, and cell components. E. Pathway results were obtained through KEGG enrichment.\u003c/p\u003e","description":"","filename":"Figure3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4465565/v1/7f28d992b8214c2bfbad66f3.jpeg"},{"id":57945550,"identity":"ca938841-205c-4b16-9a66-fe2963134a08","added_by":"auto","created_at":"2024-06-07 19:41:57","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":88321,"visible":true,"origin":"","legend":"\u003cp\u003eA total of 10 pivotal genes and 3 hub genes were identified. A. PPI network analysis chart. B. Identify 10 pivotal genes, among which aco2, ndufs1 and bcs1l are hub genes\u003c/p\u003e","description":"","filename":"Figure4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4465565/v1/54fabb59609bb08a93be6c9c.jpeg"},{"id":57945279,"identity":"fee10351-9bb9-4193-84fb-9c54685384ad","added_by":"auto","created_at":"2024-06-07 19:33:57","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":121085,"visible":true,"origin":"","legend":"\u003cp\u003eThe level of ACO2、NDUFS1 and BCS1L in aging hair cells are downregulated. A-C.results of immunofluorescence. D. results of Western blot. Full-length blots/gels are presented in Supplementary Figure 1-4.\u003c/p\u003e","description":"","filename":"Figure5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4465565/v1/018475a1271e6a2d6c888332.jpeg"},{"id":78190734,"identity":"a1f453a2-4061-4975-9818-6a1cb1a4bc7c","added_by":"auto","created_at":"2025-03-10 19:50:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1424859,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4465565/v1/94ad3df7-d6a5-4449-9645-5ddadc7e7ff3.pdf"},{"id":57945282,"identity":"ef74524d-4e3f-4098-a206-10cccff991df","added_by":"auto","created_at":"2024-06-07 19:33:58","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":351710,"visible":true,"origin":"","legend":"","description":"","filename":"supFigure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4465565/v1/ec17529085551d5b07f13826.jpg"},{"id":57945549,"identity":"b22f8b27-5489-4326-a81f-fb365c1cbb1e","added_by":"auto","created_at":"2024-06-07 19:41:57","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":319456,"visible":true,"origin":"","legend":"","description":"","filename":"supFigure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4465565/v1/3acdf8febbbb4e70bad560c9.jpg"},{"id":57945551,"identity":"dd160a74-b78c-46ce-9fc9-5aa236565847","added_by":"auto","created_at":"2024-06-07 19:41:58","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":348443,"visible":true,"origin":"","legend":"","description":"","filename":"supFigure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4465565/v1/3b1894caa3aef2bd006e3b32.jpg"},{"id":57945277,"identity":"f175cb16-4f8a-4914-83a6-7d6cdead8e5e","added_by":"auto","created_at":"2024-06-07 19:33:57","extension":"jpg","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":237017,"visible":true,"origin":"","legend":"","description":"","filename":"supFigure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4465565/v1/66ed35ec78a4cfc16e47bd8e.jpg"},{"id":57945281,"identity":"23247895-da18-4e38-9beb-816fb91c0616","added_by":"auto","created_at":"2024-06-07 19:33:57","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":14854,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryFigurelegend.docx","url":"https://assets-eu.researchsquare.com/files/rs-4465565/v1/bf660532c24533eb7e2bcdee.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis and identification of mitochondrial DNA associated with age-related hearing loss","fulltext":[{"header":"Background","content":"\u003cp\u003eAge-related hearing loss (ARHL) is a degenerative condition affecting the cochlea and vestibule, commonly associated with aging (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), It is characterized by progressive and irreversible bilateral symmetrical sensorineural hearing impairment. Deafness can result in diminished social functioning, heightened risk of dementia, anxiety, and depression among older individuals, significantly jeopardizing their physical and mental well-being while imposing a substantial burden on both families and society(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)。Due to the unknown etiology of ARHL, treatment primarily relies on hearing aids as there are currently no effective preventive or therapeutic measures available. Recent research advancements have suggested that mitochondrial homeostasis imbalance may be implicated in the development of ARHL(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)。\u003c/p\u003e \u003cp\u003eThe homeostasis of mitochondria in cells is achieved through division and fusion, ensuring the normal functioning of mitochondria, which primarily relies on mitochondrial DNA (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)。Within cells, mitochondria play a crucial role in regulating oxidative metabolism and serve as the primary source of Reactive Oxygen Species (ROS). Mitochondrial dysfunction serves as an indicator of cellular aging. Excessive ROS production during cellular aging results in the loss of mitochondrial membrane potential, an increase in mitochondrial mass, alterations to the mitochondrial respiratory complex, release of cytochrome C, reduction in mitochondrial transcription factor A levels, and an accumulation of fragmented mitochondrial DNA. These events ultimately lead to impaired mitochondrial function and subsequent activation of the apoptotic pathway within mitochondria,which lead to cell senescence and death (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)。Among these factors influencing ROS production or deficiency regulation lies mitochondrial DNA - a pivotal target for excessive ROS (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)。Mutations and deletions within mitochondrial DNA can induce apoptosis and contribute to age-related diseases (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)。To date, over 150 mtDNA deletions associated with various diseases have been identified through the Mitomap database dedicated to studying the human mitochondrial genome (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.mitomap.org\u003c/span\u003e\u003cspan address=\"http://www.mitomap.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)。\u003c/p\u003e \u003cp\u003eCurrently, there is no definitive conclusion regarding the alterations and impacts of mitochondrial DNA in the onset and progression of ARHL. However, the significant role of mitochondrial DNA in cellular aging has compelled researchers to give it due attention. In this study, we employed bioinformatics methods to investigate the pivotal mitochondrial DNA factors influencing ARHL. Our findings indicate that ACO2, BCS1L, and Ndufs1 are key mitochondrial genes associated with ARHL, which were further validated through in vitro experiments.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCollection and acquisition of gene chip data\u003c/h2\u003e \u003cp\u003eAccess the GEO public database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/geo/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)and download the GSE49543 dataset of gene chip raw data for research purposes. The GSE49543 dataset comprises gene sequencing data from the cochlea of 40 presbycusis mice, obtained using the GPL339 platform (MOE430A) Affymetrix array. The GEO2R online tool was utilized to standardize the microarray data from the GSE49543 dataset, and a total of 13661 differentially expressed genes (ARHL-DEGs) were identified using ggplot2 package analysis with a significance threshold of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eFor further investigation, we downloaded Mouse MitoCarta3.0 from Broad Institute's MitoCarta 3.0 database - an inventory of mammalian mitochondrial proteins and pathways that includes a list of 1,136 human and 1,140 mouse protein-coding genes localized on mitochondria(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This database provides information on submitochondrial localization, pathway annotation, and assigns genes to 149 mitochondrial terms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eValidation of key genes\u003c/h2\u003e \u003cp\u003eThe accuracy of key genes identified from the GSE49543 dataset was validated using the GEO database. R software (version 4.1.3; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.org/\u003c/span\u003e\u003cspan address=\"https://www.r-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is a programming language utilized for statistical analysis, graphical visualization, and reporting purposes. The data set was normalized using the \"limma\" package of R software, and Wilcoxon tests were employed (* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The ggplot2 data package was utilized to standardize the microarray data from the GSE49543 dataset, resulting in the identification of differential genes. Subsequently, we employed Sangerbox, a web-based platform for clinical health analysis (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://vip.sangerbox.com)(14)\u003c/span\u003e\u003cspan address=\"http://vip.sangerbox.com)(14)\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, to generate a volcano plot.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDifferential expression analysis of mitochondria-related genes\u003c/h2\u003e \u003cp\u003eThe intersection genes between the identified differentially expressed genes and mitochondrial genes were selected. A Venn diagram was generated using the \"VennDiagram package\" in R software to visually represent the number of differentially expressed genes (DE-MFRGS) associated with senior-onset deafness.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eGO analysis\u003c/h2\u003e \u003cp\u003eGene Ontology (GO) is an internationally recognized standard classification system for gene function. GO analysis, a bioinformatics method available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://geneontology.org/\u003c/span\u003e\u003cspan address=\"https://geneontology.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, involves categorizing genes or proteins based on their biological functions through the analysis of biological data(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). This provides a crucial theoretical framework for conducting research in biology. GO comprises three ontologies that describe the molecular function (MF), biological process (BP), and cellular component (CC) of a gene. The fundamental unit of GO is a gene set or term, which refers to a group of genes with similar biological processes and metabolic pathways located within the same signaling pathway. Each term corresponds to an attribute representing either a functional category or cell localization.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eKEGG analysis\u003c/h2\u003e \u003cp\u003eKEGG analysis, the Kyoto Encyclopedia of Genes and Genomes, was established in 1995 by the Kanehisa Laboratory of the Bioinformatics Center at Kyoto University, Japan(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). It is widely recognized as one of the most extensively utilized biological information databases worldwide. KEGG (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genome.jp/kegg/\u003c/span\u003e\u003cspan address=\"https://www.genome.jp/kegg/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) serves as a comprehensive resource for exploring advanced features and understanding biological systems such as cells, organisms, and ecological systems. It particularly focuses on molecular-level information derived from large-scale datasets generated through genome sequencing and other high-throughput experimental technologies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGSEA\u003c/h2\u003e \u003cp\u003eGene Set Enrichment Analysis (GSEA) is a computational method utilized to determine whether a predefined set of genes exhibits a statistically significant and consistent difference between two biological states(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The \"clusterProfiler package\" in the R language was employed for linking the gene set of GO functional terms and KEGG Pathway in GSEA analysis, while converting the gene expression profile into an expression matrix for GSEA analysis. Metascape (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://metascape.org/gp/index.html#/main/step1\u003c/span\u003e\u003cspan address=\"http://metascape.org/gp/index.html#/main/step1\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is a web tool that offers gene enrichment analysis, protein interaction network analysis, and other functionalities. This website integrates over 40 gene functional annotation databases and also provides various visualizations(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eConstruction of PPI network and identification of hub gene\u003c/h2\u003e \u003cp\u003eThe Protein-Protein Interaction Networks (PPI) were constructed using the STRING online database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cn.string-db.org/)(20)\u003c/span\u003e\u003cspan address=\"https://cn.string-db.org/)(20)\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Through the utilization of Cytoscape (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.statistical-analysis.top/Cytoscape)(21, 22)\u003c/span\u003e\u003cspan address=\"https://www.statistical-analysis.top/Cytoscape)(21, 22)\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, a software for biological network analysis and visualization, we performed an analysis on CytoHubba MCC to identify the top 10 genes in the PPI network, which were determined as key genes: Fdx1, Mrpl24 Mtif2, Arg2, Aco2 Ndufs1, Bcs1l, Ndufaf5, Nsun2, Sdhaf1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCell line\u003c/h2\u003e \u003cp\u003eIn this experiment, the mouse cochlea hair cell immortal HEI-OC1 cell line, purchased from Ubigene Company, was cultured in Dulbecco's modified Eagle's culture medium (DMEM) (Gibco, USA) under humid conditions with 5% CO2 at 37℃. The culture medium was supplemented with 10% fetal bovine serum (FBS) (ExCell, CHINA) and 100 U/ml penicillin/streptomycin (Gibco, USA). To induce aging in the cells, they were treated with D-galactose (Solebol, China) at a concentration of 30mg/ml for 72 hours.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eWestern blot\u003c/h2\u003e \u003cp\u003eHEI-OC1 cells were lysed with RIPA buffer containing PMSF and protease inhibitor, and the protein concentration was determined using the BCA method. 20 \u0026micro;g of protein were separated by 12% SDS-PAGE and transferred onto a PVDF membrane, followed by overnight incubation with specific primary antibodies at 4℃. Immunoreactive bands were detected using chemiluminescence. Antibodies used included anti-ACO2 (proteintech, China), anti-BCS1L (proteintech, China), anti-NDUSF1 (proteintech, China), and anti-GAPDH (proteintech, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence\u003c/h2\u003e \u003cp\u003eThe cells were seeded onto small glass slides and subsequently subjected to the corresponding treatments. After fixation with 4% PFA for 30 minutes, permeabilization was achieved by incubating the cells with 0.5% Triton X-100 for 30 minutes. Subsequently, blocking was performed using 5% BSA for 1 hour. The cells were then incubated overnight at 4℃ with the primary antibody specific to their target protein. On the following day, fluorescently labeled secondary antibodies and DAPI were applied to stain the nuclei of the cells. Finally, immunofluorescence analysis was conducted under a fluorescence microscope.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eA total of 503 differentially expressed genes associated with ARHL were identified\u003c/h2\u003e \u003cp\u003eA total of 503 differentially expressed genes (ARHL-DEGs) were identified using the R language package \"limma (v3.48.3)\"(Fig.\u0026nbsp;2). 233 genes exhibited upregulation with a conditional logFC\u0026thinsp;\u0026gt;\u0026thinsp;0 threshold, while 270 genes showed downregulation with a logFC\u0026thinsp;\u0026lt;\u0026thinsp;0 threshold.\u003c/p\u003e \u003cp\u003eThrough the enrichment analysis of differentially expressed genes, it was determined that these genes were associated with mitochondrial function. The clusterProfiler software package was utilized to analyze the differential gene expression in ARHL, resulting in 659 significant GO terms and 35 KEGG pathways (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The identified biological processes primarily encompassed mitochondrial respiratory chain complex assembly, small molecule catabolism process, NADH dehydrogenase complex assembly, organic acid catabolism process, generation of precursor metabolites and energy, mitochondrial transmembrane transport, and reactive oxygen species metabolic process(Table\u0026nbsp;1). Cellular components included integral component of mitochondrial membrane, mitochondrial matrix, extracellular exosomes, integral component of organelle membrane, extracellular vesicle(Table\u0026nbsp;2༉. Molecular functions comprised iron-sulfur cluster binding, metal cluster binding mRNA methyltransferase activity ,2-sulfur cluster binding, tRNA methyltransferase activity, carboxylic ester hydrolase activity,and lyase activity(Table\u0026nbsp;3). KEGG pathway analysis revealed involvement in Biosynthesis of amino acids, biosynthesis of unsaturated fatty acids, peroxisome,carbon metabolism,and primary bile acid biosynthesis(Table\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eTable 1. GO analysis: Biological Processes (Top 10）\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1717788573.png\" alt=\"image\" style=\"width: 687px;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. GO analysis: Cellular Components (Top 10）\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img171778857337.png\" alt=\"image\" style=\"width: 709px;\"\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3. GO analysis: Molecular Function (Top 10) \u003cimg src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1717788574.png\" alt=\"image\" style=\"width: 695px;\"\u003e\u003c/p\u003e\n\u003cp\u003eTable 4. KEGG enrichment pathway analysis (Top 10) \u003cimg src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img171778857399.png\" alt=\"image\" style=\"width: 748px;\"\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eA total of 28 mitochondrial genes were differentially expressed\u003c/h2\u003e \u003cp\u003eWe observed a strong association between gene enrichment results and mitochondria, thus we integrated these 503 differential genes with mitochondrial genes to identify the differentially expressed genes related to mitochondria. A total of 28 differentially expressed mitochondrial genes (DE-MFRGS) associated with ARHL were analyzed using Venn mapping software package (1.7.1) (Fig.\u0026nbsp;3A).\u003c/p\u003e \u003cp\u003eThe Metascape tool was utilized to perform enrichment analysis on these 28 differentially expressed mitochondrial genes, using the following criteria: Min Overlap\u0026thinsp;\u0026le;\u0026thinsp;3, P Value Cutoff\u0026thinsp;\u0026le;\u0026thinsp;0.01, and Min Enrichment\u0026thinsp;\u0026le;\u0026thinsp;1.5. The results were visualized in a bar chart. We observed that NDUFS1, FDX1, ACO2, ALDH2, NDUFAF5, HSD17B4 and AASS were significantly enriched in iron-sulfur cluster binding at the molecular function. Additionally, ALDH2, ACOT7 and ABHD10 exhibited enrichment in catalytic activity, acting on a tRNA. METTL8, NSUN2, NDUFAF5 and GARS1 showed enrichment in carboxylic ester hydrolase activity while CLYBL, ACO2 and HSD17B4 demonstrated enrichment in lyase activity (Fig.\u0026nbsp;3B). In terms of biological processes, GTP2, ARG2, AASS, HSD17B4, AcoT7, ALDH2, NUDT5 and GARS1 are involved in small molecule catabolic process. NDUFAF5, NDUFS1, BCS1L, SLC25A33, SDHAF1 and RHOT1 contribute to the assembly of mitochondrial respiratory chain complex assembly. ACOT7,HSD17B4,AASS ,NDUFS1 ,NUDT5,GARS1 and CKMT1B play a role in mitochondrial gene expression. SLC25A33,SFXN1,SFXN4 and RHOT participate in nucleotide metabolism. ALDH2 ,FDX1 ,ACO2,and NDUFS participate in the electron transport chain; METTL8 ,NSUN2,GARS,and NDUFAF5 are involved tRNA metabolism (Fig.\u0026nbsp;3C). In terms of cell components, SDHAF1 MRPL24, NDUFS1, ARG2, GARS1, GPT2, FDX1, ABHD10, AASS, ALDH2, AC02 participated in the composition of mitochondrial membrane. NDUFS1, MRPL24, BCS1L, SLC25A33, SFXN1, NDUFAF5, CKMT1B, SFXN4, RHOT1 SLC30A9 participate in the formation of mitochondrial matrix(Fig.\u0026nbsp;3D). KEGG analysis showed that ALDH2, CKMT1B and ARG2 were involved in the metabolic pathways of arginine and proline. ARG2, AC02 and GPT2 participate in the metabolic pathway of amino acids (Fig.\u0026nbsp;3E).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eThree crucial mitochondrial genes were identified\u003c/h2\u003e \u003cp\u003eA network diagram depicting protein interactions of differentially expressed mitochondrial genes was constructed using the STRING database. Subsequently, a network clustering module comprising 28 nodes and 17 edges was obtained (Fig.\u0026nbsp;4A). Next, Cytoscape's CytoHubba MCC software plugin was employed for analysis, leading to the identification of ten top hub genes: Fdx1, Mrpl24, Mtif2, Arg2, Aco2, Ndufs1, Bcs1l, Ndufaf5, Nsun2, and Sdhaf1. Notably among them are Aco2, Bcs1l and Ndufs1 which occupy central positions within the module and serve as hub genes associated with ARHL (Fig.\u0026nbsp;4B). Furthermore,the expression levels of these three hub genes exhibit significant downregulation in ARHL.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eThe expression of Aco2, Bcs1l and Ndufs1 decreased in senescent hair cells\u003c/h2\u003e \u003cp\u003eIn order to validate the conclusion derived from the aforementioned analysis, we conducted cell experiments to corroborate it. Specifically, we performed in vitro experiments using the hair cell immortal cell line HEI-OC1 and exposed the cells to D-galactose at a concentration of 30mg/ml for 72 hours to simulate senescent hair cells. Subsequently, we assessed the levels of three hub genes through immunofluorescence and Western blot techniques. Our findings revealed a significant downregulation in the expression levels of Aco2, Bcs1l, and Ndufs1 in aging hair cells compared to the control group(Fig.\u0026nbsp;5).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAccording to previous speculation,age-related hearing loss is primarily attributed to the degeneration of Stira vascularis (SV), which plays a crucial role in maintaining the electrical potential of the inner ear and facilitating the conversion of mechanical signals into electrical signals in the cochlea. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)。Recent research has identified that cochlear hair cells (HC) are pivotal in determining ARHL. In their autopsy study involving 120 cadaver patients, Liberman et al. observed a significant correlation between hair cell loss and the extent of hearing damage, while stira vascularis were found to be unrelated to hearing damage levels. This groundbreaking study provided novel insights into the key component responsible for ARHL within human cochlea(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCochlear hair cells are highly energy-consuming cells, primarily relying on the oxidative phosphorylation process of mitochondria for their energy source(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).Mitochondria in hair cells maintain homeostasis through division and fusion, thereby ensuring normal mitochondrial function. In hair cells, mitochondria play a crucial role in regulating oxidative metabolism and generating Reactive Oxygen Species (ROS). The aging of hair cells is characterized by the accumulation of oxidative damage caused by ROS buildup, with mitochondria being the primary site of ROS-induced cellular damage (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Additionally, mitochondria are involved in various other processes such as signaling, cell differentiation, and regulation of the cell cycle and growth (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). During the aging process of cochlear hair cells, disturbances in mitochondrial homeostasis lead to mitochondrial dysfunction (MD), resulting in alterations in intracellular REDOX levels and subsequent cell death(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe human mitochondrial genome is a circular, double-stranded, supercoiled molecule with one to several thousand copies per cell consisting of 16,569 bases (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e)。Although mitochondrial genes are also protected by proteins, their protective effect is significantly weaker than that of nuclear DNA, rendering them more susceptible to external genotoxic substances (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e)。Accumulation of ROS in hair cells also induces mutations in the mitochondrial genome, leading to damage in mitochondrial DNA. Mutation and deletion of mitochondrial mtDNA play a crucial role in hair cell senescence. Markaryan et al. discovered that cochlear tissues from elderly humans exhibited deficiency in 4977-bp mitochondria and and the probability of deficiency would increase with age (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)。Enhanced protection of mitochondrial DNA could be beneficial. Jun Li et al. utilized the DNA methylation inhibitor 5-azacytidine to reduce the methylation level of SOD2, thereby decreasing oxidative stress and copy number variations (CNVs) of mtDNA4834 mutations while inhibiting H2O2-induced apoptosis in hair cells (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)。Subsequently, more studies have confirmed the close association between mutation and deletion of mtDNA with age-related hearing loss (ARHL), suggesting an increased risk for ARHL due to its mutation (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e)。\u003c/p\u003e \u003cp\u003eA total of 503 DEGs were identified. KEGG pathway enrichment analysis revealed significant enrichment of DEGs in the oxidative phosphorylation signaling pathway, amino acid anabolic signaling pathway, ribosome signaling pathway, peroxisome signaling pathway, and other pathways associated with mitochondrial function. These findings suggest that alterations in these signaling pathways may contribute to mitochondrial dysfunction and subsequently induce ARHL. Following GO functional enrichment analysis of DEGs, Tables present the top ten entries for each of the three Go ontologies. BP primarily encompasses processes related to mitochondrial transmembrane transport, metabolic processes involving reactive oxygen species, assembly of mitochondrial respiratory chain complexes and genes expression within mitochondria, NADH dehydrogenase complex assembly, precursor metabolite and energy production as well as organic acid decomposition and small molecule metabolism. CC involves the formation of components such as mitochondrial membranes, mitochondrial matrixes, myelin sheaths, extracellular exosomes as well as complete components found in other organelle membranes including extracellular vesicles and organelles. MM molecules are involved in activities such as binding to 2- and 4-ferric sulfur clusters or metal clusters; mRNA/tRNA methyltransferase activity; catalytic activity; carboxylic ester hydrolase activity.\u003c/p\u003e \u003cp\u003eIn light of the strong correlation observed between these differential genes and mitochondrial function, we performed an intersection analysis with mitochondrial DNA to identify differentially expressed mitochondrial DNA associated with age-related hearing loss. Among them, Aco2, Bcs1l, and Ndufs1 emerged as three key hub genes closely linked to mitochondrial function.\u003c/p\u003e \u003cp\u003eMitochondrial aconitase 2 (ACO2) belongs to the iron-sulfur cluster hydratase family. Upon binding to the enzyme structure, the active iron-sulfur cluster catalyzes citric acid reversibly into isocitrate in the TCA cycle and facilitates dehydration and rehydration reactions (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Aco2 is an indispensable enzyme in the tricarboxylic acid cycle, playing a crucial role in coordinating mitochondrial and autophagy functions for energy metabolism within cellular mitochondrial respiratory chain. ACO2 significantly contributes to cellular energy metabolism, maintenance of iron homeostasis, resistance against oxidative stress, as well as preservation of mitochondrial DNA (mtDNA) integrity (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Research has indicated that mutations in the ACO2 gene may be associated with premature aging (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Furthermore, studies have demonstrated that ACO2 impacts neuronal function and survival during aging process, potentially contributing to Alzheimer's disease onset (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).Targeting ACO2 for enhancing energy metabolism could serve as a promising therapeutic strategy for Parkinson's disease and other neurodegenerative disorders(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e)。Currently, there are extensive reports on the involvement of ACO2 mutations in energy metabolism issues and progression of neurodegenerative diseases such as optic atrophy, microcephaly, intellectual impairment cognitive decline hypotonia spastic paraplegia(\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs a chaperone and translocation enzyme in the inner mitochondrial membrane, the BCS1L protein plays a crucial role in promoting the final folding and assembly of respiratory complex III by facilitating the insertion of the Rieske iron-sulfur subunit into the complex(\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). The functional structure of BCS1L consists of three distinct domains: (a) N-terminal domain comprising three special parts - transmembrane domain (TMD), mitochondrial targeting sequence (MTS), and input auxiliary sequence (IAS); (b) BSC1L-specific domain; and (c) C-terminal AAA-ATPase domain. The interactions between TMD/MTS and BCS1L assist in anchoring proteins within the mitochondrial matrix for subsequent transport (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e)。Mutations in BCS1L are commonly associated with defects in human mitochondrial complex III (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e), where mutated BCS1L protein disrupts complex III assembly, reduces mitochondrial electron transport chain activity, impairs ATP synthesis, and increases reactive oxygen species production(\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e), thereby causing damage to cellular components that accelerates aging. In addition to various diseases such as sensorineural hearing loss (Bjornstad syndrome) and severe multisystem organ failure (Complex III deficiency and GRACILE syndrome), mutations in BCS1L also lead to features related to central nervous system dysfunction including movement disorders, seizures, and clinical manifestations resembling Leigh's encephalopathy(\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). Furthermore, BCS1L is involved in regulating mitochondrial autophagy; its dysfunction affects damaged mitochondria clearance leading to dysfunctional organelle accumulation which can contribute to cell senescence (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNADH:ubiquinone oxidoreductase core subunit S1 (NDUFS1) is the largest subunit within mitochondrial complex I, responsible for catalyzing the initial step of respiratory nicotinamide adenine dinucleotide (NADH) oxidation in mitochondria. It plays a pivotal role in maintaining the stability and functionality of mitochondrial complex I (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e).Deletion or mutation of NDUFS1 results in reduced levels and catalytic activity of mitochondrial complex I, disrupting NADH homeostasis and impeding electron transfer within the respiratory chain. Consequently, this leads to substantial intracellular reactive oxygen species (ROS) production(\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e),impaired mitochondrial function, and ultimately accelerates cellular aging processes. Furthermore, deficiency in NDUFS1 causes loss of mitochondrial complex I, contributing to Leigh encephalopathy (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Additionally, studies have suggested that mutations in Ndufs1 may be associated with Parkinson's disease and can serve as diagnostic markers for its detection(\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). A Danish cohort study has also demonstrated that NDUFS1 reflects physical conditions among elderly individuals by correlating with grip strength and walking speed(\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, this study identified 503 differentially expressed genes in age-related hearing loss using bioinformatics tools. Among them, 28 differentially expressed mtDNA were further associated with the mitochondrial function database. Subsequently, three hub genes (Aco2, Bcs1l, and Ndufs1) involved in mitochondrial function injury were discovered. The expression of these three genes was found to be decreased in the hair cells of ARHL. Investigating the role of ACO2, BCS1L, and NDUFS1 in the ARHL process is crucial for understanding its mechanism and developing related therapeutic approaches. The integrity of mitochondrial function and disruption of homeostasis are important mechanisms underlying hair cell senescence and play a significant role in the occurrence and progression of age-related hearing loss. This study provides valuable insights into the pathogenesis of ARHL and offers an important target for understanding its pathogenesis as well as developing treatment strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available in the GEO public database (https://www.ncbi.nlm.nih.gov/geo/) and Mouse MitoCarta 3.0 database (https://personal.broadinstitute.org/scalvo/MitoCarta3.0/mouse.mitocarta3.0.html). The data that support the findings of this study are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTianyu Ma receives the Heilongjiang Provincial Nature Foundation(YQ2022H013) and Innovation Program of the First Hospital of Harbin Medical University. Mengting Liu receives funding from Postdoctoral Program in Heilongjiang Province (LBH-Z23220) and Innovation Program of Harbin Medical University. Tianhong Zhang receives funding from Key Research and Development program of Heilongjiang Province (2023ZX06C07) .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTianhong Zhang is the corresponding author, and she contributes to the conception of the study. Tianyu Ma contributes to design. Xiaoyun Zeng complete the bioinformatics analysis. Mengting Liu, Shijia Xu contribute to the experiment in vitro. Yuyao Wang and Qilong Wu contribute to data analysis and interpretation. All authors contributes to the writing of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHearing loss prevalence. and years lived with disability, 1990\u0026ndash;2019: findings from the Global Burden of Disease Study 2019. 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Exp Gerontol. 2014;52:23\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"ARHL, mtDNA, Mitochondrial homeostasis","lastPublishedDoi":"10.21203/rs.3.rs-4465565/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4465565/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTo explore the mitochondrial genes that play a key role in the occurrence and development of age-related hearing loss(ARHL), provide a basis for the study of the mechanism of ARHL.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 503 differentially expressed genes (DEGs) were detected in the GSE49543 dataset,233 genes were up-regulated and 270 genes were down-regulated. There are a total of 1140 genes in the mitochondrial gene bank and 28 DE-MFRGS related to ARHL. These genes are mainly involved in mitochondrial respiratory chain complex assembly, small molecule catabolism, NADH dehydrogenase complex assembly, organic acid catabolism, precursor metabolites and energy production, and mitochondrial span Membrane transport, metabolic processes of active oxygen species. Then, the three key genes were identified by Cytoscape software :Aco2,Bcs1l and Ndufs1. Immunofluorescence and Western blot experiments confirmed that the protein content of three key genes in aging cochlear hair cells decreased.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eWe employed bioinformatics analysis to screen 503 differentially expressed genes and identified three key genes associated with ARHL. Subsequently, we conducted in vitro experiments to validate their significance, thereby providing a valuable reference for further elucidating the role of mitochondrial function in the pathogenesis and progression of ARHL.\u003c/p\u003e","manuscriptTitle":"Analysis and identification of mitochondrial DNA associated with age-related hearing loss","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-07 19:33:52","doi":"10.21203/rs.3.rs-4465565/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-09T10:49:52+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"190870449920703488880924697831191396405","date":"2024-12-04T19:38:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-03T14:53:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"122306582545526168926982640596485130836","date":"2024-12-01T16:25:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-11T12:49:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6524562922336093813072941632331330112","date":"2024-06-02T04:08:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-01T12:08:09+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-31T10:05:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-27T10:40:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-27T10:40:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2024-05-23T08:53:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dec8e965-3948-45fd-84ca-456ba28bbafc","owner":[],"postedDate":"June 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-10T19:49:25+00:00","versionOfRecord":{"articleIdentity":"rs-4465565","link":"https://doi.org/10.1186/s12864-025-11287-5","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2025-03-05 15:58:21","publishedOnDateReadable":"March 5th, 2025"},"versionCreatedAt":"2024-06-07 19:33:52","video":"","vorDoi":"10.1186/s12864-025-11287-5","vorDoiUrl":"https://doi.org/10.1186/s12864-025-11287-5","workflowStages":[]},"version":"v1","identity":"rs-4465565","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4465565","identity":"rs-4465565","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}