Abstract
Introduction:
Several studies have reported a significant correlation between noise-induced hearing loss and cognitive decline. However, comprehensive analyses of this relationship are rare. This study aimed to assess the influence of hearing impairment on cognitive functions by analyzing organ samples in the afferent auditory pathway of deafened mice using mRNA sequencing.
Methods:
We prepared 10 female 12-week-old C57BL/6N mice as the experimental and control groups in equal numbers. Mice in the experimental group were deafened with 120 dB sound pressure level (SPL) wideband noise for 2 h. Cochlea, auditory cortex, and hippocampus were obtained from all mice. After constructing cDNA libraries for the extracted RNA from the samples, we performed next-generation sequencing. Subsequently, we analyzed the results using gene ontologies (GOs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases for differentially expressed genes (DEGs) of each organ.
Results:
Our results revealed 102, 89, and 176 DEGs for cochlea, auditory cortex, and hippocampus, respectively. We identified 294, 203, and 211 GOs; 10, 7, and 17 KEGG pathways in the cochlea, auditory cortex, and hippocampus, respectively. In the long term (12 weeks) from noise-induced hearing loss, GOs and KEGG pathways related to apoptosis or inflammation persisted more actively in the order of hippocampus, auditory cortex, and cochlea.
Discussion:
This implies that the neurodegenerative effects of noise exposure persist more longer time in the central regions.
Introduction
Dementia is one of the biggest global healthcare problems, affecting 55 million people worldwide (Gauthier et al., 2022). Since there is no effective disease-modifying treatment option for dementia progression (Tisher and Salardini, 2019), the prevention of early-stage cognitive decline seems more important. Notably, it has been reported that hearing loss is associated with dementia (Lin et al., 2011; Gurgel et al., 2014). As relevant studies progressed, hearing loss has been accepted as a major modifiable risk factor for dementia (Livingston et al., 2017). It is thought that hearing loss can lead to cognitive decline, which may then serve as a “second hit,” exacerbating dementia in the presence of organic brain pathology (Lin and Albert, 2014).
Several independent studies have suggested underlying mechanisms by which hearing impairment leads to cognitive decline. Some studies suggest that the increased cognitive demands resulting from hearing loss can evoke cognitive decline (Lin and Albert, 2014; Cardin, 2016). Other researchers suggest that the oxidative stress triggered by hearing loss may adversely affect the hippocampus by increasing neuroinflammation, accelerating apoptosis, and reducing neurogenesis (Gonzalez-Perez et al., 2011; Paciello et al., 2023). Abnormalities in the neurotransmitter system, such as the N-methyl-d-aspartic acid receptor 2B, have been reported to be related to cognitive decline (Cui et al., 2013). Disorders of Schaffer collateral-1 long-term potentiation through depressed levels of brain-derived neurotrophic factors due to high-intensity sound are known to cause cognitive decline (de Deus et al., 2021). Additionally, it has been proposed that stress hormones and corticosteroids produced in response to hearing loss-induced stress can impact neuronal function in the hippocampus, ultimately leading to cognitive decline (Jin et al., 2017; Kurioka et al., 2021).
These studies provide an overview of how hearing impairment affects cognitive function. However, it is difficult to draw a comprehensive explanation because each study reveals only discrete aspects of the phenomenon from the researcher's viewpoint. In this case, omics studies can provide a broader understanding. An omics study quantitatively analyzes the whole set of specific biomolecules, such as the genome, transcriptome, proteome, or metabolome, in a given time (Vailati-Riboni et al., 2017; Subedi et al., 2022). This enables us to obtain a balanced insight into complex genetic mechanisms. Gene expression patterns can be primarily understood by mRNA sequencing.
Recent studies using omics technologies have uncovered the hidden mechanisms of hearing loss progresses at the molecular level. A previous study showed that noise exposure immediately evokes global cochlear protein ubiquitylation and upregulates ribosomal proteins in the cochlea (Jongkamonwiwat et al., 2020). Another study found that acoustic trauma modulates the expression of inflammation- and immunity-related genes (Maeda et al., 2021; Miao et al., 2021). However, few omics studies have investigated the relationship between hearing loss and cognitive decline. A transcriptome-wide association study has shown that age-related hearing loss impairs the glutamatergic synapse pathway in the hippocampus of BXD-recombinant inbred mice (Deng et al., 2021). Except this, we could not find out any omics study on the relationship between hearing loss and cognitive decline.
From this perspective, the current study was designed to evaluate the impact of auditory impairment on cognitive functioning. This was achieved by analyzing tissue samples from key components of the afferent auditory pathway—specifically the cochlea, the auditory cortex, and the hippocampus—through mRNA sequencing techniques. The auditory cortex was selected for its critical role in the processing and interpretation of auditory signals. The hippocampus was included due to its integral function in spatial and episodic memory; noteworthily, hippocampal impairment has been identified as a hallmark feature in a range of cognitive disorders, including dementia (Nadhimi and Llano, 2021; Billig et al., 2022). Furthermore, we used gene ontologies (GOs) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases to examine the types of events that occur after noise-induced hearing loss.
Materials and methods
Animal management
Ten female C57BL/6N mice were used. To prevent sex act as a confounding factor, we used only female mice. Mice were placed in cage with freely access to distilled water and chow under pathogen free condition (12 h light/dark cycle, 23°C, 50% humidity). They were divided into experimental (n = 5) and control (n = 5) groups. Mice in the experimental group were deafened with a single exposure of 120 dB sound pressure level (SPL) wideband noise for 2 h in an audiometric booth at the age of 12 weeks. To confirm the audiometric state, we checked the hearing thresholds of both ears just before noise exposure, 2 weeks post-exposure, and at the age of 24 weeks just before sacrifice.
All experimental procedures were approved by the Institutional Animal Care and Use Committee (IACUC) of Boramae Hospital (IACUC number 2022-0133).
Tissue preparation
All the mice were sacrificed at 24 weeks of age. They were fully anesthetized by isoflurane inhalation in an airtight cage. Cardiac perfusion was performed using phosphate-buffered saline (PBS) to remove red blood cells from the tissues. After decapitation, we harvested the bilateral cochleae, auditory cortical areas, and hippocampus of each mouse by referencing an anatomy atlas (Franklin and Paxinos, 2013). All right and left specimens were combined into one sample for each mouse organ.
mRNA sequencing
The samples were lysed using the RNeasy Mini Kit (Qiagen, Germany) following the manufacturer's instructions for total RNA extraction. Total RNA quantity and quality were determined by UV/Vis spectrophotometer (NanoDrop 2000, ThermoFisher Scientific, USA). All RNA samples showed suitable A260/A280 and 28s/18s ratios. A cDNA library was subsequently constructed, and next-generation sequencing was performed. The entire NGS procedure was performed using an Illumina NovaSeq 6000 system (Macrogen, South Korea).
Statistical analysis on expressed genes
To reduce bias in the results, we conducted quality control analysis of the raw sequencing reads. This involved removing low-quality data, adaptor sequences, contaminant DNA, PCR duplicates, and other artifacts. After confirming all samples satisfied quality control criteria, we selected three sets out of five sets in analyzing samples of cochlea, auditory cortex, and hippocampus for experimental and control groups.
The preprocessed reads were then mapped to the reference genome using HISAT2 version 2.1.0 (https://ccb.jhu.edu/software/hisat2/index.shtml/) to generate aligned reads. Subsequently, transcript assembly was performed using StringTie version 2.1.3b (https://ccb.jhu.edu/software/stringtie/). Expression profiles were extracted through transcript quantification for each sample, and fragments per kilobase of transcript per million mapped reads (FPKM), reads per kilobase of transcript per million mapped reads (RPKM), and transcripts per kilobase million (TPM) values were calculated. Differentially expressed genes (DEGs) were selected using this process, and functional annotation and gene-set enrichment analyses were performed using the GOs and KEGG databases. We set |fold change| of ≥2.0 and p-value of < 0.05 as statistically significant. For the selection of differentially expressed genes (DEGs), we utilized the raw p-values obtained from the direct gene comparisons between control and experimental groups. In contrast, for the identification of GOs and KEGG pathways, we employed adjusted p-values derived from hypergeometric testing and multiple testing corrections to control the false discovery rate. The sample size was determined to ensure sufficient quantity, taking into account cell type, tissue specificity, and library preparation methods. Since all samples met the quality control standards, we required only three samples per group.
We used GOnet (https://tools.dice-database.org/GOnet/) and REVIGO (http://revigo.irb.hr/) to visualize the relationships among genes and their ontologies. In the GOnet, we performed “GO term annotation” analysis using “generic GO slim” subset. In the REVIGO, we set resulting list size as “medium,” and chose “SimRel” semantic similarity measure.
Results
Audiometric tests
Prior to noise exposure, all the mice exhibited normal hearing thresholds in both ears during the auditory brainstem response (ABR) tests using click, 8 and 16 kHz tone-burst sound. Two weeks after noise exposure, it was found that none of the mice in the experimental group had an ABR response to sound stimulations of 90 dB SPL in either ear. In contrast, all the mice in the control group maintained normal thresholds in both ears. The hearing status of all mice was assessed prior to sacrifice, and it was confirmed that there had been no changes since the last hearing test.
Data quality control
We excluded genes that were not detected in at least one of the 18 samples. Of the 45,777 genes detected, 27,122 were not detected in at least one sample and were excluded. Thus, 18,655 genes were analyzed in this study.
To reduce systemic bias in sample comparisons, we performed relative log-expression normalization prior to statistical analysis. The necessary size factor was estimated using the read count data. Additionally, we performed multidimensional scaling and hierarchical clustering analyses to check for the presence of outlier samples and similarity in expression patterns among biological replicates and confirmed that there were no discrepancies.
Differentially expressed genes
To compare the experimental and control groups, we used the up-regulated and down-regulated genes that were differentially expressed in each organ. In the cochlea, there were 57 up-regulated and 45 down-regulated DEGs, while in the auditory cortex, there were 62 up-regulated and 27 down-regulated DEGs. In the hippocampus, 141 DEGS were up-regulated, and 35 were down-regulated (Figure 1).
Figure 1

Number of DEGs for each organ. The numbers are calculated for the genes whose fold changes are >2 and raw p-values are within 0.05.
However, these results included not only protein-coding genes but also pseudogenes, lncRNAs, snoRNAs, and miRNAs. We excluded the non-protein-coding genes to determine the functions of the RNAs. When only the protein-coding genes were considered, the number of DEGs reduced. In the cochlea, there were 16 up-regulated and 32 down-regulated protein-coding DEGs (Table 1), while in the auditory cortex, there were 31 up-regulated and 21 down-regulated protein-coding DEGs (Table 2). In the hippocampus, 99 up-regulated and 15 down-regulated protein-coding DEGs were expressed (Table 3). In total, there are 146 up-regulated protein-coding DEGs and 68 down-regulated protein-coding DEGs (Figure 2). This transcriptomic data can be accessed in SRA database of NCBI site (reference number: PRJNA1061000).
Table 1
| Gene ID | Gene symbol | Description | Fold change (deaf/control) | Raw p-value (deaf/control) |
|---|---|---|---|---|
| a. Up-regulated genes | ||||
| 104362 | Meig1 | Meiosis expressed gene 1 | 2.72451 | 0.00115 |
| 15564 | Htr5b | 5-hydroxytryptamine (serotonin) receptor 5B | 2.55739 | 0.00696 |
| 217698 | Acot5 | Acyl-CoA thioesterase 5 | 2.53157 | 0.00317 |
| 100034363 | Tmsb15b2 | Thymosin beta 15b2 | 2.48637 | 0.00089 |
| 238680 | Cntnap3 | Contactin associated protein-like 3 | 2.47875 | 0.00331 |
| 20716 | Serpina3n | Serine (or cysteine) peptidase inhibitor, clade A, member 3N | 2.45358 | 0.00000 |
| 67483 | 1700028P14Rik | RIKEN cDNA 1700028P14 gene | 2.42483 | 0.01373 |
| 102633301 | Gm31160 | Predicted gene, 31160, transcript variant X5 | 2.38870 | 0.00004 |
| 277353 | Tcfl5 | Transcription factor-like 5 (basic helix-loop-helix) | 2.32988 | 0.00345 |
| 231727 | B3gnt4 | UDP-GlcNAc:betaGal beta-1,3-N-acetylglucosaminyltransferase 4 | 2.30858 | 0.00169 |
| 192164 | Pcdha12 | Protocadherin alpha 12 | 2.27350 | 0.00193 |
| 74369 | Mei1 | Meiotic double-stranded break formation protein 1 | 2.20177 | 0.00046 |
| 75040 | Efcab10 | EF-hand calcium binding domain 10 | 2.17077 | 0.00534 |
| 14038 | Wfdc18 | WAP four-disulfide core domain 18 | 2.13102 | 0.01006 |
| 21331 | T2 | Brachyury 2 | 2.12875 | 0.00004 |
| 74230 | 1700016K19Rik | RIKEN cDNA 1700016K19 gene | 2.09831 | 0.00397 |
| b. Down-regulated genes | ||||
| 57814 | Kcne4 | Potassium voltage-gated channel, Isk-related subfamily, gene 4 | −2.02804 | 0.01304 |
| 215418 | Csrnp1 | Cysteine-serine-rich nuclear protein 1 | −2.04434 | 0.00124 |
| 15936 | Ier2 | Immediate early response 2 | −2.05776 | 0.00506 |
| 57738 | Slc15a2 | Solute carrier family 15 (H+/peptide transporter), member 2 | −2.06791 | 0.00000 |
| 115488282 | LOC115488282 | Uncharacterized LOC115488282, transcript variant X1 | −2.08478 | 0.00443 |
| 74155 | Errfi1 | ERBB receptor feedback inhibitor 1 | −2.10587 | 0.00413 |
| 13537 | Dusp2 | Dual specificity phosphatase 2 | −2.12057 | 0.00014 |
| 320145 | Sp8 | Trans-acting transcription factor 8 | −2.12946 | 0.02599 |
| 16364 | Irf4 | Interferon regulatory factor 4 | −2.13488 | 0.00023 |
| 12014 | Bach2 | BTB and CNC homology, basic leucine zipper transcription factor 2 | −2.14126 | 0.00001 |
| 381823 | Apold1 | Apolipoprotein L domain containing 1 | −2.16870 | 0.03508 |
| 21334 | Tac2 | Tachykinin 2 | −2.17265 | 0.00348 |
| 19683 | Rdh16 | Retinol dehydrogenase 16 | −2.19381 | 0.01938 |
| 12702 | Socs3 | Suppressor of cytokine signaling 3 | −2.24148 | 0.00516 |
| 100037278 | Fam129c | Family with sequence similarity 129, member C | −2.27732 | 0.00000 |
| 17691 | Sik1 | Salt inducible kinase 1 | −2.29470 | 0.00112 |
| 22695 | Zfp36 | Zinc finger protein 36 | −2.44989 | 0.00618 |
| 12227 | Btg2 | B cell translocation gene 2, anti-proliferative | −2.45579 | 0.00008 |
| 637079 | Iqcn | IQ motif containing N | −2.46003 | 0.01062 |
| 18227 | Nr4a2 | Nuclear receptor subfamily 4, group A, member 2 | −2.52660 | 0.00069 |
| 83885 | Slc25a2 | Solute carrier family 25 (mitochondrial carrier, ornithine transporter) member 2 | −2.74525 | 0.03672 |
| 19252 | Dusp1 | Dual specificity phosphatase 1 | −2.80397 | 0.00000 |
| 16007 | Ccn1 | Cellular communication network factor 1 | −2.86252 | 0.01801 |
| 380728 | Kcnh4 | Potassium voltage-gated channel, subfamily H (eag-related), member 4 | −2.86412 | 0.00003 |
| 19373 | Rag1 | Recombination activating 1 | −2.97390 | 0.00000 |
| 16477 | Junb | Jun B proto-oncogene | −3.01155 | 0.00040 |
| 83379 | Klb | Klotho beta | −3.17551 | 0.01020 |
| 19225 | Ptgs2 | Prostaglandin-endoperoxide synthase 2 | −3.25476 | 0.00418 |
| 11910 | Atf3 | Activating transcription factor 3 | −3.60211 | 0.00123 |
| 13653 | Egr1 | Early growth response 1 | −4.08707 | 0.00151 |
| 15370 | Nr4a1 | Nuclear receptor subfamily 4, group A, member 1 | −5.27951 | 0.00002 |
| 14281 | Fos | FBJ osteosarcoma oncogene | −8.35415 | 0.00000 |
Differentially expressed genes in the cochlea.
Table 2
| Gene ID | Gene symbol | Description | Fold change (deaf/control) | Raw p-value (deaf/control) |
|---|---|---|---|---|
| a. Up-regulated genes | ||||
| 14559 | Gdf1 | Growth differentiation factor 1 | 16.52491 | 0.00010 |
| 11540 | Adora2a | Adenosine A2a receptor | 3.56210 | 0.00062 |
| 13489 | Drd2 | Dopamine receptor D2 | 3.51378 | 0.00426 |
| 66722 | Spag16 | Sperm associated antigen 16 | 3.07310 | 0.01554 |
| 73712 | Dmkn | Dermokine | 2.73336 | 0.00029 |
| 19144 | Klk6 | Kallikrein related-peptidase 6 | 2.71373 | 0.00722 |
| 211135 | D130040H23Rik | RIKEN cDNA D130040H23 gene | 2.69533 | 0.00246 |
| 103655 | Sec14l4 | SEC14-like lipid binding 4 | 2.60984 | 0.00482 |
| 278795 | Lrrc10b | Leucine rich repeat containing 10B | 2.56226 | 0.00062 |
| 242474 | Tmem245 | Transmembrane protein 245 | 2.42146 | 0.00380 |
| 666907 | Ms4a4a | Membrane-spanning 4-domains, subfamily A, member 4A | 2.40839 | 0.00888 |
| 232984 | B3gnt8 | UDP-GlcNAc:betaGal beta-1,3-N-acetylglucosaminyltransferase 8 | 2.33381 | 0.00027 |
| 230779 | Serinc2 | Serine incorporator 2 | 2.33204 | 0.00005 |
| 18491 | Pappa | Pregnancy-associated plasma protein A | 2.33128 | 0.01320 |
| 236643 | Sytl5 | Synaptotagmin-like 5 | 2.30804 | 0.00168 |
| 75556 | Cfap161 | Cilia and flagella associated protein 161 | 2.30577 | 0.00229 |
| 333670 | Gm867 | Predicted gene 867 | 2.25836 | 0.01556 |
| 69398 | Cdhr4 | Cadherin-related family member 4 | 2.24019 | 0.00583 |
| 14580 | Gfap | Glial fibrillary acidic protein | 2.17004 | 0.00029 |
| 74717 | Spata17 | Spermatogenesis associated 17 | 2.14429 | 0.04395 |
| 18619 | Penk | Preproenkephalin | 2.13625 | 0.01126 |
| 240327 | Gm4951 | Predicted gene 4951 | 2.13048 | 0.04154 |
| 18733 | Pirb | Paired Ig-like receptor B | 2.09880 | 0.00292 |
| 71738 | Mamdc2 | MAM domain containing 2 | 2.07577 | 0.00016 |
| 100861668 | Gm21119 | Predicted gene, 21119 | 2.05938 | 0.04798 |
| 18198 | Musk | Muscle, skeletal, receptor tyrosine kinase | 2.05913 | 0.00261 |
| 69032 | Lyzl4 | Lysozyme-like 4 | 2.05672 | 0.01272 |
| 70274 | Ly6g6e | Lymphocyte antigen 6 complex, locus G6E | 2.05624 | 0.00089 |
| 223650 | Eppk1 | Epiplakin 1 | 2.05213 | 0.01360 |
| 105246824 | Gm42048 | Predicted gene, 42048 | 2.01962 | 0.03546 |
| 58223 | Mmp19 | Matrix metallopeptidase 19 | 2.01409 | 0.00299 |
| b. Down-regulated genes | ||||
| 665622 | Hist1h2br | Histone cluster 1 H2br | −2.00065 | 0.03103 |
| 208372 | Asb18 | Ankyrin repeat and SOCS box-containing 18 | −2.00749 | 0.03440 |
| 229320 | Clrn1 | Clarin 1 | −2.03603 | 0.00422 |
| 12363 | Casp4 | Caspase 4, apoptosis-related cysteine peptidase | −2.04280 | 0.01282 |
| 19252 | Dusp1 | Dual specificity phosphatase 1 | −2.04784 | 0.00063 |
| 11596 | Ager | Advanced glycosylation end product-specific receptor | −2.05349 | 0.00429 |
| 170720 | Card14 | Caspase recruitment domain family, member 14 | −2.13673 | 0.02004 |
| 217143 | Gpr179 | G protein-coupled receptor 179 | −2.16473 | 0.00713 |
| 102871 | Radx | RPA1 related single stranded DNA binding protein, X-linked | −2.18001 | 0.00881 |
| 109245 | Lrrc39 | Leucine rich repeat containing 39 | −2.28429 | 0.00044 |
| 14281 | Fos | FBJ osteosarcoma oncogene | −2.30223 | 0.04435 |
| 21667 | Tdgf1 | Teratocarcinoma-derived growth factor 1 | −2.37906 | 0.04659 |
| 239250 | Slitrk6 | SLIT and NTRK-like family, member 6 | −2.42304 | 0.00278 |
| 97122 | H4c14 | Histone cluster 2, H4 | −2.43449 | 0.02622 |
| 11924 | Neurog2 | Neurogenin 2 | −2.67322 | 0.00954 |
| 102633345 | Gm9922 | Predicted gene 9922 | −2.73599 | 0.00258 |
| 22127 | Tsx | Testis specific X-linked gene | −2.83551 | 0.01123 |
| 12227 | Btg2 | B cell translocation gene 2, anti-proliferative | −3.00434 | 0.00000 |
| 100169864 | Gm44504 | Predicted readthrough transcript (NMD candidate), 44504 | −3.62548 | 0.04615 |
| 16007 | Ccn1 | Cellular communication network factor 1 | −3.63716 | 0.00380 |
| 319164 | H2ac6 | Histone cluster 1, H2ac | −5.58621 | 0.01429 |
Differentially expressed genes in the auditory cortex.
Table 3
| Gene ID | Gene symbol | Description | Fold change (deaf/control) | Raw p-value (deaf/control) |
|---|---|---|---|---|
| a. Up-regulated genes | ||||
| 14067 | F5 | Coagulation factor V | 11.32650 | 0.00051 |
| 100040591 | Kcnj13 | Potassium inwardly-rectifying channel, subfamily J, member 13 | 8.65329 | 0.01092 |
| 11826 | Aqp1 | Aquaporin 1 | 7.30121 | 0.01005 |
| 19116 | Prlr | Prolactin receptor | 6.15455 | 0.00349 |
| 12837 | Col8a1 | Collagen, type VIII, alpha 1 | 5.81586 | 0.00660 |
| 73608 | Marveld3 | MARVEL (membrane-associating) domain containing 3 | 4.63891 | 0.00105 |
| 96875 | Prg4 | Proteoglycan 4 (megakaryocyte stimulating factor, articular superficial zone protein) | 4.44379 | 0.00000 |
| 434223 | Gm1966 | Predicted gene 1966 | 4.08558 | 0.00000 |
| 63873 | Trpv4 | Transient receptor potential cation channel, subfamily V, member 4 | 4.08263 | 0.02017 |
| 54612 | Sfrp5 | Secreted frizzled-related sequence protein 5 | 4.06183 | 0.02991 |
| 16668 | Krt18 | Keratin 18 | 3.99511 | 0.01639 |
| 338403 | Cndp1 | Carnosine dipeptidase 1 (metallopeptidase M20 family) | 3.92104 | 0.00727 |
| 12374 | Casr | Calcium-sensing receptor | 3.91579 | 0.00079 |
| 14960 | H2-Aa | Histocompatibility 2, class II antigen A, alpha | 3.75704 | 0.00265 |
| 100169864 | Gm44504 | Predicted readthrough transcript (NMD candidate), 44504 | 3.62006 | 0.04651 |
| 12828 | Col4a3 | Collagen, type IV, alpha 3 | 3.55651 | 0.01753 |
| 245945 | Rbm47 | RNA binding motif protein 47 | 3.55321 | 0.03480 |
| 18606 | Enpp2 | Ectonucleotide pyrophosphatase/phosphodiesterase 2 | 3.42590 | 0.01823 |
| 18784 | Pla2g5 | Phospholipase A2, group V | 3.31853 | 0.03922 |
| 16149 | Cd74 | CD74 | 3.22550 | 0.01522 |
| 71355 | Col24a1 | Collagen, type XXIV, alpha 1 | 3.17166 | 0.00002 |
| 329941 | Col8a2 | Collagen, type VIII, alpha 2 | 3.17105 | 0.02224 |
| 246048 | Chodl | Chondrolectin | 3.08834 | 0.04821 |
| 18542 | Pcolce | Procollagen C-endopeptidase enhancer protein | 3.05446 | 0.00968 |
| 12737 | Cldn1 | Claudin 1 | 3.00102 | 0.02733 |
| 20347 | Sema3b | Sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3B | 2.98934 | 0.01241 |
| 102639145 | LOC102639145 | Transcription factor SKN7 | 2.97922 | 0.00561 |
| 208890 | Slc26a7 | Solute carrier family 26, member 7 | 2.97441 | 0.00013 |
| 330830 | Drc7 | Dynein regulatory complex subunit 7 | 2.86807 | 0.03430 |
| 14089 | Fap | Fibroblast activation protein | 2.85711 | 0.02732 |
| 100038882 | Isg15 | ISG15 ubiquitin-like modifier | 2.85010 | 0.00456 |
| 16591 | Kl | Klotho | 2.82507 | 0.02258 |
| 268970 | Arhgap28 | Rho GTPase activating protein 28 | 2.81550 | 0.00376 |
| 277328 | Trpa1 | Transient receptor potential cation channel, subfamily A, member 1 | 2.79628 | 0.00108 |
| 74732 | Stx11 | Syntaxin 11 | 2.76440 | 0.00776 |
| 18400 | Slc22a18 | Solute carrier family 22 (organic cation transporter), member 18 | 2.74952 | 0.00940 |
| 217169 | Tns4 | Tensin 4 | 2.74538 | 0.04620 |
| 625286 | Tmem236 | Transmembrane protein 236 | 2.74531 | 0.01272 |
| 16847 | Lepr | Leptin receptor | 2.63457 | 0.02200 |
| 16159 | Il12a | Interleukin 12a | 2.60059 | 0.00039 |
| 243755 | Slc13a4 | Solute carrier family 13 (sodium/sulfate symporters), member 4 | 2.58458 | 0.03987 |
| 211577 | Mrgprf | MAS-related GPR, member F | 2.55384 | 0.00442 |
| 71889 | Epn3 | Epsin 3 | 2.54936 | 0.03085 |
| 208943 | Myo5c | Myosin VC | 2.52633 | 0.00544 |
| 56072 | Lgals12 | Lectin, galactose binding, soluble 12 | 2.52565 | 0.01337 |
| 270097 | Vat1l | Vesicle amine transport protein 1 like | 2.52434 | 0.00503 |
| 74071 | Lmntd1 | Lamin tail domain containing 1 | 2.51746 | 0.00012 |
| 217430 | Pqlc3 | PQ loop repeat containing | 2.49585 | 0.00191 |
| 19682 | Rdh5 | Retinol dehydrogenase 5 | 2.47215 | 0.01969 |
| 57890 | Il17re | Interleukin 17 receptor E | 2.44971 | 0.04852 |
| 226691 | Ifi207 | Interferon activated gene 207 | 2.44593 | 0.00009 |
| 192212 | Prom2 | Prominin 2 | 2.42215 | 0.00144 |
| 66898 | Baiap2l1 | BAI1-associated protein 2-like 1 | 2.41073 | 0.01571 |
| 244416 | Ppp1r3b | Protein phosphatase 1, regulatory subunit 3B | 2.40559 | 0.00342 |
| 353169 | Slc2a12 | Solute carrier family 2 (facilitated glucose transporter), member 12 | 2.39779 | 0.01277 |
| 235631 | Prss50 | Protease, serine 50 | 2.36875 | 0.00626 |
| 105246303 | Gm41607 | Predicted gene, 41607 | 2.35532 | 0.00008 |
| 269823 | Pon3 | Paraoxonase 3 | 2.35186 | 0.00767 |
| 242509 | Bnc2 | Basonuclin 2 | 2.34916 | 0.00009 |
| 64378 | Gpr88 | G-protein coupled receptor 88 | 2.33412 | 0.00001 |
| 94352 | Loxl2 | Lysyl oxidase-like 2 | 2.33005 | 0.01761 |
| 277353 | Tcfl5 | Transcription factor-like 5 (basic helix-loop-helix) | 2.32594 | 0.02125 |
| 22626 | Slc23a3 | Solute carrier family 23 (nucleobase transporters), member 3 | 2.32299 | 0.00865 |
| 24110 | Usp18 | Ubiquitin specific peptidase 18 | 2.29958 | 0.02345 |
| 12841 | Col9a3 | Collagen, type IX, alpha 3 | 2.29593 | 0.00937 |
| 102631705 | Gm29975 | Predicted gene, 29975, transcript variant X1 | 2.27515 | 0.00175 |
| 20698 | Sphk1 | Sphingosine kinase 1 | 2.27148 | 0.00111 |
| 21956 | Tnnt2 | Troponin T2, cardiac | 2.26911 | 0.00001 |
| 11768 | Ap1m2 | Adaptor protein complex AP-1, mu 2 subunit | 2.26132 | 0.01163 |
| 319239 | Npsr1 | Neuropeptide S receptor 1 | 2.24119 | 0.01661 |
| 20271 | Scn5a | Sodium channel, voltage-gated, type V, alpha | 2.20943 | 0.01370 |
| 269120 | Optc | Opticin | 2.19504 | 0.01620 |
| 243634 | Ano2 | Anoctamin 2 | 2.18771 | 0.00009 |
| 667803 | H2-T-ps | Histocompatibility 2, T region locus, pseudogene | 2.18066 | 0.02451 |
| 23962 | Oasl2 | 2′-5′ oligoadenylate synthetase-like 2 | 2.17714 | 0.01093 |
| 15957 | Ifit1 | Interferon-induced protein with tetratricopeptide repeats 1 | 2.17630 | 0.01729 |
| 217325 | Llgl2 | LLGL2 scribble cell polarity complex component | 2.17085 | 0.00156 |
| 54123 | Irf7 | Interferon regulatory factor 7 | 2.16945 | 0.02250 |
| 64058 | Perp | PERP, TP53 apoptosis effector | 2.16029 | 0.02229 |
| 11856 | Arhgap6 | Rho GTPase activating protein 6 | 2.15633 | 0.00255 |
| 12577 | Cdkn1c | Cyclin-dependent kinase inhibitor 1C (P57) | 2.15592 | 0.01175 |
| 67473 | Slc47a1 | Solute carrier family 47, member 1 | 2.15002 | 0.00787 |
| 64242 | Ngb | Neuroglobin | 2.13014 | 0.04284 |
| 237759 | Col23a1 | Collagen, type XXIII, alpha 1 | 2.12340 | 0.01515 |
| 15959 | Ifit3 | Interferon-induced protein with tetratricopeptide repeats 3 | 2.12169 | 0.00910 |
| 27375 | Tjp3 | Tight junction protein 3 | 2.09354 | 0.01509 |
| 105247220 | Gm42355 | Predicted gene, 42355, transcript variant X29 | 2.09040 | 0.00952 |
| 73338 | Itpripl1 | Inositol 1,4,5-triphosphate receptor interacting protein-like 1 | 2.09034 | 0.02630 |
| 22420 | Wnt6 | Wingless-type MMTV integration site family, member 6 | 2.09021 | 0.00848 |
| 12904 | Crabp2 | Cellular retinoic acid binding protein II | 2.08715 | 0.00121 |
| 105734727 | Gm27021 | Predicted gene, 27021 | 2.08179 | 0.04292 |
| 74424 | Tmc5 | Transmembrane channel-like gene family 5 | 2.07842 | 0.02560 |
| 14264 | Fmod | Fibromodulin | 2.07183 | 0.00313 |
| 234582 | Ccdc102a | Coiled-coil domain containing 102A | 2.06606 | 0.01392 |
| 69550 | Bst2 | Bone marrow stromal cell antigen 2 | 2.05917 | 0.00037 |
| 667370 | Ifit3b | Interferon-induced protein with tetratricopeptide repeats 3B | 2.02357 | 0.01225 |
| 20289 | Scx | Scleraxis | 2.01667 | 0.01186 |
| 6543 | Mdfic | MyoD family inhibitor domain containing | 2.01167 | 0.01726 |
| 12835 | Col6a3 | Collagen, type VI, alpha 3 | 2.00305 | 0.00554 |
| b. Down-regulated genes | ||||
| 217216 | BC030867 | cDNA sequence BC030867 | −2.11057 | 0.00374 |
| 211135 | D130040H23Rik | RIKEN cDNA D130040H23 gene | −2.11174 | 0.01995 |
| 18071 | Nhlh1 | Nescient helix loop helix 1 | −2.14504 | 0.00259 |
| 240879 | Mettl11b | Methyltransferase like 11B | −2.19592 | 0.02249 |
| 12939 | Pcdha7 | Protocadherin alpha 7 | −2.21782 | 0.04278 |
| 15442 | Hpse | Heparanase | −2.25788 | 0.00477 |
| 74589 | Kbtbd12 | Kelch repeat and BTB (POZ) domain containing 12 | −2.27407 | 0.03156 |
| 210853 | Zfp947 | Zinc finger protein 947 | −2.28188 | 0.00010 |
| 116903 | Calcb | Calcitonin-related polypeptide, beta | −2.31538 | 0.02406 |
| 320604 | Ccdc169 | Coiled-coil domain containing 169 | −2.37904 | 0.02867 |
| 69852 | Tcf23 | Transcription factor 23 | −2.44860 | 0.00361 |
| 75015 | 4930503B20Rik | RIKEN cDNA 4930503B20 gene | −2.44869 | 0.02793 |
| 97122 | H4c14 | Histone cluster 2, H4 | −2.50098 | 0.02006 |
| 383592 | Kif28 | Kinesin family member 28 | −2.90396 | 0.01641 |
| 115488671 | LOC115488671 | Uncharacterized LOC115488671 | −3.20361 | 0.02140 |
Differentially expressed genes in the hippocampus.
Figure 2

Protein-coding DEGs of the cochlea, audigory cortex, and hippocampus. In the cochlea, there were 16 up-regulated and 32 down-regulated protein-coding DEGs, while in the auditory cortex, there were 31 up-regulated and 21 down-regulated protein-coding DEGs. In the hippocampus, 99 up-regulated and 15 down-regulated protein-coding DEGs were expressed.
Results of GO analysis
Cochlea
When we analyzed the cochlea, 294 GOs were identified as statistically significant (biological process, 259; molecular function, 34; cellular component, 1). The highly enriched GOs in the biological processes of the cochlea were mostly networked with down-regulated genes (Figure 3A). When the GOs of the biological process were classified into upper categories by the treemap technique, many categories were related to cell proliferation (regulation of lipid biosynthetic process, skeletal muscle cell differentiation, transcription by RNA polymerase II, response to fibroblast growth factor, and regulation of keratinocyte differentiation). There were other categories related to apoptosis [positive regulation of the apoptotic process, negative regulation of the mitogen-activated protein kinase (MAPK) cascade, regulation of cell death, and cell death; Figure 3B, Supplementary Table 1].
Figure 3

GO analysis on biological process of the cochlea. (A) Term annotation analysis from GOnet. Many genes are turned out down-regulated. (B) Treemap analysis from REVIGO. Many GOs can be categorized into cell proliferation and apoptosis.
Auditory cortex
In the auditory cortex, 211 GOs were identified (biological processes, 193; molecular functions, 1; and cell components, 17). In the biological processes of the auditory cortex, the up-regulated and down-regulated genes play similar roles (Figure 4A). GOs of the biological process can be classified as behavior-concerning (behavior and regulation of behavior), synapse-related (regulation of long-term synaptic potentiation and synaptic signaling), cell-signaling (response to purine-containing compound and regulation of kinase activity), cell metabolism (response to purine-containing compound, regulation of kinase activity, and protein dephosphorylation), and apoptosis (regulation of neuron death) categories, among others (Figure 4B, Supplementary Table 2).
Figure 4

GO analysis on biological process of the auditory cortex. (A) Term annotation analysis from GOnet. Up-regulated genes and down-regulated genes are mixed to a similar degree. (B) Treemap analysis from REVIGO. GOs can be classified into behavior-related, synapse-related, cell signaling, cell metabolism, and apoptosis categories.
Hippocampus
In the hippocampus, 203 GOs were identified (biological processes, 137; molecular functions, 40; and cell components, 26). In the biological process of the hippocampus, most key genes were upregulated (Figure 5A). GOs of the biological process can be classified as inflammation-related (response to cytokine, regulation of cytokine-mediated signaling pathway, and positive regulation of fibroblast proliferation) and viral infection-related categories (negative regulation of the viral process, regulation of viral process, extracellular matrix organization, secretion, and regulation of hydrolase activity, among others; Figure 5B, Supplementary Table 3).
Figure 5

GO analysis on biological process of the hippocampus. (A) Term annotation analysis from GOnet. Most genes are up-regulated. (B) Treemap analysis from REVIGO. GOs can be classified into inflammation-related and viral infection-related categories.
KEGG pathway results
Cochlea
Ten KEGG pathways were statistically significant. These included pathways related to immune responses, such as the tumor necrosis factor (TNF) signaling pathway, and those related to apoptosis, such as the MAPK signaling pathway. Twelve genes were included in these pathways, most of which were down-regulated (Table 4).
Table 4
| Map ID | Map name | p-value | Gene ID | Gene symbol | Description | Fold change (deaf/control) | Raw p-value (deaf/control) |
|---|---|---|---|---|---|---|---|
| 04668 | TNF signaling pathway | < 0.001 | 12702 | Socs3 | Suppressor of cytokine signaling 3 | −2.241 | 0.005 |
| 14281 | Fos | FBJ osteosarcoma oncogene | −8.354 | < 0.001 | |||
| 16477 | Junb | Jun B proto-oncogene | −3.012 | < 0.001 | |||
| 19225 | Ptgs2 | Prostaglandin-endoperoxide synthase 2 | −3.255 | 0.004 | |||
| 04010 | MAPK signaling pathway | 0.001 | 13537 | Dusp2 | Dual specificity phosphatase 2 | −2.121 | < 0.001 |
| 14281 | Fos | FBJ osteosarcoma oncogene | −8.354 | < 0.001 | |||
| 15370 | Nr4a1 | Nuclear receptor subfamily 4, group A, member 1 | −5.280 | < 0.001 | |||
| 19252 | Dusp1 | Dual specificity phosphatase 1 | −2.804 | < 0.001 | |||
| 04935 | Growth hormone synthesis, secretion and action | 0.003 | 12702 | Socs3 | Suppressor of cytokine signaling 3 | −2.241 | 0.005 |
| 14281 | Fos | FBJ osteosarcoma oncogene | −8.354 | < 0.001 | |||
| 16477 | Junb | Jun B proto-oncogene | −3.012 | < 0.001 | |||
| 04380 | Osteoclast differentiation | 0.004 | 12702 | Socs3 | Suppressor of cytokine signaling 3 | −2.241 | 0.005 |
| 14281 | Fos | FBJ osteosarcoma oncogene | −8.354 | < 0.001 | |||
| 16477 | Junb | Jun B proto-oncogene | −3.012 | < 0.001 | |||
| 04928 | Parathyroid hormone synthesis, secretion and action | 0.003 | 13653 | Egr1 | Early growth response 1 | −4.087 | 0.002 |
| 14281 | Fos | FBJ osteosarcoma oncogene | −8.354 | < 0.001 | |||
| 18227 | Nr4a2 | Nuclear receptor subfamily 4, group A, member 2 | −2.527 | 0.001 | |||
| 04726 | Serotonergic synapse | 0.004 | 15564 | Htr5b | 5-hydroxytryptamine (serotonin) receptor 5B | 2.557 | 0.007 |
| 19225 | Ptgs2 | Prostaglandin-endoperoxide synthase 2 | −3.255 | 0.004 | |||
| 19252 | Dusp1 | Dual specificity phosphatase 1 | −2.804 | < 0.001 | |||
| 05167 | Kaposi sarcoma-associated herpesvirus infection | 0.011 | 14281 | Fos | FBJ osteosarcoma oncogene | −8.354 | < 0.001 |
| 19225 | Ptgs2 | Prostaglandin-endoperoxide synthase 2 | −3.255 | 0.004 | |||
| 22695 | Zfp36 | Zinc finger protein 36 | −2.450 | 0.006 | |||
| 05166 | Human T-cell leukemia virus 1 infection | 0.014 | 13653 | Egr1 | Early growth response 1 | −4.087 | 0.002 |
| 14281 | Fos | FBJ osteosarcoma oncogene | −8.354 | < 0.001 | |||
| 22695 | Zfp36 | Zinc finger protein 36 | −2.450 | 0.006 | |||
| 05140 | Leishmaniasis | 0.050 | 14281 | Fos | FBJ osteosarcoma oncogene | −8.354 | < 0.001 |
| 19225 | Ptgs2 | Prostaglandin-endoperoxide synthase 2 | −3.255 | 0.004 | |||
| 04913 | Ovarian steroidogenesis | 0.045 | 19225 | Ptgs2 | Prostaglandin-endoperoxide synthase 2 | −3.255 | 0.004 |
| 217698 | Acot5 | Acyl-CoA thioesterase 5 | 2.532 | 0.003 |
Statistically significant KEGG pathways in the cochlea.
Auditory cortex
Seven KEGG pathways were statistically significant. Pathways related to immune reactions (neutrophil extracellular trap formation and B cell receptor signaling pathway), cell death [cyclic adenosine monophosphate (cAMP) signaling pathway], and neuronal synapses (neuroactive ligand-receptor interaction) were expressed. Eleven genes were found in these pathways, and the up-regulated and downregulated genes were combined (Table 5).
Table 5
| Map ID | Map name | p-value | Gene ID | Gene symbol | Description | Fold change (deaf/control) | Raw p-value (deaf/control) |
|---|---|---|---|---|---|---|---|
| 05034 | Alcoholism | < 0.001 | 11540 | Adora2a | Adenosine A2a receptor | 3.562 | 0.001 |
| 13489 | Drd2 | Dopamine receptor D2 | 3.514 | 0.004 | |||
| 97122 | H4c14 | Histone cluster 2, H4 | −2.434 | 0.026 | |||
| 319164 | H2ac6 | Histone cluster 1, H2ac | −5.586 | 0.014 | |||
| 665622 | Hist1h2br | HISTONE cluster 1 H2br | −2.001 | 0.031 | |||
| 04613 | Neutrophil extracellular trap formation | < 0.001 | 11596 | Ager | Advanced glycosylation end product-specific receptor | −2.053 | 0.004 |
| 12363 | Casp4 | Caspase 4, apoptosis-related cysteine peptidase | −2.043 | 0.013 | |||
| 97122 | H4c14 | Histone cluster 2, H4 | −2.434 | 0.026 | |||
| 319164 | H2ac6 | Histone cluster 1, H2ac | −5.586 | 0.014 | |||
| 665622 | Hist1h2br | Histone cluster 1 H2br | −2.001 | 0.031 | |||
| 05322 | Systemic lupus erythematosus | 0.003 | 97122 | H4c14 | Histone cluster 2, H4 | −2.434 | 0.026 |
| 319164 | H2ac6 | Histone cluster 1, H2ac | −5.586 | 0.014 | |||
| 665622 | Hist1h2br | Histone cluster 1 H2br | −2.001 | 0.031 | |||
| 04024 | cAMP signaling pathway | 0.006 | 11540 | Adora2a | Adenosine A2a receptor | 3.562 | 0.001 |
| 13489 | Drd2 | Dopamine receptor D2 | 3.514 | 0.004 | |||
| 14281 | Fos | FBJ osteosarcoma oncogene | −2.302 | 0.044 | |||
| 05012 | Parkinson's disease | 0.009 | 11540 | Adora2a | Adenosine A2a receptor | 3.562 | 0.001 |
| 13489 | Drd2 | Dopamine receptor D2 | 3.514 | 0.004 | |||
| 19252 | Dusp1 | Dual specificity phosphatase 1 | −2.048 | 0.001 | |||
| 04080 | Neuroactive ligand-receptor interaction | 0.017 | 11540 | Adora2a | Adenosine A2a receptor | 3.562 | 0.001 |
| 13489 | Drd2 | Dopamine receptor D2 | 3.514 | 0.004 | |||
| 18619 | Penk | Preproenkephalin | 2.136 | 0.011 | |||
| 04662 | B cell receptor signaling pathway | 0.043 | 14281 | Fos | FBJ osteosarcoma oncogene | −2.302 | 0.044 |
| 18733 | Pirb | Paired Ig-like receptor B | 2.099 | 0.003 |
Statistically significant KEGG pathways in the auditory cortex.
Hippocampus
Seventeen KEGG pathways were statistically significant. These include inflammatory pathways [cytokine-cytokine receptor interaction and the Janus kinases-signal transducer and activator of transcription proteins (JAK-STAT) signaling pathway] and viral infection-related pathways. Twenty-seven genes were involved in these pathways, most of which were up-regulated (Table 6).
Table 6
| Map ID | Map name | p-value | Gene ID | Gene Symbol | Description | Fold change (deaf/control) | Raw p-value (deaf/control) |
|---|---|---|---|---|---|---|---|
| 04974 | Protein digestion and absorption | < 0.001 | 12828 | Col4a3 | Collagen, type IV, alpha 3 | 3.557 | 0.018 |
| 12835 | Col6a3 | Collagen, type VI, alpha 3 | 2.003 | 0.006 | |||
| 12837 | Col8a1 | Collagen, type VIII, alpha 1 | 5.816 | 0.007 | |||
| 12841 | Col9a3 | Collagen, type IX, alpha 3 | 2.296 | 0.009 | |||
| 71355 | Col24a1 | Collagen, type XXIV, alpha 1 | 3.172 | 0.000 | |||
| 237759 | Col23a1 | Collagen, type XXIII, alpha 1 | 2.123 | 0.015 | |||
| 329941 | Col8a2 | Collagen, type VIII, alpha 2 | 3.171 | 0.022 | |||
| 100040591 | Kcnj13 | Potassium inwardly-rectifying channel, subfamily J, member 13 | 8.653 | 0.011 | |||
| 05165 | Human papillomavirus infection | < 0.001 | 12828 | Col4a3 | Collagen, type IV, alpha 3 | 3.557 | 0.018 |
| 12835 | Col6a3 | Collagen, type VI, alpha 3 | 2.003 | 0.006 | |||
| 12841 | Col9a3 | Collagen, type IX, alpha 3 | 2.296 | 0.009 | |||
| 22420 | Wnt6 | Wingless-type MMTV integration site family, member 6 | 2.090 | 0.008 | |||
| 23962 | Oasl2 | 2'-5' oligoadenylate synthetase-like 2 | 2.177 | 0.011 | |||
| 217325 | Llgl2 | LLGL2 scribble cell polarity complex component | 2.171 | 0.002 | |||
| 667803 | H2-T-ps | Histocompatibility 2, T region locus, pseudogene | 2.181 | 0.025 | |||
| 100038882 | Isg15 | ISG15 ubiquitin-like modifier | 2.850 | 0.005 | |||
| 05168 | Herpes simplex virus 1 infection | < 0.001 | 14960 | H2-Aa | Histocompatibility 2, class II antigen A, alpha | 3.757 | 0.003 |
| 16149 | Cd74 | CD74 antigen | 3.225 | 0.015 | |||
| 16159 | Il12a | Interleukin 12a | 2.601 | 0.000 | |||
| 54123 | Irf7 | Interferon regulatory factor 7 | 2.169 | 0.023 | |||
| 69550 | Bst2 | Bone marrow stromal cell antigen 2 | 2.059 | 0.000 | |||
| 210853 | Zfp947 | Zinc finger protein 947 | −2.282 | 0.000 | |||
| 667803 | H2-T-ps | Histocompatibility 2, T region locus, pseudogene | 2.181 | 0.025 | |||
| 04530 | Tight junction | 0.005 | 12737 | Cldn1 | Claudin 1 | 3.001 | 0.027 |
| 27375 | Tjp3 | Tight junction protein 3 | 2.094 | 0.015 | |||
| 73608 | Marveld3 | MARVEL domain containing 3 | 4.639 | 0.001 | |||
| 217325 | Llgl2 | LLGL2 scribble cell polarity complex component | 2.171 | 0.002 | |||
| 05152 | Tuberculosis | 0.006 | 14960 | H2-Aa | Histocompatibility 2, class II antigen A, alpha | 3.757 | 0.003 |
| 16149 | Cd74 | CD74 antigen | 3.225 | 0.015 | |||
| 16159 | Il12a | Interleukin 12a | 2.601 | < 0.001 | |||
| 20698 | Sphk1 | Sphingosine kinase 1 | 2.271 | 0.001 | |||
| 05330 | Allograft rejection | 0.007 | 14960 | H2-Aa | Histocompatibility 2, class II antigen A, alpha | 3.757 | 0.003 |
| 16159 | Il12a | Interleukin 12a | 2.601 | < 0.001 | |||
| 667803 | H2-T-ps | Histocompatibility 2, T region locus, pseudogene | 2.181 | 0.025 | |||
| 04622 | RIG-I-like receptor signaling pathway | 0.009 | 16159 | Il12a | Interleukin 12a | 2.601 | < 0.001 |
| 54123 | Irf7 | Interferon regulatory factor 7 | 2.169 | 0.023 | |||
| 100038882 | Isg15 | ISG15 ubiquitin-like modifier | 2.850 | 0.005 | |||
| 04940 | Type I diabetes mellitus | 0.009 | 14960 | H2-Aa | Histocompatibility 2, class II antigen A, alpha | 3.757 | 0.003 |
| 16159 | Il12a | Interleukin 12a | 2.601 | < 0.001 | |||
| 667803 | H2-T-ps | Histocompatibility 2, T region locus, pseudogene | 2.181 | 0.025 | |||
| 05169 | Epstein-Barr virus infection | 0.012 | 14960 | H2-Aa | Histocompatibility 2, class II antigen A, alpha | 3.757 | 0.003 |
| 54123 | Irf7 | Interferon regulatory factor 7 | 2.169 | 0.023 | |||
| 667803 | H2-T-ps | Histocompatibility 2, T region locus, pseudogene | 2.181 | 0.025 | |||
| 100038882 | Isg15 | ISG15 ubiquitin-like modifier | 2.850 | 0.005 | |||
| 04512 | ECM-receptor interaction | 0.014 | 12828 | Col4a3 | Collagen, type IV, alpha 3 | 3.557 | 0.018 |
| 12835 | Col6a3 | Collagen, type VI, alpha 3 | 2.003 | 0.006 | |||
| 12841 | Col9a3 | Collagen, type IX, alpha 3 | 2.296 | 0.009 | |||
| 04612 | Antigen processing and presentation | 0.015 | 14960 | H2-Aa | Histocompatibility 2, class II antigen A, alpha | 3.757 | 0.003 |
| 16149 | Cd74 | CD74 antigen | 3.225 | 0.015 | |||
| 667803 | H2-T-ps | Histocompatibility 2, T region locus, pseudogene | 2.181 | 0.025 | |||
| 04060 | Cytokine-cytokine receptor interaction | 0.022 | 16159 | Il12a | Interleukin 12a | 2.601 | < 0.001 |
| 16847 | Lepr | Leptin receptor | 2.635 | 0.022 | |||
| 19116 | Prlr | prolactin receptor | 6.155 | 0.003 | |||
| 57890 | Il17re | Interleukin 17 receptor E | 2.450 | 0.049 | |||
| 04151 | PI3K-Akt signaling pathway | 0.037 | 12828 | Col4a3 | Collagen, type IV, alpha 3 | 3.557 | 0.018 |
| 12835 | Col6a3 | Collagen, type VI, alpha 3 | 2.003 | 0.006 | |||
| 12841 | Col9a3 | Collagen, type IX, alpha 3 | 2.296 | 0.009 | |||
| 19116 | Prlr | Prolactin receptor | 6.155 | 0.003 | |||
| 05160 | Hepatitis C | 0.045 | 12737 | Cldn1 | Claudin 1 | 3.001 | 0.027 |
| 15957 | Ifit1 | Interferon-induced protein with tetratricopeptide repeats 1 | 2.176 | 0.017 | |||
| 54123 | Irf7 | Interferon regulatory factor 7 | 2.169 | 0.023 | |||
| 04630 | JAK-STAT signaling pathway | 0.046 | 16159 | Il12a | Interleukin 12a | 2.601 | < 0.001 |
| 16847 | Lepr | Leptin receptor | 2.635 | 0.022 | |||
| 19116 | Prlr | Prolactin receptor | 6.155 | 0.003 | |||
| 05164 | Influenza A | 0.049 | 14960 | H2-Aa | Histocompatibility 2, class II antigen A, alpha | 3.757 | 0.003 |
| 16159 | Il12a | Interleukin 12a | 2.601 | < 0.001 | |||
| 54123 | Irf7 | Interferon regulatory factor 7 | 2.169 | 0.023 | |||
| 04514 | Cell adhesion molecules | 0.049 | 12737 | Cldn1 | Claudin 1 | 3.001 | 0.027 |
| 14960 | H2-Aa | Histocompatibility 2, class II antigen A, alpha | 3.757 | 0.003 | |||
| 667803 | H2-T-ps | Histocompatibility 2, T region locus, pseudogene | 2.181 | 0.025 |
Statistically significant KEGG pathways in the hippocampus.
Discussion
We conducted an omics study to determine how hearing loss affects the central auditory pathway, including cognitive organs. We examined the effects of hearing loss on the cochlea, auditory cortex, and hippocampus using mRNA sequencing. First, we compared the DEGs in these organs. The number of up-regulated genes was the lowest in the cochlea, and it increased toward the central nervous system. In contrast, the number of down-regulated genes increased as we moved toward the periphery (Tables 1–3, Figures 3A, 4A, 5A). Most DEGs in the cochlea exhibited an inhibitory pattern, whereas those in the hippocampus were excitatory.
In the cochlea, genes related to activator protein 1 (AP-1) transcription (Fos and Junb) and inflammation (Ptgs2 and Socs3) were down-regulated. AP-1 transcription factors control cell differentiation, proliferation, and apoptosis during stress and infections (Ameyar et al., 2003; Hess et al., 2004). This suggests that the peak time of inflammatory response and cell death has passed. In the auditory cortex, genes related to the guanine nucleotide-binding protein (G protein)-coupled receptor superfamily (Drd2 and Adora2a) were up-regulated. They are known to have relation with regulation of cognitive function and mood by promoting dopamine binding and dopamine neurotransmitter receptor activity (Komatsu et al., 2014; Khlghatyan et al., 2019). In the hippocampus, genes related to the major histocompatibility complex (H2-T-ps, H2-Aa, Cd74), helper T cell type 1 (Il12a), and the extracellular matrix (Col4a3, Col6a3, Col9a3) were up-regulated, implying an actively processed adaptive immune reactions and cellular changes.
When examining the GOs and KEGG pathways, we observed that the expression patterns differed for each organ. Genes related to cell proliferation and death were simultaneously expressed in the cochlea (Figure 3B, Supplementary Table 1). The TNF signaling pathway, associated with the immune response, and the MAPK signaling pathway, related to apoptosis, were also activated (Table 4). However, most gene activities were down-regulated. Considering cell proliferation, inflammation, and apoptosis occur simultaneously after hearing loss in the cochlea (Shu et al., 2019; Milon et al., 2021; Warnecke et al., 2021; Chen et al., 2022; Paciello et al., 2023), all of these processes seem to be in the finishing stage.
In the auditory cortex, the GO patterns were quite different. Genes related to behavior and neuronal synapse function were highly expressed, and those associated with cellular metabolism, cell signaling, and apoptosis were also observed (Figure 4B, Supplementary Table 2). The cAMP signaling pathway and neuroactive ligand-receptor interactions seem to be related to neuronal cell death and synaptic activity (Table 5). Therefore, it can be inferred that brain plasticity mechanisms occur through synaptic changes along with neuronal cell death, affecting cognitive function in the auditory cortex. Notably, alcoholism and Parkinson's disease appeared in the KEGG pathway, suggesting that changes in the auditory cortex following hearing loss progress in a similar pattern to these disorders.
The hippocampus differs from the other two organs in that most genes exhibited excitatory activity (Figure 5A). Inflammation-related pathways, such as cytokine-cytokine receptor interactions, were commonly activated, indicating ongoing inflammation (Figure 5B, Table 6, Supplementary Table 3). Interestingly, there are many pathways related to viral and fungal infections that seem unrelated, suggesting that when the hippocampus is challenged, it exhibits a response similar to infection. Thus, neuroinflammation persists in the hippocampus even after 3 months of hearing loss.
In conclusion, apoptosis and inflammation persisted more actively in the order of hippocampus, auditory cortex, cochlea in the long term (12 weeks) after noise-induced hearing loss. This implies that the neurodegenerative effects of noise exposure do not resolve quickly in the central regions but persist for a considerable period. Therefore, cognitive decline following noise-induced hearing loss is likely to be a progressive process rather than an instant deterioration (Figure 6). Some studies see the cognitive decline not just as elongated degeneration, but as accelerated aging (Zhuang et al., 2020; Paciello et al., 2021). In the case of normal C57BL/6J mice, no histological changes are observed in the auditory cortex or hippocampus up to 6 months of age (Dong et al., 2018). However, it appears that there are gradual changes in proteins that play significant roles in plasticity and cognitive functions, such as MMP-9 (Dong et al., 2018). Hence, proactive treatment to prevent the progression of cognitive decline remain of substantial importance even if there are little chance of auditory restoration. For example, auditory rehabilitation strategies, including the utilization of hearing aids or cochlear implants, as well as medical interventions such as antioxidant therapy, may prove beneficial for patients with hearing impairment in mitigating the risk of cognitive decline.
Figure 6

Proposed mechanism how noise-induced hearing loss cause mice cognitive decline. Three months after the onset of noise-induced hearing loss, processes such as cell proliferation, inflammation, and apoptosis come to finishing stage in the cochlea. However, neuronal cell death is still progressing in the auditory cortex, and neuroinflammation persists in the hippocampus. These prolonged neurodegeneration processes in the central region accelerates cognitive decline.
This study has a few limitations. First, this study was conducted only in the aspect of mRNA expression, so it may appear differently at the level of protein. Secondly, this was a cross-sectional study that included 24-week-old mice, and we analyzed its results by considering the general progression of neuroinflammation. However, a time-series study of each organ is required to determine the dynamic mechanisms of neuroinflammation accurately. Finally, the noise used in this study was large enough to evoked permanent hearing loss in a single exposure. Loud noise can affect the central auditory pathway and the hippocampus within a few days (Groschel et al., 2018; Chen et al., 2022). And long-term exposure to noise could affect central neural system differently. In particular, the effects on cognitive function may differ significantly in cases of noise stress or gradual hearing deterioration due to sustained high-intensity noise. Further studies are required to generalize these findings to the overall context of noise-induced hearing loss.
Statements
Data availability statement
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1061000/.
Ethics statement
The animal study was approved by Institutional Animal Care and Use Committee (IACUC) of Boramae Hospital (IACUC number 2022-0133). The study was conducted in accordance with the local legislation and institutional requirements.
Author contributions
S-YL: Data curation, Formal analysis, Investigation, Software, Visualization, Writing—original draft. HL: Data curation, Investigation, Methodology, Validation, Writing—review & editing. M-HP: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing—review & editing.
Funding
The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by the Korea National Research Fund (NRF-2020R1A2C1006254; PI: M-HP). The funding body played no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
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Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnins.2024.1340854/full#supplementary-material
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Summary
Keywords
noise-induced hearing loss, transcriptomics, neurodegeneration, cochlea, auditory cortex, hippocampus
Citation
Lee S-Y, Lee HS and Park M-H (2024) Transcriptomic analysis reveals prolonged neurodegeneration in the hippocampus of adult C57BL/6N mouse deafened by noise. Front. Neurosci. 18:1340854. doi: 10.3389/fnins.2024.1340854
Received
19 November 2023
Accepted
25 January 2024
Published
12 February 2024
Volume
18 - 2024
Edited by
Gi Jung Im, Korea University, Republic of Korea
Reviewed by
Athanasia Warnecke, Hannover Medical School, Germany
Jiwon Chang, Hallym University Medical Center, Republic of Korea
Joong Ho Ahn, University of Ulsan, Republic of Korea
Updates
Copyright
© 2024 Lee, Lee and Park.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Min-Hyun Park drpark@snu.ac.kr
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.