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Single cell RNA sequencing provides novel cellular transcriptional profiles and underlying pathogenesis of presbycusis

BMC Medical Genomics volume 17, Article number: 237 (2024) Cite this article

Abstract

Age-related hearing loss (ARHL) or presbycusis is associated with irreversible progressive damage in the inner ear, where the sound is transduced into electrical signal; but the detailed mechanism remains unclear. Here, we sought to determine the potential molecular mechanism involved in the pathogeneses of ARHL with bioinformatics methods. A single-cell transcriptome sequencing study was performed on the cochlear samples from young and aged mice. Detection of identified cell type marker allowed us to screen 18 transcriptional clusters, including myeloid cells, epithelial cells, B cells, endothelial cells, fibroblasts, T cells, inner pillar cells, neurons, inner phalangeal cells, and red blood cells. Cell-cell communications were analyzed between young and aged cochlear tissue samples by using the latest integration algorithms Cellchat. A total of 56 differentially expressed genes were screened between the two groups. Functional enrichment analysis showed these genes were mainly involved in immune, oxidative stress, apoptosis, and metabolic processes. The expression levels of crucial genes in cochlear tissues were further verified by immunohistochemistry. Overall, this study provides new theoretical support for the development of clinical therapeutic drugs.

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Introduction

Age-related hearing loss (ARHL) or presbycusis is characterized by progressive hearing loss and is often accompanied by poor speech discrimination. A recent systematic review suggests hearing loss affects an estimated 1.57 billion people worldwide, accounting for one in five people, and 2.45 billion individuals will suffer hearing loss by 2050 [1, 2]. The prevalence of hearing loss rises across all age-specific categories, particularly those aged 60 and up to over 80% in adults aged 85 years [3]. As a constellation of sensorineural dysfunctions, ARHL can cause depression, social isolation, and cognitive decline, leading to a severely reduced quality of life [4]. ARHL is a multifactorial condition and is influenced by various internal and external factors, including aging, exposure to noise and ototoxic drugs, genetics, and epigenetic variables [5, 6]. The major sites of cochlear pathology are associated with inner hair cells (HCs), outer HCs, spiral ganglion neurons, and stria vascularis. For example, BNIP3L/NIX is involved in the regulation of cochlear hair cell homeostasis through mitophagy and oxidative stress in ARHL [7]. Oxidative stress can induce premature senescence in auditory cells, leading to ARHL [8]. Meanwhile, the role of immune inflammation in the pathogenesis of presbycusis has also attracted people’s attention [9]. However, the biological and pathological mechanisms of ARHL are complex and not yet fully delineated.

Inner ear is a complex structure located in the temporal bone and cochlea is the main sound receiver in the inner ear. Meanwhile, the hair cells and spiral ganglion cells are major structures of sound transmission in the cochlea [10]. Recently, single-cell RNA sequencing (scRNA-seq) technology has been used to define cellular transcriptional data with significant heterogeneity in tissue and organ. Kolla et al. present a scRNA-seq analysis for the cochlear epithelium developing at differential embryonic and postnatal time points; the validation results provides a reliable resource for detecting developmental events during the cochlear formation [11]. Paul et al. demonstrate novel insights into hearing biology according to scRNA-seq of inner and outer hair cells from differential developmental stages, promoting the cell type-defining genes associated with deafness [12].

In this study, we set out to detect the transcriptional heterogeneity of cochlear cell type between young and aged mice. The alteration of cell-cell communications in both young and aged group was analyzed with CellChat, a novel algorithm that can infer cellular communications with scRNA-seq profiles [13]. Moreover, we identified differentially expressed genes (DEGs) associated with presbycusis, followed by functional analysis and immunohistochemical verification. Our data may shed new light on the potential role of cochlea intercellular communications in presbycusis.

Materials and methods

Experimental model

Male C57BL/6J mice were obtained from the Experimental Animal Center of Chongqing Medical University and were divided into two groups, control group (1–2 months old, n = 3) and aged group (14 months old, n = 3). All mice were maintained under a low-noise conditions in a 12:12 h light-dark cycle. None of the mice had experienced exposure of noise, otitis media, or ototoxic drugs. The animals were euthanized and cochlear samples were quickly dissected from both ears and submitted to following detection. All experimental procedures were approved by the Laboratory Animal Welfare and Ethics Committee of the Third Military Medical University (ID: IACUC-CQMU-2022-0030).

Auditory brainstem response (ABR) audiometry

ABR tests were performed using a Tucker-Davis Technology equipment as previously described [14]. The mice were anesthetized by intraperitoneal injection of sodium pentobarbital (30 mg/kg), and warmed with a heating pad for maintaining temperature. The recording electrodes were placed in the middle of skull. Reference electrode was inserted subcutaneously behind the ear, while the ground wire was inserted subcutaneously at the tail base. The impedance between the electrodes was less than 3KΩ. The loudspeaker was placed in the external auditory canal, and the ABR threshold was set as the lowest intensity at which the repeatable ABR waveform was identified. The neuronal activity was amplified, filtered, and then digitized with the analog-to-digital converter (AD3; Tucker-Davis Technologies, Alachua, USA). The stimulation pattern used had a rise time of 5 milliseconds and a plateau time of 0.5 milliseconds. The persistence index was detected for 1,000-ms as the ratio of response amplitude at the four frequencies: 8, 16, 24, and 32 kHz. The intensity of the stimuli ranged from 20 to 90 dB sound pressure level (SPL) in 5 dB increments. Three mice with 6 ears were tested.

Single cell RNA sequencing on 10x chromium genomics platform

The mice were euthanized by carbon dioxide to dissect the cochlea and was transported into the iced DMEM (Thermo Fisher Scientific, Waltham, MA) immediately. The stapes, vessels and connective tissues around the cochlea were removed gently under a dissecting microscope. Cochlea was carefully peeled off with dissecting forceps, and the cochlea shaft was removed. Microdissection was completed in 6 cochlear tissues from 3 mice in each group. One biological replicate in each group was used for scRNA-seq. After being washed with the PBS for three times, cochlear tissues were minced into < 1 mm3 size and transferred into a 50 ml tube (BD Falcon, Franklin Lakes, NJ) containing DMEM supplement. Briefly, harvested cochlear tissues were digested with 0.2% collagenase type I for 20 min and then digested with 0.25% trypsin for 10 min. All cells were passed through 40 μm strainers and centrifuged at 300 g at 4 °C for 6 min. The cell pellet was harvested and re-suspended in iced DMEM prior to barcoding on the chromium genomics platform.

The cell counts and cell viability of single cell suspension was measured by Countess II Automated Cell Counter (Thermo Fisher Scientific). The cell viability larger than 85% was adjusted to a concentration of 700–1200 cells/µL and loaded onto the Chromium Controller (10x Genomics, CA, USA). RNA-Seq libraries were prepared using the Chromium Single Cell 5’ Reagent Kit v2 (10x Genomics, CA, USA) according to the manufacturer’s instructions. The library was constructed for high-throughput sequencing and the reads were subsequently processed using the CellRanger pipeline. Finally, the Cellranger aggr was used to aggregate multiple libraries.

Sequencing data processing

The raw fastq data were mapped to reference genome and quantitated by identifying cellular barcodes using CellRanger [13] (10× Genomics, v3). The quality control criteria were as follows: firstly, the harvested cells outside 2 standard deviations (SDs) from the mean unique molecular identifier (UMI) gene number were filtered out for each sample to discard low-quality cells and doublets. Moreover, the low-quality cells (> 10% mitochondrial genes) were further excluded. Doublet analysis was conducted using the DoubletFinder [15] (v2). Finally, a total of 15,401 single cells were acquired.

Seurat clustering

Principal component analysis (PCA) was performed for dimensionality reduction. Clustering results were demonstrated by uniform manifold approximation and project (UMAP). Marker genes were calculated using the function “FindAllMarkers” [16]. The definition of a marker gene is that the gene is highly expressed in the vast majority of the given cell population and lowly expressed in other cell types and the gene is significantly up-regulated in one cell cluster relative to other cell clusters. The specific marker genes of each cell cluster were identified by presto test based on the criteria that the expression proportion of the given cluster was greater than 25% and its expression was higher than that of other clusters. The top 10 marker genes of each cluster were identified based on gene_diff, which was calculated by pct1/pct2. The pct1 was the proportion of cells expressing marker gene in the given cell cluster and pct2 was the proportion of cells expressing marker gene in other cell culsters. Marker gene expression was visualized using VlnPlot and FeaturePlot functions. Cluster annotation was performed using the SingleR [17] package, which compares the transcriptome of single cell to reference datasets that enabled the sub-clustering.

Differential gene identification and enrichment analysis

DEGs between control and aged groups were screened by FindMarkers function in Seurat package based on the criteria of adjusted p-value < 0.05 and fold change > 1.5. The cell-type specific DEGs were screened based on the criteria of p-value < 0.05 and fold change > 1.5. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed based on hypergeometric distribution test.

Cell-cell communication

Intercellular communication networks perturbed or induced in the cochlear organ were inferred using CellChat1.0.0 [13]. The overall interaction number and interaction strength in differential cell types were quantified and compared between control and disease conditions. The information flows for each signaling pathway were calculated. Finally, to determine the major senders and receivers in the signaling network, cell-cell communications among these seven cell types, were analyzed and compared respectively.

Immunohistochemistry

The cochlear explants (n = 5) were fixed in 4% paraformaldehyde for 24 h and decalcified with ethylenediaminetetraacetic acid (EDTA) for one month. Then, the cochlear samples were dehydrated by graded alcohol and embedded in paraffin for immunohistochemistry. Cochlear tissue sections were sliced at a thickness of 4–5 μm. After dewaxing, rehydration, and antigen retrieval, the sections were added dropwise with goat serum for endogenous peroxidase blocking. The cochlear tissues were incubated with the primary antibodies including Autotaxin (Enpp2) antibody 1:25; SAA3 antibody 1:50; GH antibody 1:200; RANTES antibody (CCL5) 1:100; CXCL10 antibody 1:100 overnight at 4 °C. Primary antibodies were decanted in PBS and detected using horseradish enzyme-conjugated goat anti-rabbit IgG II (H + L, 1:1000). All images were captured using a confocal microscope (Leica, Heidelberg, Germany).

Results

Identification of major cochlear cell clusters associated with presbycusis

Firstly, the aged mice with severe hearing loss were assessed by ABR threshold assay. Auditory stimuli were applied to mice, and frequency-modulated tones ranging of 8–32 kHz were conducted to test hearing threshold as defined. The median ABR threshold in the aged group was notably elevated compared with the young group mice (Fig. 1A). No hearing was detected in aged mice even at the upper limit of 90dB SPL.

Fig. 1
figure 1

Identification of crucial cochlear cell types between control and aged mice. (A) Hearing threshold of C57BL/6J mice in control and aged group. Frequency dependent stimulus was applied to evaluate the ABR threshold in two groups. n = 3 mice/6 ears. (B) Uniform Manifold Approximation and Projection plot visualized the single cell clustering colored by different cell types. Each color represents one cluster. (C, D) The distribution of cells derived from different sample origins. The cell cluster 15 is circled by a black circle

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The cellular heterogeneity in presbycusis-related cochlear tissue was evaluated by analyzing mRNA transcripts of the two groups of mice. After filtering the low-quality cells, a total of 10,966 cells were obtained, including 5165 cells in the sample of control group and 5801 cells in the sample of aged group. The average number of UMIs in each cell was ranged from 3636 to 4282 and the average number of genes in each cell was between 879 and 1021. After dimensionality reduction clustering, each single cell was unambiguously assigned to a distinct cluster. A total of 18 optimal cell clusters were visualized by UMAP based on shared nearest neighbor clustering algorithm (Fig. 1B). The distribution differences of the 18 clusters between the two groups is displayed in Fig. 1C and D. The cell numbers of clusters 1, 3, 6, 10, 11, 16 and 18 in the aged mice accounted for more than 50% of all cells in the corresponding clusters. Cell cluster 15, which included 136 cells, only appeared in the cochlea of aged mice (Fig. 1D).

Subsequently, the 18 cell clusters were annotated by FindAllMarkers and Single R with well-established marker genes. The heatmap of top 10 marker genes of each cluster is shown in Fig. 2 and the detail information of these marker genes is displayed in Supplementary Table 1. For example, Fcrla, Spib, Gm30211, and Pax5 were the top marker genes of B cells. Ncmap, Fam178b, Pllp, and Cldn19 were the top marker genes of inner pillar cells. Wnt6, Kcna6, Slc35f1, and Cadm2 were the top marker genes of inner phalangeal cells. The cell cluster 15 mainly expressed Ecrg4, Igfbp2, Folr1, and other top marker genes (Supplementary Fig. 1), which can be involved in the regulation of various biological processes such as immunity and metabolism.

Fig. 2
figure 2

The heatmap of the top ten marker genes in the 18 clusters. The X-axis is cell cluster, and the Y-axis is marker genes. Red indicates high expression and blue indicates low expression

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Unique gene expression signatures of cochlear subclusters in presbycusis

Annotation of these 18 clusters by marker genes resulted in 10 cell types, including myeloid cells, epithelial cells, B cells, endothelial cells, fibroblasts, T cells, inner pillar, inner phalangeal cells, neurons, and red blood cells (Fig. 3A). Eight distinct clusters of myeloid cells were identified, including cell clusters 1, 2, 3, 4, 6, 8, 14, and 15. Besides, combined with the dataset analysis and the marker genes selection reports in the previous literatures [18,19,20], clusters 5 and 9 were annotated to be epithelial cells, and both of them showed a decreased number in the cochlea of aged mice. Cells identified as myeloid cells and epithelial cells belong to multiple clusters, suggesting that these cell types were heterogeneous. In addition, although both clusters 5 and 9 were epithelial cells, their top marker gene expression was different. In addition, the counts of epithelial cells, inner pillar cells, inner phalangeal cells, T and B cells were decreased in the cochlear tissues of aged mice, while the counts of endothelial cells, neurons, fibrocytes, and red blood cells were increased in the aged samples (Fig. 3B).

Fig. 3
figure 3

Annotation of cell clusters. (A). Annotated cell types of the single cell clusters. (B). Histogram of the cellular proportions between samples from the two groups

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Differential expression analysis

To investigate the DEGs involved in the pathogenesis of presbycusis, we compared the genetic changes between young and aged mice and summarized the most representative signal pathways and biological processes for specific DEG enrichment. A total of 56 DEGs were screened from the aged cochlear tissue comparing with young samples according to the criteria of adjusted p-value < 0.05 (Table 1). Moreover, the DEGs were arranged by the fold change values, and the top 20 significant up- or down- regulated genes were visualized in the heatmap (Fig. 4A). Gene expression status was distinguishable between aged and young cochlear tissues. KEGG functional enrichment showed that the DEGs were mainly involved in “Toll-like receptor signaling pathway”, “Cytosolic DNA-sensing pathway”, “Leukocyte transendothelial migration”, “apoptosis”, “Chemokine signaling pathway”, “TNF signaling pathway”, “Rap1 signaling pathway” and “IL-17 signaling pathway” (Table 2).

Table 1 The list of 56 differentially expressed genes (DEGs) between control and aged mice
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Fig. 4
figure 4

Identifying the presbycusis-related genes and functional analysis. (A). Heatmap of top 20 genes with up-regulated or down-regulated expression in cochlear tissue. (B). The VENN diagram of cell-type specific DEGs

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Table 2 KEGG enrichment analysis of DEGs between control and aged groups
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Moreover, the cell-type specific gene expression changes were also analyzed between aged and young mice. A total of 119 DEGs were found in the epithelial cells of aged mice, of which 49 genes were up-regulated and 70 genes were down-regulated. A total of 38 DEGs were found in T cells, including 19 up-regulated and 19 down-regulated. There were 113 DEGs in inner pillar cells, including 52 up-regulated and 61 down-regulated. Meanwhile, a total of 242 DEGs were found in the inner phalangeal cells, including 105 up-regulated and 137 down-regulated. A total of 99 DEGs were screened from the endothelial cells, including 29 up-regulated and 70 down-regulated (Supplementary Table 2). VENN analysis of these DEGs showed that Ttr, Prl, Gh and Lyz2 were differentially expressed in all the five cell types (Fig. 4B).

KEGG enrichment analysis of the cell-type specific DEGs showed that the DEGs in epithelial cells were significantly associated with “TNF signaling pathway”, “IL-17 signaling pathway”, the DEGs in T cells were significantly associated with “cytokine-cytokine receptor interaction”, the DEGs in inner pillar cells were significantly associated with “TNF signaling pathway”, “Necroptosis”, “cellular senescence” and “c-type lectin receptor signaling pathway”, the DEGs in inner phalangeal cells were significantly associated with “PI3K-Akt signaling pathway”, “Oxidative phosphorylation”, and “RNA transport”, and the DEGs in endothelial cells were significantly associated with “Toll-like receptor signaling pathway”, “Cytokine-cytokine receptor interaction” and “Rap1 signaling pathway” (Supplementary Table 3).

Immunohistochemical verification of presbycusis-related proteins

The protein expression of five DEGs, including two upregulated genes, Enpp2 and Saa3, and three downregulated genes, Cxcl10, Ccl5 and Gh, was further verified by immunohistochemical analysis. As shown in Fig. 5, Enpp2, Cxcl10, Gh, Ccl5 and Saa3 markers can be detected in the mouse cochlea. Among them, Enpp2 and Saa3 were up-regulated in the aged mouse cochlea, while Cxcl10, Gh, and Ccl5 were down-regulated in the aged mouse cochlea.

Fig. 5
figure 5

Immunohistochemical verification for crucial molecules related to presbycusis. Five biological replicates of the whole cochlear tissues in each group were performed for each protein. The representative images for each protein are displayed

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Alterations of intercellular communication mediated by specific signaling pathways in presbycusis

To explore potential interactions among these presbycusis-related cell types, we performed CellChat analysis on the datasets. The global intercellular communication between the control and aged cochlear samples was quantified and visualized. We observed the general interaction number and interaction strength between fibroblast and other four cell types (T cell, B cell, inner phalangeal cell, and myeloid cell) were decreased in presbycusis status compared with that under healthy status (Fig. 6A and B).

Fig. 6
figure 6

Analysis of cellular communication by CellChat displayed the alterations of several pathways in normal and presbycusis. (A-B). Circle plots (left side) and heatmaps (right side) of interaction number and interaction strength among differential cell types. Blue lines or columns represented the communication decreased in disease condition, whereas red lines or columns indicate the communication increased compared with control. (C). Differences in overall information flow of the signaling pathways between control and aged presbycusis samples

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We also calculated the information flow of the signal, which was defined as communication probability among the cell types. Notably, 34 out of 48 pathways were highly activated both in control and in the aged cochlea. Compared with the control group, Fn1, Galectin, Spp1, Sema3, Fgf, Calcr, Gas, and Sema6 signals were turned off. Collagen, Cd52, and Ptn signals were significantly decreased, whereas Mpz, App, and Cxcl signals were increased (Fig. 6C).

Discussion

We conducted a single-cell transcriptome sequencing study on the mice cochlear tissue from young and aged group, identified 18 distinct transcriptionally defined clusters, corresponding to 10 cell types, including myeloid cells, epithelial cells, fibroblasts, inner pillar cells and inner phalangeal cells. Cellchat analysis revealed the intercellular communications of several cell types were greatly altered in presbycusis status, and specific signaling pathways changed were also observed, such as collagen, Cd52, and Cxcl signals. Moreover, numerous DEGs were screened from aged cochlear tissue, and these genes were mainly involved in immune, oxidative stress, apoptosis, and metabolic processes. Immunohistochemistry verification showed five (Enpp2, Cxcl10, Gh, Ccl5, and Saa3) markers could be detected in the mouse cochlea and displayed a significant differential expression in presbycusis.

Among these molecules, ectonucleotide pyrophosphatase/phosphodiesterase family member 2 (ENPP2) is ubiquitously expressed in human tissues, and plays a key role in the production of extracellular lysophosphatidic acid [21]. It is closely related to both senile diseases [22] and erastin-induced ferroptosis [23]. Here, we found ENPP2 was significantly up-regulated in the cochlea of presbycusis mice. Functional enrichment shows that ENPP2 is mainly involved in ferroptosis-related processes such as ion metabolism, lipid decomposition, and metabolism. Thus, we speculate that ENPP2 may be critically involved in the human presbycusis by regulating ferroptosis.

CCL5 encodes a protein of RANTES, which is a member of the chemokine family and serves a crucial role in inflammation and immune responses [24]. Previous studies have determined that CCL5 was involved in the human deafness via multiple pathways. For example, CCL5 may directly regulate the occurrence of noise-induced deafness through inducing cochlear oxidative stress [25]. The infiltration of CCL5 in eosinophilic otitis media (EOM) is significantly increased [26]. In our study, the expression of CCL5 mRNA is also deregulated in the cochlear sample of aged group, which is in accordance with its protein expression pattern detected by immunohistochemistry.

CXCL10 belongs to non-ELR subfamily. It is a class of chemokine induced by interferon-gamma that can chemotactic a variety of immune cells such as monocyte, T lymphocyte, and natural killer cell. CXCL10 regulates inflammatory responses via binding to the specific chemokine receptor CXCR3. The expression of CXCL10 is up-regulated in the presbycusis patients serum, suggesting that immune related gene CXCL10 plays an important role in the presbycusis occurrence [27].

Growth hormone (GH) is an anterior pituitary hormone secreted by the anterior pituitary gland. GH can affect the metabolism of sugar, protein and lipid in animals, as well as reproduction and immunity. GH is supposed to take part in the embryonic auditory development. GH deficiency led to hearing loss and central auditory process dysfunction. Furthermore, GH can stimulate the hair cells proliferation and synaptic transmission recovery after cochlear injury. Exogenous factors (noise, drugs or trauma) induce the GH releasing and activate downstream mediators to exert protective effects for the auditory pathways [28]. Here our data reveal the evident decrease of GH in the aged cochlea, which may be responsible for auditory transmission in presbycusis. Additionally, serum amyloid A (SAA) are evolutionary-conserved acute phase proteins in response to inflammation. The broad biological effects of SAA3 have been attributed to leukocyte recruitment, production of chemokines and MMPs [29]. There are few studies on the relationship between SAA3 and deafness.

The intercellular communications among differential cell types were analyzed and compared between two groups of cochleae. Here, we focused on those greatly altered signaling pathways in disease conditions, such as Collagen, Cd52, Ptn, Mpz, App, and Cxcl. For details, the hub of the Collagen signal is fibroblasts, and the outgoing signal to other cell types was significantly reduced in presbycusis (Supplementary Fig. 2). Collagen is the essential constituent of extracellular matrix (ECM), which plays an vital role in the structure maintaining of inner ear [30]. The expression of multiple collagen types (I-V, IX, and XI) has been detected in the inner ear [31, 32]. The mice lacking DDR1, a main class of collagen-binding receptor, displayed inner ear defects and hearing loss [30]. Collagen changes in the aged rats cochlea were also revealed, and the collagen fibers were markedly decreased in the inner ear area of connecting spiral ligament and stria vascular [33]. A recent study showed collagen proteins abundance were significant decreased in loud noise-induced hearing loss; the potential mechanisms were associated with proteotoxic stress and proteostasis network activation [34]. Considering this, we suggested that fibroblasts crosstalk with inner phalangeal cell and myeloid cell via collagen signaling in presbycusis.

Some limitations remain existed in our study. Firstly, the number of cochlear tissues used for single cell sequencing was small in this study. Due to limitation of fund, only one biological replicate was used for each age group. A notable finding of our study was that myeloid cells constitute the predominant cell population of samples in both young and aged groups. Besides, we noticed the counts of epithelial cells, inner pillar cells, inner phalangeal cells, T and B cells were decreased in the cochlear tissues of aged mice, while the counts of endothelial cells, neurons, fibrocytes, and red blood cells were increased in the aged samples. The abundance of immune cells might because that the tissues used in the single cell sequencing included the bony shell of the cochlea, which contains a significant amount of bone marrow immune cells. However, these discrepancies warrant thorough confirmation with an additional observation using histology or flow cytometry since only one biological replicate was used. Second, due to the known technological difficulties associated with isolating mature neurons with intact dendrites and axons as well as the scarcity in the number of HCs, we only captured a small number of spiral ganglion neurons and HCs were not clustered and we could not assess the crosstalk effect between HCs and other cell types. Therefore, more samples across multiple developmental time points should be acquired for the cell type’s specific changes detection.

In this study, we established a cell-type-specific transcriptome profile of the cochlea of aged mice, and verified significantly DEGs by immunohistochemical assay. In addition, we performed pathway analysis to identify the underlying mechanisms by which presbycusis occurs. The completion of this study promoted new ideas for further revealing the pathogenesis of presbycusis, and provided novel potential targets for the development of therapeutic drugs.

Data availability

The datasets generated during the current study are available from the NCBI SRA database with accession number of PRJNA1013607.

Abbreviations

ARHL:

Age-related hearing loss

DEGs:

Differentially expressed genes

scRNA-seq:

Hair cells (HCs); single-cell sequencing

ABR:

Auditory brainstem response

SPL:

Sound pressure level

EDTA:

Ethylenediaminetetraacetic acid

SDs:

Standard deviations

UMI:

Unique molecular identifier

PCA:

Principal component analysis

tSNE:

t-distributed stochastic neighbor embedding

GO:

Gene ontology

KEGG:

Kyoto Encyclopedia of Genes and Genomes

ENPP2:

Ectonucleotide pyrophosphatase/phosphodiesterase family member 2

ENPP2:

Ectonucleotide pyrophosphatase/phosphodiesterase family member 2

GH:

Growth hormone

SAA:

Serum amyloid A

ECM:

Extracellular matrix

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Acknowledgements

Not applicable.

Funding

This study was supported by the Young and middle-aged medical high-end talents in Chongqing (The 7th batch), Chongqing medical scientific research general project (Joint project of Chongqing Health Commission and Science and Technology Bureau) (No. cstc2021jcyj-bshX0026), Chongqing Technology innovation and application development special project (No. CSTB2023TIAD-KPX0059), Chongqing young and middle-aged medical excellence team (The 1st batch), Chongqing Talent Program. Innovative leading talents in the medical field (2021), Chongqing medical scientific research major project (Joint project of Chongqing Health Commission and Science and Technology Bureau) (No. 2022DBXM006) and General Program of Chongqing Natural Science Foundation (No. cstc2021jcyj-msxmX0128).

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Authors and Affiliations

  1. Department of Otorhinolaryngology Head and Neck Surgery, Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, 401147, China

    Juhong Zhang, Wenfang Sun, Menglong Feng, Zhiji Chen, Hailan Mo, Haizhu Ma, Li Yang, Shaojing Kuang, Yaqin Hu, Jialin Guo, Yijun Li & Wei Yuan

  2. Department of Otorhinolaryngology Head and Neck Surgery and Hearing Screening and Diagnosis Center, Jinan Maternity and Child Care Hospital, Jinan, Shandong, China

    Lili Xiang

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  1. Juhong Zhang
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  2. Lili Xiang
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Contributions

JZ carried out the conception and design of the research, JZ, WS, YL, SK and WY participated in the acquisition of data. MF and ZC carried out the analysis and interpretation of data. HLM and HZM performed the statistical analysis. JZ and SK drafted the manuscript. YH, JG, YJL, LLX and WY revised the manuscript for important intellectual content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Wei Yuan.

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Ethics approval and consent to participate

All animal experiments were reported in accordance with ARRIVE guidelines and the experimental procedures were approved by the Laboratory Animal Welfare and Ethics Committee of the Third Military Medical University (ID: IACUC-CQMU-2022-0030).

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The authors declare no competing interests.

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Zhang, J., Xiang, L., Sun, W. et al. Single cell RNA sequencing provides novel cellular transcriptional profiles and underlying pathogenesis of presbycusis. BMC Med Genomics 17, 237 (2024). https://doi.org/10.1186/s12920-024-02001-7

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Keywords

BMC Medical Genomics

ISSN: 1755-8794

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