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年龄相关性听力损失的预后基因表达特征

Prognostic Gene Expression Signature for Age-Related Hearing Loss.

作者信息

Peng Lu, Li Nianshen, Huang Zhanrong, Qiu Chunqin, Yin Shihua

机构信息

Department of Otorhinolaryngology Head and Neck Surgery, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.

出版信息

Front Med (Lausanne). 2022 Apr 7;9:814851. doi: 10.3389/fmed.2022.814851. eCollection 2022.

DOI:10.3389/fmed.2022.814851
PMID:35463035
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9021842/
Abstract

BACKGROUND

Our study aimed to determine the pathological mechanism of presbycusis at the molecular level, and determine potential biomarkers for the same.

METHODS

Differentially expressed genes (DEGs) for presbycusis were obtained by analyzing the microarray data sets (GSE6045 and GSE49543) downloaded from the Gene Expression Omnibus (GEO). Gene ontology (GO), Kyoto Encyclopedia of Genes and Genome (KEGG) pathway, and protein-protein interaction (PPI) network analyses, and Gene Set Enrichment Analysis (GSEA) were performed to analyze the biological functions, molecular pathways, autophagy-related molecular markers, and the immune microenvironment of the DEGs in presbycusis. Then the prognostic roles of the hub genes were analyzed and verified .

RESULTS

In the old mild hearing loss group (27.7 ± 3.4 months old), 27 down-regulated and 99 up-regulated genes were significantly differentially expressed compared with those in the young control group (3.5 ± 0.4 months old). In the old severe hearing loss group (30.6 ± 1.9 months old), 131 down-regulated and 89 up-regulated genes were significantly differentially expressed compared with those in the young control group. The results of the GO, GSEA, KEGG pathway, and immune infiltration analyses showed that the enrichment terms were mainly focused on immune response in mild presbycusis, and immune response and cell death in severe presbycusis. In the PPI network, autophagy-related genes showed the highest node scores in mild presbycusis; whereas showed the highest scores in severe presbycusis. In the GSE49543 data set, four genes () were used to construct the prognostic model, and those four genes were significantly up-regulated in the rat model of presbycusis.

CONCLUSION

Our study is the first to report the difference in autophagy factors and immune microenvironment among different degrees of hearing loss in presbycusis. Furthermore, we provide the prognostic gene expression signature for age-related hearing loss, intending to develop preventative therapies.

摘要

背景

我们的研究旨在从分子水平确定老年性聋的病理机制，并确定其潜在的生物标志物。

方法

通过分析从基因表达综合数据库（GEO）下载的微阵列数据集（GSE6045和GSE49543），获得老年性聋的差异表达基因（DEG）。进行基因本体（GO）、京都基因与基因组百科全书（KEGG）通路、蛋白质-蛋白质相互作用（PPI）网络分析以及基因集富集分析（GSEA），以分析老年性聋中DEG的生物学功能、分子通路、自噬相关分子标志物和免疫微环境。然后分析并验证枢纽基因的预后作用。

结果

在老年轻度听力损失组（27.7±3.4月龄）中，与年轻对照组（3.5±0.4月龄）相比，有27个下调基因和99个上调基因存在显著差异表达。在老年重度听力损失组（30.6±1.9月龄）中，与年轻对照组相比，有131个下调基因和89个上调基因存在显著差异表达。GO、GSEA、KEGG通路和免疫浸润分析结果表明，富集术语在轻度老年性聋中主要集中于免疫反应，在重度老年性聋中主要集中于免疫反应和细胞死亡。在PPI网络中，自噬相关基因在轻度老年性聋中显示出最高的节点分数；而在重度老年性聋中显示出最高分数。在GSE49543数据集中，使用四个基因（）构建预后模型，这四个基因在老年性聋大鼠模型中显著上调。

结论

我们的研究首次报道了老年性聋不同程度听力损失之间自噬因子和免疫微环境的差异。此外，我们提供了与年龄相关听力损失的预后基因表达特征，旨在开发预防性治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/af821923615e/fmed-09-814851-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/ebc6a7dedb6f/fmed-09-814851-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/b9268e914c06/fmed-09-814851-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/302fecee78d9/fmed-09-814851-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/4cef8d2af86d/fmed-09-814851-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/7f559c5c39c2/fmed-09-814851-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/b8b15ea04a98/fmed-09-814851-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/a15a1796305c/fmed-09-814851-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/14910803b872/fmed-09-814851-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/af821923615e/fmed-09-814851-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/ebc6a7dedb6f/fmed-09-814851-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/b9268e914c06/fmed-09-814851-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/302fecee78d9/fmed-09-814851-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/4cef8d2af86d/fmed-09-814851-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/7f559c5c39c2/fmed-09-814851-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/b8b15ea04a98/fmed-09-814851-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/a15a1796305c/fmed-09-814851-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/14910803b872/fmed-09-814851-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a0e/9021842/af821923615e/fmed-09-814851-g009.jpg

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