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端粒功能障碍和免疫浸润在特发性肺纤维化中的作用:来自生物信息学分析的新见解

Role of telomere dysfunction and immune infiltration in idiopathic pulmonary fibrosis: new insights from bioinformatics analysis.

作者信息

Fu Chenkun, Tian Xin, Wu Shuang, Chu Xiaojuan, Cheng Yiju, Wu Xiao, Yang Wengting

机构信息

Department of Respiratory and Critical Care Medicine, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.

Department of Respiratory and Critical Care Medicine, The Fourth People's Hospital of Guiyang, Guiyang, China.

出版信息

Front Genet. 2024 Sep 13;15:1447296. doi: 10.3389/fgene.2024.1447296. eCollection 2024.

Abstract

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive interstitial lung disease characterized by unexplained irreversible pulmonary fibrosis. Although the etiology of IPF is unclear, studies have shown that it is related to telomere length shortening. However, the prognostic value of telomere-related genes in IPF has not been investigated.

METHODS

We utilized the GSE10667 and GSE110147 datasets as the training set, employing differential expression analysis and weighted gene co-expression network analysis (WGCNA) to screen for disease candidate genes. Then, we used consensus clustering analysis to identify different telomere patterns. Next, we used summary data-based mendelian randomization (SMR) analysis to screen core genes. We further evaluated the relationship between core genes and overall survival and lung function in IPF patients. Finally, we performed immune infiltration analysis to reveal the changes in the immune microenvironment of IPF.

RESULTS

Through differential expression analysis and WGCNA, we identified 35 significant telomere regulatory factors. Consensus clustering analysis revealed two distinct telomere patterns, consisting of cluster A (n = 26) and cluster B (n = 19). Immune infiltration analysis revealed that cluster B had a more active immune microenvironment, suggesting its potential association with IPF. Using GTEx eQTL data, our SMR analysis identified two genes with potential causal associations with IPF, including GPA33 (P = 0.0013; P = 0.0741) and MICA (P = 0.0112; P = 0.9712). We further revealed that the expression of core genes is associated with survival time and lung function in IPF patients. Finally, immune infiltration analysis revealed that NK cells were downregulated and plasma cells and memory B cells were upregulated in IPF. Further correlation analysis showed that GPA33 expression was positively correlated with NK cells and negatively correlated with plasma cells and memory B cells.

CONCLUSION

Our study provides a new perspective for the role of telomere dysfunction and immune infiltration in IPF and identifies potential therapeutic targets. Further research may reveal how core genes affect cell function and disease progression, providing new insights into the complex mechanisms of IPF.

摘要

背景

特发性肺纤维化(IPF)是一种慢性进行性间质性肺疾病,其特征为无法解释的不可逆性肺纤维化。尽管IPF的病因尚不清楚,但研究表明它与端粒长度缩短有关。然而,端粒相关基因在IPF中的预后价值尚未得到研究。

方法

我们利用GSE10667和GSE110147数据集作为训练集,采用差异表达分析和加权基因共表达网络分析(WGCNA)来筛选疾病候选基因。然后,我们使用一致性聚类分析来识别不同的端粒模式。接下来,我们使用基于汇总数据的孟德尔随机化(SMR)分析来筛选核心基因。我们进一步评估了核心基因与IPF患者总生存和肺功能之间的关系。最后,我们进行了免疫浸润分析,以揭示IPF免疫微环境的变化。

结果

通过差异表达分析和WGCNA,我们鉴定出35个重要的端粒调节因子。一致性聚类分析揭示了两种不同的端粒模式,即A簇(n = 26)和B簇(n = 19)。免疫浸润分析显示,B簇具有更活跃的免疫微环境,提示其与IPF的潜在关联。利用GTEx eQTL数据,我们的SMR分析鉴定出两个与IPF有潜在因果关联的基因,包括GPA33(P = 0.0013;P = 0.0741)和MICA(P = 0.0112;P = 0.9712)。我们进一步揭示,核心基因的表达与IPF患者的生存时间和肺功能相关。最后,免疫浸润分析显示,IPF中自然杀伤细胞下调,浆细胞和记忆B细胞上调。进一步的相关性分析表明,GPA33表达与自然杀伤细胞呈正相关,与浆细胞和记忆B细胞呈负相关。

结论

我们的研究为端粒功能障碍和免疫浸润在IPF中的作用提供了新的视角,并确定了潜在的治疗靶点。进一步的研究可能揭示核心基因如何影响细胞功能和疾病进展,为IPF的复杂机制提供新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/feea/11427275/8ace8f780e47/fgene-15-1447296-g001.jpg

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