Department of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Department of Internal Medicine, Sichuan Academy of Medical Science and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Front Immunol. 2023 Oct 19;14:1288098. doi: 10.3389/fimmu.2023.1288098. eCollection 2023.
BACKGROUND: Dermatomyositis (DM) is an autoimmune and inflammatory disease that can affect the lungs, causing interstitial lung diseases (ILD). However, the exact pathophysiological mechanisms underlying DM-ILD are unknown. Idiopathic pulmonary fibrosis (IPF) belongs to the broader spectrum of ILD and evidence shows that common pathologic pathways might lie between IPF and DM-ILD. METHODS: We retrieved gene expression profiles of DM and IPF from the Gene Expression Omnibus (GEO) and utilized weighted gene co-expression network analysis (WGCNA) to reveal their co-expression modules. We then performed a differentially expressed gene (DEG) analysis to identify common DEGs. Enrichment analyses were employed to uncover the hidden biological pathways. Additionally, we conducted protein-protein interaction (PPI) networks analysis, cluster analysis, and successfully found the hub genes, whose levels were further validated in DM-ILD patients. We also examined the relationship between hub genes and immune cell abundance in DM and IPF. Finally, we conducted a common transcription factors (TFs)-genes network by NetworkAnalyst. RESULTS: WGCNA revealed 258 intersecting genes, while DEG analysis identified 66 shared genes in DM and IPF. All of these genes were closely related to extracellular matrix and structure, cell-substrate adhesion, and collagen metabolism. Four hub genes (, , , and ) were derived through intersecting the top 30 genes of the WGCNA and DEG sets. They were validated as active transcripts and showed diagnostic values for DM and IPF. However, ssGSEA revealed distinct infiltration patterns in DM and IPF. These four genes all showed a positive correlation with immune cells abundance in DM, but not in IPF. Finally, we identified one possible key transcription factor, MYC, that interact with all four hub genes. CONCLUSION: Through bioinformatics analysis, we identified common hub genes and shared molecular pathways underlying DM and IPF, which provides valuable insights into the intricate mechanisms of these diseases and offers potential targets for diagnostic and therapeutic interventions.
背景：皮肌炎（DM）是一种自身免疫性和炎症性疾病，可影响肺部，导致间质性肺疾病（ILD）。然而，DM-ILD 的确切病理生理机制尚不清楚。特发性肺纤维化（IPF）属于ILD 的更广泛范畴，有证据表明，IPF 和 DM-ILD 之间可能存在共同的病理途径。
方法：我们从基因表达综合数据库（GEO）中检索了 DM 和 IPF 的基因表达谱，并利用加权基因共表达网络分析（WGCNA）来揭示它们的共表达模块。然后，我们进行了差异表达基因（DEG）分析，以确定共同的 DEG。富集分析用于揭示隐藏的生物学途径。此外，我们进行了蛋白质-蛋白质相互作用（PPI）网络分析、聚类分析，并成功找到了枢纽基因，这些基因在 DM-ILD 患者中进一步得到验证。我们还研究了 DM 和 IPF 中枢纽基因与免疫细胞丰度的关系。最后，我们通过 NetworkAnalyst 进行了共同转录因子（TFs）-基因网络分析。
结果：WGCNA 揭示了 258 个重叠基因，而 DEG 分析确定了 DM 和 IPF 之间的 66 个共同基因。所有这些基因都与细胞外基质和结构、细胞-基质粘附和胶原代谢密切相关。通过 WGCNA 和 DEG 集合的前 30 个基因的交集，得到了 4 个枢纽基因（、、、和）。它们被验证为活跃转录物，对 DM 和 IPF 具有诊断价值。然而，ssGSEA 显示 DM 和 IPF 之间存在明显不同的浸润模式。这四个基因在 DM 中与免疫细胞丰度呈正相关，但在 IPF 中则没有。最后，我们确定了一个可能的关键转录因子 MYC，它与所有四个枢纽基因相互作用。
结论：通过生物信息学分析，我们确定了 DM 和 IPF 之间共同的枢纽基因和共享的分子途径，这为这些疾病的复杂机制提供了有价值的见解，并为诊断和治疗干预提供了潜在的靶点。
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