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程序性细胞死亡与增生性瘢痕之间的因果联系:多组学孟德尔随机化的综合分析及初步实验验证

Causal links between programmed cell death and hypertrophic scars: Integrative analysis of multi-omics Mendelian randomization and preliminary experimental validation.

作者信息

Zhang Yushen, Zhao Chenyuyao, Zhao Ran

机构信息

Department of Burns and Plastic Surgery, Shandong Provincial Hospital Affiliated To Shandong First Medical University, Jinan, Shandong 250021, China.

Department of Burns and Plastic Surgery, Shandong Provincial Hospital Affiliated To Shandong First Medical University, Jinan, Shandong 250021, China.

出版信息

Burns. 2025 Aug 19;51(8):107667. doi: 10.1016/j.burns.2025.107667.

Abstract

OBJECTIVE

This study aims to explore the causal relationship between programmed cell death (PCD) genes and the formation of hypertrophic scars (HS) using integrative multi-omics analysis (including DNA methylation, gene expression, and protein abundance) alongside preliminary experimental validation.

METHODS

We leveraged publicly available databases (eQTL Gen, UKB-PPP, and FinnGen) to obtain quantitative trait loci (QTLs) data of DNA methylation, gene expression and protein abundance. We employed Mendelian randomization (MR) approaches to uncover causal relationships and validate robustness. The methods used included inverse variance weighted (IVW) analysis, false discovery rate (FDR), Cochran's Q test, I² statistic, MR-Egger regression, MR-PRESSO, leave-one-out method, co-localization analysis, and Steiger filtering test. Then, the multi-omic MR results were integrated and three tiers of genes were identified. Further, the tier 1 genes were chosen to perform drug prediction in DSigDB and molecular docking analyses with Autodock Vina. Lastly, the effects of the selected genes and drugs in HS were validated at both the tissue and cellular levels.

RESULTS

Through integrating multi-omics data, we identified one tier 1 gene (GLB1), twelve tier 2 genes (including DAPK2, AP4E1, ARSA, CTSF, MSH6, NEDD4, PDK1, PELI3, RB1, UNC13D, CTSC, and GZMB), and two tier 3 genes (NOS3 and ITGA6), all of which show varying associations with HS. Particularly, the GLB1(cg05120113) was causal associated with HS risk in DNA methylation (OR=1.0972, 95 % CI: 1.0532-1.1430, FDR=0.0163), gene expression (OR=1.2923, 95 % CI: 1.1816-1.4135, FDR<0.001) and protein abundance (OR=1.5430, 95 % CI: 1.3296-1.7905, FDR<0.001). The candidate drugs for GLB1 included Fulvestrant (adjusted P = 0.046, Affinity=-8.8 kcal/mol) and Cyperquat (adjusted P = 0.036, Affinity=-6.2 kcal/mol). Further, the GLB1 expression and inhibitory effect of Fulvestrant were validated in HS tissues and HSFs. Additionally, significant changes in the mRNA and protein expression levels of fibrosis-related markers, including TGF-β1 and α-SMA, were observed in HSFs.

FINDINGS

This study provides robust evidence for the causal involvement of PCD genes in HS formation and identified GLB1 along with 14 other potential genes. Fulvestrant demonstrated therapeutic potential for HS by modulating fibrosis-related pathways in fibroblasts.

摘要

目的

本研究旨在通过整合多组学分析(包括DNA甲基化、基因表达和蛋白质丰度)以及初步实验验证,探索程序性细胞死亡(PCD)基因与增生性瘢痕(HS)形成之间的因果关系。

方法

我们利用公开可用的数据库(eQTL Gen、UKB-PPP和FinnGen)获取DNA甲基化、基因表达和蛋白质丰度的数量性状位点(QTL)数据。我们采用孟德尔随机化(MR)方法来揭示因果关系并验证稳健性。使用的方法包括逆方差加权(IVW)分析、错误发现率(FDR)、Cochran's Q检验、I²统计量、MR-Egger回归、MR-PRESSO、留一法、共定位分析和Steiger过滤检验。然后,整合多组学MR结果并鉴定出三层基因。此外,选择第一层基因在DSigDB中进行药物预测,并使用Autodock Vina进行分子对接分析。最后,在组织和细胞水平上验证所选基因和药物对HS的影响。

结果

通过整合多组学数据,我们鉴定出一个第一层基因(GLB1)、十二个第二层基因(包括DAPK2、AP4E1、ARSA、CTSF、MSH6、NEDD4、PDK1、PELI3、RB1、UNC13D、CTSC和GZMB)和两个第三层基因(NOS3和ITGA6),所有这些基因与HS均有不同程度的关联。特别是,GLB1(cg05120113)在DNA甲基化(OR=1.0972,95%CI:1.0532-1.1430,FDR=0.0163)、基因表达(OR=1.2923,95%CI:1.1816-1.4135,FDR<0.001)和蛋白质丰度(OR=1.5430,95%CI:1.3296-1.7905,FDR<0.001)方面与HS风险存在因果关联。GLB1的候选药物包括氟维司群(校正P=0.046,亲和力=-8.8 kcal/mol)和环丙喹(校正P=0.036,亲和力=-6.2 kcal/mol)。此外,在HS组织和人皮肤成纤维细胞(HSFs)中验证了GLB1的表达以及氟维司群的抑制作用。另外,在HSFs中观察到纤维化相关标志物(包括TGF-β1和α-SMA)的mRNA和蛋白质表达水平有显著变化。

结论

本研究为PCD基因参与HS形成提供了有力证据,并鉴定出GLB1以及其他14个潜在基因。氟维司群通过调节成纤维细胞中的纤维化相关途径,显示出对HS的治疗潜力。

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