Identification and Validation of Key Genes Related to Arginine Methylation Modification in Sepsis Using Transcriptome Combined with Mendelian Randomization Analysis.

IF 2.7 3区医学 Q2 CRITICAL CARE MEDICINE

SHOCK Pub Date : 2026-08-01 Epub Date: 2025-10-21 DOI:10.1097/SHK.0000000000002741

Peng Huang, Meifeng Wang, Weihong Hong, Jinyuan Kang, Yuyang Li, Ying Li, Xiao Lin

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引用次数: 0

Abstract

Background: Patients with sepsis often exhibit a decrease in lymphatic numbers, which can be facilitated by protein arginine methyltransferase (PRMT). However, it is unclear how PRMT contributes to lymphopenia in sepsis.

Methods: This study employed the sepsis-related datasets (GSE65682 and GSE134347) and nine PRMT genes. First, we intersected the differentially expressed genes with the weighted gene co-expression network analysis module genes to identify differentially expressed PRMT-related genes. Thereafter, candidate key genes were obtained after Mendelian randomization analysis and machine learning screening. Eventually, we subjected key genes identified by expression analysis and receiver operating characteristic curves to gene set enrichment analysis, immune infiltration analysis, immune checkpoint analysis, molecular docking, regulatory networks construction, and nomogram development.

Results: We first intersected 4,246 differentially expressed genes with 1,884 PRMT scoring module genes to obtain 969 differentially expressed PRMT-related genes. Further Mendelian randomization analysis and machine learning jointly identified five candidate genes ( CRLF3 , ELAC2 , PBX2 , MCTP2 , and EMB ). Among these, ELAC2 , PBX2 , MCTP2 , and EMB demonstrated consistent expression trends, with the area under the curve values of the receiver operating characteristic curve exceeding 0.7 in GSE65682 and GSE134347. Therefore, they were defined as key PRMT-related genes. The gene set enrichment analysis showed enrichment in cytoplasmic translation ( ELAC2 , MCTP2 ), noncoding RNA metabolism ( EMB ), and metabolic processes ( PBX2 ). The immune infiltration analysis revealed a significant correlation between PBX2 and neutrophils, as well as between ELAC2 / MCTP2 / EMB with activated natural killer cells, CD8+ T cells.

Conclusion: In this study, ELAC2 , PBX2 , MCTP2 , and EMB were identified as key genes related to PRMT for sepsis, which provided a theoretical basis for the study of sepsis.

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利用转录组结合孟德尔随机化分析鉴定和验证脓毒症中精氨酸甲基化修饰相关的关键基因。

背景：脓毒症患者经常表现为淋巴细胞数量减少，这可以通过蛋白精氨酸甲基转移酶（PRMT）促进。然而，目前尚不清楚PRMT如何导致败血症中的淋巴细胞减少。方法：本研究采用败血症相关数据集（GSE65682和GSE134347）和9个PRMT基因。首先，我们将差异表达基因（deg）与加权基因共表达网络分析（WGCNA）模块基因相交，以鉴定de - prmt相关基因（DE-PRMT-RGs）。然后，通过孟德尔随机化（MR）分析和机器学习筛选获得候选关键基因。最后，我们将通过表达分析和受试者工作特征（ROC）曲线鉴定出的关键基因进行基因集富集分析（GSEA）、免疫浸润分析、免疫检查点分析、分子对接、调控网络构建和nomogram开发。结果：我们首先将4246个deg与1884个PRMT评分模块基因相交，得到969个DE-PRMT-RGs。进一步的MR分析和机器学习共同确定了5个候选基因（CRLF3、ELAC2、PBX2、MCTP2和EMB）。其中，ELAC2、PBX2、MCTP2和EMB的表达趋势一致，GSE65682和GSE134347的ROC曲线下面积（AUC）值均超过0.7。因此，它们被定义为关键的prmt相关基因。GSEA分析显示细胞质翻译（ELAC2, MCTP2），非编码RNA代谢（EMB）和代谢过程（PBX2）富集。免疫浸润分析显示PBX2与中性粒细胞、ELAC2/MCTP2/EMB与活化的NK细胞、CD8+ T细胞有显著相关性。结论：本研究确定了ELAC2、PBX2、MCTP2和EMB为脓毒症PRMT相关的关键基因，为脓毒症的研究提供了理论依据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

SHOCK 医学-外科

CiteScore

6.20

自引率

3.20%

发文量

199

审稿时长

1 months

期刊介绍： SHOCK®: Injury, Inflammation, and Sepsis: Laboratory and Clinical Approaches includes studies of novel therapeutic approaches, such as immunomodulation, gene therapy, nutrition, and others. The mission of the Journal is to foster and promote multidisciplinary studies, both experimental and clinical in nature, that critically examine the etiology, mechanisms and novel therapeutics of shock-related pathophysiological conditions. Its purpose is to excel as a vehicle for timely publication in the areas of basic and clinical studies of shock, trauma, sepsis, inflammation, ischemia, and related pathobiological states, with particular emphasis on the biologic mechanisms that determine the response to such injury. Making such information available will ultimately facilitate improved care of the traumatized or septic individual.