氨来呫诺通过下调S100A12降低脓毒症中新发房颤的风险:一项孟德尔随机化研究
Amlexanox reduces new-onset atrial fibrillation risk in sepsis by downregulating S100A12: a Mendelian randomization study.
作者信息
Yang Hang, Feng Lin, Jiang Zhenjie, Wu Xiaodan, Zeng Kai
机构信息
Department of Anesthesiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Department of Hematology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
出版信息
Front Cardiovasc Med. 2024 Oct 9;11:1401314. doi: 10.3389/fcvm.2024.1401314. eCollection 2024.
BACKGROUND
Sepsis is characterized by high morbidity and mortality rates, alongside limited therapeutic efficacy. Atrial fibrillation (AF), the most common arrhythmia, has been closely linked to sepsis in prior research. However, the specific mechanisms through which sepsis leads to new-onset AF remain poorly understood. This study focuses on identifying critical genes that are dysregulated in the development of new-onset AF within the context of sepsis, with the goal of uncovering new potential targets for its diagnosis and prevention.
MATERIAL AND METHODS
Our study began by applying Mendelian Randomization (MR) to assess the causal link between sepsis and AF. We then sourced sepsis and AF datasets from the Gene expression Omnibus (GEO) database. Using Weighted Gene Co-expression Network Analysis (WGCNA), we pinpointed key modules and genes associated with both sepsis and AF conditions. Protein-protein interaction (PPI) network was constructed. The Transcriptional Regulatory Relationships Unravelled by Sentence-based Text-mining (TRRUST) database helped build the transcription factor (TF) interaction network. Key genes were scrutinized through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) to delve into their roles in new-onset AF's pathophysiology during sepsis. We employed the CIBERSORT algorithm to evaluate immune infiltration and the association between key genes and immune cells. The Connectivity Map (CMap) database facilitated the prediction of potential small molecule compounds targeting key genes. To culminate, an acute sepsis mouse model was developed to validate the implicated mechanisms of key genes involved in new-onset AF during sepsis, and to assess the prophylactic effectiveness of identified drug candidates.
RESULTS
MR revealed potential independent risk factors for new-onset AF in sepsis. S100A12 was identified as a core interaction gene with elevated levels in sepsis and AF, underscoring its diagnostic and predictive significance. S100A12, along with associated genes, was mainly linked to immune and inflammatory response signaling pathways, correlating with immune cell levels. Targeting S100A12 identifies five potential small molecule therapeutics: amlexanox, balsalazide, methandriol, olopatadine, and tiboloe. In animal studies, acute sepsis increased S100A12 expression in serum and atrial tissues, correlating positively with inflammatory markers (IL-1β, IL-6, TNF-α) and negatively with heart rate, indicating a predisposition to AF. Early amlexanox administration can reduced S100A12 expression, dampened inflammation, and lessened new-onset AF risk in sepsis.
CONCLUSION
This study demonstrates that sepsis may independently increase the risk of new-onset AF. We identified S100A12 as a key gene influencing the new-onset AF in sepsis through immune regulation, presenting considerable diagnostic and predictive value. Notably, amlexanox, by targeting S100A12 emerges as the most clinical relevant intervention for managing new-onset AF in sepsis patients.
背景
脓毒症的特点是发病率和死亡率高,治疗效果有限。心房颤动(AF)是最常见的心律失常,先前的研究已将其与脓毒症紧密联系起来。然而,脓毒症导致新发房颤的具体机制仍知之甚少。本研究聚焦于识别在脓毒症背景下新发房颤发展过程中失调的关键基因,旨在揭示其诊断和预防的新潜在靶点。
材料与方法
我们的研究首先应用孟德尔随机化(MR)来评估脓毒症与房颤之间的因果关系。然后,我们从基因表达综合数据库(GEO)中获取脓毒症和房颤数据集。使用加权基因共表达网络分析(WGCNA),我们确定了与脓毒症和房颤状况相关的关键模块和基因。构建了蛋白质 - 蛋白质相互作用(PPI)网络。基于句子的文本挖掘揭示的转录调控关系(TRRUST)数据库帮助构建了转录因子(TF)相互作用网络。通过基因本体(GO)、京都基因与基因组百科全书(KEGG)、基因集富集分析(GSEA)和基因集变异分析(GSVA)对关键基因进行仔细研究,以深入了解它们在脓毒症期间新发房颤病理生理学中的作用。我们采用CIBERSORT算法评估免疫浸润以及关键基因与免疫细胞之间的关联。连通性图谱(CMap)数据库有助于预测靶向关键基因的潜在小分子化合物。最后,建立了急性脓毒症小鼠模型,以验证脓毒症期间新发房颤相关关键基因的潜在机制,并评估已鉴定候选药物的预防效果。
结果
MR揭示了脓毒症中新发房颤的潜在独立危险因素。S100A12被确定为脓毒症和房颤中水平升高的核心相互作用基因,凸显了其诊断和预测意义。S100A12及其相关基因主要与免疫和炎症反应信号通路相关,与免疫细胞水平相关。靶向S100A12可识别出五种潜在的小分子治疗药物:氨来呫诺、巴柳氮、美雄醇、奥洛他定和替勃龙。在动物研究中,急性脓毒症增加了血清和心房组织中S100A12的表达,与炎症标志物(IL - 1β、IL - 6、TNF - α)呈正相关,与心率呈负相关,表明易患房颤。早期给予氨来呫诺可降低S100A中的表达,减轻炎症,并降低脓毒症中新发房颤的风险。
结论
本研究表明脓毒症可能独立增加新发房颤的风险。我们确定S100A12是通过免疫调节影响脓毒症中新发房颤的关键基因,具有相当大的诊断和预测价值。值得注意的是,氨来呫诺通过靶向S100A12成为脓毒症患者新发房颤管理中最具临床相关性的干预措施。
相似文献
Front Cardiovasc Med. 2024-10-9
Front Cardiovasc Med. 2024-7-11
Front Cardiovasc Med. 2024-8-29
Altern Ther Health Med. 2024-3
本文引用的文献
Biomolecules. 2023-8-31
Int J Mol Sci. 2023-5-18
ESC Heart Fail. 2023-8
Crit Care. 2023-3-4