Identification and mechanistic analysis of shared biomarkers and pathogenesis in acute pancreatitis and sepsis based on differential gene expression and protein interaction networks.

基于差异基因表达和蛋白质相互作用网络,对急性胰腺炎和脓毒症的共有生物标志物和发病机制进行鉴定和机制分析

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作者:Lu Weina, Mao Yifeng, Cai Shangwen, Chen Qingqing, Xu Panpan, Xu Chenghua, Zheng Cheng, Lan Jian
Acute pancreatitis (AP) is a common gastrointestinal inflammatory disease that requires hospitalization, with 40-70% of patients in moderate to severe stages potentially developing sepsis, which is closely related to high mortality rates and poor prognosis. Therefore, early identification of AP patients at risk of developing sepsis is crucial for reducing mortality. This study aims to identify core genes associated with sepsis to provide new core genes for early warning and management of patients with acute pancreatitis. The study utilized the GSE54514, GSE57065, GSE95233, and GSE194331 datasets for analysis, employing weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network construction. Six core genes were identified using two machine learning methods and validated with the GSE3644 and GSE28750 datasets. The analysis revealed that the identified core genes (NDUFA1, COX7A2, COX7B, UQCRQ, SNRPG, and NDUFA4) are related to the oxidative phosphorylation (OxPhos) pathway, and significant differences were observed in the immune cell composition between AP and sepsis patients. SNRPG may play a role in the progression from AP to sepsis by regulating NDUFA4, linking it to cellular metabolism and redox balance. The newly identified core genes and their associated molecular mechanisms provide important clinical insights into the progression of acute pancreatitis to sepsis, potentially offering new research directions for future therapeutic strategies. Clinical trial number: This study was approved by the Ethics Committee of (Municipal Hospital affiliated to Taizhou University), in accordance with the Declaration of Helsinki. Approval number: LWSL202400220.

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