Kuang Zhongshu, Li Runrong, Lu Su, Wang Yusong, Luo Yue, Shen Yongqi, Yuan Li, Yang Yilin, Song Zhenju, Jiang Ning, Tong Chaoyang
1Department of Emergency Medicine, Zhongshan Hospital, Fudan University, Shanghai 200030, China.
2State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200030, China.
World J Emerg Med. 2025 May 1;16(3):248-255. doi: 10.5847/wjem.j.1920-8642.2025.063.
Community-acquired pneumonia (CAP) represents a significant public health concern due to its widespread prevalence and substantial healthcare costs. This study was to utilize an integrated proteomic and metabolomic approach to explore the mechanisms involved in severe CAP.
We integrated proteomics and metabolomics data to identify potential biomarkers for early diagnosis of severe CAP. Plasma samples were collected from 46 CAP patients (including 27 with severe CAP and 19 with non-severe CAP) and 19 healthy controls upon admission. A comprehensive analysis of the combined proteomics and metabolomics data was then performed to elucidate the key pathological features associated with CAP severity.
The proteomic and metabolic signature was markedly different between CAPs and healthy controls. Pathway analysis of changes revealed complement and coagulation cascades, ribosome, tumor necrosis factor (TNF) signaling pathway and lipid metabolic process as contributors to CAP. Furthermore, alterations in lipid metabolism, including sphingolipids and phosphatidylcholines (PCs), and dysregulation of cadherin binding were observed, potentially contributing to the development of severe CAP. Specifically, within the severe CAP group, sphingosine-1-phosphate (S1P) and apolipoproteins (APOC1 and APOA2) levels were downregulated, while S100P level was significantly upregulated.
The combined proteomic and metabolomic analysis may elucidate the complexity of CAP severity and inform the development of improved diagnostic tools.
社区获得性肺炎（CAP）因其广泛流行和高昂的医疗成本而成为重大的公共卫生问题。本研究旨在利用蛋白质组学和代谢组学相结合的方法来探索重症CAP所涉及的机制。
我们整合蛋白质组学和代谢组学数据，以确定用于早期诊断重症CAP的潜在生物标志物。在入院时从46例CAP患者（包括27例重症CAP患者和19例非重症CAP患者）以及19名健康对照者中采集血浆样本。然后对蛋白质组学和代谢组学的综合数据进行全面分析，以阐明与CAP严重程度相关的关键病理特征。
CAP患者与健康对照者之间的蛋白质组学和代谢特征存在显著差异。对变化进行的通路分析显示，补体和凝血级联反应、核糖体、肿瘤坏死因子（TNF）信号通路以及脂质代谢过程与CAP有关。此外，观察到脂质代谢的改变，包括鞘脂和磷脂酰胆碱（PCs），以及钙黏蛋白结合失调，这可能导致重症CAP的发生。具体而言，在重症CAP组中，1-磷酸鞘氨醇（S1P）和载脂蛋白（APOC1和APOA2）水平下调，而S100P水平显著上调。
蛋白质组学和代谢组学的联合分析可能阐明CAP严重程度的复杂性，并为改进诊断工具的开发提供信息。
