Department of MedicineVirginia Commonwealth University and Central Virginia Veterans Healthcare SystemRichmondVirginiaUSA.
Department of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA.
Liver Transpl. 2022 Dec;28(12):1831-1840. doi: 10.1002/lt.26552. Epub 2022 Aug 26.
Cirrhosis is complicated by a high rate of nosocomial infections (NIs), which result in poor outcomes and are challenging to predict using clinical variables alone. Our aim was to determine predictors of NI using admission serum metabolomics and gut microbiota in inpatients with cirrhosis. In this multicenter inpatient cirrhosis study, serum was collected on admission for liquid chromatography-mass spectrometry metabolomics, and a subset provided stool for 16SrRNA analysis. Hospital course, including NI development and death, were analyzed. Metabolomic analysis using analysis of covariance (ANCOVA) (demographics, Model for End-Stage Liver Disease [MELD] admission score, white blood count [WBC], rifaximin, and infection status adjusted) and random forest analyses for NI development were performed. Additional values of serum metabolites over clinical variables toward NI were evaluated using logistic regression. Stool microbiota and metabolomic correlations were compared in patients with and without NI development. A total of 602 patients (231 infection admissions) were included; 101 (17%) developed NIs, which resulted in worse inpatient outcomes, including intensive care unit transfer, organ failure, and death. A total of 127 patients also gave stool samples, and 20 of these patients developed NIs. The most common NIs were spontaneous bacterial peritonitis followed by urinary tract infection, Clostridioides difficile, and pneumonia. A total of 247 metabolites were significantly altered on ANCOVA. Higher MELD scores (odds ratio, 1.05; p < 0.0001), admission infection (odds ratio, 3.54; p < 0.0001), and admission WBC (odds ratio, 1.05; p = 0.04) predicted NI (area under the curve, 0.74), which increased to 0.77 (p = 0.05) with lower 1-linolenoyl-glycerolphosphocholine (GPC) and 1-stearoyl-GPC and higher N-acetyltryptophan and N-acetyl isoputreanine. Commensal microbiota were lower and pathobionts were higher in those who developed NIs. Microbial-metabolite correlation networks were complex and dense in patients with NIs, especially sub-networks centered on Ruminococcaceae and Pseudomonadaceae. NIs are common and associated with poor outcomes in cirrhosis. Admission gut microbiota in patients with NIs showed higher pathobionts and lower commensal microbiota. Microbial-metabolomic correlations were more complex, dense, and homogeneous among those who developed NIs, indicating greater linkage strength. Serum metabolites and gut microbiota on admission are associated with NI development in cirrhosis.
肝硬化患者易发生医院获得性感染(NI),感染发生率高,预后差,且仅使用临床变量难以预测。我们旨在通过肝硬化住院患者入院时的血清代谢组学和肠道微生物组学来确定 NI 的预测因子。在这项多中心肝硬化住院患者研究中,入院时采集血清进行液相色谱-质谱代谢组学分析,部分患者提供粪便进行 16SrRNA 分析。分析了住院期间的病程,包括 NI 的发展和死亡。采用协方差分析(ANCOVA)(人口统计学、终末期肝病模型 [MELD] 入院评分、白细胞计数 [WBC]、利福昔明和感染状态调整)和随机森林分析对 NI 发展进行代谢组学分析。使用逻辑回归评估血清代谢物对 NI 的预测价值是否优于临床变量。比较了有和无 NI 发展的患者的粪便微生物组和代谢组学相关性。共纳入 602 例患者(231 例感染入院);101 例(17%)发生了 NI,导致住院期间预后更差,包括转入重症监护病房、器官衰竭和死亡。共有 127 例患者还提供了粪便样本,其中 20 例发生了 NI。最常见的 NI 是自发性细菌性腹膜炎,其次是尿路感染、艰难梭菌和肺炎。ANCOVA 分析显示共有 247 种代谢物发生显著改变。较高的 MELD 评分(比值比,1.05;p<0.0001)、入院时感染(比值比,3.54;p<0.0001)和入院时白细胞计数(比值比,1.05;p=0.04)预测 NI(曲线下面积,0.74),当纳入较低的 1-亚麻酰基甘油磷酸胆碱(GPC)和 1-硬脂酰基-GPC 以及较高的 N-乙酰色氨酸和 N-乙酰异亮氨酸时,该值增加至 0.77(p=0.05)。发生 NI 的患者肠道共生菌减少,病原菌增多。发生 NI 的患者微生物-代谢物相关网络复杂且密集,尤其是以瘤胃球菌科和假单胞菌科为中心的子网络。NI 在肝硬化患者中很常见,与不良预后相关。发生 NI 的患者入院时肠道微生物组中的病原菌增加,共生菌减少。发生 NI 的患者微生物-代谢物相关性更复杂、密集和均匀,表明关联强度更大。肝硬化患者入院时的血清代谢物和肠道微生物组与 NI 的发展相关。