Association of serum metabolites and gut microbiota at hospital admission with nosocomial infection development in patients with cirrhosis

Abstract

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.

FIGURE 1

Flowchart of patients.

FIGURE 2

RFA analysis for NIs. Black dots indicate measurements were higher in those who developed NIs, and blue dots indicate measurements were lower in those who developed NIs. Metabolites with “X-” indicate unknown metabolites.

FIGURE 3

Microbiota LEfSe on NIs. LEfSe with green indicates NIs developed, and red indicates NIs did not develop.

FIGURE 4

Overall microbial–metabolite correlation network. Pink indicates bacteria, green indicates metabolites, red lines indicate positive linkage, and blue lines indicate negative linkage. (A) Those who developed NIs had a complex, dense, and homogeneous correlation network between microbiota and metabolites. (B) Those who did not develop NIs had a loose and heterogeneous correlation network between microbiota and metabolites.

FIGURE 5

Correlation network analysis subnetworks. Pink indicates bacteria, green indicates metabolites, red lines indicate positive linkage, and blue lines indicate negative linkage. (A) Ruminococcaceae subnetwork in those who developed NIs. (B) Ruminococcaceae subnetwork in those who did not develop NIs. (C) Lachnospiraceae subnetwork in those who developed NIs. (D) Lachnospiraceae subnetwork in those who did not develop NIs. (E) Pseudomonadaceae subnetwork in those who developed NIs.