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.

Prebiotic activity of lactulose optimizes gut metabolites and prevents systemic infection in liver disease patients

“…The gut microbiome has been implicated in the development of systemic infections in many disease states 24,40 , including cirrhosis 41 . A recent prospective study used untargeted serum metabolites and fecal 16S rRNA microbiota data to predict nosocomial infections 42 ; however, many of the serum metabolites of interest were not microbially derived and did not substantially improve the ability to predict infection development beyond standard clinical metrics (including known infection, model of end stage liver disease (MELD) score, and leukocyte count) 42 . Antibiotics, while highly effective for treatment and prophylaxis against common infections in liver disease 43,44 , are associated with increasing antibiotic resistance genes in the gut microbiomes and subsequent poor clinical outcomes [45][46][47][48] .…”

Sympathetic nervous activation, mitochondrial dysfunction and outcome in acutely decompensated cirrhosis: the metabolomic prognostic models (CLIF-C MET)

“…To value the superior accuracy of CLIF-C MET over the MELDNa score or of some metabolites versus others in predicting short-term mortality in AD, it is important to understand the mechanisms by which SI impacts on metabolism and survival. This issue, which has been extensively studied in sepsis,26–29 is also increasingly being explored in cirrhosis,20 30 31 with solid data showing that both conditions share similar pathophysiological pathways. Severe SI is among the most common acute stressful situations in humans and leads to a coordinated stress (alarm) response by the central nervous system, endocrine system and metabolism, to fight against the stressor 27–29.…”

“…This issue, which has been extensively studied in sepsis,26–29 is also increasingly being explored in cirrhosis,20 30 31 with solid data showing that both conditions share similar pathophysiological pathways. Severe SI is among the most common acute stressful situations in humans and leads to a coordinated stress (alarm) response by the central nervous system, endocrine system and metabolism, to fight against the stressor 27–29. The routine inflammation markers (WCC, C-reactive protein (CRP), IL-6) either alone or in combination with (or within) CLIF-C AD and CLIF-C ACLF score performed worse than the new models in the prediction of mortality in patients with and without ACLF.…”

“…In order to explain these findings, one should remember that the alarm response is initiated within specific areas in the brainstem and hypothalamus which have no blood-brain barrier and are inflamed by circulating pathogen associated molecular pattern (PAMPs), danger associated molecular pattern (DAMPs) and inflammatory mediators 27. Central nervous nodes (eg, locus coeruleous32) integrate inputs from multiple alarm responsive circuits and releases norepinephrine initiating the metabolic response to SI, which results in a massive release of glucose, fatty acids and amino acids from tissue stores to the periphery and prioritisation of energy metabolism to the immune cells, to cover the high energy demands of the systemic inflammatory reaction 28 29. As discussed above, the top prognostic metabolite identified in our patients was 4-hydroxy-3-methoxyphenylglycol sulfate, a terminal metabolite of norepinephrine closely related to the alarm reaction.…”

Current Research on the Pathogenesis of NAFLD/NASH and the Gut–Liver Axis: Gut Microbiota, Dysbiosis, and Leaky-Gut Syndrome

“…In this study, a combined panel of multiple species of intestinal bacteria allowed differentiation between NAFLD-derived cirrhosis and non-cirrhosis with a very good diagnostic performance (AUROC: 0.92). Liver biopsy, which is considered the gold standard for diagnosing cirrhosis, has problems such as invasiveness and sampling errors; therefore, gut microbiota analysis is expected to be developed as a new testing tool for cirrhosis [ 60 , 61 ].…”