Circulating bacterial peptides and linked metabolomic signatures are indicative of early mortality in pediatric cirrhosis

Abstract

Background: Patients with pediatric cirrhosis-sepsis (PC-S) attain early mortality. Plasma bacterial composition, the cognate metabolites, and their contribution to the deterioration of patients with PC-S to early mortality are unknown. We aimed to delineate the plasma metaproteome-metabolome landscape and identify molecular indicators capable of segregating patients with PC-S predisposed to early mortality in plasma, and we further validated the selected metabolite panel in paired 1-drop blood samples using untargeted metaproteomics-metabolomics by UHPLC-HRMS followed by validation using machine-learning algorithms. Methods: We enrolled 160 patients with liver diseases (cirrhosis-sepsis/ nonsepsis [n = 110] and noncirrhosis [n = 50]) and performed untargeted metaproteomics-metabolomics on a training cohort of 110 patients (Cirrhosis-Sepsis/Nonsepsis, n = 70 and noncirrhosis, n = 40). The candidate predictors were validated on 2 test cohorts—T1 (plasma test cohort) and T2 (1-drop blood test cohort). Both T1 and T2 had 120 patients each, of which 70 were from the training cohort. Results: Increased levels of tryptophan metabolites and Salmonella enterica and Escherichia coli–associated peptides segregated patients with cirrhosis. Increased levels of deoxyribose-1-phosphate, N5-citryl-D-ornithine, and Herbinix hemicellulolytic and Leifsonia xyli segregated patients with PCS. MMCN-based integration analysis of WMCNA-WMpCNA identified key microbial-metabolic modules linked to PC-S nonsurvivors. Increased Indican, Staphylobillin, glucose-6-phosphate, 2-octenoylcarnitine, palmitic acid, and guanidoacetic acid along with L. xyli, Mycoplasma genitalium, and Hungateiclostridium thermocellum segregated PC-S nonsurvivors and superseded the liver disease severity indices with high accuracy, sensitivity, and specificity for mortality prediction using random forest machine-learning algorithm. Conclusions: Our study reveals a novel metabolite signature panel capable of segregating patients with PC-S predisposed to early mortality using as low as 1-drop blood.