Circulating bacterial peptides and linked metabolomic signatures are indicative of early mortality in pediatric cirrhosis.
Hepatol Commun
; 8(6)2024 06 01.
Article
em En
| MEDLINE
| ID: mdl-38836842
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 PC-S. 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acid along with L. xyli, Mycoplasma genitalium, and Hungateiclostridium thermocellum segregated PC-S nonsurvivors and superseded the liver disease severity indices with high accuracy, sensitivity, and specificity for mortality prediction using random forest machine-learning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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Sepse
/
Metabolômica
/
Cirrose Hepática
Limite:
Adolescent
/
Child
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Child, preschool
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Female
/
Humans
/
Male
Idioma:
En
Revista:
Hepatol Commun
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Índia