Metabolomics profiling in acute liver transplant rejection in a pediatric population

Pediatric liver transplantation rejection affects 20% of children. Currently, liver biopsy, expensive and invasive, is the best method of diagnosis. Discovery and validation of clinical biomarkers from blood or other biospecimens would improve clinical care. For this study, stored plasma samples wer...

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Bibliographic Details
Published in:Scientific reports 2022-11, Vol.12 (1), p.18663-18663, Article 18663
Main Authors: Frediani, Jennifer K., Beyh, Yara S., Gupta, Nitika, Westbrook, Adrianna L., Cleeton, Rebecca, Cordero, Maria, Hernandez, Albert, Tran, ViLinh, Jones, Dean P., Vos, Miriam B.
Format: Article
Language:English
Subjects:
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692/308
Biomarkers
Biopsy
Biosynthesis
Child
Children
Cross-Sectional Studies
Graft rejection
Graft Rejection - pathology
Humanities and Social Sciences
Humans
Liver
Liver - pathology
Liver Transplantation
Liver transplants
Metabolism
Metabolites
Metabolomics
Metabolomics - methods
multidisciplinary
Pediatrics
Postoperative Complications - pathology
Regression analysis
Science
Science (multidisciplinary)
Tryptophan
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Summary:Pediatric liver transplantation rejection affects 20% of children. Currently, liver biopsy, expensive and invasive, is the best method of diagnosis. Discovery and validation of clinical biomarkers from blood or other biospecimens would improve clinical care. For this study, stored plasma samples were utilized from two cross-sectional cohorts of liver transplant patients at Children’s Healthcare of Atlanta. High resolution metabolic profiling was completed using established methods. Children with (n = 18) or without (n = 25) acute cellular rejection were included in the analysis (n = 43 total). The mean age of these racially diverse cohorts ranged from 12.6 years in the rejection group and 13.6 years in the no rejection group. Linear regression provided 510 significantly differentiating metabolites between groups, and OPLS-DA showed 145 metabolites with VIP > 2. A total of 95 overlapping significant metabolites between OPLS-DA and linear regression analyses were detected. Pathway analysis (p  500 significant metabolites. This result suggests that development of a non-invasive biomarker-based test is possible for rejection screening.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-022-18957-4