AIM: To study the metabolic profiling of serum samples from compensated and decompensated cirrhosis patients. METHODS: A pilot metabolic profiling study was conducted using three groups: compensated cirrhosis patients (n = 30), decompensated cirrhosis patients (n = 30) and healthy controls (n = 30). A ¹H nuclear magnetic resonance (NMR)-based metabonomics approach was used to obtain the serum metabolic profiles of the samples. The acquired data were processed by multivariate principal component analysis and orthogonal partial least-squares discriminant analysis (OPLS-DA). RESULTS: The OPLS-DA model was capable of distinguishing between decompensated and compensated cirrhosis patients, with an R²Y of 0.784 and a Q²Y of 0.598. Twelve metabolites, such as pyruvate, phenylalanine and succinate, were identified as the most influential factors for the difference between the two groups. The validation of the diagnosis prediction showed that the accuracy of the OPLS-DA model was 85% (17/20). CONCLUSION: ¹H NMR spectra combined with pattern recognition analysis techniques offer a new way to diagnose compensated and decompensated cirrhosis in the future.
AIM: To study the metabolic profiling of serum samples from compensated and decompensated cirrhosispatients. METHODS: A pilot metabolic profiling study was conducted using three groups: compensated cirrhosispatients (n = 30), decompensated cirrhosispatients (n = 30) and healthy controls (n = 30). A ¹H nuclear magnetic resonance (NMR)-based metabonomics approach was used to obtain the serum metabolic profiles of the samples. The acquired data were processed by multivariate principal component analysis and orthogonal partial least-squares discriminant analysis (OPLS-DA). RESULTS: The OPLS-DA model was capable of distinguishing between decompensated and compensated cirrhosispatients, with an R²Y of 0.784 and a Q²Y of 0.598. Twelve metabolites, such as pyruvate, phenylalanine and succinate, were identified as the most influential factors for the difference between the two groups. The validation of the diagnosis prediction showed that the accuracy of the OPLS-DA model was 85% (17/20). CONCLUSION: ¹H NMR spectra combined with pattern recognition analysis techniques offer a new way to diagnose compensated and decompensated cirrhosis in the future.
Authors: Cornelis H C Dejong; Marcel C G van de Poll; Peter B Soeters; Rajiv Jalan; Steven W M Olde Damink Journal: J Nutr Date: 2007-06 Impact factor: 4.798
Authors: Caroline J Sands; Indra N Guha; Michael Kyriakides; Mark Wright; Olaf Beckonert; Elaine Holmes; William M Rosenberg; Muireann Coen Journal: Am J Gastroenterol Date: 2014-12-23 Impact factor: 10.864
Authors: Laurence Le Moyec; Mohamed N Triba; Pierre Nahon; Nadia Bouchemal; Edith Hantz; Corentine Goossens; Roland Amathieu; Philippe Savarin Journal: Biomed Rep Date: 2017-03-03
Authors: Courtney E Hershberger; Alejandro I Rodarte; Shirin Siddiqi; Amika Moro; Lou-Anne Acevedo-Moreno; J Mark Brown; Daniela S Allende; Federico Aucejo; Daniel M Rotroff Journal: Liver Cancer Int Date: 2021-05-20