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Multivariate metabotyping of plasma predicts survival in patients with decompensated cirrhosis

BACKGROUND & AIMS: Predicting survival in decompensated cirrhosis (DC) is important in decision making for liver transplantation and resource allocation. We investigated whether high-resolution metabolic profiling can determine a metabolic phenotype associated with 90-day survival. METHODS: Two...

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Autores principales: McPhail, Mark J.W., Shawcross, Debbie L., Lewis, Matthew R., Coltart, Iona, Want, Elizabeth J., Antoniades, Charalambos G., Veselkov, Kiril, Triantafyllou, Evangelos, Patel, Vishal, Pop, Oltin, Gomez-Romero, Maria, Kyriakides, Michael, Zia, Rabiya, Abeles, Robin D., Crossey, Mary M.E., Jassem, Wayel, O’Grady, John, Heaton, Nigel, Auzinger, Georg, Bernal, William, Quaglia, Alberto, Coen, Muireann, Nicholson, Jeremy K., Wendon, Julia A., Holmes, Elaine, Taylor-Robinson, Simon D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4876170/
https://www.ncbi.nlm.nih.gov/pubmed/26795831
http://dx.doi.org/10.1016/j.jhep.2016.01.003
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author McPhail, Mark J.W.
Shawcross, Debbie L.
Lewis, Matthew R.
Coltart, Iona
Want, Elizabeth J.
Antoniades, Charalambos G.
Veselkov, Kiril
Triantafyllou, Evangelos
Patel, Vishal
Pop, Oltin
Gomez-Romero, Maria
Kyriakides, Michael
Zia, Rabiya
Abeles, Robin D.
Crossey, Mary M.E.
Jassem, Wayel
O’Grady, John
Heaton, Nigel
Auzinger, Georg
Bernal, William
Quaglia, Alberto
Coen, Muireann
Nicholson, Jeremy K.
Wendon, Julia A.
Holmes, Elaine
Taylor-Robinson, Simon D.
author_facet McPhail, Mark J.W.
Shawcross, Debbie L.
Lewis, Matthew R.
Coltart, Iona
Want, Elizabeth J.
Antoniades, Charalambos G.
Veselkov, Kiril
Triantafyllou, Evangelos
Patel, Vishal
Pop, Oltin
Gomez-Romero, Maria
Kyriakides, Michael
Zia, Rabiya
Abeles, Robin D.
Crossey, Mary M.E.
Jassem, Wayel
O’Grady, John
Heaton, Nigel
Auzinger, Georg
Bernal, William
Quaglia, Alberto
Coen, Muireann
Nicholson, Jeremy K.
Wendon, Julia A.
Holmes, Elaine
Taylor-Robinson, Simon D.
author_sort McPhail, Mark J.W.
collection PubMed
description BACKGROUND & AIMS: Predicting survival in decompensated cirrhosis (DC) is important in decision making for liver transplantation and resource allocation. We investigated whether high-resolution metabolic profiling can determine a metabolic phenotype associated with 90-day survival. METHODS: Two hundred and forty-eight subjects underwent plasma metabotyping by (1)H nuclear magnetic resonance (NMR) spectroscopy and reversed-phase ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC-TOF-MS; DC: 80-derivation set, 101-validation; stable cirrhosis (CLD) 20 and 47 healthy controls (HC)). RESULTS: (1)H NMR metabotyping accurately discriminated between surviving and non-surviving patients with DC. The NMR plasma profiles of non-survivors were attributed to reduced phosphatidylcholines and lipid resonances, with increased lactate, tyrosine, methionine and phenylalanine signal intensities. This was confirmed on external validation (area under the receiver operating curve [AUROC] = 0.96 (95% CI 0.90–1.00, sensitivity 98%, specificity 89%). UPLC-TOF-MS confirmed that lysophosphatidylcholines and phosphatidylcholines [LPC/PC] were downregulated in non-survivors (UPLC-TOF-MS profiles AUROC of 0.94 (95% CI 0.89–0.98, sensitivity 100%, specificity 85% [positive ion detection])). LPC concentrations negatively correlated with circulating markers of cell death (M30 and M65) levels in DC. Histological examination of liver tissue from DC patients confirmed increased hepatocyte cell death compared to controls. Cross liver sampling at time of liver transplantation demonstrated that hepatic endothelial beds are a source of increased circulating total cytokeratin-18 in DC. CONCLUSION: Plasma metabotyping accurately predicts mortality in DC. LPC and amino acid dysregulation is associated with increased mortality and severity of disease reflecting hepatocyte cell death.
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spelling pubmed-48761702016-06-01 Multivariate metabotyping of plasma predicts survival in patients with decompensated cirrhosis McPhail, Mark J.W. Shawcross, Debbie L. Lewis, Matthew R. Coltart, Iona Want, Elizabeth J. Antoniades, Charalambos G. Veselkov, Kiril Triantafyllou, Evangelos Patel, Vishal Pop, Oltin Gomez-Romero, Maria Kyriakides, Michael Zia, Rabiya Abeles, Robin D. Crossey, Mary M.E. Jassem, Wayel O’Grady, John Heaton, Nigel Auzinger, Georg Bernal, William Quaglia, Alberto Coen, Muireann Nicholson, Jeremy K. Wendon, Julia A. Holmes, Elaine Taylor-Robinson, Simon D. J Hepatol Research Article BACKGROUND & AIMS: Predicting survival in decompensated cirrhosis (DC) is important in decision making for liver transplantation and resource allocation. We investigated whether high-resolution metabolic profiling can determine a metabolic phenotype associated with 90-day survival. METHODS: Two hundred and forty-eight subjects underwent plasma metabotyping by (1)H nuclear magnetic resonance (NMR) spectroscopy and reversed-phase ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC-TOF-MS; DC: 80-derivation set, 101-validation; stable cirrhosis (CLD) 20 and 47 healthy controls (HC)). RESULTS: (1)H NMR metabotyping accurately discriminated between surviving and non-surviving patients with DC. The NMR plasma profiles of non-survivors were attributed to reduced phosphatidylcholines and lipid resonances, with increased lactate, tyrosine, methionine and phenylalanine signal intensities. This was confirmed on external validation (area under the receiver operating curve [AUROC] = 0.96 (95% CI 0.90–1.00, sensitivity 98%, specificity 89%). UPLC-TOF-MS confirmed that lysophosphatidylcholines and phosphatidylcholines [LPC/PC] were downregulated in non-survivors (UPLC-TOF-MS profiles AUROC of 0.94 (95% CI 0.89–0.98, sensitivity 100%, specificity 85% [positive ion detection])). LPC concentrations negatively correlated with circulating markers of cell death (M30 and M65) levels in DC. Histological examination of liver tissue from DC patients confirmed increased hepatocyte cell death compared to controls. Cross liver sampling at time of liver transplantation demonstrated that hepatic endothelial beds are a source of increased circulating total cytokeratin-18 in DC. CONCLUSION: Plasma metabotyping accurately predicts mortality in DC. LPC and amino acid dysregulation is associated with increased mortality and severity of disease reflecting hepatocyte cell death. Elsevier 2016-05 /pmc/articles/PMC4876170/ /pubmed/26795831 http://dx.doi.org/10.1016/j.jhep.2016.01.003 Text en © 2016 European Association for the Study of the Liver. Elsevier B.V. All rights reserved. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
McPhail, Mark J.W.
Shawcross, Debbie L.
Lewis, Matthew R.
Coltart, Iona
Want, Elizabeth J.
Antoniades, Charalambos G.
Veselkov, Kiril
Triantafyllou, Evangelos
Patel, Vishal
Pop, Oltin
Gomez-Romero, Maria
Kyriakides, Michael
Zia, Rabiya
Abeles, Robin D.
Crossey, Mary M.E.
Jassem, Wayel
O’Grady, John
Heaton, Nigel
Auzinger, Georg
Bernal, William
Quaglia, Alberto
Coen, Muireann
Nicholson, Jeremy K.
Wendon, Julia A.
Holmes, Elaine
Taylor-Robinson, Simon D.
Multivariate metabotyping of plasma predicts survival in patients with decompensated cirrhosis
title Multivariate metabotyping of plasma predicts survival in patients with decompensated cirrhosis
title_full Multivariate metabotyping of plasma predicts survival in patients with decompensated cirrhosis
title_fullStr Multivariate metabotyping of plasma predicts survival in patients with decompensated cirrhosis
title_full_unstemmed Multivariate metabotyping of plasma predicts survival in patients with decompensated cirrhosis
title_short Multivariate metabotyping of plasma predicts survival in patients with decompensated cirrhosis
title_sort multivariate metabotyping of plasma predicts survival in patients with decompensated cirrhosis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4876170/
https://www.ncbi.nlm.nih.gov/pubmed/26795831
http://dx.doi.org/10.1016/j.jhep.2016.01.003
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