Imperial College London

DrCarolineSands

Faculty of MedicineDepartment of Metabolism, Digestion and Reproduction

Research Associate (Chemometrician)
 
 
 
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Contact

 

+44 (0)20 7594 3268caroline.sands01

 
 
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Location

 

Institute of Reproductive and Developmental BiologyHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Sands:2015:10.1038/ajg.2014.370,
author = {Sands, CJ and Guha, IN and Kyriakides, M and Wright, M and Beckonert, O and Holmes, E and Rosenberg, WM and Coen, M},
doi = {10.1038/ajg.2014.370},
journal = {American Journal of Gastroenterology},
pages = {159--169},
title = {Metabolic phenotyping for enhanced mechanistic stratification of chronic Hepatitis C-Induced liver fibrosis},
url = {http://dx.doi.org/10.1038/ajg.2014.370},
volume = {110},
year = {2015}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Objectives: The invasive nature of biopsy alongside issues with categorical staging and sampling error has driven research into noninvasive biomarkers for the assessment of liver fibrosis in order to stratify and personalize treatment of patients with liver disease. Here, we sought to determine whether a metabonomic approach could be used to identify signatures reflective of the dynamic, pathological metabolic perturbations associated with fibrosis in chronic hepatitis C (CHC) patients.Methods: Plasma nuclear magnetic resonance (NMR) spectral profiles were generated for two independent cohorts of CHC patients and healthy controls (n=50 original andn=63 validation). Spectral data were analyzed and significant discriminant biomarkers associated with fibrosis (as graded by enhanced liver fibrosis (ELF) and METAVIR scores) identified using orthogonal projection to latent structures (O-PLS).Results: Increased severity of fibrosis was associated with higher tyrosine, phenylalanine, methionine, citrate and, very-low-density lipoprotein (vLDL) and lower creatine, low-density lipoprotein (LDL), phosphatidylcholine, and N-Acetyl-α1-acid-glycoprotein. Although area under the receiver operator characteristic curve analysis revealed a high predictive performance for classification based on METAVIR-derived models, <40% of identified biomarkers were validated in the second cohort. In the ELF-derived models, however, over 80% of the biomarkers were validated.Conclusions: Our findings suggest that modeling against a continuous ELF-derived score of fibrosis provides a more robust assessment of the metabolic changes associated with fibrosis than modeling against the categorical METAVIR score. Plasma metabolic phenotypes reflective of CHC-induced fibrosis primarily define alterations in amino-acid and lipid metabolism, and hence identify mechanistically relevant pathways for further investigation as therapeutic targets.
AU - Sands,CJ
AU - Guha,IN
AU - Kyriakides,M
AU - Wright,M
AU - Beckonert,O
AU - Holmes,E
AU - Rosenberg,WM
AU - Coen,M
DO - 10.1038/ajg.2014.370
EP - 169
PY - 2015///
SN - 0002-9270
SP - 159
TI - Metabolic phenotyping for enhanced mechanistic stratification of chronic Hepatitis C-Induced liver fibrosis
T2 - American Journal of Gastroenterology
UR - http://dx.doi.org/10.1038/ajg.2014.370
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000351914700016&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - https://journals.lww.com/ajg/Fulltext/2015/01000/Metabolic_Phenotyping_for_Enhanced_Mechanistic.22.aspx
VL - 110
ER -