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A quantitative metabolomics profiling approach for the noninvasive assessment of liver histology in patients with chronic hepatitis C

Overview of attention for article published in Clinical and Translational Medicine, August 2016
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Title
A quantitative metabolomics profiling approach for the noninvasive assessment of liver histology in patients with chronic hepatitis C
Published in
Clinical and Translational Medicine, August 2016
DOI 10.1186/s40169-016-0109-2
Pubmed ID
Authors

M. Omair Sarfaraz, Robert P. Myers, Carla S. Coffin, Zu‐Hua Gao, Abdel Aziz M. Shaheen, Pam M. Crotty, Ping Zhang, Hans J. Vogel, Aalim M. Weljie

Abstract

High-throughput technologies have the potential to identify non-invasive biomarkers of liver pathology and improve our understanding of basic mechanisms of liver injury and repair. A metabolite profiling approach was employed to determine associations between alterations in serum metabolites and liver histology in patients with chronic hepatitis C virus (HCV) infection. Sera from 45 non-diabetic patients with chronic HCV were quantitatively analyzed using (1)H-NMR spectroscopy. A metabolite profile of advanced fibrosis (METAVIR F3-4) was established using orthogonal partial least squares discriminant analysis modeling and validated using seven-fold cross-validation and permutation testing. Bioprofiles of moderate to severe steatosis (≥33 %) and necroinflammation (METAVIR A2-3) were also derived. The classification accuracy of these profiles was determined using areas under the receiver operator curves (AUROCSs) measuring against liver biopsy as the gold standard. In total 63 spectral features were profiled, of which a highly significant subset of 21 metabolites were associated with advanced fibrosis (variable importance score >1 in multivariate modeling; R(2) = 0.673 and Q(2) = 0.285). For the identification of F3-4 fibrosis, the metabolite bioprofile had an AUROC of 0.86 (95 % CI 0.74-0.97). The AUROCs for the bioprofiles for moderate to severe steatosis were 0.87 (95 % CI 0.76-0.97) and for grade A2-3 inflammation were 0.73 (0.57-0.89). This proof-of-principle study demonstrates the utility of a metabolomics profiling approach to non-invasively identify biomarkers of liver fibrosis, steatosis and inflammation in patients with chronic HCV. Future cohorts are necessary to validate these findings.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 18%
Other 3 14%
Student > Bachelor 2 9%
Student > Ph. D. Student 2 9%
Student > Doctoral Student 1 5%
Other 4 18%
Unknown 6 27%
Readers by discipline Count As %
Medicine and Dentistry 5 23%
Chemistry 3 14%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Physics and Astronomy 1 5%
Agricultural and Biological Sciences 1 5%
Other 2 9%
Unknown 9 41%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 October 2016.
All research outputs
#9,803,898
of 15,414,285 outputs
Outputs from Clinical and Translational Medicine
#132
of 243 outputs
Outputs of similar age
#153,135
of 269,991 outputs
Outputs of similar age from Clinical and Translational Medicine
#1
of 1 outputs
Altmetric has tracked 15,414,285 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 243 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.9. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
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