2 research outputs found
Statistical Health Monitoring Applied to a Metabolomic Study of Experimental Hepatocarcinogenesis: An Alternative Approach to Supervised Methods for the Identification of False Positives
In
a typical metabolomics experiment, two or more conditions (e.g.,
treated versus untreated) are compared, in order to investigate the
potential differences in the metabolic profiles. When dealing with
complex biological systems, a two-class classification is often unsuitable,
since it does not consider the unpredictable differences between samples
(e.g., nonresponder to treatment). An approach based on statistical
process control (SPC), which is able to monitor the response to a
treatment or the development of a pathological condition, is proposed
here. Such an approach has been applied to an experimental hepatocarcinogenesis
model to discover early individual metabolic variations associated
with a different response to the treatment. Liver study was performed
by nuclear magnetic resonance (NMR) spectroscopy, followed by multivariate
statistical analysis. By this approach, we were able to (1) identify
which treated samples have a significantly different metabolic profile,
compared to the control (in fact, as confirmed by immunohistochemistry,
the method correctly classified 7 responders and 3 nonresponders among
the 10 treated animals); (2) recognize, for each individual sample,
the metabolites that are out of control (e.g., glutathione, acetate,
betaine, and phosphocholine). The first point could be used for classification
purposes, and the second point could be used for a better understanding
of the mechanisms underlying the early phase of carcinogenesis. The
statistical control approach can be used for diagnosis (e.g., healthy
versus pathological, responder versus nonresponder) and for generation
of an individual metabolic profile, leading to a better understanding
of the individual pathological processes and to a personalized diagnosis
and therapy
Additional file 1: Figure S1. of 1H NMR spectroscopy-based metabolomics analysis for the diagnosis of symptomatic E. coli-associated urinary tract infection (UTI)
Representative 1H NMR spectra of E.Coli-pos urine sample. 1 TSP; 2 lactate; 3 alanine; 4 acetate; 5 citrate; 6 dimethylamine; 7 trimethylamine; 8 creatinine; 9 histidine; 10 choline; 11 TMA N-Oxide; 12 taurine; 13 glycine; 14 urea; 15 phenylalanine;16 hippurate; 17 formate. (TIFF 156 kb