Nuclear magnetic resonance -based metabolomics analysis of patients exposed to sulfur mustard in different stages using random forest method

Bibi Fatemeh Nobakht Motlagh Ghoochani; Rasoul Aliannejad; Afsaneh Arefi Oskouie; fariba fattahi; Hossein Ali Sahakhah; Mostafa Rezaei-Tavirani

doi:10.5812/koomesh-153909

Koomesh

Journal of Semnan University of Medical Sciences

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Nuclear magnetic resonance -based metabolomics analysis of patients exposed to sulfur mustard in different stages using random forest method

Author(s):

Bibi Fatemeh Nobakht Motlagh Ghoochani^{1, 2},

Rasoul Aliannejad³,

Afsaneh Arefi Oskouie⁴,

fariba fattahi⁵,

Hossein Ali Sahakhah⁶,

Mostafa Rezaei-Tavirani

^7,*

1– Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

2Dept. of Basic Sciences, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

3Pulmonary Department, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran

4– Dept. of Basic Sciences, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

5Dept. of Chemistry, Sharif University of Technology, Tehran, Iran

6Phhysiology Research Center and Dept. of Physiology, Semnan University of Medical Sciences, Semnan, Iran

7Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Koomesh:Vol. 17, issue 3; e153909

Published online:Aug 21, 2016

Article type:Research Article

How to Cite:Bibi Fatemeh Nobakht Motlagh GhoochaniRasoul AliannejadAfsaneh Arefi Oskouiefariba fattahiHossein Ali SahakhahMostafa Rezaei-Taviraniet al.Nuclear magnetic resonance -based metabolomics analysis of patients exposed to sulfur mustard in different stages using random forest method.koomesh.17(3):e153909.

Abstract

Introduction: Metabolomics is a powerful technique for determination of biomarkers. Here, we aimed to determine discriminatory metabolomic profiles in different stages of sulfur mustard-exposed patients (SMEPs). Materials and methods: Nuclear magnetic resonance spectroscopy was used to analyze serum samples from 17 SMEPs (normal group patients) and 17 SMEPs (severe group patients). Multivariate statistical analysis using random forest (RF) was performed on a ‘training set’ (70% of the total sample) in order to produce a discriminatory model classifying two groups of patients, and the model tested in the remaining subjects. Results: A classification model was derived using data from the training set with an area under the receiver operating curve (AUC) of 0.87. In the test set (the remaining 30% of subjects), the AUC was 0.8, thus RF model had good predictive power. We observed significant changes in lipid, amino acids and energy metabolism between two groups of patients. Conclusion: Nuclear magnetic resonance spectroscopy of serum successfully differentiates two groups of patients exposed to sulfur mustard. This technique has the potential to provide novel diagnostics and identify novel pathophysiological mechanisms, biomarkers and therapeutic targets

Keywords

Mustard Gas

Serum

Metabolomics

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