TY - JOUR ID - 9924 TI - Metabolomics diagnostic approach to mustard airway diseases: a preliminary study JO - Iranian Journal of Basic Medical Sciences JA - IJBMS LA - en SN - 2008-3866 AU - Nobakht Mothlagh Ghoochani, BiBi Fatemeh AU - Aliannejad, Rasoul AU - Arefi Oskuei, Afsaneh AU - Rezaei-Tavirani, Mostafa AU - Kalantari, Shiva AU - Naseri, Mohammad Taghi AU - Bagheban, Alireza AU - Parastar, Hadi AU - Aliakbarzadeh, Ghazale AD - Department of Basic Medical Sciences, Neyshabur University of Medical Sciences, Neyshabur, Iran AD - Pulmonary Department, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran AD - Department of Basic Sciences, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran AD - Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran AD - Chronic Kidney Disease Research Center, Labbafinejad Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran AD - Department of Chemistry, Faculty of Sciences, Tarbiat Modares University, Tehran, Iran AD - Physiotherapy Research Center, School of Rehabilitation, Shahid Beheshti University of Medical Sciences, Tehran, Iran AD - Department of Chemistry, Sharif University of Technology, Tehran, Iran AD - Department of Chemistry, Faculty of Science, University of Tehran, Tehran, Iran Y1 - 2018 PY - 2018 VL - 21 IS - 1 SP - 59 EP - 69 KW - GC-MS KW - Metabolomics KW - Multivariate analysis KW - NMR spectroscopy KW - Sulfur mustard DO - 10.22038/ijbms.2017.23792.5982 N2 - Objective(s): This study aims to evaluate combined proton nuclear magnetic resonance (1H NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS) metabolic profiling approaches, for discriminating between mustard airway diseases (MADs) and healthy controls and for providing biochemical information on this disease. Materials and Methods: In the present study, analysis of serum samples collected from 17 MAD subjects and 12 healthy controls was performed using NMR. Of these subjects, 14 (8 patients and 6 controls) were analyzed by GC-MS. Then, their spectral profiles were subjected to principal component analysis (PCA) and orthogonal partial least squares regression discriminant analysis (OPLS-DA). Results: A panel of twenty eight metabolite biomarkers was generated for MADs, sixteen  NMR-derived metabolites (3-methyl-2-oxovaleric acid, 3-hydroxyisobutyrate, lactic acid, lysine, glutamic acid, proline, hydroxyproline, dimethylamine, creatine, citrulline, choline, acetic acid, acetoacetate, cholesterol, alanine, and lipid (mainly VLDL)) and twelve GC-MS-derived metabolites (threonine, phenylalanine, citric acid, myristic acid, pentadecanoic acid, tyrosine, arachidonic acid, lactic acid, propionic acid, 3-hydroxybutyric acid, linoleic acid, and oleic acid). This composite biomarker panel could effectively discriminate MAD subjects from healthy controls, achieving an area under receiver operating characteristic curve (AUC) values of 1 and 0.79 for NMR and GC-MS, respectively. Conclusion: In the present study, a robust panel of twenty-eight biomarkers for detecting MADs was established. This panel is involved in three metabolic pathways including aminoacyl-tRNA biosynthesis, arginine, and proline metabolism, and synthesis and degradation of ketone bodies, and could differentiate MAD subjects from healthy controls with a higher accuracy. UR - https://ijbms.mums.ac.ir/article_9924.html L1 - https://ijbms.mums.ac.ir/article_9924_68e116fbf106b759dd44ce3e151908a6.pdf ER -