Metabolomics diagnostic approach to mustard airway diseases: a preliminary study

• Main Authors: BiBi Fatemeh Nobakht Mothlagh Ghoochani, Rasoul Aliannejad, Afsaneh Arefi Oskuei, Mostafa Rezaei-Tavirani, Shiva Kalantari, Mohammad Taghi Naseri, Alireza Bagheban, Hadi Parastar, Ghazale Aliakbarzadeh
• Format: Article
• Language: English
• Published: Mashhad University of Medical Sciences 2018-01-01
• Series: Iranian Journal of Basic Medical Sciences
• Subjects: GC-MS; Metabolomics; Multivariate analysis; NMR spectroscopy; Sulfur mustard
• Online Access: http://ijbms.mums.ac.ir/article_9924_68e116fbf106b759dd44ce3e151908a6.pdf

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.