Untargeted GC–MS investigation of serum metabolomics of coronary artery disease patients

• Main Authors: Wajhul Qamar, Saeed Alqahtani, Syed Rizwan Ahamad, Nemat Ali, Mohammad A. Altamimi
• Format: Article
• Language: English
• Published: Elsevier 2020-12-01
• Series: Saudi Journal of Biological Sciences
• Subjects: Metabolomics; AUCs; GC–MS; Principal component analysis; Serum metabolome
• Online Access: http://www.sciencedirect.com/science/article/pii/S1319562X20303661

Recent advances in metabolomics provide tools to investigate human metabolome in order to establish new parameters to study different approaches towards diagnostics, diseases and their treatment. The present study focused on the untargeted identification of metabolites in serum of patients with coronary artery disease who were under treatment at the time of sample collection. AUCs (Area Under the Curves) from different peaks were considered for the analysis and comparison purposes. The metabolome was studied using GC–MS (Gas Chromatography Mass Spectrometry) and the metabolites were identified with NIST (The National Institute of Standards and Technology) and Wiley library matches. A total of 17 metabolites were identified and focused on to compare with the metabolome of healthy individuals. T test analysis found significant differences in alanine, malonic acid, ribitol, D-glucose, mannose (P < 0.001), acetohydroxamic acid, N-carboxyglycine, and aminobutyrate (P < 0.05). Principal Component Analysis of serum metabolites data found three components out of 17 metabolites; RC1 (Acetohydroxamic acid, alanine, D-glucose, malonic acid, mannose, N-carboxy glycine and ribitol), RC2 (Heptadecanoic acid, hexadecanoic acid, octadecanoic acid and Trans-9-octadecanoic acid), RC3 (Aminobutyrate, D-sorbit, gamma lactone, valine, benzene propanoic acid and lactic acid). No correlation was found among the components.