The application of metabolomics in human health and disease

  • Ahmed Dhaher A Alshehri

Student thesis: Doctoral Thesis


Metabolomics remains one of the rapidly growing tools for the identification of new disease diagnostic biomarkers. Mass spectrometry (MS) coupled to a liquid chromatographic (LC) system and nuclear magnetic resonance (NMR) are the two major analytical plaforms currently employed in metabolomic profiling studies of complex biofluid samples. However, due to its inherent higher sensitivity and fast data acquisition, MS remains one of the most dominant analytical techniques used in metabolomics. In this project, metabolomics was employed in various studies to assess metabolite biomarkers associated with health and disease. All the studies employed liquid chromatography-mass spectrometry (LC-MS) on an Orbitrap Exactive mass analyser, andusing ZIC-pHILIC or/and C18 analytical columns. Data was acquired using XCalibur software and metabolite identification was ascertained based on accurate mass detection, retention time comparisons with authentic external standards, and database searching. The acquired data was analysed using both unsupervised (PCA-X) and supervised (OPLS-DA) models in SIMCA in order to determine discriminating metabolite biomarkers responsible for the observed clustering patterns. Investigation of metabolomic effects of an 80 km ultramarathon exercise among healthy volunteers on a treadmill gave clear separation between the pre- and post 80km samples. The study revealed that many of the amino acids were lowered in plasma post-exercise but the clearest impact of endurance exercise observed was on fatty acid metabolism with respect to formation of medium chain unsaturated and partially oxidised fatty acids and conjugates of fatty acids with carnitines, which suggested that exercise may have led to increased peroxisomal metabolism. It is becoming increasingly clear that human health is strongly impacted by the gut microbiome.Evaluation of metabolomics effects of E. coli incubation in vivo with different carbon sources of 1% cooked meat, 1% maize meal and 1% olive kernel oil revealed that there were significant effects on amino acid, lipid, carbohydrate, and nucleotide metabolism. In addition, there were effects on intermediates of peptide and polyketide biosynthesis, as well as on xenobiotic breakdown products and vitamin cofactors. These findings suggested that the E. coli metabolome is closely associated with the type of fibre that the microorganism is exposed to and this was consistent with a number of other previous studies.The study of metabolomic effects of dietary fibres on urinary metabolites from patients with Crohn’s disease revealed that each of the 7 dietary fibres did not induce any significant differences in Crohn’s disease patients relative to the controls. On the other hand, it was found that metabolites were affected by the time of sample collection post treatment, and the overall effect was that the levels of specific metabolites tended to increase post treatment.The most common pathways affected were those of amino acid metabolism, lipid metabolism, nucleotide metabolism, polyketides, vitamins and cofactors, and xenobiotics, but the effect on carbohydrate metabolism was minimal. Finally, the study to ascertain whether it was possible to predict cancer associated muscle wasting from plasma metabolites in patients with upper gastrointestinal cancer (oesophageal, gastric, pancreatic) revealed that the levels of significantly altered metabolites were generally higher in patients who had lost so much weight (>7.6 kgweight loss). The discriminating metabolites belonged mainly to the lipid metabolic pathways where long chain fatty acids and lysolipids were affected. The observed effects on lipid metabolisms in cancer cachexia suggests that there is an increased tendency towards peroxisomal proliferation in patients who had lost significant muscle mass. Based on these findings, it can be concluded that LC-MS b
Date of Award9 Oct 2019
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SupervisorAlexander Mullen (Supervisor) & David Watson (Supervisor)

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