Winston, Brent W.Mohamed Metwaly, Sayed Ahmed Osman2022-11-152020-08-06Mohamed Metwaly, S. (2020). Metabolomics Study of ARDS Diagnosis, Heterogeneity, and Mortality (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.http://hdl.handle.net/1880/115470https://dx.doi.org/10.11575/PRISM/40437Background: Acute Respiratory Distress Syndrome (ARDS) represents 10.4% of all Intensive Care Unit (ICU) admissions with an overall mortality rate of 35.3%. Early diagnosis of ARDS is an important requirement for the timely institution of proper supportive care but it is hampered by the unreliable tissue diagnosis, lack of an early diagnostic biomarker and lack of specific therapy. Metabolomics is a systems biology approach to examine changes in metabolites in response to physiological and pathological stimuli. It is more closely related to observed phenotypes and more responsive to real-time pathophysiological changes, thus constitutes an attractive platform for studying ARDS.Hypothesis: We hypothesize that the diverse inflammatory, pathobiological and adaptive processes involved in ARDS would manifest as unique metabolic fingerprint that sets ARDS apart from other ICU conditions. Biomarker identification may help early diagnosis of ARDS, explore its mechanism, differentiate ARDS subclasses and predict ARDS mortality. Methodology: Serum samples from 108 ARDS patients and 27 ICU ventilated age- and sex-matched controls were included in this study. Samples were analyzed by proton nuclear magnetic resonance spectroscopy (1H-NMR) and gas chromatography mass spectrometry (GC-MS). The proteins/cytokines IL-6, IL-8, IL-10, TNF-?, Ang-2, RAGE, vWF, TNF-RI, ICAM-1, PAI-1, SP-D and Protein-C were also measured. Multivariate statistical models that distinguish ARDS from ICU controls (diagnose ARDS), subclassify ARDS and predict ARDS non-survival were built. Results were externally validated in an independent cohort of 188 patients comprising 118 ARDS patients and 70 ICU ventilated controls.Results: Our data indicates that NMR and GC-MS metabolomics are more accurate than proteins/cytokines in differentiating ARDS from ICU controls and ARDS subgroups. Pathway analysis of ARDS versus controls identified a dominant involvement of serine-glycine metabolism. In external validation, ARDS patients were correctly identified in 93% using NMR and 96% using GC-MS. Metabolomics was not able to predict mortality in the ARDS population studied.Conclusion: ARDS subgroups are metabolically distinct. Further research is needed to explore the role of dysfunctional folate metabolism in the development of ARDS. Metabolomics provides a novel technology to not only understand but intervene on the pathophysiology of ARDS.enUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.ARDSmetabolomicsbiomarkersstatisticscytokinesendotypingfolate hypothesiswaning of the initial insult effectmachine learningvisualizationProbabilistic universal model approximatorPUMAHealth Sciences--Medicine and SurgeryArtificial IntelligenceChemistry--BiochemistryStatisticsdoctoral thesis