Description
A Doctor of Philosophy Dissertation in Engineering Systems Management by Bayan Hassan Banimfreg entitled, “Biomarker Discovery Utilizing Big Data: The Case of Diabetes in United Arab Emirates”, submitted in May 2022. Dissertation advisor is Dr. Abdulrahim Shamayleh and dissertation co-advisor is Dr. Hussam Alshraideh. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
Abstract
Diabetes Mellitus (DM) received substantial attention for exploring its mechanism as expected to be the seventh primary reason for death worldwide by 2030. The hallmark of DM leads to damaging effects on many organ systems, mainly the cardiovascular, ophthalmic, and renal systems. The number of adults with DM to reach 95 million by 2030 and 136 million by 2045 in the Middle East and North Africa region. Type 2 diabetes (T2DM) is the most common type of DM, accounting for around 90% of diabetes cases. T2DM is a multifactorial chronic metabolic disease caused by genetic and non-genetic factors resulting from an imbalance between energy intake and output and other lifestyle-related factors. However, the detailed understanding of T2DM etiology is still limited. As the focus of this work is the metabolomic derived biomarker discovery, a non-targeted metabolomics experiment using liquid chromatography with tandem mass spectrometry (LC-MS/MS) is conducted to explore the metabolic profile of diabetic Emirati Citizens to uncover potential novel diabetes biomarkers through big data analytics. The study is twofold: in the first part, a comprehensive analysis is performed to reveal the profiling metabolites of diabetic Emirates compared to healthy ones. Blood samples of 50 diabetic Emiratis versus 42 healthy were utilized to investigate for differential metabolites. In the second part, a metabolomic study of patients with diabetic kidney disease against dialysis non-diabetics patients was conducted to uncover their distinct biomarkers. Blood samples of 11 dialysis diabetics and 25 dialysis non-diabetic were used to reveal potential biomarkers. A great panel of potential differential metabolites was identified among diabetic and non-diabetic Emirates. The identified metabolites were sorted into classes, including Tryptophan and Purines. Several potential biomarkers and their related pathways were pinpointed among dialysis patients, including Tyrosine metabolism-related metabolite and 3,4-Dihydroxymandelic acid. These studies provide detailed coverage of blood metabolic changes related to T2DM in the Emirati population. The results of this work are mainly consistent with similar international studies, with a few added biomarkers reflecting the region-specific health profile. The worldwide consensus on common metabolites encourages the clinical trials of novel biomarkers that could expedite the treatment process for diabetics. Monitoring and managing diseases might move medicine from a therapeutic model to a prevention model.