- About
- Admissions
- Study at AUS
- Prospective Students
- Bachelor's Degrees
- Master's Degrees
- Doctoral Degrees
- Admission Publications
- International Students
- Contact Admissions
- Grants and Scholarships
- Sponsorship Liaison Services
- Testing Center
- New Student Guide
- File Completion
- New Student Orientation
- Payment Guide
- Executive Education
- Students with Disabilities
- Academics
- Life at AUS
- Virtual Campus Tour
- Around Campus
- One Stop Solution Center
- Residential Halls
- Commercial Outlets
- Athletics and Recreation
- Celebrating our Graduates
- Health and Wellness
- Sustainability
- Student Life
- Merchandise
- Alumni
- AUS Discount Program
- On-Campus Services
- Students with Disabilities
- COVID Update
- AUS Leopards Day
- Blog
- Research and Graduate Studies
- Contact Us
- Apply Now
- .
PhD Dissertation Final Oral Defense (April 2022)
Title of dissertation: Biomarker Discovery Utilizing Big Data: The Case of Diabetes in the United Arab Emirates
Name of Candidate: Bayan Hassan Banimfreg
Name of Supervisor: Dr. Abdulrahim Shamayleh, Dr. Hussam Alshraideh
Program: PhD in Engineering - Engineering Systems Management
Abstract
Diabetes mellitus (DM) received substantial attention to 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. It is estimated that the number of adults with DM will 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 microbiome derived biomarker discovery, a non-targeted metabolomics experiment using liquid chromatography with tandem mass spectrometry (LC-MS/MS) is conducted to explore the microbiome profile of diabetic UAE 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 profiling metabolites of diabetic Emiratis in contrast 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 were identified among diabetic and non-diabetic Emiratis. The identified metabolites were sorted into classes including tryptophan and purines, and others. 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. Results of this work are mainly consistent with previous similar international studies with a few added biomarkers reflecting the region-specific health profile. Potential metabolites were connected to their respective pathways to better understand their roles in diabetes development. The worldwide consensus on common metabolites encourages the clinical trials of novel biomarkers that could expedite the treatment process and boost the healthcare system beating increasing numbers of diabetic cases. Monitoring and managing diseases might move medicine from a therapeutic model to a prevention model. Finally, a framework for optimum biomarker discovery was proposed motivated by previous studies and the challenges faced in this research.