Genomic Determinants of Prediabetes Within a UAE Populations

Abstract

Prediabetes is an intermediate state of hyperglycemia in which the blood sugar level is above the normal range but still less than the diagnostic ranges of diabetes. It is a significant stage in preventing or delaying the progression of overt type 2 diabetes. Type 2 diabetes (T2D) is a severe worldwide metabolic disease with abnormally high blood glucose, leading to multiple serious complications, including death. It has a high prevalence globally, and the United Arab Emirates (UAE) has one of the world's highest prevalence rates. It is also one of the leading causes of death in the world. Hence, it is crucial to investigate the SNPs biomarkers associated with the prediabetes stage for early-onset disease prediction. SNPs are the primary units of genetic variants used as a stable biomarker of genomic regions associated with a specific trait. By analyzing the SNPs biomarkers associated with prediabetes, we can estimate an individual's risk of prediabetes and mark the genomic differences between healthy individuals and prediabetics. Unfortunately, the studies covering the genetic variants associated with prediabetes are extremely limited worldwide, as most focus on diabetes. Thus, this study is aimed to identify SNPs biomarkers associated with prediabetes in the UAE population. The DNA is extracted from blood, and Illumina microarray technology is used to process the samples. The BeadChip was customized due to the low percentage of the relevant SNPs covered in the commercial chips. The chip customization was done for The CoreExome-24 chip as it showed the highest coverage of our regions of interest compared to other commercial chips. Due to this customization, a custom cluster file was constructed following Illumina’s guidelines. Estimation of a risk prediction model for prediabetes was also done and showed that five socioeconomic and lifestyle-related factors were significantly associated with HbA1c value at a 10% significance level. In this model, 12 risk factors were selected to be studied based on a literature review and existing theoretical and empirical research. After adjustment to age and gender, the Exome-wide association study (EWAS) analysis revealed the top 12 genetic variants that showed suggestive association (p<0.05) with prediabetes within a UAE population. These biomarkers were located in various gene loci, and most of them were previously reported to be associated with T2D risk factors.

Date of Award	Aug 2023
Original language	American English