Genetic of Non-Alcohol Fatty Liver and Type 2 Diabetes Disease in UAE

Abstract

Non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM) are two interconnected metabolic disorders with a rising prevalence worldwide, including the United Arab Emirates (UAE). This study aimed to investigate the genetic factors associated with NAFLD and T2DM in the UAE population through a comprehensive genetics analysis. A literature review highlighted the established link between NAFLD and T2DM, emphasizing shared underlying mechanisms such as insulin resistance, glucose metabolism, and lipid metabolism. It also identified numerous genetic variants associated with both diseases, including those involved in these metabolic pathways (rs738409, rs58542926, rs1260326, rs266729, and resistin +299AA). 653 samples were collected from diabetes centre. The genomic DNA for all the samples was extracted using automated method, the extracted DNA were assessed using nanodrop and gel electrophoresis and the good once were genotyped using infimum global screening array. All samples were investigated for the presence of NAFLD and T2DM. Healthy samples or samples with prediabetes or T1DM were excluded from the study. Among the 653 we ended up accepting 436 (25 control and 411 cases) samples. The Demographic and the GWAS statistical analyses were conducted as a case-control panel, with controls characterized as T2DM patients and cases characterized as NAFLD diagnosis with T2DM. The study included a demographic analysis of a cohort of UAE individuals with NAFLD and T2DM. Although no significant associations were found between most demographic variables and the presence of NAFLD, cholesterol levels emerged as an important factor requiring monitoring in individuals with T2DM. To identify specific genetic variants associated with NAFLD and T2DM in the UAE population, a genome-wide association study (GWAS) was conducted Followed by Next Generation sequencing (NGS) of seven randomly chosen case samples. The GWAS analysis identified several novel genetic variants with suggestive associations to NAFLD and T2DM, providing insights into the genetic basis of these diseases in the UAE population. These variants are rs1518651, rs12723678, rs6919309, rs7488387, rs34779359, rs10002393, rs728837, rs10774330, rs57794618, rs2280940, rs12621817, rs1041200, rs7959626, rs6965830, rs11118988, rs6798431, rs9990367, and rs290175. Moreover, our GWAS analysis indicates a lack of association between the previously reported variant (rs16861194 of ADIPQ gene) and NAFLD in the Emirati population .The sequencing analysis has identified a multitude of significantly associated variants with non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM) in Emirati population. These variants are located in the ABCA1, ATXN3, CD36, CREBBP, FGA, HAL, HLA-B, HLADQA1, HLA-DRB1, HLA-G, KIF1A, KIR3DL1, LFNG, LGI4, LIPC, MUC3A, MUC6, PAX6, PRSS2, SALL1, SERPINA1, SETD1A, SLC25A24, SLC25A5, SLC30A9, TINF2, UNC45B, VEGFA, and ZMIZ1 genes. The recurrence of these specific variants in multiple samples exhibiting the same study phenotype suggests their potential association with the phenotype. These findings emphasize the significance of these genetic variants in the development of NAFLD in the Emirati population with T2DM, providing valuable insights for further research and enhancing our understanding of the underlying genetic factors contributing to these diseases in the United Arab Emirates.
Several limitations were acknowledged, including the challenge of detecting NAFLD in its early stages, a relatively small sample size, and the use of non-specific genotyping arrays. Future research should focus on larger sample sizes, population-specific genotyping arrays, and functional investigations to validate and understand the role of these genetic variants. The findings of this study lay the foundation for the development of genetic screening tests for early detection and risk assessment of NAFLD and T2DM in the UAE population. Early identification of individuals at risk can facilitate timely interventions, potentially reducing the burden of complications and healthcare costs associated with these diseases.

Date of Award	Aug 2023
Original language	American English
Supervisor	Habiba Alsafar (Supervisor)