Area of Research: Diabetes, and Hypertension in Kuwait
Approaches: Health Informatics, and Computational Genetics and Genome Informatics
The department of Integrative Informatics at Dasman Diabetes Institute aims to analyse epidemiology and genetics data on diabetes and hypertension in Kuwait to identify associations among risk factors. The department identifies substructures in Kuwaiti Population, derives reference genome sequence resources for the substructures, and develops prognostic models for diabetes and hypertension.
The department has, to date, published two papers in prestigious international journals. The first paper is in Diabetes Care, entitled “State of Diabetes, Hypertension, and Comorbidity in Kuwait: Showcasing the Trends as Seen in Native Versus Expatriate Populations”. In this article, we discuss the prevalence of type 1 and type 2 diabetes among Kuwaitis and foreign nationals (of different age groups), and also show the rising trend of hypertension and comorbidity. We also show the effect of certain risk factors such as BMI on the onset age of type 2 diabetes. The second paper is published in BMJOpen, entitled “Predictive models for diabetes and hypertension in Kuwait”. In this paper, we show that using simple measurements such as BMI, ethnicity, and age, we can predict the onset of diabetes, hypertension, and comorbidity using state-of-the-art artificial intelligence algorithms. When such a system is used nationwide, it can greatly lower the economic and physical burden of the healthcare system in Kuwait.
A third paper entitled “Genetic Substructure of Kuwaiti Population Reveals Migration History”, has been reviewed by PLOS ONE journal and has been tentatively accepted for publication (pending a revision). This article presents genome-wide data for the Kuwait population and delienates its genetic structure and deliberates how the history of the settlements influenced the distribution of genetic variation. This understanding helps in studies designed to understand the underlying causes for the high prevalence of recessive disorders and metabolic syndromes (that lead to diabetes and cardiovascular complications).