This team focuses on the identification of biomarkers for type 2 diabetes and prediabetes and is interested in finding markers to predict the occurrence of diabetes in order to prevent it. They use data from the Qatar Biobank to investigate the relationship between diabetes or obesity and the salivary amylase activity.

The team is also investigating the molecular mechanisms that underly the positive effect of the glucagon-like-peptide 1 receptor agonists, such as Exendin-4, on hepatic steatosis and uses whole transcriptome sequencing to study the role of long non-coding RNAs in this effect.

Additionally, in collaboration with experts in machine learning and biostatics, the team also develops risk models for diabetes and prediabetes.