Identifying drivers of glycaemic control in response to sulphonylurea treatment

  • Declan McGuigan

Student thesis: Doctoral Thesis


Type 2 diabetes (T2DM) is a complex disease, brought about by the interaction of genetic and environmental factors. Coupled with a growing obesity problem, the disease has reached epidemic proportions globally. Several heterogeneous metabolic disorders including hyperglycaemia and impaired insulin secretion and/or action play a part in the progression of the disease. Large-scale cohort studies have identified several biomarkers for diabetes risk and for glycaemic control. The current study focused on the sulphonylurea drug class, which is associated with poor response rates and significant adverse events including an increased risk of hypoglycaemia. This study aimed to validate existing markers and to identify new biomarkers that may aid in patient stratification, especially in response to sulphonylurea therapy. 500 participants with T2DM were recruited from the Western Health and Social Care Trust and formed the basis of the DIASTRAT cohort. Clinical and anthropometric data suggest that those receiving sulphonylureas had significantly worse outcomes in terms of glycaemic control and BMI, especially when this was combined with an exogenous insulin reparation. Genetic studies confirmed a role for ABCC8 and KCNJ11 in sulphonylurea response from beta cell (β-cell) lines. Furthermore, several SNPs in ABCC8, KCNJ11 and HNF1α were found to be significantly associated with glycemic control in participants receiving sulphonylurea therapy. A unique 75-protein signature was identified that correctly identifies those with T2DM to within 99.2% accuracy. Additionally, several of these proteins were found to correlate with glycaemic control in the DIASTRAT cohort. Overall, the work has identified several unique targets worthy of further validation in larger cohorts and secondary cohorts from other sites. Moreover, the work outlined in this thesis underlines the importance of considering both clinical and biological data for patient stratification.
Date of AwardMay 2018
Original languageEnglish
SupervisorCatriona Kelly (Supervisor), Tony Bjourson (Supervisor) & Paula McClean (Supervisor)


  • Diabetes
  • Sulphonylurea

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