Developing a Stratified Approach to Treatment in Type 2 Diabetes

Abstract

Type 2 diabetes (T2D) is a leading cause of global morbidity and mortality characterised by deficits in insulin secretion and function. Diabetes’ poor health outcomes are largely attributed to its macrovascular and microvascular complications, which can be prevented by ensuring adequate glycaemic control. Current guidance recommends optimising lifestyle interventions (weight loss and exercise) as first line management in T2D progressing to oral pharmacotherapy with metformin. If however poor glycaemic control persists, second and third line agents are added. The numerous glucose-lowering agents available and a lack of robust comparative outcome data make selecting the most appropriate second and third line therapies for individuals with T2D a major clinical dilemma.

There is huge inter-individual variation in response to type 2 diabetes medication: some individuals may elicit a significant glucose-lowering response to one medication, but the same medication may have little effect on others. As diabetes is a heterogeneous disease (a disease likely manifesting from multiple aetiologies) it is likely that a biological basis partly underpins the variation in therapeutic response. These disease attributes suggest the potential for the integration of a stratified approach to diabetes therapy. Stratification involves prescribing medication based on factors other than patients’ presenting symptoms; such as phenotypic traits or biomarkers. The main aim of stratification is to identify and provide individualised therapies that maximise therapeutic efficacy and minimise adverse events.

Limited research has been conducted into the mechanisms underpinning variation in diabetes treatment response. The main aim of this thesis is to investigate potential mechanisms underpinning the inter-individual variation in response to sitagliptin (a DPP-4 inhibitor) and gliclazide (a sulphonylurea) using data from the MASTERMIND randomised control crossover trial. This will aid in understanding variation in therapeutic response in T2D and support the development of a stratified approach.

Chapter 1 provides an overview of stratified medicine and introduces T2D as a potential candidate for stratification. In this chapter, we also review the literature surrounding the pharmacokinetics of sitagliptin and gliclazide, the agents investigated in this thesis to answer questions of stratification and inter-individual variation in therapeutic response.

Chapter 2 provides a detailed overview of the MASTERMIND randomised control crossover study design, from which data for this thesis was analysed.

Chapter 3 explores potential associations between trough and total plasma drug levels and (fasting and post-prandial plasma) glucose response to sitagliptin and gliclazide. We found that while plasma drug levels were highly variable this variation did not substantially explain short term glycaemic response to these agents.

In Chapter 4 we assess whether medication adherence, calculated using medication possession ratio (MPR) is associated with therapeutic response to sitagliptin and gliclazide therapy. We found that, in a trial setting most participants were adherent to study medication and that variation in adherence did not explain variation in glucose-lowering response in this setting.

In Chapter 5 we explore whether measurable differences in lifestyle factors explain the variation in glucose-lowering response to sitagliptin and gliclazide by analysing weight and accelerometer data. We show that both weight and physical activity were stable within an individual during the study period and that individual differences of these lifestyle factors between each treatment period, do not explain the corresponding differences in glycaemic responses.

Chapter 6 investigates whether glucose-lowering response to diabetes therapy is specific to an individual. We show that the change in fasting glycaemia from after stopping sulphonylurea (SU) therapy strongly correlates with the fasting glycaemic response observed when re-starting SU therapy but does not predict fasting glycaemic response to DPP-4 inhibitor therapy.

An overview of the major finding of each chapter and their implications for future precision medicine research in diabetes is discussed in Chapter 7.