Quantitative analysis of key protein phosphorylation events as pathway biomarkers of metabolic disease in human cells.
Lead Research Organisation:
University of Dundee
Department Name: Pathology and Neuroscience
Abstract
A combination of a more sedentary lifestyle and diets rich in fat has resulted in an explosion of health problems associated with metabolic dysfunction. For example, there are 2.3 million people in the UK with Type 2 diabetes, while one in ten women of child bearing age will experience polycystic ovarian syndrome. Indeed, simply being overweight increases the chances of developing these diseases. Type 2 diabetes alone costs the NHS around #2 billion pounds per year, while diabetes diagnosis is expected to double in the next 10 years. Type 2 diabetes is a major cause of heart disease, blindness, amputation and stroke, so reduces quality of life for individuals for many years as well as reducing life expectancy by around 10 years.
One of the key features of Type 2 diabetes is poor response to the hormone insulin. All evidence points to this ?insulin resistance? occurring prior to the development of Type 2 diabetes, but it is technically impossible at present to screen for insulin resistance in the general population. We strongly believe that earlier diagnosis and more targeted therapy would prevent progression to Type 2 diabetes, hence preventing the devastating complications of the disease. In addition, insulin resistance is strongly associated with all obesity related diseases, including polycystic ovarian syndrome, hypertension and fatty liver disease. Therefore the same diagnostic approach, and potentially the same therapy could be applied to all these ?metabolic diseases?.
In this proposal we aim to develop novel methodology (using state-of the-art Mass Spectrometry techniques) to accurately measure multiple biomarkers of insulin action inside cells. Insulin induces modifications of many proteins inside cells, and these modifications do not occur in the same pattern when cells or tissues are insulin resistant. Therefore accurate measurement of these biomarkers gives three things; firstly the pattern of modification after exposure to insulin provides the insulin sensitivity of the cells or tissues, secondly, an abnormal pattern provides the specific location of the molecular defect in the cells or tissues, and finally identification of the molecular defect allows classification of different forms of insulin resistance in order to identify the correct treatment for that subgroup.
The project will be split into two phases, the development of the methodology, and validation of the new methodology using cells and carefully collected muscle biopsies from volunteers with different amounts of body fat (obesity), and therefore a range of different levels of insulin resistance.
One of the key features of Type 2 diabetes is poor response to the hormone insulin. All evidence points to this ?insulin resistance? occurring prior to the development of Type 2 diabetes, but it is technically impossible at present to screen for insulin resistance in the general population. We strongly believe that earlier diagnosis and more targeted therapy would prevent progression to Type 2 diabetes, hence preventing the devastating complications of the disease. In addition, insulin resistance is strongly associated with all obesity related diseases, including polycystic ovarian syndrome, hypertension and fatty liver disease. Therefore the same diagnostic approach, and potentially the same therapy could be applied to all these ?metabolic diseases?.
In this proposal we aim to develop novel methodology (using state-of the-art Mass Spectrometry techniques) to accurately measure multiple biomarkers of insulin action inside cells. Insulin induces modifications of many proteins inside cells, and these modifications do not occur in the same pattern when cells or tissues are insulin resistant. Therefore accurate measurement of these biomarkers gives three things; firstly the pattern of modification after exposure to insulin provides the insulin sensitivity of the cells or tissues, secondly, an abnormal pattern provides the specific location of the molecular defect in the cells or tissues, and finally identification of the molecular defect allows classification of different forms of insulin resistance in order to identify the correct treatment for that subgroup.
The project will be split into two phases, the development of the methodology, and validation of the new methodology using cells and carefully collected muscle biopsies from volunteers with different amounts of body fat (obesity), and therefore a range of different levels of insulin resistance.
Technical Summary
Loss of regulatory control of intracellular signalling is closely associated with many diseases. For example, reduced insulin signalling is a major characteristic of Type 2 Diabetes Mellitus, which affects the lives of 2.3 million people in the UK, costing the NHS #2 billion a year. Intracellular signalling is mediated, in large part, by reversible posttranslational modification of proteins. Possibly the best characterised is protein phosphorylation. Quantitative assessment of a range of key phosphorylation events would provide biomarkers of the status of the signalling ?network? within cells/tissues. Identification of defective pathways in disease, and importantly the specific pathway component responsible for the defect, would improve understanding of disease mechanisms, and classify metabolic diseases at the molecular level. This would improve therapy selection and confirmation of drug efficacy in trials. The latter is particularly the case with drugs targeting a specific component in a signalling pathway.
Until recently, only semi-quantitative analysis of such pathways has been possible using techniques such as western blotting and immunohistochemistry. This is also limited by availability and quality of phosphorylation-specific antibodies. However, recent progress in quantitative phosphoproteomics makes the process less comparative and more accurate. In a pilot project, we have developed a LC-MS/MS procedure to quantify the phosphorylation status of the residues responsible for activation of protein kinase B/Akt. This method provides a stiochiometry measurement rather than fold difference between experimental samples. We propose to build on this and develop the technique to rapidly quantify eighteen phosphorylation events, in eight key proteins, as markers of the insulin sensitivity of important signalling networks. This will include key nodes in the PI-3 kinase/Akt pathway, the ERK signalling pathway, proximal events in insulin signalling, and nutrient sensing pathways. Many of these are currently impossible to quantify, primarily due to the quality of available phosphospecific antibodies. Importantly, we will validate the biomarkers in 5 different cell systems, 2 animal models of diabetes, and muscle biopsies from volunteers with variable whole body insulin sensitivity. These biopsies have already been collected and screened for a few pathways using current techniques and so a direct comparison of the new technology can be made. The biomarkers can then be used in the classification of insulin resistant states and the analysis of drug response.
Until recently, only semi-quantitative analysis of such pathways has been possible using techniques such as western blotting and immunohistochemistry. This is also limited by availability and quality of phosphorylation-specific antibodies. However, recent progress in quantitative phosphoproteomics makes the process less comparative and more accurate. In a pilot project, we have developed a LC-MS/MS procedure to quantify the phosphorylation status of the residues responsible for activation of protein kinase B/Akt. This method provides a stiochiometry measurement rather than fold difference between experimental samples. We propose to build on this and develop the technique to rapidly quantify eighteen phosphorylation events, in eight key proteins, as markers of the insulin sensitivity of important signalling networks. This will include key nodes in the PI-3 kinase/Akt pathway, the ERK signalling pathway, proximal events in insulin signalling, and nutrient sensing pathways. Many of these are currently impossible to quantify, primarily due to the quality of available phosphospecific antibodies. Importantly, we will validate the biomarkers in 5 different cell systems, 2 animal models of diabetes, and muscle biopsies from volunteers with variable whole body insulin sensitivity. These biopsies have already been collected and screened for a few pathways using current techniques and so a direct comparison of the new technology can be made. The biomarkers can then be used in the classification of insulin resistant states and the analysis of drug response.