Title: Validation of Novel and Candidate Biomarkers for Diabetic Kidney Disease in Large Cohorts of people with Type 1 Diabetes
Funder: Juvenile Diabetes Research Foundation

Abstract: Diabetic kidney disease (DKD) is the major determinant of increased mortality in diabetes. Advances in the care of people with type 1 diabetes have delayed the age of onset of end stage renal disease in T1DM but have not prevented its occurrence. The current cornerstones of management are still blood pressure and glycaemic control - no specific preventive drugs exist. A major bar to developing new therapies to prevent DKD is incomplete knowledge of pathways involved. Another major bar is that demonstrating that a new drug is effective in preventing progression to ESRD requires very large trials as there is considerable heterogeneity in the rates of progression to ESRD in those with impaired renal function. We propose to validate and characterize potential biomarkers of chronic kidney disease in Type 1 Diabetes and its progression using samples and data from large prospective cohorts of participants with type 1 diabetes. A key objective is to create models for predicting progression that incorporate the best panel of biomarkers and clinical characteristics so as to enable shorter more feasible trial programmes. Ultimately models for prediction can then be applicable clinically for planning health care provision and for planning early targeted intervention with new therapies. Associated biomarkers for which there is also causal evidence can inform our understanding of the pathogenesis of CKD in diabetes thereby assisting drug target discovery and therefore assssing whether some biomarkers play a causal role is a second aim. The work we propose is directly in line with JDRF 2014 Research Priority Area “Prognostic and predictive biomarkers in diabetic kidney disease”. For biomarker discovery to translate into clinical usefulness it is important to demonstrate generalizability and to incorporate biomarkers into prediction models that use clinical information. There is currently no accepted validated measure of prediction of CKD risk and progression in use in diabetes. The work proposed will translate biomarker discovery by building such models. It also provides an important framework for the rapid validation of any subsequent novel biomarkers from other JDRF funded biomarker initiatives including gene discovery initiatives. The specific objectives are 1. To select the biomarkers showing strongest associations and predictive utility for CKD progression in type 2 Diabetes (T2D) from another EU funded research programme in type 2 diabetes called the SUMMIT programme and measure these in relevant samples from large type 1 diabetes (T1DM) cohorts 2. Confirm or reject the association of these biomarkers with CKD progression as measured by eGFR progression in T1DM 3. Quantify the improvement in prediction beyond clinical data obtainable with associated biomarkers 4. Validate a CKD progression model that uses clinical data and incorporates novel associated biomarkers across cohorts. There are 15 biomarkers arising from the SUMMIT programme that we especially want to measure. These will be measured using a liquid chromatography (LC) electrospray tandem mass spectrometry (MSMS) and serum tryptic peptide targeted proteomic LC-MSMS platform at the Dalton Lab King's College London UK and by using a Luminex technology that performs multiplexed, microsphere-based assays at Myriad Rules Based medicine Clia certified laboratory in Austin Texas. Using these platforms to measure the 15 biomarkers of especial interest will actually yield data on 155 biomarkers ( metabolites, amino acids and proteins) altogether. We will use data analysis techniques appropriate for such high dimensional data to build and evaluate predictive models of eGFR decline. In addition to these models this work will provide a useful framework for the rapid validation of any subsequent novel biomarkers from other JDRF funded biomarker initiatives including gene discovery initiatives.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: METABOLIC AND ENDOCRINE;RENAL AND UROGENITAL