Report

Teaser, summary, work performed and final results

Periodic Reporting for period 2 - BEAt-DKD (Biomarker Enterprise to Attack DKD - Sofia ref.: 115974)

Teaser

Diabetic kidney disease (DKD) is the leading cause of end stage renal disease, and its global incidence and prevalence have reached epidemic dimensions. There are no effective means to prevent or cure DKD may be due to: (i) the current diagnosis of diabetes based on one...

Summary

Diabetic kidney disease (DKD) is the leading cause of end stage renal disease, and its global incidence and prevalence have reached epidemic dimensions. There are no effective means to prevent or cure DKD may be due to: (i) the current diagnosis of diabetes based on one metabolite, glucose, which is inaccurate and not useful in predicting disease outcome and choice of therapy; (ii) the consequences of early dysglycemia or metabolic memory for development of DKD have often been ignored; (iii) histological analysis is not usually used to differentiate DKD from CKD of other aetiology; (iv) unsuccessful identification of novel biomarkers, with micro-/macroalbuminuria remaining among the best predictors of DKD in addition to the decline in glomerular filtration rate. Few studies have attempted to explore the full potential of urine and plasma as sources of kidney biomarkers or to associate markers with kidney biopsy analyses.

The overall goals of Biomarker Enterprise to Attack DKD (BEAt-DKD) are:
1. to provide a holistic systems medicine view of the pathogenesis of DKD with the aim to identify targetable mechanisms and pathways underlying initiation and progression of DKD, applying a novel sub-classification of diabetes, and
2. to identify and validate biomarkers of disease progression and treatment responses representing first steps towards precision medicine in the management of DKD.

Work performed

BEAt-DKD is organized in four “discovery” actions (1-4) that feed their findings into two “validation, integration and translation” actions (5-6), all efforts leading towards personalised precision medicine.

1. Biomarker in observational prospective studies
A data driven analysis in patients with newly diagnosed diabetes revealed 5 replicable clusters of patients with significantly different patient characteristics and risk of complications, one of which (the most resistant to insulin) with increased risk to develop DKD. This new substratification may help to tailor and target early treatment to patients who would benefit most. In year 2, we completed the validation of previously identified plasma biomarkers: many candidate biomarkers were associated with eGFR decline, but had low predictive power; with eGFR as the strongest predictor of future eGFR levels. Much emphasis was on identification of novel biomarkers, with the completion of measurements of metabolomics and lipidomics in plasma and the further development and refinement of methodologies, including urine exosome RNA and micro RNA analyses as well as DNA chip-seq.

2. Efficacy biomarkers in intervention studies
BEAt-DKD focuses on the discovery of biomarkers that predict if a DKD patient responds to a drug, through experimental studies in cells and animals as well as using samples from completed trials. In year 2, an extensive profiling of clinical trial samples, including diverse -omics and mRNA profiling, as well as initial data analyses have been completed. In a multi-centre collaboration, BEAt-DKD profiled kidney tissues from animals and cultured cells exposed to common treatments related to DKD. The team in Groningen organised December 2017 an international symposium on personalized medicine in diabetic kidney disease.

3. Mechanisms and pathways
The individual cellular programs driving DKD are defined through their epigenetic, transcriptional- and protein networks. The BEAt-DKD groups focusing on mechanisms and pathways in DKD have successfully refined and validated protocols to isolate specific cell types, in order to study them individually. They developed insulin-sensitive and -resistant model systems, in which insulin sensitivity mechanisms can be investigated to identify mechanisms and relevant biomarkers. With state-of-the-art 3D techniques in animal models, processes involved in early stages of kidney disease are revealed. All results are fed back into other parts of the project.

4. Development, identification and validation of prognostic and predictive imaging biomarkers
A central BEAt-DKD activity is iBEAt, a longitudinal 4-year observational study in 500 patients with early stage DKD, recruited in 5 sites across Europe. Extensive characterisation is done at baseline and annual follow-ups to identify associations between imaging biomarkers and known biomarkers of disease progression and test whether imaging biomarkers at baseline improve predictions of functional decline. The central study protocol has been completed and the infrastructures for sample collection and the central biobank in Malmö are in place. All study centres are aligned in their tasks and the first patients have recently been recruited and scanned.

5. Integration and prioritization of DKD biomarkers and targets (systems medicine)
The systems medicine section in BEAt-DKD interfaces with the data-generating teams to provide data management solutions and systems biology expertise to support DKD biomarker discovery. Major achievements in year 2 have been the further development of the federated database and knowledge management system, the analysis of biomarker data, integrated analysis of cellular, animal and human data to identify predictive and dynamic biomarkers of drug response and the aggregation of external data to sources to support biomarker prioritisation efforts.

6. Optimization of trial design and preparation of implementation in the regulatory process
BEAt-DKD

Final results

Improved DKD clinical trial efficiency: A template of a new trial design including a better risk score that integrates multiple markers will improve indication of renal risk and of drug efficacy/safety changes, improving clinical trial efficiency.
Clinical and societal impact: Bringing predictive and dynamic biomarkers to clinical practice will help to tailor drugs to specific subgroups of patients and to mitigate adverse drug reactions and/or events.
Improved imaging tools: BEAt-DKD will be the first to direct the full power of quantitative imaging data onto the problem of patient stratification and treatment response. With focus on MRI and Ultrasound, BEAt-DKD efforts will lead to the largest imaging study in the kidney worldwide.
Innovation impact: The approach of integrating data from in vitro cell studies, an unprecedentedly large collection of in vivo kidney tissues and human clinical trial studies is completely novel.

Website & more info

More info: http://www.beat-dkd.eu.