Periodic Reporting for period 6 - BEAt-DKD (Biomarker Enterprise to Attack DKD - Sofia ref.: 115974)
Berichtszeitraum: 2021-09-01 bis 2022-08-31
Today, 537 million adults (20-79 years) are living with diabetes - 1 in 10 and this number is predicted to rise to 643 million by 2030 and 783 million by 2045. This will inevitably result in growing number of patients suffering from diabetes kidney disease (DKD), since approximately 20-50% of patients with diabetes will develop DKD, the leading cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD).
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.
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 precision medicine in DKD: “The right prevention and treatment, to the right patients at the right time”.
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.
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 precision medicine in DKD: “The right prevention and treatment, to the right patients at the right time”.
Six years into the project, BEAt-DKD has generated important insights in the pathogenesis, heterogeneity and treatment response in DKD as evidenced by a total of 131 publications in relevant journals and with a high overall mean Impact Factor of 8.03. Noteworthy, 22% of all papers have an IF>10. The scientific community appreciates the work: 5507 citations, with several papers having >100. Ahlqvist et al (Lancet Diabetes & Endocrinology 2018) reached 1415 citations: a data-driven analysis revealing 5 novel subgroups of adult-onset diabetes, with a severe insulin-resistant group having a higher risk to develop DKD.
1. Biomarker in observational prospective studies
BEAt-DKD harmonized clinical cohorts, validated biomarkers previously identified to have excellent performance in pilot studies and discovered novel markers.
Evaluating large observational cohorts showed that ~50% of patients with rapidly decreasing kidney function had (near-) normal albumin-to-creatinine ratio, revealing a group not typically considered at risk in normal clinical practice. We validated our previous findings that elevated plasma levels of KIM-1 are especially strong predictors of future renal decline. Urinary extracellular vesicles are shown to offer a promising non-invasive liquid kidney biopsy of DKD.
2. Efficacy biomarkers in intervention studies
BEAt-DKD focuses on the discovery of biomarkers that predict if a DKD patient responds to a drug, by integrating omics data from cell- and animal models, and samples from clinical trials. We discovered and validated 4 biomarkers that predict the response to an endothelin receptor antagonist, enabling selection of patients more likely to respond to this drug class. thereby reducing the size and costs of clinical trials. We validated TNF receptor markers that can be used to monitor the response to SGLT2 inhibitors and can predict the long-term risk of kidney endpoints, thus supporting decision making in clinical practice. Against the background of the discovered correlation between insulin resistance and increased DKD risk, existing treatments are being re-evaluated, possibly leading to new disease indications.
3. Mechanisms and pathways
A comprehensive cell encyclopedia of the kidney was established to unravel the molecular changes of the epigenome, transcriptome, proteome and post-translational modifications in different renal cells (podocytes, parietal epithelial cells, glomerular endothelial cells, mesangial cells, proximal tubular cells). Integration of cell and animal data identified common and cell-specific insulin resistance and DKD molecular programs. Single nucleus RNA-sequencing to identify molecular mechanisms of SGLT2 inhibitors and AI-based image analysis pipelines for biomarker validation were established, as well as novel confocal imaging to quantify glomerular endothelial glycocalyx damage. Advances in identification of novel mechanisms and pathways underlying DKD progression, insulin resistance, the role of glycocalyx and response to endothelin receptor antagonist and SGLT2 inhibitors have been made.
4. Development, identification and validation of prognostic and predictive imaging biomarkers
The iBEAt study, a prospective multi-centre observational cohort study in 620 patients with early stage DKD, explores associations between imaging biomarkers and renal function, and whether imaging biomarkers improve the prediction of DKD progression. Ancillary substudies aim to: (1) validate imaging biomarkers against renal histopathology; (2) validate MRI based renal blood flow measurements against positron-emission tomography (PET); (3) validate methods for (semi-)automated processing of renal MRI; (4) examine longitudinal changes in imaging biomarkers; (5) examine whether glycocalyx and microvascular measures are associated with imaging biomarkers and eGFR decline; (6) explore if findings in type 2 diabetes can be extrapolated to type 1.
5. Integration and prioritization of DKD biomarkers and targets (systems medicine)
BEAt-DKD applied systems biology analyses of human, rodent and cell line data to identify predictive and dynamic biomarkers. Integrative analyses of multi-omics data from cell lines have been used to identify pathways and mechanisms underlying DKD, as well as integrative analysis of metabolomics and lipidomics profiling and assessment of predictive power in early stage DKD. Sustainability plans for data and resources generated by BEAt-DKD beyond the lifetime of the project are in place, and we are sharing our results within the European Platform for Diabetes and Complications.
6. Optimization of trial design and preparation of implementation in the regulatory process
BEAt-DKD collaborates with key stakeholders including patient and physician groups, regulators, health technology assessors, and scientists from academia, pharmaceutical and biotech companies to develop an optimized blueprint for clinical studies. Recent highlights are the submission of the PRE-score document to the EMA for a Qualification Opinion with a request in consultation of the FDA as external stakeholder, as well as several review articles on the biomarker qualification process and on their use in personalised medicine.
1. Biomarker in observational prospective studies
BEAt-DKD harmonized clinical cohorts, validated biomarkers previously identified to have excellent performance in pilot studies and discovered novel markers.
Evaluating large observational cohorts showed that ~50% of patients with rapidly decreasing kidney function had (near-) normal albumin-to-creatinine ratio, revealing a group not typically considered at risk in normal clinical practice. We validated our previous findings that elevated plasma levels of KIM-1 are especially strong predictors of future renal decline. Urinary extracellular vesicles are shown to offer a promising non-invasive liquid kidney biopsy of DKD.
2. Efficacy biomarkers in intervention studies
BEAt-DKD focuses on the discovery of biomarkers that predict if a DKD patient responds to a drug, by integrating omics data from cell- and animal models, and samples from clinical trials. We discovered and validated 4 biomarkers that predict the response to an endothelin receptor antagonist, enabling selection of patients more likely to respond to this drug class. thereby reducing the size and costs of clinical trials. We validated TNF receptor markers that can be used to monitor the response to SGLT2 inhibitors and can predict the long-term risk of kidney endpoints, thus supporting decision making in clinical practice. Against the background of the discovered correlation between insulin resistance and increased DKD risk, existing treatments are being re-evaluated, possibly leading to new disease indications.
3. Mechanisms and pathways
A comprehensive cell encyclopedia of the kidney was established to unravel the molecular changes of the epigenome, transcriptome, proteome and post-translational modifications in different renal cells (podocytes, parietal epithelial cells, glomerular endothelial cells, mesangial cells, proximal tubular cells). Integration of cell and animal data identified common and cell-specific insulin resistance and DKD molecular programs. Single nucleus RNA-sequencing to identify molecular mechanisms of SGLT2 inhibitors and AI-based image analysis pipelines for biomarker validation were established, as well as novel confocal imaging to quantify glomerular endothelial glycocalyx damage. Advances in identification of novel mechanisms and pathways underlying DKD progression, insulin resistance, the role of glycocalyx and response to endothelin receptor antagonist and SGLT2 inhibitors have been made.
4. Development, identification and validation of prognostic and predictive imaging biomarkers
The iBEAt study, a prospective multi-centre observational cohort study in 620 patients with early stage DKD, explores associations between imaging biomarkers and renal function, and whether imaging biomarkers improve the prediction of DKD progression. Ancillary substudies aim to: (1) validate imaging biomarkers against renal histopathology; (2) validate MRI based renal blood flow measurements against positron-emission tomography (PET); (3) validate methods for (semi-)automated processing of renal MRI; (4) examine longitudinal changes in imaging biomarkers; (5) examine whether glycocalyx and microvascular measures are associated with imaging biomarkers and eGFR decline; (6) explore if findings in type 2 diabetes can be extrapolated to type 1.
5. Integration and prioritization of DKD biomarkers and targets (systems medicine)
BEAt-DKD applied systems biology analyses of human, rodent and cell line data to identify predictive and dynamic biomarkers. Integrative analyses of multi-omics data from cell lines have been used to identify pathways and mechanisms underlying DKD, as well as integrative analysis of metabolomics and lipidomics profiling and assessment of predictive power in early stage DKD. Sustainability plans for data and resources generated by BEAt-DKD beyond the lifetime of the project are in place, and we are sharing our results within the European Platform for Diabetes and Complications.
6. Optimization of trial design and preparation of implementation in the regulatory process
BEAt-DKD collaborates with key stakeholders including patient and physician groups, regulators, health technology assessors, and scientists from academia, pharmaceutical and biotech companies to develop an optimized blueprint for clinical studies. Recent highlights are the submission of the PRE-score document to the EMA for a Qualification Opinion with a request in consultation of the FDA as external stakeholder, as well as several review articles on the biomarker qualification process and on their use in personalised medicine.
Improved DKD clinical trial efficiency: An improved risk score that integrates multiple markers, expected to improve indication of renal risk and of drug efficacy/safety changes, was submitted to EMA for Qualification Opinion.
Clinical and societal impact: Bringing predictive and dynamic biomarkers to clinical practice will help tailor drugs to specific subgroups of patients and to mitigate adverse drug reactions. BEAt-DKD biomarker results led to a new European project, to test biomarkers in a clinical setting.
Improved imaging tools: BEAt-DKD is the first to direct the full power of quantitative imaging data onto the problem of patient stratification and treatment response, leading the largest MRI and Ultrasound kidney imaging study worldwide, with >620 patients recruited.
Innovation impact: Integrating data from in vitro cell studies, in vivo kidney tissues and clinical trials is a completely novel approach. Urinary extracellular vesicles for detecting biomarkers opens up new avenues for new, non-invasive, clinical practices.
Clinical and societal impact: Bringing predictive and dynamic biomarkers to clinical practice will help tailor drugs to specific subgroups of patients and to mitigate adverse drug reactions. BEAt-DKD biomarker results led to a new European project, to test biomarkers in a clinical setting.
Improved imaging tools: BEAt-DKD is the first to direct the full power of quantitative imaging data onto the problem of patient stratification and treatment response, leading the largest MRI and Ultrasound kidney imaging study worldwide, with >620 patients recruited.
Innovation impact: Integrating data from in vitro cell studies, in vivo kidney tissues and clinical trials is a completely novel approach. Urinary extracellular vesicles for detecting biomarkers opens up new avenues for new, non-invasive, clinical practices.