Periodic Reporting for period 7 - BEAt-DKD (Biomarker Enterprise to Attack DKD - Sofia ref.: 115974)
Período documentado: 2022-09-01 hasta 2023-08-31
Today, 537 million, or 1 in 10 adults are living with diabetes. This number is predicted to rise to 643 million by 2030 and 783 million by 2045. Up to 50% of patients with diabetes will develop diabetic kidney disease (DKD), the leading cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD).
BEAt-DKD goals:
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.
2. to identify and validate biomarkers of disease progression and treatment response, representing first steps towards precision medicine in the management of DKD.
BEAt-DKD has generated important insights in the pathogenesis, heterogeneity and treatment response in DKD, as evidenced by a growing number of well-cited and high impact publications (167 papers by the end of the project; 24% with IF>10); with papers like the Ahlqvist et al (2018) describing a novel diabetes classification and showing increased risk of renal decline in insulin resistant patients, with >2200 citations.
BEAt-DKD goals:
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.
2. to identify and validate biomarkers of disease progression and treatment response, representing first steps towards precision medicine in the management of DKD.
BEAt-DKD has generated important insights in the pathogenesis, heterogeneity and treatment response in DKD, as evidenced by a growing number of well-cited and high impact publications (167 papers by the end of the project; 24% with IF>10); with papers like the Ahlqvist et al (2018) describing a novel diabetes classification and showing increased risk of renal decline in insulin resistant patients, with >2200 citations.
Biomarker in observational prospective studies
BEAt-DKD harmonized clinical cohorts, validated biomarkers previously identified in pilot studies and discovered novel markers. A novel stress score associated with long-term decline of eGFR in both early and late DKD was developed based on a comprehensive characterization of mRNA transcriptomes from urinary extracellular vesicles (uEVs). We demonstrated technical quality and reproducibility of the mRNAseq pipeline and feasibility in the clinical setting, establishing uEVs as promising non-invasive liquid biopsies in DKD.
Efficacy biomarkers in intervention studies
By integrating omics data from cell- and animal models, and samples from clinical trials, two promising pharmacodynamic markers that can predict the response to atrasentan and canagliflozin have been discovered and validated. Clinical implementation is currently assessed in new prospective clinical trials across Europe within a new EU Horizon RIA grant PRIME-CKD (https://prime-ckd.com(se abrirá en una nueva ventana)). 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.
Mechanisms and pathways
A comprehensive cell encyclopaedia 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 imaging to quantify glomerular endothelial glycocalyx damage. Some of the more recent discoveries are based on extensive single-cell transcriptomics work, experimental work to gain further mechanistic insight with regards to insulin and leptin resistance, to explore epigenetic regulation in kidney organoids, to test the role of endothelial glycocalyx in DKD.
Development, identification and validation of prognostic and predictive imaging biomarkers
The iBEAt study, a prospective multi-centre observational cohort study in 608 patients with early stage DKD, explores associations between imaging biomarkers and renal function, and tests if imaging biomarkers can better predict DKD progression. Ancillary studies aim to: (1) validate imaging biomarkers against renal histopathology; (2) validate MRI measured renal blood flow against positron-emission tomography (PET); (3) validate methods for (semi-)automated processing of renal MRI; (4) examine longitudinal changes in imaging biomarkers; (5) examine if 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. We established a central repository of biofluids with generous volumes to allow extensive targeted and untargeted omics analyses in serum, plasma, whole blood, urine, urinary vesicles and urinary sediment. Study protocols including standard operating procedures have been published (PMID: 32600374).
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. Integration of multi-omics data from cell lines was 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. To ensure sustainability of resources generated by BEAt-DKD and according to FAIRification principles, results have been stored in a central repository, visualized and shared via the European Platform for Diabetes and Complications.
Optimization of trial design and preparation of implementation in the regulatory process
BEAt-DKD collaborated 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, resulting in a Letter of Support from EMA, as well as several review articles on the biomarker qualification process and use in personalised medicine.
BEAt-DKD harmonized clinical cohorts, validated biomarkers previously identified in pilot studies and discovered novel markers. A novel stress score associated with long-term decline of eGFR in both early and late DKD was developed based on a comprehensive characterization of mRNA transcriptomes from urinary extracellular vesicles (uEVs). We demonstrated technical quality and reproducibility of the mRNAseq pipeline and feasibility in the clinical setting, establishing uEVs as promising non-invasive liquid biopsies in DKD.
Efficacy biomarkers in intervention studies
By integrating omics data from cell- and animal models, and samples from clinical trials, two promising pharmacodynamic markers that can predict the response to atrasentan and canagliflozin have been discovered and validated. Clinical implementation is currently assessed in new prospective clinical trials across Europe within a new EU Horizon RIA grant PRIME-CKD (https://prime-ckd.com(se abrirá en una nueva ventana)). 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.
Mechanisms and pathways
A comprehensive cell encyclopaedia 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 imaging to quantify glomerular endothelial glycocalyx damage. Some of the more recent discoveries are based on extensive single-cell transcriptomics work, experimental work to gain further mechanistic insight with regards to insulin and leptin resistance, to explore epigenetic regulation in kidney organoids, to test the role of endothelial glycocalyx in DKD.
Development, identification and validation of prognostic and predictive imaging biomarkers
The iBEAt study, a prospective multi-centre observational cohort study in 608 patients with early stage DKD, explores associations between imaging biomarkers and renal function, and tests if imaging biomarkers can better predict DKD progression. Ancillary studies aim to: (1) validate imaging biomarkers against renal histopathology; (2) validate MRI measured renal blood flow against positron-emission tomography (PET); (3) validate methods for (semi-)automated processing of renal MRI; (4) examine longitudinal changes in imaging biomarkers; (5) examine if 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. We established a central repository of biofluids with generous volumes to allow extensive targeted and untargeted omics analyses in serum, plasma, whole blood, urine, urinary vesicles and urinary sediment. Study protocols including standard operating procedures have been published (PMID: 32600374).
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. Integration of multi-omics data from cell lines was 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. To ensure sustainability of resources generated by BEAt-DKD and according to FAIRification principles, results have been stored in a central repository, visualized and shared via the European Platform for Diabetes and Complications.
Optimization of trial design and preparation of implementation in the regulatory process
BEAt-DKD collaborated 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, resulting in a Letter of Support from EMA, as well as several review articles on the biomarker qualification process and use in personalised medicine.
Improved DKD clinical trial efficiency: A risk score that integrates multiple markers, expected to improve indication of renal risk and of drug efficacy/safety changes, has received a positive evaluation by the EMA (https://www.beat-dkd.eu/news/(se abrirá en una nueva ventana))
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 results led to a new European project, PRIME-CKD, 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 to the largest MRI and ultrasound kidney imaging study worldwide. Sharing of protocols will help maximise opportunities of alignment for pooling renal imaging data in the future.
Innovation impact: Integrating data from in vitro cell studies, in vivo kidney tissues and clinical trials is a completely novel approach. Urinary extracellular vesicles are promising non-invasive liquid kidney biopsies in DKD.
Overall, BEAt-DKD has delivered tools and knowledge for better patient stratification, contributing to improved clinical development processes for evaluating new therapies, via a reduction in the size and potentially also costs of future confirmatory trials needed for regulatory approval, accelerating the improved management of DKD.
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 results led to a new European project, PRIME-CKD, 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 to the largest MRI and ultrasound kidney imaging study worldwide. Sharing of protocols will help maximise opportunities of alignment for pooling renal imaging data in the future.
Innovation impact: Integrating data from in vitro cell studies, in vivo kidney tissues and clinical trials is a completely novel approach. Urinary extracellular vesicles are promising non-invasive liquid kidney biopsies in DKD.
Overall, BEAt-DKD has delivered tools and knowledge for better patient stratification, contributing to improved clinical development processes for evaluating new therapies, via a reduction in the size and potentially also costs of future confirmatory trials needed for regulatory approval, accelerating the improved management of DKD.