BEAT-DKD

Biomarker enterprise to attack DKD

Summary

About half of all people living with diabetes will develop diabetic kidney disease (DKD), which is the leading cause of chronic kidney disease. It results in the need for dialysis and transplantation, reducing life expectancy and quality of life.

When the BEAt-DKD project kicked off, research into DKD had largely stagnated. There was a limited understanding of the molecular mechanisms underlying disease progression and what triggered the disease, and there were limited tools available for diagnosis, prognosis and monitoring whether patients were responsive or not to the available treatments. BEAt-DKD generated important insights into the mechanisms behind the disease progression, heterogeneity and treatment response in DKD.

A major contribution by the project to the field of diabetic kidney disease research is that there is now a better understanding of the disease’s heterogeneity. As a result of the project’s work, it’s now clear that not all patients have the same disease progression nor the same response to treatment. The project discovered new pathways and mechanisms driving disease, some of which are potentially targetable.

BEAt-DKD shone a spotlight on insulin-resistance as a core driver of DKD, and profiled insulin-resistant kidney models and biopsies to reveal both common and cell-type-specific mechanisms underpinning DKD.

BEAt-DKD is running the iBEAT multicentre observational study, a large study exploring the associations between imaging biomarkers and renal functioning. Roughly 780 patients with type 2 diabetes (including 62 individuals with type 1 diabetes) were recruited from six study centres across the UK, Italy, Finland and France. All participants underwent a deep and thorough phenotypic characterisation and were followed up with every year for four years.

The project also developed a multi-parameter drug response score that predicts the risk of reaching renal endpoints as consequence of a drug effect, called the PRE score. The score can improve drug development and study design for registration trials in patients with diabetes and chronic kidney disease. The European Medicines Agency issued a letter of support for the validation of the PRE score as a tool for drug development in kidney diseases.

Importantly, BEAt-DKD made strides in highlighting the much better utilisation of urine as a source of information. Urinary extracellular vesicles were examined for their potential as carriers of information, and a novel stress score associated with long-term decline of kidney function in both early and late DKD was developed based on transcriptomic data.

This was important because, before the BEAt-DKD project started, only two biomarkers were available to detect diabetic kidney disease. Both were insensitive and it was generally only possible to detect them when the disease was already advanced.

Today, thanks to the BEAt-DKD project, there are multiple new biomarkers available that are much more sensitive. Some of the new biomarkers can help to predict the risk of disease progression (prognostic biomarkers), while others can help to monitor the patient’s response soon after treatment initiation (dynamic biomarkers). These biomarkers also have commercial potential as companion diagnostics and could be used for personalised medicine approaches to treat DKD. Clinical implementation of some of these biomarkers is currently being tested in prospective clinical trials across Europe within the framework of a new EU Horizon RIA grant PRIME-CKD (https://prime-ckd.com).

Achievements & News

Diabetes treatments set to get personal, thanks to new IT tool

Building on ground-breaking results from IMI diabetes projects, scientists are now working on a software tool that would identify what subtype of diabetes a patient has, and suggest which treatment would work best for them.###

For many years, the medical world has recognised two main types of diabetes: type 1 and type 2. However, research funded in part by IMI through the BEAt-DKD and RHAPSODY projects paints a different picture, suggesting that there are not two subtypes of diabetes, but five. The scientists have since validated these initial findings in additional patient populations, and several studies are currently ongoing to test the effects of different treatments on the different diabetes subtypes.

Meanwhile, investigators have developed a software tool, which is currently used for research purposes and is soon to be implemented in the clinic, to allow doctors to identify which diabetes subtype the patient has. The researchers have received funding from other sources beyond IMI to carry out these additional studies. All in all, this story shows how IMI projects can deliver ground-breaking results, validate them, and turn them into a tool that can hopefully assist in providing the right treatment for the right patient at the right time.

Find out more

Taking a tailored approach to type 2 diabetes

Diabetes is a chronic and incurable illness linked to blood sugar that has traditionally been divided into type 1 and type 2. Type 2 accounts for the vast majority of cases – some 285 million – and its prevalence is expected to soar over the coming decade. Amid this backdrop, IMI's RHAPSODY project set out to look more closely at type 2 in a bid to develop targeted treatments for the condition, which can vary significantly and cause serious complications such as kidney failure. ###In a major development, RHAPSODY – in conjunction with others including IMI's BEAT-DKD project – has broken type 2 diabetes down into five subgroups which need different treatments and have different progressions. And this, the researchers believe, has the potential to revolutionise how doctors deal with diabetics. ‘What RHAPSODY is really about is individualising diabetes treatment,’ says vice project coordinator Leif Groop of Lund University in Sweden. ‘For too long, we have had the situation that one size fits all.’  The subgroups grew out of a Swedish study known as ANDIS involving more than 13 000 diabetics and initiated by Groop. It monitored not only patients' blood sugar but also factors such as insulin resistance and secretion, as well as age. The study has since been replicated, including in China.

Scientists identify five subtypes of diabetes

Scientists have identified five subtypes of diabetes, a finding that will pave the way for more personalised treatments for the disease. The work, published in The Lancet Diabetes and Endocrinology, was funded in part by IMI through the projects BEAT-DKD and RHAPSODY. ###Currently, two main types of diabetes are recognised, and diagnosis is through a measurement of a patient’s blood sugar levels. In this study, scientists monitored over 13 000 newly-diagnosed diabetes patients, analysing blood sugar levels, insulin resistance, insulin secretion, and age of onset among other things. This revealed five distinct groups of patients with different risk levels for certain complications associated with diabetes. For example, patients in group 2 (‘severe insulin-deficient diabetes’) are at greatest risk of eye disease, while patients in group 3 (‘severe insulin-resistant diabetes’) had the highest incidence of kidney damage. ‘Current diagnostics and classification of diabetes are insufficient and unable to predict future complications or choice of treatment,’ said Leif Groop of Lund University in Sweden. ‘This is the first step towards personalised treatment of diabetes.’ Until now, the team has only studied people in Sweden and Finland; they now plan to carry out similar studies in China and India, to see if their findings apply in different ethnic groups.

Participants

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Universities, research organisations, public bodies, non-profit groups
  • Academisch Ziekenhuis Groningen, Groningen, Netherlands
  • Astellas Pharma Europe BV, Leiden, Netherlands
  • Bayer Aktiengesellschaft, Leverkusen, Germany
  • Boehringer Ingelheim Internationalgmbh, Ingelheim, Germany
  • Breakthrough T1d, New York, United States
  • Chu Hopitaux De Bordeaux, Talence, France
  • Eli Lilly And Company LTD, Basingstoke, United Kingdom
  • Istituto Di Ricerche Farmacologiche Mario Negri, Milano, Italy
  • Itä-Suomen yliopisto, Kuopio, Finland
  • Klinikum Der Universitaet Regensburg, Regensburg, Germany
  • Lunds Universitet, Lund, Sweden
  • Medizinische Universitaet Wien, Wien, Austria
  • Medizinische Universitat Innsbruck, Innsbruck, Austria
  • Novo Nordisk A/S, Bagsvaerd, Denmark
  • SIB Institut Suisse De Bioinformatique, CH-660-0733998-3, Geneve, Switzerland
  • The University Of Exeter, Exeter, United Kingdom
  • The University Of Sheffield, Sheffield, United Kingdom
  • Universita Degli Studi Di Bari Aldo Moro, Bari, Italy
  • Universitaetsklinikum Hamburg-Eppendorf, Hamburg, Germany
  • Universitatsklinikum Erlangen, Erlangen, Germany
  • University Of Bristol, Bristol, United Kingdom
  • University Of Dundee, Dundee, United Kingdom
  • University Of Hull, Hull, United Kingdom
  • University Of Leeds, Leeds, United Kingdom
  • University Of Michigan The Regents Of The University Of Michigan, Ann Arbor, United States
  • University of Helsinki, Helsingin Yliopisto, Finland
  • University of Turku, Turku, Finland
Small and medium-sized enterprises (SMEs) and mid-sized companies (<€500 m turnover)
  • Antaros Medical AB, Molndal, Sweden
  • Lipotype, Dresden, Germany
Third parties
  • Apuliabiotech Societa Consortile Ar L, Valenzano, Italy
  • Azienda Ospedaliero Universitaria Consorziale Policlinico Di Bari, Bari, Italy
  • The Leeds Teaching Hospitals National Health Service Trust, Leeds, United Kingdom
  • Varsinais-Suomen Sairaanhoitopiirin Kuntayhtyma, Turku, Finland

Participants
NameEU funding in €
Academisch Ziekenhuis Groningen1 942 896
Antaros Medical AB16 125
Chu Hopitaux De Bordeaux33 087
Istituto Di Ricerche Farmacologiche Mario Negri150 000
Itä-Suomen yliopisto200 000
Klinikum Der Universitaet Regensburg360 000
Lipotype300 000
Lunds Universitet2 509 153
Medizinische Universitaet Wien950 000
Medizinische Universitat Innsbruck930 000
SIB Institut Suisse De Bioinformatique, CH-660-0733998-3444 000
The University Of Exeter670 656
The University Of Sheffield775 192
Universita Degli Studi Di Bari Aldo Moro568 000
Universitaetsklinikum Freiburg (left the project)44 083
Universitaetsklinikum Hamburg-Eppendorf1 544 468
Universitatsklinikum Erlangen387 500
University Of Bristol583 883
University Of Dundee655 000
University of Helsinki1 001 300
University Of Hull250 000
University Of Leeds373 798
University of Oxford (left the project)5 078
University of Turku162 313
 
Third parties
NameFunding in €
Apuliabiotech Societa Consortile Ar L42 000
Azienda Ospedaliero Universitaria Consorziale Policlinico Di Bari10 000
The Leeds Teaching Hospitals National Health Service Trust94 717
Varsinais-Suomen Sairaanhoitopiirin Kuntayhtyma82 688
 
Total Cost15 085 937