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Abstract: FR-PO424

Prognostic Imaging Biomarkers for Diabetic Kidney Disease (iBEAT): A BEAt-DKD Study

Session Information

Category: Diabetic Kidney Disease

  • 602 Diabetic Kidney Disease: Clinical

Authors

  • Sourbron, Steven, University of Leeds, Leeds, United Kingdom
  • Gooding, Kim, University of Exeter Medical School, Exeter, United Kingdom
  • Lienczewski, Chrysta C., University of Michigan Medical Center, Ann Arbor, Michigan, United States
  • Papale, Massimo, University of Bari, Bari, Italy
  • Koivuviita, Niina S., Hospital District of Southwest Filand, Turku, Finland
  • Zetterqvist, Anna V., Lund University, Malmö, Sweden
  • Andersson, Anna-Maria Dutius, Lund University, Malmö, Sweden
  • Sharma, Kanishka, University of Leeds, Leeds, United Kingdom
  • Garcia-Hernandez, Alberto, Astellas Pharma Europe B.V., Leiden, Netherlands
  • Kuznetsov, Dmitry, SIB, Lausanne, Switzerland
  • Saunavaara, Virva, Turku PET centre c/o Turku University Hospital, Turku, Finland
  • Tagkalakis, Fotios, University of Leeds, Leeds, United Kingdom
  • Pesce, Francesco, University of Bari, Bari, Italy
  • Teh, Irvin, University of Leeds, Leeds, United Kingdom
  • Ball, Claire, NIHR Exeter Clinical Research Facility, Exeter, United Kingdom
  • Puppala, Sapna, Leeds teaching hospital, Leeds, United Kingdom
  • Metsarinne, Kaj P., Turku University Central Hospital, Turku, Finland
  • Combe, Christian, CHU de Bordeaux, Bordeaux, France
  • Ibberson, Mark, SIB, Lausanne, Switzerland
  • Holthofer, Harry B., University of Helsinki, Finnish Institute of Molecular Medicine, Helsinki, Finland
  • Simons, Kai, MPI-CBG, Dresden, Germany
  • Karihaloo, Anil K., Novo Nordisk, Seattle, Washington, United States
  • Ju, Wenjun, University of Michigan, Ann Arbor, Michigan, United States
  • Urquhart, Richard, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, Connecticut, United States
  • Rigalleau, Vincent, CHU de Bordeaux, Bordeaux, France
  • Banks, Rosamonde Elizabeth, University of Leeds, Leeds, United Kingdom
  • Gilmour, Peter S., Astellas Pharma Europe BV, Leiden, Netherlands
  • Mansfield, Michael W., University of Leeds, Leeds, United Kingdom
  • Gilchrist, Mark, Royal Devon and Exeter Hospital, Devon, Exeter, United Kingdom
  • de Zeeuw, Dick, University Medical Center Groningen, Groningen, Netherlands
  • Lambers Heerspink, Hiddo Jan, University Medical Center Groningen, Groningen, Netherlands
  • Kretzler, Matthias, U.Michigan, Ann Arbor, Michigan, United States
  • Welberry smith, Matthew, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
  • Gesualdo, Loreto, University of Bari, Bari, Italy
  • Andress, Dennis L., AbbVie, North Chicago, Illinois, United States
  • Grenier, Nicolas, Pellegrin Hospital, Bordeaux, France
  • Shore, Angela C., University of Exeter, Exeter, United Kingdom
  • Gomez, Maria F., Lund University, Malmö, Sweden
Background

BEAt-DKD (Biomarker Enterprise to Attack DKD) is a public-private partnership committed to deliver more effective patient stratification, DKD prevention and management (www.beat-dkd.eu; IMI-JU No 115974). We report here on an early milestone in BEAt-DKD, the design and setup of a clinical study (iBEAT) to explore the utility of imaging biomarkers.

Methods

iBEAT was developed as a collaborative project with central coordination between sept 2016 and June 2018. iBEAT will be run by 7 core sites including 5 recruiting centres, one of whom is the coordinating site (Leeds), a central biobank (Lund), a data management centre (Lausanne), and an image processing and QA centre (Leeds)

Results

iBEAT is a 4-year prospective observational cohort study in 500 patients with Type 2 diabetes and eGFR>30mL/min, aiming to identify MRI & Ultrasound (US) biomarkers that can improve DKD prognosis. MRI and US will be collected at baseline only. Demographics, clinical, family and medication history, blood (70mL) and urine will be collected annually.
Additional data will be collected by four sites to address ancillary objectives (100 patients per site): Kidney biopsies, digitalized and characterized by histology and EM (Bari); PET-based renal blood flow (Turku); glycocalyx and microvascular assessments (Exeter); 2-year follow-up MRI and US (Bordeaux).
Biopsies and biofluids including urinary vesicles and sediment will be used for biomarker discovery using state of the art omics, and stored for validation studies. A parsimonious set of baseline biomarkers associated with eGFR (primary) and eGFR slope over time (secondary) will be identified.

Conclusion

iBEAT is the largest functional imaging biomarker study in DKD performed to date. The study will test the utility of imaging biomarkers for DKD prognosis, and may also help improve our understanding of disease pathogenesis.

Funding

  • Commercial Support