Abstract
BackgroundDiabetic kidney disease (DKD) remains one of the leading causes of premature death in diabetes. DKD is classified on albuminuria and reduced kidney function (estimated glomerular filtration rate (eGFR)) but these have modest value for predicting future renal status. There is an unmet need for biomarkers that can be used in clinical settings which also improve prediction of renal decline on top of routinely available data, particularly in the early stages. The iBEAt study of the BEAt-DKD project aims to determine whether renal imaging biomarkers (magnetic resonance imaging (MRI) and ultrasound (US)) provide insight into the pathogenesis and heterogeneity of DKD (primary aim) and whether they have potential as prognostic biomarkers in DKD (secondary aim).MethodsiBEAt is a prospective multi-centre observational cohort study recruiting 500 patients with type 2 diabetes (T2D) and eGFR ≥30 ml/min/1.73m2. At baseline, blood and urine will be collected, clinical examinations will be performed, and medical history will be obtained. These assessments will be repeated annually for 3 years. At baseline each participant will also undergo quantitative renal MRI and US with central processing of MRI images. Biological samples will be stored in a central laboratory for biomarker and validation studies, and data in a central data depository. Data analysis will explore the potential associations between imaging biomarkers and renal function, and whether the imaging biomarkers improve the prediction of DKD progression. Ancillary substudies will: (1) validate imaging biomarkers against renal histopathology; (2) validate MRI based renal blood flow measurements against H2O15 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 whether the findings in T2D can be extrapolated to type 1 diabetes.DiscussioniBEAt is the largest DKD imaging study to date and will provide valuable insights into the progression and heterogeneity of DKD. The results may contribute to a more personalised approach to DKD management in patients with T2D.Trial registrationClinicaltrials.gov (NCT03716401).
Highlights
Diabetic kidney disease (DKD) remains one of the leading causes of premature death in diabetes
It is currently estimated that approximately 20–40% of people with diabetes will develop DKD [3], and this is expected to rise in the future
DKD is routinely classified clinically based on albuminuria and reduced kidney function (estimated glomerular filtration rate)
Summary
The BEAt-DKD project Diabetic kidney disease (DKD) is the leading cause of end stage renal disease [1, 2]. 51% of participants in the UK Prospective Diabetes Study whose eGFR declined below 60 ml/min/1.73 m2 had normoalbuminuria [7] This heterogeneity in DKD highlights the need for novel biomarkers and a more personalised medicine-based approach to managing DKD. The key hypotheses are that (1) imaging biomarkers of DKD provide additional information on the pathogenesis and histological and clinical heterogeneity of DKD compared to biomarkers sourced from blood or urine samples or physical exams, and that (2) changes in imaging biomarkers precede increases in albuminuria and decline in kidney function as measured by eGFR slope.
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