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Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol
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- Gooding, Kim (author)
- University of Exeter,Royal Devon & Exeter Hospital
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- Maziarz, Marlena (author)
- Lund University,Lunds universitet,Diabetiska komplikationer,Forskargrupper vid Lunds universitet,Diabetic Complications,Lund University Research Groups
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- Dutius Andersson, Anna-Maria (author)
- Lund University,Lunds universitet,Diabetiska komplikationer,Forskargrupper vid Lunds universitet,Diabetic Complications,Lund University Research Groups
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- (creator_code:org_t)
- 2020-06-29
- 2020
- English.
- In: BMC Nephrology. - : Springer Science and Business Media LLC. - 1471-2369. ; 21:1
- Journal article (peer-reviewed)
Abstract
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- BACKGROUND: Diabetic 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). METHODS: iBEAt 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. DISCUSSION: iBEAt 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 REGISTRATION: Clinicaltrials.gov ( NCT03716401 ).
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Endokrinologi och diabetes (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Endocrinology and Diabetes (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Urologi och njurmedicin (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Urology and Nephrology (hsv//eng)
Keyword
- Albuminuria
- Biomarkers
- Chronic kidney disease stages 1–3
- Diabetic kidney disease
- Magnetic resonance imaging
- Progression
- Prospective cohort
- Renal decline
- Type 2 diabetes
- Ultrasound
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- art (subject category)
- ref (subject category)
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