Prognostic imaging biomarkers for diabetic kidney disease (iBEAt):study protocol

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)

Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol

Abstract 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 ).http://deepblue.lib.umich.edu/bitstream/2027.42/173568/1/12882_2020_Article_1901.pd

NIHR Liver/Renal Biomarker Programme Final Report: Evaluating the benefits for patients and the NHS of new and existing biological fluid biomarkers in liver and renal disease

Protein biomarkers are naturally occurring substances that can be measured, often in fluids such as blood or urine, and which provide information about a patient and their illness. Different diseases have different biomarkers. When people become ill, changes in biomarker levels may occur before any clinical symptoms or signs become apparent. Measuring biomarkers in blood or urine is simple, safe and may help the doctor diagnose which disease the patient has, determine how severe it is, help choose the best treatment and help detect if the disease is getting worse or better. Unfortunately, for many diseases there are not enough biomarkers that are of proven usefulness in patient care today. New developments in research mean that many more are now being discovered but there is no quick and reliable way to decide which of the markers are good enough to be useful clinically. While our research proposal focusses on diseases of the liver and kidney, in the future it can also serve as the "blueprint" for similar work in other diseases. It is aimed at developing a structure and methods to assess the clinical usefulness of biomarkers as quickly and efficiently as possible. The research is divided into three parallel workstreams : 1. Identification of the best research methods for monitoring disease or treatment with biomarkers - the lack of understanding this has hampered this field so far. 2. The creation of a sample "banking" system for collecting and storing patient samples and relevant clinical data from large numbers of patients. This will allow the immediate testing of potential new biomarkers now and in the future. The best biomarkers would then go on to full trials to see if patients and the NHS would benefit from their use. 3. A clinical trial at multiple hospitals in the UK of three new biomarkers for liver damage (together called the "Enhanced liver fibrosis" or "ELF", test). We will find out if ELF can give early warning of dangerous liver damage (cirrhosis) and therefore reduce the risk of major complications. This trial may radically alter the way in which patients with liver disease can be looked after clinically. This research programme will benefit patients and the NHS by ensuring that biomarkers in the future can be evaluated and introduced more rapidly, improving clinical management for each individual patient and leading to better use of NHS resources

Additional file 2 of Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol

Additional file 2: 2.1 Biofluid collection SOPs. PDF file. Biofluid collection protocol. The protocol for the collection of blood and urine samples within iBEAt. 2.2 SOPs Biofluid processing. PDF file. Biofluid processing protocol. The protocol for processing blood and urine samples within iBEAt. 2.3 Biofluid schematics. PDF file. iBEAt kit contents and biofluid processing schematics. Schematics of iBEAt collection kits, and processing and storage protocols for collected blood and urine samples within iBEAt

Additional file 4 of Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol

Additional file 4: 4.0 Biopsy SOP. PDF file. Biopsy and pathology SOPs. Protocol for storing and capturing meta-data regarding the renal biopsy tissue for the iBEAt study. (EXE 543 kb

Additional file 3 of Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol

Additional file 3: 3.0 CRF Screening. PDF file. Study recruitment – prescreening / screening. Clinical record form for prescreening / screening data. 3.1 CRF Adherence Checklist. PDF file. Baseline visit (V1) – adherence checklist. Clinical record form documenting participant adherence to guidance for the baseline visit. 3.2 CRF Limited Clinical Exam. PDF file. Limited Clinical Exam. Clinical record form for clinical examination data including, for example, blood pressure, height and weight. 3.3 CRF Medical and Family Hx. PDF file. Baseline (V1) – Medical and family history V2. Clinical record form for medical and family history (version 2). 3.4 CRF Local Study Labs. PDF file. Baseline (V1) – local study labs. Clinical record form for laboratory measurements performed at recruiting centre. 3.5 CRF Routine Labs. PDF file. Baseline visit (V1) – labs. Clinical record form for documenting all available laboratory values in the year prior to the baseline visit. 3.6 CRF Medications. PDF file. Medication log. Clinical record form documenting all current medications. 3.7 CRF Ultrasound. PDF file. Baseline visit (V1) – Ultrasound. Clinical record form for the renal ultrasound measurements. 3.8 CRF Biosamples. PDF file. Study biosamples. Clinical record form / checklist documenting what biofluid samples were collected and processed for the iBEAt study

Additional file 1 of Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol

Additional file 1: 1.1 MRI biomarkers. File type: PDF file. Title: List of primary MRI biomarkers. Description: A table listing the biomarkers that will be derived from the MRI data to address the primary objectives. 1.2 MRI acquisition protocol. PDF file. MRI acquisition protocol (reference scanner). MRI sequence parameters for the iBEAt protocol on the reference scanner (Siemens 3 T). 1.3 Renal ultrasound SOP. PDF file. Ultrasound Standard Operating Procedures. Standard operating procedures for Ultrasound scanning in iBEAt