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

BEAt-DKD Consortium; Kim M. Gooding; Chrysta Lienczewski; Massimo Papale; Niina Koivuviita; Marlena Maziarz; Anna-Maria Dutius Andersson; Kanishka Sharma; Paola Pontrelli; Alberto Garcia Hernandez; Julie Bailey; Kay Tobin; Virva Saunavaara; Anna Zetterqvist; David Shelley; Irvin Teh; Claire Ball; Sapna Puppala; Mark Ibberson; Anil Karihaloo; Kaj Metsarinne; Rosamonde E. Banks; Peter S. Gilmour; Michael Mansfield; Mark Gilchrist; Dick de Zeeuw; Hiddo J. L. Heerspink; Pirjo Nuutila; Matthias Kretzler; Matthew Welberry Smith; Loreto Gesualdo; Dennis Andress; Nicolas Grenier; Angela C. Shore; Maria F. Gomez; Steven Sourbron

doi:10.1186/s12882-020-01901-x

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

BEAt-DKD Consortium, Kim M. Gooding^*, Chrysta Lienczewski, Massimo Papale, Niina Koivuviita, Marlena Maziarz, Anna-Maria Dutius Andersson, Kanishka Sharma, Paola Pontrelli, Alberto Garcia Hernandez, Julie Bailey, Kay Tobin, Virva Saunavaara, Anna Zetterqvist, David Shelley, Irvin Teh, Claire Ball, Sapna Puppala, Mark Ibberson, Anil KarihalooKaj Metsarinne, Rosamonde E. Banks, Peter S. Gilmour, Michael Mansfield, Mark Gilchrist, Dick de Zeeuw, Hiddo J. L. Heerspink, Pirjo Nuutila, Matthias Kretzler, Matthew Welberry Smith, Loreto Gesualdo, Dennis Andress, Nicolas Grenier, Angela C. Shore, Maria F. Gomez, Steven Sourbron

^*Corresponding author voor dit werk

Onderzoeksoutput › Academic › peer review

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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).

Originele taal-2	English
Artikelnummer	242
Aantal pagina's	11
Tijdschrift	Bmc nephrology
Volume	21
Nummer van het tijdschrift	1
DOI's	https://doi.org/10.1186/s12882-020-01901-x
Status	Published - 29-jun.-2020

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Prognostic imaging biomarkers for diabeticFinal publisher's version, 791 KBLicentie: CC BY

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Additional file 1 of Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol
Lienczewski, C. (Contributor), Karihaloo, A. (Contributor), Kretzler, M. (Contributor), Dutius Andersson, A.-M. (Contributor), Pontrelli, P. (Contributor), Gesualdo, L. (Contributor), Sharma, K. (Contributor), Welberry Smith, M. (Contributor), Gooding, K. M. (Contributor), Shore, A. C. (Contributor), Ibberson, M. (Contributor), Lambers Heerspink, H. (Contributor), Gomez, M. F. (Contributor), Gilchrist, M. (Contributor), Nuutila, P. (Contributor), Teh, I. (Contributor), Mansfield, M. (Contributor), Papale, M. (Contributor), Banks, R. E. (Contributor), Bailey, J. (Contributor), Andress, D. (Contributor), Koivuviita, N. (Contributor), Sourbron, S. (Contributor), Tobin, K. (Contributor), Metsärinne, K. (Contributor), Zetterqvist, A. (Contributor), Garcia Hernandez, A. (Contributor), De Zeeuw, D. (Contributor), Ball, C. (Contributor), Grenier, N. (Contributor), Saunavaara, V. (Contributor), Maziarz, M. (Contributor), Gilmour, P. S. (Contributor), Shelley, D. (Contributor) & Puppala, S. (Contributor), University of Groningen, 29-jun.-2020
DOI: 10.6084/m9.figshare.12586625.v1
Dataset
Additional file 2 of Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol
Dutius Andersson, A.-M. (Contributor), Garcia Hernandez, A. (Contributor), Tobin, K. (Contributor), Ball, C. (Contributor), Saunavaara, V. (Contributor), Teh, I. (Contributor), Banks, R. E. (Contributor), Sharma, K. (Contributor), Lienczewski, C. (Contributor), Koivuviita, N. (Contributor), Metsärinne, K. (Contributor), De Zeeuw, D. (Contributor), Karihaloo, A. (Contributor), Mansfield, M. (Contributor), Lambers Heerspink, H. (Contributor), Maziarz, M. (Contributor), Gesualdo, L. (Contributor), Pontrelli, P. (Contributor), Bailey, J. (Contributor), Papale, M. (Contributor), Nuutila, P. (Contributor), Gomez, M. F. (Contributor), Ibberson, M. (Contributor), Gooding, K. M. (Contributor), Sourbron, S. (Contributor), Shelley, D. (Contributor), Grenier, N. (Contributor), Shore, A. C. (Contributor), Zetterqvist, A. (Contributor), Welberry Smith, M. (Contributor), Gilchrist, M. (Contributor), Kretzler, M. (Contributor), Gilmour, P. S. (Contributor), Puppala, S. (Contributor) & Andress, D. (Contributor), University of Groningen, 29-jun.-2020
DOI: 10.6084/m9.figshare.12586628.v1
Dataset
Additional file 4 of Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol
Pontrelli, P. (Contributor), Grenier, N. (Contributor), Sharma, K. (Contributor), Dutius Andersson, A.-M. (Contributor), Garcia Hernandez, A. (Contributor), Mansfield, M. (Contributor), Teh, I. (Contributor), De Zeeuw, D. (Contributor), Lambers Heerspink, H. (Contributor), Ibberson, M. (Contributor), Papale, M. (Contributor), Saunavaara, V. (Contributor), Shore, A. C. (Contributor), Koivuviita, N. (Contributor), Sourbron, S. (Contributor), Bailey, J. (Contributor), Andress, D. (Contributor), Lienczewski, C. (Contributor), Banks, R. E. (Contributor), Metsärinne, K. (Contributor), Gilmour, P. S. (Contributor), Maziarz, M. (Contributor), Tobin, K. (Contributor), Shelley, D. (Contributor), Gesualdo, L. (Contributor), Puppala, S. (Contributor), Kretzler, M. (Contributor), Welberry Smith, M. (Contributor), Gooding, K. M. (Contributor), Nuutila, P. (Contributor), Gilchrist, M. (Contributor), Karihaloo, A. (Contributor), Ball, C. (Contributor), Zetterqvist, A. (Contributor) & Gomez, M. F. (Contributor), University of Groningen, 29-jun.-2020
DOI: 10.6084/m9.figshare.12586637.v1
Dataset

Citeer dit

BEAt-DKD Consortium, Gooding, K. M., Lienczewski, C., Papale, M., Koivuviita, N., Maziarz, M., Dutius Andersson, A.-M., Sharma, K., Pontrelli, P., Garcia Hernandez, A., Bailey, J., Tobin, K., Saunavaara, V., Zetterqvist, A., Shelley, D., Teh, I., Ball, C., Puppala, S., Ibberson, M., ... Sourbron, S. (2020). Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol. Bmc nephrology, 21(1), Artikel 242. https://doi.org/10.1186/s12882-020-01901-x

@article{eb900d0a490a49ee9cf54c6a4e72c89c,

title = "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).",

keywords = "Diabetic kidney disease, Type 2 diabetes, Magnetic resonance imaging, Ultrasound, Albuminuria, Chronic kidney disease stages 1-3, Prospective cohort, Renal decline, Biomarkers, Progression, RENAL-FUNCTION, DIFFUSION, MRI, POPULATION, SELECTION, DECLINE",

author = "{BEAt-DKD Consortium} and Gooding, {Kim M.} and Chrysta Lienczewski and Massimo Papale and Niina Koivuviita and Marlena Maziarz and {Dutius Andersson}, Anna-Maria and Kanishka Sharma and Paola Pontrelli and {Garcia Hernandez}, Alberto and Julie Bailey and Kay Tobin and Virva Saunavaara and Anna Zetterqvist and David Shelley and Irvin Teh and Claire Ball and Sapna Puppala and Mark Ibberson and Anil Karihaloo and Kaj Metsarinne and Banks, {Rosamonde E.} and Gilmour, {Peter S.} and Michael Mansfield and Mark Gilchrist and {de Zeeuw}, Dick and Heerspink, {Hiddo J. L.} and Pirjo Nuutila and Matthias Kretzler and {Welberry Smith}, Matthew and Loreto Gesualdo and Dennis Andress and Nicolas Grenier and Shore, {Angela C.} and Gomez, {Maria F.} and Steven Sourbron",

note = "Funding Information: The organisation of iBEAt is shown in Fig. 1. The study is led by the coordinating centre in Sheffield with a co-lead in Exeter and a study manager in Michigan. Currently there are 5 recruiting centres (University of Leeds, University of Exeter Medical School, University of Bari, University of Bordeaux and University of Turku), a central laboratory (Lund University) and a central data repository (Swiss Institute of Bioinformatics (SIB)). University of Sheffield is the central imaging processing and quality assurance (QA) site, with support from Antaros Medical (Sweden) for biomarkers of body composition. All ethical and relevant local approvals are in place at each recruiting site. As a BEAt-DKD work package the study is supported by the BEAt-DKD consortium Steering Committee and an external Scientific Advisory Board. Funding Information: This project is principally funded by the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115974. This Joint Undertaking receives support from the European Union{\textquoteright}s Horizon 2020 research and innovation programme and EFPIA with JDRF. This study receives additional support (personnel support) by grants from the Swedish Heart and Lung Foundation [20160872]; the Swedish Research Council [2018–02837; EXODIAB 2009–1039]; the Swedish Foundation for Strategic Research (LUDC-IRC 15–0067) to MFG; and the UK Medical Research Council (MR/R02264X/1) and Kidney Research UK (RP55/2012) to SS. This project is also supported by the National Institute for Health Research (NIHR) Exeter Clinical Research Facility and the NIHR Leeds Clinical Research Facility. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The funding bodies, except for JDRF, played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. Funding Information: This work forms part of the BEAt-DKD consortium that is funded by the IMI 2 Joint Undertaking that receives support from the European Federation of Pharmaceutical Industries and Associations (EFPIA). BEAt-DKD EFPIA partners that have contributed to the iBEAT study development are Astellas, AbbVie and Novo Nordisk. JDRF also contributed to the iBEAT study design. AMDA reports grants from Boehringer Ingelheim Pharma GmbH during the conduct of the study. AZ reports non-financial support and other from Boehringer Ingelheim Pharma GmbH during the conduct of the study. MG reports personal fees from Lilly and other from Sanofi Genzyme, outside of the submitted work. DZ reports other from Fresenius, other from Boehringer Ingelheim, other from Bayer, other from Mitsubishi Tanabe, other from Mundipharma, other from Janssen, other from AbbVie, outside the submitted work. HJLH reports other from Merck, other from Mitsubishi Tanabe, grants and other from Janssen, other from Mundipharma, other from Gilead, grants and other from AstraZeneca, grants and other from Abbvie, other from Retrophin, outside the submitted work. MK reports grants from NIH, non-financial support from University of Michigan, during the conduct of the study; grants from JDRF, grants from Astra-Zeneca, grants from NovoNordisc, grants from Eli Lilly, grants from Gilead, grants from Goldfinch Bio, grants from Merck, grants from Janssen, grants from Boehringer-Ingelheim, outside the submitted work; In addition, MK has a patent Biomarkers for CKD progression (encompassing urinary EGF as biomarker of CKD progression) issued. DA reports other from AbbVie, outside the submitted work. MFG reports non-financial support and other from Boehringer Ingelheim Pharma GmbH, non-financial support and other from JDRF International, non-financial support and other from Eli Lilly, non-financial support and other from AbbVie, non-financial support and other from Sanofi-Aventis, non-financial support and other from Astellas, non-financial support and other from Novo Nordisk A/S, non-financial support and other from Bayer AG, during the conduct of the study; personal fees from Lilly, non-financial support and other from Novo Nordisk, nonfinancial support and other from Pfizer, non-financial support and other from Follicum, non-financial support and other from Abcentra, non-financial support from Probi, non-financial support from Johnson & Johnson, outside the submitted work. SS reports non-financial support from Siemens, during the conduct of the study. Publisher Copyright: {\textcopyright} 2020 The Author(s).",

year = "2020",

month = jun,

day = "29",

doi = "10.1186/s12882-020-01901-x",

language = "English",

volume = "21",

journal = "Bmc nephrology",

issn = "1471-2369",

publisher = "BMC",

number = "1",

}

BEAt-DKD Consortium, Gooding, KM, Lienczewski, C, Papale, M, Koivuviita, N, Maziarz, M, Dutius Andersson, A-M, Sharma, K, Pontrelli, P, Garcia Hernandez, A, Bailey, J, Tobin, K, Saunavaara, V, Zetterqvist, A, Shelley, D, Teh, I, Ball, C, Puppala, S, Ibberson, M, Karihaloo, A, Metsarinne, K, Banks, RE, Gilmour, PS, Mansfield, M, Gilchrist, M, de Zeeuw, D , Heerspink, HJL, Nuutila, P, Kretzler, M, Welberry Smith, M, Gesualdo, L, Andress, D, Grenier, N, Shore, AC, Gomez, MF & Sourbron, S 2020, 'Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol', Bmc nephrology, vol. 21, nr. 1, 242. https://doi.org/10.1186/s12882-020-01901-x

TY - JOUR

T1 - Prognostic imaging biomarkers for diabetic kidney disease (iBEAt)

T2 - study protocol

AU - BEAt-DKD Consortium

AU - Gooding, Kim M.

AU - Lienczewski, Chrysta

AU - Papale, Massimo

AU - Koivuviita, Niina

AU - Maziarz, Marlena

AU - Dutius Andersson, Anna-Maria

AU - Sharma, Kanishka

AU - Pontrelli, Paola

AU - Garcia Hernandez, Alberto

AU - Bailey, Julie

AU - Tobin, Kay

AU - Saunavaara, Virva

AU - Zetterqvist, Anna

AU - Shelley, David

AU - Teh, Irvin

AU - Ball, Claire

AU - Puppala, Sapna

AU - Ibberson, Mark

AU - Karihaloo, Anil

AU - Metsarinne, Kaj

AU - Banks, Rosamonde E.

AU - Gilmour, Peter S.

AU - Mansfield, Michael

AU - Gilchrist, Mark

AU - de Zeeuw, Dick

AU - Heerspink, Hiddo J. L.

AU - Nuutila, Pirjo

AU - Kretzler, Matthias

AU - Welberry Smith, Matthew

AU - Gesualdo, Loreto

AU - Andress, Dennis

AU - Grenier, Nicolas

AU - Shore, Angela C.

AU - Gomez, Maria F.

AU - Sourbron, Steven

N1 - Funding Information: The organisation of iBEAt is shown in Fig. 1. The study is led by the coordinating centre in Sheffield with a co-lead in Exeter and a study manager in Michigan. Currently there are 5 recruiting centres (University of Leeds, University of Exeter Medical School, University of Bari, University of Bordeaux and University of Turku), a central laboratory (Lund University) and a central data repository (Swiss Institute of Bioinformatics (SIB)). University of Sheffield is the central imaging processing and quality assurance (QA) site, with support from Antaros Medical (Sweden) for biomarkers of body composition. All ethical and relevant local approvals are in place at each recruiting site. As a BEAt-DKD work package the study is supported by the BEAt-DKD consortium Steering Committee and an external Scientific Advisory Board. Funding Information: This project is principally funded by the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115974. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA with JDRF. This study receives additional support (personnel support) by grants from the Swedish Heart and Lung Foundation [20160872]; the Swedish Research Council [2018–02837; EXODIAB 2009–1039]; the Swedish Foundation for Strategic Research (LUDC-IRC 15–0067) to MFG; and the UK Medical Research Council (MR/R02264X/1) and Kidney Research UK (RP55/2012) to SS. This project is also supported by the National Institute for Health Research (NIHR) Exeter Clinical Research Facility and the NIHR Leeds Clinical Research Facility. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The funding bodies, except for JDRF, played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. Funding Information: This work forms part of the BEAt-DKD consortium that is funded by the IMI 2 Joint Undertaking that receives support from the European Federation of Pharmaceutical Industries and Associations (EFPIA). BEAt-DKD EFPIA partners that have contributed to the iBEAT study development are Astellas, AbbVie and Novo Nordisk. JDRF also contributed to the iBEAT study design. AMDA reports grants from Boehringer Ingelheim Pharma GmbH during the conduct of the study. AZ reports non-financial support and other from Boehringer Ingelheim Pharma GmbH during the conduct of the study. MG reports personal fees from Lilly and other from Sanofi Genzyme, outside of the submitted work. DZ reports other from Fresenius, other from Boehringer Ingelheim, other from Bayer, other from Mitsubishi Tanabe, other from Mundipharma, other from Janssen, other from AbbVie, outside the submitted work. HJLH reports other from Merck, other from Mitsubishi Tanabe, grants and other from Janssen, other from Mundipharma, other from Gilead, grants and other from AstraZeneca, grants and other from Abbvie, other from Retrophin, outside the submitted work. MK reports grants from NIH, non-financial support from University of Michigan, during the conduct of the study; grants from JDRF, grants from Astra-Zeneca, grants from NovoNordisc, grants from Eli Lilly, grants from Gilead, grants from Goldfinch Bio, grants from Merck, grants from Janssen, grants from Boehringer-Ingelheim, outside the submitted work; In addition, MK has a patent Biomarkers for CKD progression (encompassing urinary EGF as biomarker of CKD progression) issued. DA reports other from AbbVie, outside the submitted work. MFG reports non-financial support and other from Boehringer Ingelheim Pharma GmbH, non-financial support and other from JDRF International, non-financial support and other from Eli Lilly, non-financial support and other from AbbVie, non-financial support and other from Sanofi-Aventis, non-financial support and other from Astellas, non-financial support and other from Novo Nordisk A/S, non-financial support and other from Bayer AG, during the conduct of the study; personal fees from Lilly, non-financial support and other from Novo Nordisk, nonfinancial support and other from Pfizer, non-financial support and other from Follicum, non-financial support and other from Abcentra, non-financial support from Probi, non-financial support from Johnson & Johnson, outside the submitted work. SS reports non-financial support from Siemens, during the conduct of the study. Publisher Copyright: © 2020 The Author(s).

PY - 2020/6/29

Y1 - 2020/6/29

N2 - 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).

AB - 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).

KW - Diabetic kidney disease

KW - Type 2 diabetes

KW - Magnetic resonance imaging

KW - Ultrasound

KW - Albuminuria

KW - Chronic kidney disease stages 1-3

KW - Prospective cohort

KW - Renal decline

KW - Biomarkers

KW - Progression

KW - RENAL-FUNCTION

KW - DIFFUSION

KW - MRI

KW - POPULATION

KW - SELECTION

KW - DECLINE

U2 - 10.1186/s12882-020-01901-x

DO - 10.1186/s12882-020-01901-x

M3 - Article

SN - 1471-2369

VL - 21

JO - Bmc nephrology

JF - Bmc nephrology

IS - 1

M1 - 242

ER -

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

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

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

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

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