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Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes

AIMS/HYPOTHESIS: We examined whether candidate biomarkers in serum or urine can improve the prediction of renal disease progression in type 1 diabetes beyond prior eGFR, comparing their performance with urinary albumin/creatinine ratio (ACR). METHODS: From the population-representative Scottish Diab...

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Autores principales: Colombo, Marco, McGurnaghan, Stuart J., Blackbourn, Luke A. K., Dalton, R. Neil, Dunger, David, Bell, Samira, Petrie, John R., Green, Fiona, MacRury, Sandra, McKnight, John A., Chalmers, John, Collier, Andrew, McKeigue, Paul M., Colhoun, Helen M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054370/
https://www.ncbi.nlm.nih.gov/pubmed/31915892
http://dx.doi.org/10.1007/s00125-019-05081-8
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author Colombo, Marco
McGurnaghan, Stuart J.
Blackbourn, Luke A. K.
Dalton, R. Neil
Dunger, David
Bell, Samira
Petrie, John R.
Green, Fiona
MacRury, Sandra
McKnight, John A.
Chalmers, John
Collier, Andrew
McKeigue, Paul M.
Colhoun, Helen M.
author_facet Colombo, Marco
McGurnaghan, Stuart J.
Blackbourn, Luke A. K.
Dalton, R. Neil
Dunger, David
Bell, Samira
Petrie, John R.
Green, Fiona
MacRury, Sandra
McKnight, John A.
Chalmers, John
Collier, Andrew
McKeigue, Paul M.
Colhoun, Helen M.
author_sort Colombo, Marco
collection PubMed
description AIMS/HYPOTHESIS: We examined whether candidate biomarkers in serum or urine can improve the prediction of renal disease progression in type 1 diabetes beyond prior eGFR, comparing their performance with urinary albumin/creatinine ratio (ACR). METHODS: From the population-representative Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) we sampled 50% and 25% of those with starting eGFR below and above 75 ml min(−1) [1.73 m](−2), respectively (N = 1629), and with median 5.1 years of follow-up. Multiplexed ELISAs and single molecule array technology were used to measure nine serum biomarkers and 13 urine biomarkers based on our and others’ prior work using large discovery and candidate studies. Associations with final eGFR and with progression to <30 ml min(−1) [1.73] m(−2), both adjusted for baseline eGFR, were tested using linear and logistic regression models. Parsimonious biomarker panels were identified using a penalised Bayesian approach, and their performance was evaluated through tenfold cross-validation and compared with using urinary ACR and other clinical record data. RESULTS: Seven serum and seven urine biomarkers were strongly associated with either final eGFR or progression to <30 ml min(−1) [1.73 m](−2), adjusting for baseline eGFR and other covariates (all at p<2.3 × 10(−3)). Of these, associations of four serum biomarkers were independent of ACR for both outcomes. The strongest associations with both final eGFR and progression to <30 ml min(−1) [1.73 m](−2) were for serum TNF receptor 1, kidney injury molecule 1, CD27 antigen, α-1-microglobulin and syndecan-1. These serum associations were also significant in normoalbuminuric participants for both outcomes. On top of baseline covariates, the r(2) for prediction of final eGFR increased from 0.702 to 0.743 for serum biomarkers, and from 0.702 to 0.721 for ACR alone. The area under the receiver operating characteristic curve for progression to <30 ml min(−1) [1.73 m](−2) increased from 0.876 to 0.953 for serum biomarkers, and to 0.911 for ACR alone. Other urinary biomarkers did not outperform ACR. CONCLUSIONS/INTERPRETATION: A parsimonious panel of serum biomarkers easily measurable along with serum creatinine may outperform ACR for predicting renal disease progression in type 1 diabetes, potentially obviating the need for urine testing. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00125-019-05081-8) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
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spelling pubmed-70543702020-03-16 Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes Colombo, Marco McGurnaghan, Stuart J. Blackbourn, Luke A. K. Dalton, R. Neil Dunger, David Bell, Samira Petrie, John R. Green, Fiona MacRury, Sandra McKnight, John A. Chalmers, John Collier, Andrew McKeigue, Paul M. Colhoun, Helen M. Diabetologia Article AIMS/HYPOTHESIS: We examined whether candidate biomarkers in serum or urine can improve the prediction of renal disease progression in type 1 diabetes beyond prior eGFR, comparing their performance with urinary albumin/creatinine ratio (ACR). METHODS: From the population-representative Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) we sampled 50% and 25% of those with starting eGFR below and above 75 ml min(−1) [1.73 m](−2), respectively (N = 1629), and with median 5.1 years of follow-up. Multiplexed ELISAs and single molecule array technology were used to measure nine serum biomarkers and 13 urine biomarkers based on our and others’ prior work using large discovery and candidate studies. Associations with final eGFR and with progression to <30 ml min(−1) [1.73] m(−2), both adjusted for baseline eGFR, were tested using linear and logistic regression models. Parsimonious biomarker panels were identified using a penalised Bayesian approach, and their performance was evaluated through tenfold cross-validation and compared with using urinary ACR and other clinical record data. RESULTS: Seven serum and seven urine biomarkers were strongly associated with either final eGFR or progression to <30 ml min(−1) [1.73 m](−2), adjusting for baseline eGFR and other covariates (all at p<2.3 × 10(−3)). Of these, associations of four serum biomarkers were independent of ACR for both outcomes. The strongest associations with both final eGFR and progression to <30 ml min(−1) [1.73 m](−2) were for serum TNF receptor 1, kidney injury molecule 1, CD27 antigen, α-1-microglobulin and syndecan-1. These serum associations were also significant in normoalbuminuric participants for both outcomes. On top of baseline covariates, the r(2) for prediction of final eGFR increased from 0.702 to 0.743 for serum biomarkers, and from 0.702 to 0.721 for ACR alone. The area under the receiver operating characteristic curve for progression to <30 ml min(−1) [1.73 m](−2) increased from 0.876 to 0.953 for serum biomarkers, and to 0.911 for ACR alone. Other urinary biomarkers did not outperform ACR. CONCLUSIONS/INTERPRETATION: A parsimonious panel of serum biomarkers easily measurable along with serum creatinine may outperform ACR for predicting renal disease progression in type 1 diabetes, potentially obviating the need for urine testing. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00125-019-05081-8) contains peer-reviewed but unedited supplementary material, which is available to authorised users. Springer Berlin Heidelberg 2020-01-08 2020 /pmc/articles/PMC7054370/ /pubmed/31915892 http://dx.doi.org/10.1007/s00125-019-05081-8 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Colombo, Marco
McGurnaghan, Stuart J.
Blackbourn, Luke A. K.
Dalton, R. Neil
Dunger, David
Bell, Samira
Petrie, John R.
Green, Fiona
MacRury, Sandra
McKnight, John A.
Chalmers, John
Collier, Andrew
McKeigue, Paul M.
Colhoun, Helen M.
Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes
title Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes
title_full Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes
title_fullStr Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes
title_full_unstemmed Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes
title_short Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes
title_sort comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054370/
https://www.ncbi.nlm.nih.gov/pubmed/31915892
http://dx.doi.org/10.1007/s00125-019-05081-8
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