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Serum kidney injury molecule 1 and β2-microglobulin perform as well as larger biomarker panels for prediction of rapid decline in renal function in type 2 diabetes

, ; Colombo, Marco; Looker, Helen C.; Farran, Bassam; Hess, Sibylle; Groop, Leif LU ; Palmer, Colin N.A.; Brosnan, Mary Julia; Dalton, R. Neil and Wong, Max, et al. (2019) In Diabetologia 62(1). p.156-168
Abstract

Aims/hypothesis: As part of the Surrogate Markers for Micro- and Macrovascular Hard Endpoints for Innovative Diabetes Tools (SUMMIT) programme we previously reported that large panels of biomarkers derived from three analytical platforms maximised prediction of progression of renal decline in type 2 diabetes. Here, we hypothesised that smaller (n ≤ 5), platform-specific combinations of biomarkers selected from these larger panels might achieve similar prediction performance when tested in three additional type 2 diabetes cohorts. Methods: We used 657 serum samples, held under differing storage conditions, from the Scania Diabetes Registry (SDR) and Genetics of Diabetes Audit and Research Tayside (GoDARTS), and a further 183 nested... (More)

Aims/hypothesis: As part of the Surrogate Markers for Micro- and Macrovascular Hard Endpoints for Innovative Diabetes Tools (SUMMIT) programme we previously reported that large panels of biomarkers derived from three analytical platforms maximised prediction of progression of renal decline in type 2 diabetes. Here, we hypothesised that smaller (n ≤ 5), platform-specific combinations of biomarkers selected from these larger panels might achieve similar prediction performance when tested in three additional type 2 diabetes cohorts. Methods: We used 657 serum samples, held under differing storage conditions, from the Scania Diabetes Registry (SDR) and Genetics of Diabetes Audit and Research Tayside (GoDARTS), and a further 183 nested case–control sample set from the Collaborative Atorvastatin in Diabetes Study (CARDS). We analysed 42 biomarkers measured on the SDR and GoDARTS samples by a variety of methods including standard ELISA, multiplexed ELISA (Luminex) and mass spectrometry. The subset of 21 Luminex biomarkers was also measured on the CARDS samples. We used the event definition of loss of >20% of baseline eGFR during follow-up from a baseline eGFR of 30–75 ml min−1 [1.73 m]−2. A total of 403 individuals experienced an event during a median follow-up of 7 years. We used discrete-time logistic regression models with tenfold cross-validation to assess association of biomarker panels with loss of kidney function. Results: Twelve biomarkers showed significant association with eGFR decline adjusted for covariates in one or more of the sample sets when evaluated singly. Kidney injury molecule 1 (KIM-1) and β2-microglobulin (B2M) showed the most consistent effects, with standardised odds ratios for progression of at least 1.4 (p < 0.0003) in all cohorts. A combination of B2M and KIM-1 added to clinical covariates, including baseline eGFR and albuminuria, modestly improved prediction, increasing the area under the curve in the SDR, Go-DARTS and CARDS by 0.079, 0.073 and 0.239, respectively. Neither the inclusion of additional Luminex biomarkers on top of B2M and KIM-1 nor a sparse mass spectrometry panel, nor the larger multiplatform panels previously identified, consistently improved prediction further across all validation sets. Conclusions/interpretation: Serum KIM-1 and B2M independently improve prediction of renal decline from an eGFR of 30–75 ml min−1 [1.73 m]−2 in type 2 diabetes beyond clinical factors and prior eGFR and are robust to varying sample storage conditions. Larger panels of biomarkers did not improve prediction beyond these two biomarkers.

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published
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keywords
Clinical science, Epidemiology, Nephropathy, Proteomics/metabolomics
in
Diabetologia
volume
62
issue
1
pages
156 - 168
publisher
Springer
external identifiers
  • scopus:85054513071
ISSN
0012-186X
DOI
10.1007/s00125-018-4741-9
language
English
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yes
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a49aeb96-cffc-4d09-b94b-d925b9e69dec
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2018-11-13 11:09:35
date last changed
2019-03-19 04:02:18
@article{a49aeb96-cffc-4d09-b94b-d925b9e69dec,
  abstract     = {<p>Aims/hypothesis: As part of the Surrogate Markers for Micro- and Macrovascular Hard Endpoints for Innovative Diabetes Tools (SUMMIT) programme we previously reported that large panels of biomarkers derived from three analytical platforms maximised prediction of progression of renal decline in type 2 diabetes. Here, we hypothesised that smaller (n ≤ 5), platform-specific combinations of biomarkers selected from these larger panels might achieve similar prediction performance when tested in three additional type 2 diabetes cohorts. Methods: We used 657 serum samples, held under differing storage conditions, from the Scania Diabetes Registry (SDR) and Genetics of Diabetes Audit and Research Tayside (GoDARTS), and a further 183 nested case–control sample set from the Collaborative Atorvastatin in Diabetes Study (CARDS). We analysed 42 biomarkers measured on the SDR and GoDARTS samples by a variety of methods including standard ELISA, multiplexed ELISA (Luminex) and mass spectrometry. The subset of 21 Luminex biomarkers was also measured on the CARDS samples. We used the event definition of loss of &gt;20% of baseline eGFR during follow-up from a baseline eGFR of 30–75 ml min<sup>−1</sup> [1.73 m]<sup>−2</sup>. A total of 403 individuals experienced an event during a median follow-up of 7 years. We used discrete-time logistic regression models with tenfold cross-validation to assess association of biomarker panels with loss of kidney function. Results: Twelve biomarkers showed significant association with eGFR decline adjusted for covariates in one or more of the sample sets when evaluated singly. Kidney injury molecule 1 (KIM-1) and β<sub>2</sub>-microglobulin (B2M) showed the most consistent effects, with standardised odds ratios for progression of at least 1.4 (p &lt; 0.0003) in all cohorts. A combination of B2M and KIM-1 added to clinical covariates, including baseline eGFR and albuminuria, modestly improved prediction, increasing the area under the curve in the SDR, Go-DARTS and CARDS by 0.079, 0.073 and 0.239, respectively. Neither the inclusion of additional Luminex biomarkers on top of B2M and KIM-1 nor a sparse mass spectrometry panel, nor the larger multiplatform panels previously identified, consistently improved prediction further across all validation sets. Conclusions/interpretation: Serum KIM-1 and B2M independently improve prediction of renal decline from an eGFR of 30–75 ml min<sup>−1</sup> [1.73 m]<sup>−2</sup> in type 2 diabetes beyond clinical factors and prior eGFR and are robust to varying sample storage conditions. Larger panels of biomarkers did not improve prediction beyond these two biomarkers.</p>},
  author       = {,  and Colombo, Marco and Looker, Helen C. and Farran, Bassam and Hess, Sibylle and Groop, Leif and Palmer, Colin N.A. and Brosnan, Mary Julia and Dalton, R. Neil and Wong, Max and Turner, Charles and Ahlqvist, Emma and Dunger, David and Agakov, Felix and Durrington, Paul and Livingstone, Shona and Betteridge, John and McKeigue, Paul M. and Colhoun, Helen M.},
  issn         = {0012-186X},
  keyword      = {Clinical science,Epidemiology,Nephropathy,Proteomics/metabolomics},
  language     = {eng},
  number       = {1},
  pages        = {156--168},
  publisher    = {Springer},
  series       = {Diabetologia},
  title        = {Serum kidney injury molecule 1 and β<sub>2</sub>-microglobulin perform as well as larger biomarker panels for prediction of rapid decline in renal function in type 2 diabetes},
  url          = {http://dx.doi.org/10.1007/s00125-018-4741-9},
  volume       = {62},
  year         = {2019},
}