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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 (författare)
University of Edinburgh
Looker, Helen C. (författare)
University of Dundee
Farran, Bassam (författare)
Western General Hospital,University of Edinburgh
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Hess, Sibylle (författare)
Sanofi-Aventis Deutschland GmbH
Groop, Leif (författare)
Lund University,Lunds universitet,Translationell Muskel Forskning,Forskargrupper vid Lunds universitet,Translational Muscle Research,Lund University Research Groups
Palmer, Colin N.A. (författare)
University of Dundee,Ninewells Hospital and Medical School
Brosnan, Mary Julia (författare)
Pfizer Inc. US
Dalton, R. Neil (författare)
Guy's and St Thomas' NHS Foundation Trust
Wong, Max (författare)
Guy's and St Thomas' NHS Foundation Trust
Turner, Charles (författare)
Guy's and St Thomas' NHS Foundation Trust
Ahlqvist, Emma (författare)
Lund University,Lunds universitet,Translationell Muskel Forskning,Forskargrupper vid Lunds universitet,Translational Muscle Research,Lund University Research Groups
Dunger, David (författare)
University of Cambridge
Agakov, Felix (författare)
Pharmatics Limited
Durrington, Paul (författare)
University of Manchester
Livingstone, Shona (författare)
University of Dundee
Betteridge, John (författare)
University College London,University College London Hospital
McKeigue, Paul M. (författare)
University of Edinburgh
Colhoun, Helen M. (författare)
University of Edinburgh,Western General Hospital,NHS Fife
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 (creator_code:org_t)
 
2018-10-05
2019
Engelska.
Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 62:1, s. 156-168
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • 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.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Endokrinologi och diabetes (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Endocrinology and Diabetes (hsv//eng)

Nyckelord

Clinical science
Epidemiology
Nephropathy
Proteomics/metabolomics

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art (ämneskategori)
ref (ämneskategori)

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