Key PointsA custom-made Joslin OLINK proteomics platform was developed to quantify 21 Joslin kidney panel (JKP) proteins in circulation to predict ESKD risk.Each JKP protein discriminated moderately/well ESKD risk in diabetes; optimal predictive model included three clinical markers and eight JKP proteins.In the type 2 diabetes subgroup from the Action to Control Cardiovascular Risk in Diabetes trial, three JKP proteins identified subjects in whom fenofibrate dramatically reduced risk of fast kidney decline.BackgroundTo facilitate personalized treatment of diabetic kidney disease (DKD), we developed the Joslin kidney panel (JKP) of 21 circulating proteins associated with progression to ESKD. Prognostic models using baseline concentrations of JKP proteins in circulation and clinical markers were then developed to stratify individuals according to ESKD risk and according to response to fenofibrate, a potential renoprotective drug.MethodsThe custom-made Joslin OLINK multipurpose proteomics platform was used to quantify JKP proteins. Association between baseline serum/plasma concentrations of these proteins and kidney outcomes was examined in five independent study groups.ResultsIn type 1 diabetes individuals from Joslin (N=59), FinnDiane (N=389), and Steno (N=283), all JKP proteins were good discriminators of ESKD risk during a 10-year follow-up. Baseline concentrations of KIM-1 and WFDC2 performed the best, matching or outperforming the clinical markers. An optimal model to discriminate ESKD risk that included three clinical markers and eight JKP proteins (KIM1, TNF-R2, TNF-R3, TNF-R19L, PVRL4, WFDC2, DLL1, and SYND1) was developed using the FinnDiane cohort (C-index 0.868, SEM +/- 0.019) and validated in the Steno cohort (C-index 0.913, SEM +/- 0.104) and in type 2 diabetes Joslin study (C-index 0.807, SEM +/- 0.036). In each of these studies, the optimal model performed better than models based solely on three clinical markers. In a subgroup of 450 individuals with type 2 diabetes from the Action to Control Cardiovascular Risk in Diabetes-Lipid trial, high levels of three JKP proteins (EFNA4, DLL1, IL-1RT1) predicted amelioration of fast kidney function decline during 4 years of follow-up in those treated with fenofibrate compared with placebo.ConclusionsQuantification of circulating JKP proteins using the Joslin OLINK platform discriminates ESKD risk in individuals with diabetes and their response to renoprotective drugs. The use of this multipurpose precision medicine tool should facilitate studies on the etiology of DKD and enable the development of effective personalized treatment protocols for individuals with DKD.

Joslin Kidney Panel of Circulating Proteins

Morieri M. L.;
2026

Abstract

Key PointsA custom-made Joslin OLINK proteomics platform was developed to quantify 21 Joslin kidney panel (JKP) proteins in circulation to predict ESKD risk.Each JKP protein discriminated moderately/well ESKD risk in diabetes; optimal predictive model included three clinical markers and eight JKP proteins.In the type 2 diabetes subgroup from the Action to Control Cardiovascular Risk in Diabetes trial, three JKP proteins identified subjects in whom fenofibrate dramatically reduced risk of fast kidney decline.BackgroundTo facilitate personalized treatment of diabetic kidney disease (DKD), we developed the Joslin kidney panel (JKP) of 21 circulating proteins associated with progression to ESKD. Prognostic models using baseline concentrations of JKP proteins in circulation and clinical markers were then developed to stratify individuals according to ESKD risk and according to response to fenofibrate, a potential renoprotective drug.MethodsThe custom-made Joslin OLINK multipurpose proteomics platform was used to quantify JKP proteins. Association between baseline serum/plasma concentrations of these proteins and kidney outcomes was examined in five independent study groups.ResultsIn type 1 diabetes individuals from Joslin (N=59), FinnDiane (N=389), and Steno (N=283), all JKP proteins were good discriminators of ESKD risk during a 10-year follow-up. Baseline concentrations of KIM-1 and WFDC2 performed the best, matching or outperforming the clinical markers. An optimal model to discriminate ESKD risk that included three clinical markers and eight JKP proteins (KIM1, TNF-R2, TNF-R3, TNF-R19L, PVRL4, WFDC2, DLL1, and SYND1) was developed using the FinnDiane cohort (C-index 0.868, SEM +/- 0.019) and validated in the Steno cohort (C-index 0.913, SEM +/- 0.104) and in type 2 diabetes Joslin study (C-index 0.807, SEM +/- 0.036). In each of these studies, the optimal model performed better than models based solely on three clinical markers. In a subgroup of 450 individuals with type 2 diabetes from the Action to Control Cardiovascular Risk in Diabetes-Lipid trial, high levels of three JKP proteins (EFNA4, DLL1, IL-1RT1) predicted amelioration of fast kidney function decline during 4 years of follow-up in those treated with fenofibrate compared with placebo.ConclusionsQuantification of circulating JKP proteins using the Joslin OLINK platform discriminates ESKD risk in individuals with diabetes and their response to renoprotective drugs. The use of this multipurpose precision medicine tool should facilitate studies on the etiology of DKD and enable the development of effective personalized treatment protocols for individuals with DKD.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3576504
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