Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes

Michelle J Pena; Joachim Jankowski; Georg Heinze; Maria Kohl; Andreas Heinzel; Stephan J L Bakker; Ron T Gansevoort; Peter Rossing; Dick de Zeeuw; Hiddo J Lambers Heerspink; Vera Jankowski

doi:10.1097/HJH.0000000000000685

Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes

Michelle J Pena, Joachim Jankowski, Georg Heinze, Maria Kohl, Andreas Heinzel, Stephan J L Bakker, Ron T Gansevoort, Peter Rossing, Dick de Zeeuw, Hiddo J Lambers Heerspink, Vera Jankowski

18 Citationer (Scopus)

Abstract

Objective: Micro and macroalbuminuria are strong risk factors for progression of nephropathy in patients with hypertension or type 2 diabetes. Early detection of progression to micro and macroalbuminuria may facilitate prevention and treatment of renal diseases. We aimed to develop plasma proteomics classifiers to predict the development of micro or macroalbuminuria in hypertension or type 2 diabetes. Methods: Patients with hypertension (n=125) and type 2 diabetes (n=82) were selected for this case-control study from the Prevention of REnal and Vascular ENd-stage Disease cohort and the Steno Diabetes Center. Cases transitioned from normo to microalbuminuria, or from micro to macroalbuminuria. Controls, matched for age, sex, and baseline albuminuria stage, did not transition. Follow-up was 3.0±0.9 years. Plasma proteomics profiles were measured by liquid chromatography-electrospray-trap mass-spectrometry. Classifiers were developed and cross-validated for prediction of transition in albuminuria stage. Improvement in risk prediction was tested on top of a reference model of baseline albuminuria, estimated glomerular filtration rate, and renin-angiotensin-aldosterone system intervention. Results: In hypertensive patients, the classifier improved risk prediction for transition in albuminuria stage on top of the reference model (C-index from 0.69 to 0.78; P<0.01). In type 2 diabetes, the classifier improved risk prediction for transition from micro to macroalbuminuria (C-index from 0.73 to 0.80; P=0.04). In both diseases, the identified peptides were linked to pathways recognized to contribute to nephropathy, including fibrosis, inflammation, angiogenesis, and mineral metabolism. Conclusions: Plasma proteomics predict the transition in albuminuria stage beyond established renal risk markers in hypertension or type 2 diabetes. External validation is needed to assess reproducibility.

Originalsprog	Engelsk
Tidsskrift	Journal of Hypertension
Vol/bind	33
Udgave nummer	10
Sider (fra-til)	2123-32
Antal sider	10
ISSN	0263-6352
DOI	https://doi.org/10.1097/HJH.0000000000000685
Status	Udgivet - okt. 2015

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Pena, M. J., Jankowski, J., Heinze, G., Kohl, M., Heinzel, A., Bakker, S. J. L., Gansevoort, R. T., Rossing, P., de Zeeuw, D., Heerspink, H. J. L., & Jankowski, V. (2015). Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes. Journal of Hypertension, 33(10), 2123-32. https://doi.org/10.1097/HJH.0000000000000685

@article{95d62dce82904e4d882457224d5fcc79,

title = "Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes",

abstract = "Objective: Micro and macroalbuminuria are strong risk factors for progression of nephropathy in patients with hypertension or type 2 diabetes. Early detection of progression to micro and macroalbuminuria may facilitate prevention and treatment of renal diseases. We aimed to develop plasma proteomics classifiers to predict the development of micro or macroalbuminuria in hypertension or type 2 diabetes. Methods: Patients with hypertension (n=125) and type 2 diabetes (n=82) were selected for this case-control study from the Prevention of REnal and Vascular ENd-stage Disease cohort and the Steno Diabetes Center. Cases transitioned from normo to microalbuminuria, or from micro to macroalbuminuria. Controls, matched for age, sex, and baseline albuminuria stage, did not transition. Follow-up was 3.0±0.9 years. Plasma proteomics profiles were measured by liquid chromatography-electrospray-trap mass-spectrometry. Classifiers were developed and cross-validated for prediction of transition in albuminuria stage. Improvement in risk prediction was tested on top of a reference model of baseline albuminuria, estimated glomerular filtration rate, and renin-angiotensin-aldosterone system intervention. Results: In hypertensive patients, the classifier improved risk prediction for transition in albuminuria stage on top of the reference model (C-index from 0.69 to 0.78; P<0.01). In type 2 diabetes, the classifier improved risk prediction for transition from micro to macroalbuminuria (C-index from 0.73 to 0.80; P=0.04). In both diseases, the identified peptides were linked to pathways recognized to contribute to nephropathy, including fibrosis, inflammation, angiogenesis, and mineral metabolism. Conclusions: Plasma proteomics predict the transition in albuminuria stage beyond established renal risk markers in hypertension or type 2 diabetes. External validation is needed to assess reproducibility.",

author = "Pena, {Michelle J} and Joachim Jankowski and Georg Heinze and Maria Kohl and Andreas Heinzel and Bakker, {Stephan J L} and Gansevoort, {Ron T} and Peter Rossing and {de Zeeuw}, Dick and Heerspink, {Hiddo J Lambers} and Vera Jankowski",

year = "2015",

month = oct,

doi = "10.1097/HJH.0000000000000685",

language = "English",

volume = "33",

pages = "2123--32",

journal = "Journal of Hypertension",

issn = "0263-6352",

publisher = "Lippincott Williams & Wilkins, Ltd.",

number = "10",

}

TY - JOUR

T1 - Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes

AU - Pena, Michelle J

AU - Jankowski, Joachim

AU - Heinze, Georg

AU - Kohl, Maria

AU - Heinzel, Andreas

AU - Bakker, Stephan J L

AU - Gansevoort, Ron T

AU - Rossing, Peter

AU - de Zeeuw, Dick

AU - Heerspink, Hiddo J Lambers

AU - Jankowski, Vera

PY - 2015/10

Y1 - 2015/10

N2 - Objective: Micro and macroalbuminuria are strong risk factors for progression of nephropathy in patients with hypertension or type 2 diabetes. Early detection of progression to micro and macroalbuminuria may facilitate prevention and treatment of renal diseases. We aimed to develop plasma proteomics classifiers to predict the development of micro or macroalbuminuria in hypertension or type 2 diabetes. Methods: Patients with hypertension (n=125) and type 2 diabetes (n=82) were selected for this case-control study from the Prevention of REnal and Vascular ENd-stage Disease cohort and the Steno Diabetes Center. Cases transitioned from normo to microalbuminuria, or from micro to macroalbuminuria. Controls, matched for age, sex, and baseline albuminuria stage, did not transition. Follow-up was 3.0±0.9 years. Plasma proteomics profiles were measured by liquid chromatography-electrospray-trap mass-spectrometry. Classifiers were developed and cross-validated for prediction of transition in albuminuria stage. Improvement in risk prediction was tested on top of a reference model of baseline albuminuria, estimated glomerular filtration rate, and renin-angiotensin-aldosterone system intervention. Results: In hypertensive patients, the classifier improved risk prediction for transition in albuminuria stage on top of the reference model (C-index from 0.69 to 0.78; P<0.01). In type 2 diabetes, the classifier improved risk prediction for transition from micro to macroalbuminuria (C-index from 0.73 to 0.80; P=0.04). In both diseases, the identified peptides were linked to pathways recognized to contribute to nephropathy, including fibrosis, inflammation, angiogenesis, and mineral metabolism. Conclusions: Plasma proteomics predict the transition in albuminuria stage beyond established renal risk markers in hypertension or type 2 diabetes. External validation is needed to assess reproducibility.

AB - Objective: Micro and macroalbuminuria are strong risk factors for progression of nephropathy in patients with hypertension or type 2 diabetes. Early detection of progression to micro and macroalbuminuria may facilitate prevention and treatment of renal diseases. We aimed to develop plasma proteomics classifiers to predict the development of micro or macroalbuminuria in hypertension or type 2 diabetes. Methods: Patients with hypertension (n=125) and type 2 diabetes (n=82) were selected for this case-control study from the Prevention of REnal and Vascular ENd-stage Disease cohort and the Steno Diabetes Center. Cases transitioned from normo to microalbuminuria, or from micro to macroalbuminuria. Controls, matched for age, sex, and baseline albuminuria stage, did not transition. Follow-up was 3.0±0.9 years. Plasma proteomics profiles were measured by liquid chromatography-electrospray-trap mass-spectrometry. Classifiers were developed and cross-validated for prediction of transition in albuminuria stage. Improvement in risk prediction was tested on top of a reference model of baseline albuminuria, estimated glomerular filtration rate, and renin-angiotensin-aldosterone system intervention. Results: In hypertensive patients, the classifier improved risk prediction for transition in albuminuria stage on top of the reference model (C-index from 0.69 to 0.78; P<0.01). In type 2 diabetes, the classifier improved risk prediction for transition from micro to macroalbuminuria (C-index from 0.73 to 0.80; P=0.04). In both diseases, the identified peptides were linked to pathways recognized to contribute to nephropathy, including fibrosis, inflammation, angiogenesis, and mineral metabolism. Conclusions: Plasma proteomics predict the transition in albuminuria stage beyond established renal risk markers in hypertension or type 2 diabetes. External validation is needed to assess reproducibility.

U2 - 10.1097/HJH.0000000000000685

DO - 10.1097/HJH.0000000000000685

M3 - Journal article

C2 - 26237555

SN - 0263-6352

VL - 33

SP - 2123

EP - 2132

JO - Journal of Hypertension

JF - Journal of Hypertension

IS - 10

ER -

Plasma proteomics classifiers improve risk prediction for renal disease in patients with hypertension or type 2 diabetes

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