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Urinary proteomics for prediction of mortality in patients with type 2 diabetes and microalbuminuria

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Currie, Gemma E ; von Scholten, Bernt Johan ; Mary, Sheon ; Flores Guerrero, Jose-Luis ; Lindhardt, Morten ; Reinhard, Henrik ; Jacobsen, Peter K ; Mullen, William ; Parving, Hans-Henrik ; Mischak, Harald ; Rossing, Peter ; Delles, Christian. / Urinary proteomics for prediction of mortality in patients with type 2 diabetes and microalbuminuria. I: Cardiovascular Diabetology. 2018 ; Bind 17, Nr. 50. s. 50.

Bibtex

@article{4e2644a738094b8d9353629cede15590,
title = "Urinary proteomics for prediction of mortality in patients with type 2 diabetes and microalbuminuria",
abstract = "BACKGROUND: The urinary proteomic classifier CKD273 has shown promise for prediction of progressive diabetic nephropathy (DN). Whether it is also a determinant of mortality and cardiovascular disease in patients with microalbuminuria (MA) is unknown.METHODS: Urine samples were obtained from 155 patients with type 2 diabetes and confirmed microalbuminuria. Proteomic analysis was undertaken using capillary electrophoresis coupled to mass spectrometry to determine the CKD273 classifier score. A previously defined CKD273 threshold of 0.343 for identification of DN was used to categorise the cohort in Kaplan-Meier and Cox regression models with all-cause mortality as the primary endpoint. Outcomes were traced through national health registers after 6 years.RESULTS: CKD273 correlated with urine albumin excretion rate (UAER) (r = 0.481, p = <0.001), age (r = 0.238, p = 0.003), coronary artery calcium (CAC) score (r = 0.236, p = 0.003), N-terminal pro-brain natriuretic peptide (NT-proBNP) (r = 0.190, p = 0.018) and estimated glomerular filtration rate (eGFR) (r = 0.265, p = 0.001). On multivariate analysis only UAER (β = 0.402, p < 0.001) and eGFR (β = - 0.184, p = 0.039) were statistically significant determinants of CKD273. Twenty participants died during follow-up. CKD273 was a determinant of mortality (log rank [Mantel-Cox] p = 0.004), and retained significance (p = 0.048) after adjustment for age, sex, blood pressure, NT-proBNP and CAC score in a Cox regression model.CONCLUSION: A multidimensional biomarker can provide information on outcomes associated with its primary diagnostic purpose. Here we demonstrate that the urinary proteomic classifier CKD273 is associated with mortality in individuals with type 2 diabetes and MA even when adjusted for other established cardiovascular and renal biomarkers.",
keywords = "Journal Article",
author = "Currie, {Gemma E} and {von Scholten}, {Bernt Johan} and Sheon Mary and {Flores Guerrero}, Jose-Luis and Morten Lindhardt and Henrik Reinhard and Jacobsen, {Peter K} and William Mullen and Hans-Henrik Parving and Harald Mischak and Peter Rossing and Christian Delles",
year = "2018",
month = "12",
day = "1",
doi = "10.1186/s12933-018-0697-9",
language = "English",
volume = "17",
pages = "50",
journal = "Cardiovascular Diabetology",
issn = "1475-2840",
publisher = "BioMed Central Ltd",
number = "50",

}

RIS

TY - JOUR

T1 - Urinary proteomics for prediction of mortality in patients with type 2 diabetes and microalbuminuria

AU - Currie, Gemma E

AU - von Scholten, Bernt Johan

AU - Mary, Sheon

AU - Flores Guerrero, Jose-Luis

AU - Lindhardt, Morten

AU - Reinhard, Henrik

AU - Jacobsen, Peter K

AU - Mullen, William

AU - Parving, Hans-Henrik

AU - Mischak, Harald

AU - Rossing, Peter

AU - Delles, Christian

PY - 2018/12/1

Y1 - 2018/12/1

N2 - BACKGROUND: The urinary proteomic classifier CKD273 has shown promise for prediction of progressive diabetic nephropathy (DN). Whether it is also a determinant of mortality and cardiovascular disease in patients with microalbuminuria (MA) is unknown.METHODS: Urine samples were obtained from 155 patients with type 2 diabetes and confirmed microalbuminuria. Proteomic analysis was undertaken using capillary electrophoresis coupled to mass spectrometry to determine the CKD273 classifier score. A previously defined CKD273 threshold of 0.343 for identification of DN was used to categorise the cohort in Kaplan-Meier and Cox regression models with all-cause mortality as the primary endpoint. Outcomes were traced through national health registers after 6 years.RESULTS: CKD273 correlated with urine albumin excretion rate (UAER) (r = 0.481, p = <0.001), age (r = 0.238, p = 0.003), coronary artery calcium (CAC) score (r = 0.236, p = 0.003), N-terminal pro-brain natriuretic peptide (NT-proBNP) (r = 0.190, p = 0.018) and estimated glomerular filtration rate (eGFR) (r = 0.265, p = 0.001). On multivariate analysis only UAER (β = 0.402, p < 0.001) and eGFR (β = - 0.184, p = 0.039) were statistically significant determinants of CKD273. Twenty participants died during follow-up. CKD273 was a determinant of mortality (log rank [Mantel-Cox] p = 0.004), and retained significance (p = 0.048) after adjustment for age, sex, blood pressure, NT-proBNP and CAC score in a Cox regression model.CONCLUSION: A multidimensional biomarker can provide information on outcomes associated with its primary diagnostic purpose. Here we demonstrate that the urinary proteomic classifier CKD273 is associated with mortality in individuals with type 2 diabetes and MA even when adjusted for other established cardiovascular and renal biomarkers.

AB - BACKGROUND: The urinary proteomic classifier CKD273 has shown promise for prediction of progressive diabetic nephropathy (DN). Whether it is also a determinant of mortality and cardiovascular disease in patients with microalbuminuria (MA) is unknown.METHODS: Urine samples were obtained from 155 patients with type 2 diabetes and confirmed microalbuminuria. Proteomic analysis was undertaken using capillary electrophoresis coupled to mass spectrometry to determine the CKD273 classifier score. A previously defined CKD273 threshold of 0.343 for identification of DN was used to categorise the cohort in Kaplan-Meier and Cox regression models with all-cause mortality as the primary endpoint. Outcomes were traced through national health registers after 6 years.RESULTS: CKD273 correlated with urine albumin excretion rate (UAER) (r = 0.481, p = <0.001), age (r = 0.238, p = 0.003), coronary artery calcium (CAC) score (r = 0.236, p = 0.003), N-terminal pro-brain natriuretic peptide (NT-proBNP) (r = 0.190, p = 0.018) and estimated glomerular filtration rate (eGFR) (r = 0.265, p = 0.001). On multivariate analysis only UAER (β = 0.402, p < 0.001) and eGFR (β = - 0.184, p = 0.039) were statistically significant determinants of CKD273. Twenty participants died during follow-up. CKD273 was a determinant of mortality (log rank [Mantel-Cox] p = 0.004), and retained significance (p = 0.048) after adjustment for age, sex, blood pressure, NT-proBNP and CAC score in a Cox regression model.CONCLUSION: A multidimensional biomarker can provide information on outcomes associated with its primary diagnostic purpose. Here we demonstrate that the urinary proteomic classifier CKD273 is associated with mortality in individuals with type 2 diabetes and MA even when adjusted for other established cardiovascular and renal biomarkers.

KW - Journal Article

U2 - 10.1186/s12933-018-0697-9

DO - 10.1186/s12933-018-0697-9

M3 - Journal article

VL - 17

SP - 50

JO - Cardiovascular Diabetology

JF - Cardiovascular Diabetology

SN - 1475-2840

IS - 50

ER -

ID: 53599298