The urinary proteome as correlate and predictor of renal function in a population study

Nephrology Dialysis Transplantation

Volumn 29, Issue 12, 2014, Pages 2260-2268

  Gu, Yu Mei ^a   Thijs, Lutgarde ^a   Liu, Yan Ping ^a   Zhang, Zhenyu ^a   Jacobs, Lotte ^a   Koeck, Thomas ^b   Zürbig, Petra ^b   Lichtinghagen, Ralf ^c   Brand, Korbinian ^c   Kuznetsova, Tatiana ^a   Olivi, Laura ^a,d   Verhamme, Peter ^a   Delles, Christian ^e   Mischak, Harald ^b,f   Staessen, Jan A ^a,g  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b MOSAIQUES DIAGNOSTICS GMBH   (Germany)

^c HANNOVER MEDICAL SCHOOL   (Germany)

^d UNIVERSITY OF MILAN   (Italy)

^e UNIVERSITY OF GLASGOW   (United Kingdom)

^f UNIVERSITY OF GLASGOW   (United Kingdom)

^g MAASTRICHT UNIVERSITY   (Netherlands)

Author keywords

Chronic kidney disease; eGFR; Population science; Renal function; Urinary proteomics

Indexed keywords

CREATININE; PROTEOME; BIOLOGICAL MARKER;

ADULT; AGED; ALBUMINURIA; ARTICLE; CAPILLARY ELECTROPHORESIS; CLASSIFIER; CONTROLLED STUDY; CREATININE BLOOD LEVEL; CROSS-SECTIONAL STUDY; ESTIMATED GLOMERULAR FILTRATION RATE; FEMALE; FOLLOW UP; HEART LEFT VENTRICLE FAILURE; HUMAN; INCIDENCE; KIDNEY DYSFUNCTION; KIDNEY FUNCTION; MAJOR CLINICAL STUDY; MALE; MASS SPECTROMETRY; POPULATION RESEARCH; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROSPECTIVE STUDY; PROTEIN URINE LEVEL; RISK FACTOR; BELGIUM; GLOMERULUS FILTRATION RATE; HEALTH SURVEY; METABOLISM; MIDDLE AGED; PATHOPHYSIOLOGY; PHYSIOLOGY; PREDICTIVE VALUE; PROCEDURES; PROGNOSIS; PROTEOMICS; RENAL INSUFFICIENCY, CHRONIC; RETROSPECTIVE STUDY; SURVIVAL RATE; TRENDS; URINE;

ADULT; AGED; ALBUMINURIA; BELGIUM; BIOLOGICAL MARKERS; CROSS-SECTIONAL STUDIES; FEMALE; FOLLOW-UP STUDIES; GLOMERULAR FILTRATION RATE; HUMANS; INCIDENCE; MALE; MIDDLE AGED; POPULATION SURVEILLANCE; PREDICTIVE VALUE OF TESTS; PROGNOSIS; PROTEOME; PROTEOMICS; RENAL INSUFFICIENCY, CHRONIC; RETROSPECTIVE STUDIES; RISK FACTORS; SURVIVAL RATE;

EID: 84923780264     PISSN: 09310509     EISSN: 14602385     Source Type: Journal    
DOI: 10.1093/ndt/gfu234     Document Type: Article

References (29)

1. Coresh J, Selvin E, Stevens LA et al. Prevalence of chronic kidney disease in the United States. JAMA 2007; 298: 2038-2047
2. Wang H, Dwyer-Lindgren L, Lofgren KT et al. Age-specific and sexspecific mortality in 187 countries, 1970-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380: 2071-2094
3. Vos T, Flaxman AD, Naghavi M et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380: 2163-2196
4. Lim SS, Vos T, Flaxman AD et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380: 2224-2260
5. Zürbig P, Jerums G, Hovind P et al. Urinary proteomics for early diagnosis in diabetic nephropathy. Diabetes 2012; 61: 3304-3313
6. Argilés A, Siwy J, Duranton F et al. CKD273, a new proteomics classifier assessing CKD and its prognosis. PLoS ONE 2013; 8: e62837
7. Kuznetsova T, Mischak H, Mullen W et al. Urinary proteome analysis in hypertensive patients with left ventricular diastolic dysfunction. Eur Heart J 2012; 33: 2342-2350
8. Good DM, Zürbig P, Argilés A et al. Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease. Moll Cell Proteomics 2010; 9: 2424-2437
9. Roscioni SS, de Zeeuw D, Hellemons ME et al. A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus. Diabetologia 2013; 56: 259-267
10. Kistler AD, Serra AL, Siwy J et al. Urinary proteomic biomarkers for diagnosis and risk stratification of autosomal dominant polycystic kidney disease: a multicentric study. PLoS ONE 2013; 8: e53016
11. Li Y, Zagato L, Kuznetsova T et al. Angiotensin-converting enzyme I/D and α-adducin Gly460Trp polymorphisms. From angiotensin-converting enzyme activity to cardiovascular outcome. Hypertension 2007; 49: 1291-1297
12. Staessen JA, Wang JG, Brand E et al. Effects of three candidate genes on prevalence and incidence of hypertension in a Caucasian population. J Hypertens 2001; 19: 1349-1358
13. Jaffe M. Über den Niederschlag, welchen Pikrinsäure in normalen Harn erzeugt und über eine neue Reaction des Kreatinins. Z Physiol Chem 1886; 10: 391-400
14. Bowers LD, Wong ET. Kinetic serum creatinine assays. II. A critical evaluation and review. Clin Chem 1980; 26: 555-561
15. Peake M, Whiting M. Measurement of serum creatinine - Current status and future goals. Clin Biochem Rev 2006; 27: 173-182
16. Levey AS, Bosch JP, Lewis JB et al. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Ann Intern Med 1999; 130: 461-470
17. Levey AS, Stevens LA, Schmid CH et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009; 150: 604-612
18. Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Report of the expert committee on the diagnosis and classification of diabetes mellitus. Diabet Care 2003; 26(Suppl. 1): S5-S20
19. Delles C, Schiffer E, von Zur Muhlen C et al. Urinary proteomic diagnosis of coronary artery disease: identification and clinical validation in 623 individuals. J Hypertens 2010; 28: 2316-2322
20. Mühlenbruch K, Heraclides A, Steyerberg EW et al. Assessing improvement in disease predictionusing net reclassification improvement : impact of risk cut-offs and number of risk categories. Eur J Epidemiol 2013; 28: 25-33
21. Pencina MJ, D'Agostino RB, Sr, D'Agostino RB, Jr et al. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 2008; 27: 157-172
22. Bongartz LG, Cramer MJ, Doevendans PA et al. The severe cardiorenal syndrome: 'Guyton revisited'. Eur Heart J 2005; 26: 11-17
23. Braam B, Joles JA, Danishwar AH et al. Cardiorenal syndrome-currrent understanding and future perspectives. Nature Rev Nephrol 2014; 10: 48-55
24. Cannon PJ. The kidney in heart failure. N Engl J Med 1977; 296: 26-32
25. Borlaug BA, Paulus WJ. Heart failure with preserved ejection fraction: pathophysiology, diagnosis, and treatment. Eur Heart J 2011; 32: 670-679
26. Deen WM, Robertson CR, Brenner BM. A model of glomerular ultrafiltration in the rat. Am J Physiol 1972; 223: 1178-1183
27. Haller H, Ito S, Izzo JL et al. Olmesartan for the delay or prevention of microalbuminuria in type 2 diabetes. N Engl J Med 2011; 364: 907-917
28. Zoccali C, Kramer A, Jager KJ. Epidemiology of CKD in Europe: an uncertain scenario. Nephrol Dial Transplant 2010; 25: 1731-1733
29. Centers for Disease Control and Prevention. National Chronic Kidney Disease Fact Sheet [Online], http://www.cdc.gov/diabetes/pubs/pdf/kidney-Factsheet.pdf(2010)