title: Serum neutrophil gelatinase-associated lipocalin as a marker of renal function in non-diabetic patients with stage 2-4 chronic kidney disease.
abstract: The current Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines advocate creatinine-based equations for estimating GFR to identify patients with potential kidney disease and classify them into different stages due to the fact that serum creatinine is very insensitive to changes in the glomerular filtration rate. Very few biomarkers exist for monitoring chronic kidney disease. The aim of the study was to assess whether NGAL could represent a novel, sensitive marker of kidney function in adult patients with CKD. The study was performed on 92 non-diabetic patients with CKD stages 2-4. Serum and urinary NGAL as well as serum cystatin C were measured using commercially available kits. Serum NGAL was related, in univariate analysis, to serum creatinine, urinary NGAL, hemoglobin, hematocrit, leukocyte count, eGFR, and cystatin C. Urinary NGAL correlated with age, hemoglobin, hematocrit, serum creatinine, and eGFR. In multiple regression analysis, predictors of serum NGAL were creatinine (beta value = 0.97, p = 0.005), cystatin C (beta = 0.34, p = 0.01), and eGFR (beta value = 1.77, p = 0.001). In the healthy volunteers, serum NGAL correlated with age, serum creatinine, eGFR, leukocyte count, and cystatin C. Taking into consideration the fact that the recent DOQI (Dialysis Outcomes Quality Initiative) states that individuals with reduced GRF (glomerular filtration rate) are at greater risk for CVD and cardiac deaths, precise evaluation of renal function is important in order to select the appropriate strategy to reduce the cardiovascular risk. NGAL should be investigated as a potential early and sensitive marker of kidney impairment/injury.
authors.affiliation: Department of Nephrology, Medical University, Bialystok, Poland. jolmal@poczta.onet.pl
authors.forename: Jolanta
authors.initials: J
authors.lastname: Malyszko
authors.forename: Hanna
authors.initials: H
authors.lastname: Bachorzewska-Gajewska
authors.forename: Ewa
authors.initials: E
authors.lastname: Sitniewska
authors.forename: Jacek S
authors.initials: JS
authors.lastname: Malyszko
authors.forename: Boguslaw
authors.initials: B
authors.lastname: Poniatowski
authors.forename: Slawomir
authors.initials: S
authors.lastname: Dobrzycki
mesh_terms: D015415:Biomarkers / Q000097:blood; D016022:Case-Control Studies; D015331:Cohort Studies; D003404:Creatinine / Q000652:urine; D055316:Cystatin C; D015891:Cystatins / Q000097:blood* / Q000652:urine; D003920:Diabetes Mellitus; D018450:Disease Progression; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007676:Kidney Failure, Chronic / Q000097:blood* / Q000175:diagnosis*; D007677:Kidney Function Tests; D054834:Lipocalins / Q000097:blood* / Q000652:urine; D008297:Male; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011336:Probability; D011379:Prognosis; D012044:Regression Analysis; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index
chemical_list: D015415:Biomarkers; C525030:CST3 protein, human; D055316:Cystatin C; D015891:Cystatins; D054834:Lipocalins; D003404:Creatinine