Dataset Information

Urine E-cadherin: A Marker for Early Detection of Kidney Injury in Diabetic Patients.

ABSTRACT: Diabetic nephropathy (DN) is the main reason for end-stage renal disease. Microalbuminuria as the non-invasive available diagnosis marker lacks specificity and gives high false positive rates. To identify and validate biomarkers for DN, we used in the present study urine samples from four patient groups: diabetes without nephropathy, diabetes with microalbuminuria, diabetes with macroalbuminuria and proteinuria without diabetes. For the longitudinal validation, we recruited 563 diabetic patients and collected 1363 urine samples with the clinical data during a follow-up of 6 years. Comparative urinary proteomics identified four proteins Apolipoprotein A-I (APOA1), Beta-2-microglobulin (B2M), E-cadherin (CDH1) and Lithostathine-1-alpha (REG1A), which differentiated with high statistical strength (p < 0.05) between DN patients and the other groups. Label-free mass spectrometric quantification of the candidates confirmed the discriminatory value of E-cadherin and Lithostathine-1-alpha (p < 0.05). Immunological validation highlighted E-cadherin as the only marker able to differentiate significantly between the different DN stages with an area under the curve (AUC) of 0.85 (95%-CI: [0.72, 0.97]). The analysis of the samples from the longitudinal study confirmed the prognostic value of E-cadherin, the critical increase in urinary E-cadherin level was measured 20 ± 12.5 months before the onset of microalbuminuria and correlated significantly (p < 0.05) with the glomerular filtration rate measured by estimated glomerular filtration rate (eGFR).

SUBMITTER: Koziolek M

PROVIDER: S-EPMC7141221 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Urine E-cadherin: A Marker for Early Detection of Kidney Injury in Diabetic Patients.

Koziolek Michael M Mueller Gerhard A GA Dihazi Gry H GH Jung Klaus K Altubar Constanze C Wallbach Manuel M Markovic Ivana I Raddatz Dirk D Jahn Olaf O Karaköse Hülya H Lenz Christof C Urlaub Henning H Dihazi Abdelhi A El Meziane Abdellatif A Dihazi Hassan H

Journal of clinical medicine 20200227 3

Diabetic nephropathy (DN) is the main reason for end-stage renal disease. Microalbuminuria as the non-invasive available diagnosis marker lacks specificity and gives high false positive rates. To identify and validate biomarkers for DN, we used in the present study urine samples from four patient groups: diabetes without nephropathy, diabetes with microalbuminuria, diabetes with macroalbuminuria and proteinuria without diabetes. For the longitudinal validation, we recruited 563 diabetic patients ...[more]

PMID: 32121033

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Project description:We evaluated urine NGAL as a marker of acute kidney injury in patients undergoing partial nephrectomy. We sought to identify the preoperative clinical features and surgical factors during partial nephrectomy that are associated with renal injury, as measured by increased urine NGAL vs controls.Using patients treated with radical nephrectomy or thoracic surgery as controls, we prospectively collected and analyzed urine and serum samples from patients treated with partial or radical nephrectomy, or thoracic surgery between April 2010 and April 2012. Urine was collected preoperatively and at multiple time points postoperatively. Differences in urine NGAL levels were analyzed among the 3 surgical groups using a generalized estimating equation model. The partial nephrectomy group was subdivided based on a preoperative estimated glomerular filtration rate of less than 60, or 60 ml/minute/1.73 m(2) or greater.Of 162 patients included in final analysis more than 65% had cardiovascular disease. The median estimated glomerular filtration rate was greater than 60 ml/minute/1.73 m(2) in the radical and partial nephrectomy, and thoracic surgery groups (61, 78 and 84.5 ml/minute/1.73 m(2), respectively). Preoperatively, a 10 unit increase in the estimated glomerular filtration rate was associated with a 4 unit decrease in urine NGAL in the partial nephrectomy group. Postoperatively, urine NGAL in the partial nephrectomy group was not higher than in controls and did not correlate with ischemia time. Patients with partial nephrectomy with a preoperative estimated glomerular filtration rate of less than 60 ml/minute/1.73 m(2) had higher urine NGAL postoperatively than those with a higher preoperative estimated rate.Urine NGAL does not appear to be a useful marker for detecting renal injury in healthy patients treated with partial nephrectomy. However, patients with poorer preoperative renal function have higher baseline urine levels and appear more susceptible to acute kidney injury, as detected by urine levels and Acute Kidney Injury Network criteria, than those with a normal estimated glomerular filtration rate.

Project description:Acute kidney injury (AKI) is common in the intensive care unit, where it is associated with increased mortality. AKI is often defined using creatinine and urine output criteria. The creatinine-based definition is more reliable but less expedient, whereas the urine output based definition is rapid but less reliable. Our goal is to examine the urine output criterion and augment it with physiological features for better agreement with creatinine-based definitions of AKI. The objectives are threefold: (1) to characterize the baseline agreement of urine output and creatinine definitions of AKI; (2) to refine the urine output criteria to identify the thresholds that best agree with the creatinine-based definition; and (3) to build generalized estimating equation (GEE) and generalized linear mixed-effects (GLME) models with static and time-varying features to improve the accuracy of a near-real-time marker for AKI. We performed a retrospective observational study using data from two independent critical care databases, MIMIC-III and eICU, for critically ill patients who developed AKI in intensive care units. We found that the conventional urine output criterion (6 hr, 0.5 ml/kg/h) has specificity and sensitivity of 0.49 and 0.54 for MIMIC-III database; and specificity and sensitivity of 0.38 and 0.56 for eICU. Secondly, urine output thresholds of 12 hours and 0.6 ml/kg/h have specificity and sensitivity of 0.58 and 0.48 for MIMIC-III; and urine output thresholds of 10 hours and 0.6 ml/kg/h have specificity and sensitivity of 0.49 and 0.48 for eICU. Thirdly, the GEE model of four hours duration augmented with static and time-varying features can achieve a specificity and sensitivity of 0.66 and 0.61 for MIMIC-III; and specificity and sensitivity of 0.66 and 0.64 for eICU. The GLME model of four hours duration augmented with static and time-varying features can achieve a specificity and sensitivity of 0.71 and 0.55 for MIMIC-III; and specificity and sensitivity of 0.66 and 0.60 for eICU. The GEE model has greater performance than the GLME model, however, the GLME model is more reflective of the variables as fixed effects or random effects. The significant improvement in performance, relative to current definitions, when augmenting with patient features, suggest the need of incorporating these features when detecting disease onset and modeling at window-level rather than patient-level.

Dataset Information

Urine E-cadherin: A Marker for Early Detection of Kidney Injury in Diabetic Patients.

Publications

Urine E-cadherin: A Marker for Early Detection of Kidney Injury in Diabetic Patients.

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