The urinary proteomics classifier chronic kidney disease 273 predicts cardiovascular outcome in patients with chronic kidney disease

Abstract

Background The urinary proteomic classifier chronic kidney disease 273 (CKD273) is predictive for the development and progression of chronic kidney disease (CKD) and/or albuminuria in type 2 diabetes. This study evaluates its role in the prediction of cardiovascular (CV) events in patients with CKD Stages G1–G5. Methods We applied the CKD273 classifier in a cohort of 451 patients with CKD Stages G1–G5 followed prospectively for a median of 5.5 years. Primary endpoints were all-cause mortality, CV mortality and the composite of non-fatal and fatal CV events (CVEs). Results In multivariate Cox regression models adjusting for age, sex, prevalent diabetes and CV history, the CKD273 classifier at baseline was significantly associated with total mortality and time to fatal or non-fatal CVE, but not CV mortality. Because of a significant interaction between CKD273 and CV history (P = 0.018) and CKD stages (P = 0.002), a stratified analysis was performed. In the fully adjusted models, CKD273 classifier was a strong and independent predictor of fatal or non-fatal CVE only in the subgroup of patients with CKD Stages G1–G3b and without a history of CV disease. In those patients, the highest tertile of CKD273 was associated with a >10-fold increased risk as compared with the lowest tertile. Conclusions The urinary CKD273 classifier provides additional independent information regarding the CV risk in patients with early CKD stage and a blank CV history. Determination of CKD273 scores on a random urine sample may improve the efficacy of intensified surveillance and preventive strategies by selecting patients who potentially will benefit most from early risk management.

Proteomic Analysis of Human Serum from Patients with Chronic Kidney Disease

“…Peptide biomarkers can also provide insight into CKD diagnosis and progression. In a recent study, 273 specific urinary peptides (CKD273 classifier) were identified as reliable predictors of CKD progression [26] and cardiovascular events in CKD [27]. In this study, we hypothesized that if some proteins showed significant quantitative changes in patient serum and correlated with well-established markers, then they would be potential biomarkers for CKD diagnosis.…”

“…Our target proteomics results are compared with previously reported data from studies of different renal pathologies in Table 3. AAT, which is supposed to have anti-inflammatory properties, belongs to the group of serine proteinases [27]. Exogenous AAT inhibited apoptosis and inflammation in renal reperfusion [28] and reduced the urine kidney injury molecule-1 (KIM-1) concentration [30].…”

Urinary fetuin-A peptides as a new marker for impaired kidney function in patients with type 2 diabetes

“…The findings of this study could be indirectly confirmed with previous studies because some fetuin-A peptides are also included in the peptide-based classifier CKD273 [ 31 ]. This classifier was validated in several studies for the early diagnosis and prediction of CKD progression [ 32 , 33 ] as well as prediction of the cardiovascular outcome in diabetes patients [ 34 ]. In general, these studies showed that using a large number of clinical and proteomics data available at the Human Urinary Proteome Database can be very useful for the evaluation of specific urinary peptide levels under different disease conditions.…”

Urine Headspace Analysis with Field Asymmetric Ion Mobility Spectrometry for Detection of Chronic Kidney Disease

“…The patients in different CKD groups differed from each other with the incidence of hypertension and diabetes, which is logical, since they are diseases that cause kidney dysfunction. Since diabetes results in significant metabolic alterations reflected in urine other than just presence of glucose and proteins alone 42,43 , we performed additional analyses to exclude the possibility that the classification of CKD is rather due to diabetes-related factors and confirmed that the results are not related with diabetes.…”