Dataset Information

Urinary Biomarkers of Kidney Tubular Damage and Risk of Cardiovascular Disease and Mortality in Elders.

ABSTRACT:

Rationale & objective

Novel urinary biomarkers have enabled earlier detection of kidney tubular damage, but their prognostic value for adverse cardiovascular outcomes is uncertain. We hypothesized that tubular damage, measured by urine α₁-microglobulin (A1M), amino-terminal propeptide of type III procollagen (PIIINP), and neutrophil gelatinase-associated lipocalin (NGAL), would be associated with higher risks for cardiovascular events and mortality among elders.

Study design

Case-cohort study.

Setting & participants

This study included a randomly selected subcohort (n=502), cardiovascular disease (CVD) cases (n=245), and heart failure cases (n=220) from the Health, Aging, and Body Composition (Health ABC) Study.

Predictors

Baseline urine A1M, PIIINP, and NGAL concentrations.

Outcomes

Incident CVD, heart failure, and all-cause mortality.

Analytical approach

Cox proportional hazards models were used to evaluate biomarker associations with each outcome.

Results

At baseline, mean age was 74 years and estimated glomerular filtration rate was 73mL/min/1.73m². After adjustment for demographics, estimated glomerular filtration rate, albumin-creatinine ratio, and other cardiovascular risk factors, each doubling in biomarker concentration was associated with the following adjusted HRs for CVD: A1M, 1.51 (95% CI, 1.16-1.96); PIIINP, 1.21 (95% CI, 1.00-1.46); and NGAL, 1.12 (95% CI, 1.05-1.20). There were 248 deaths in the subcohort during a median follow-up of 12.4 years. Adjusted associations of each biomarker (HR per doubling) with all-cause mortality were: A1M, 1.29 (95% CI, 1.10-1.51); PIIINP, 1.05 (95%, 0.94-1.18); and NGAL, 1.07 (95% CI, 1.02-1.12). Biomarker concentrations did not have statistically significant associations with heart failure after multivariable adjustment.

Limitations

Urine biomarkers were measured at a single time point; no validation cohort available.

Conclusions

Kidney tubular damage is an independent risk factor for CVD and death among elders. Future studies should investigate mechanisms by which kidney tubular damage may adversely affect cardiovascular risk.

SUBMITTER: Jotwani V

PROVIDER: S-EPMC6057830 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Urinary Biomarkers of Kidney Tubular Damage and Risk of Cardiovascular Disease and Mortality in Elders.

Jotwani Vasantha V Katz Ronit R Ix Joachim H JH Gutiérrez Orlando M OM Bennett Michael M Parikh Chirag R CR Cummings Steven R SR Sarnak Mark J MJ Shlipak Michael G MG

American journal of kidney diseases : the official journal of the National Kidney Foundation 20180327 2

<h4>Rationale & objective</h4>Novel urinary biomarkers have enabled earlier detection of kidney tubular damage, but their prognostic value for adverse cardiovascular outcomes is uncertain. We hypothesized that tubular damage, measured by urine α<sub>1</sub>-microglobulin (A1M), amino-terminal propeptide of type III procollagen (PIIINP), and neutrophil gelatinase-associated lipocalin (NGAL), would be associated with higher risks for cardiovascular events and mortality among elders.<h4>Study desig ...[more]

PMID: 29602632

Similar Datasets

Project description:BackgroundCardiac surgery-associated acute kidney injury (AKI) is associated with increased morbidity and mortality. We examined the utility of combining biomarkers of kidney function loss (serum cystatin C) and kidney tubular damage (urine neutrophil gelatinase-associated lipocalin [NGAL] and Kidney Injury Molecule-1 [KIM-1]) for the prediction of post-cardiac surgery AKI.MethodsSingle-center prospective cohort study of 106 adults undergoing coronary artery bypass grafting and/or valve surgery with cardiopulmonary bypass (CPB). Primary outcome was postoperative in-hospital AKI defined by serum creatinine (SCr)-Kidney Disease: Improving Global Outcomes criteria. Biomarkers were measured preoperatively, 6 hours after CPB and on postoperative days (PODs) 1 to 4.ResultsA total of 23 subjects (21.7%) developed AKI. After adjusting for preoperative left ventricular ejection fraction, body mass index >30 kg/m2, and estimated glomerular filtration rate (eGFR) <60 ml/min per 1.73 m2, the combination of peak serum cystatin C and peak urine KIM-1/creatinine (Cr) (6 hours post-CPB to POD 1) above optimal cutoff significantly associated with postoperative AKI (odds ratio [OR]: 5.32; 95% confidence interval [CI]: 1.31-21.67; P = 0.020). This biomarker combination significantly improved the performance of the clinical model for the prediction of postoperative AKI (area under the curve [AUC]: 0.77, 95% CI: 0.65-0.90 for the clinical model alone versus 0.83, 95% CI: 0.73-0.93 for the clinical model with the addition of biomarker data, P = 0.049).ConclusionsCombining biomarkers of postoperative kidney function loss and postoperative kidney tubular damage significantly improved prediction of in-hospital AKI following cardiac surgery. Future large, multicenter studies are warranted to assess whether panels of biomarkers reflecting distinct pathobiology can be used to guide interventions and improve short- and long-term outcomes in patients undergoing cardiac surgery.

Project description:Background and objectivesKidney injury molecule-1 (KIM-1) has been suggested as a clinically relevant highly specific biomarker of acute kidney tubular damage. However, community-based data on the association between urinary levels of KIM-1 and the risk for cardiovascular mortality are lacking. This study aimed to investigate the association between urinary KIM-1 and cardiovascular mortality.Design, setting, participants, & measurementsThis was a prospective study, using the community-based Uppsala Longitudinal Study of Adult Men (N=590; mean age 77 years; baseline period, 1997-2001; median follow-up 8.1 years; end of follow-up, 2008).ResultsDuring follow-up, 89 participants died of cardiovascular causes (incidence rate, 2.07 per 100 person-years at risk). Models were adjusted for cardiovascular risk factors (age, systolic BP, diabetes, smoking, body mass index, total cholesterol, HDL cholesterol, antihypertensive treatment, lipid-lowering treatment, aspirin treatment, and history of cardiovascular disease) and for markers of kidney dysfunction and damage (cystatin C-based eGFR and urinary albumin/creatinine ratio). Higher urinary KIM-1/creatinine (from 24-hour urine collections) was associated with a higher risk for cardiovascular mortality (hazard ratio per SD increase, 1.27; 95% confidence interval [95% CI], 1.05 to 1.54; P=0.01). Participants with a combination of high KIM-1/creatinine (upper quintile, ≥175 ng/mmol), low eGFR (≤60 ml/min per 1.73 m(2)), and microalbuminuria/macroalbuminuria (albumin/creatinine ratio≥3 g/mol) had a >8-fold increased risk compared with participants with low KIM-1/creatinine (<175 ng/mmol), normal eGFR (>60 ml/min per 1.73 m(2)), and normoalbuminuria (albumin/creatinine ratio<3 g/mol) (hazard ratio, 8.56; 95% CI, 4.17 to 17.56; P<0.001).ConclusionsThese findings suggest that higher urinary KIM-1 may predispose to a higher risk of cardiovascular mortality independently of established cardiovascular risk factors, eGFR, and albuminuria. Additional studies are needed to further assess the utility of measuring KIM-1 in the clinical setting.

Project description:BackgroundCombining tubular damage and functional biomarkers may improve prediction precision of acute kidney injury (AKI). Serum cystatin C (sCysC) represents functional damage of kidney, while urinary N-acetyl-β-D-glucosaminidase (uNAG) is considered as a tubular damage biomarker. So far, there is no nomogram containing this combination to predict AKI in septic cohort. We aimed to compare the performance of AKI prediction models with or without incorporating these two biomarkers and develop an effective nomogram for septic patients in intensive care unit (ICU).MethodsThis was a prospective study conducted in the mixed medical-surgical ICU of a tertiary care hospital. Adults with sepsis were enrolled. The patients were divided into development and validation cohorts in chronological order of ICU admission. A logistic regression model for AKI prediction was first constructed in the development cohort. The contribution of the biomarkers (sCysC, uNAG) to this model for AKI prediction was assessed with the area under the receiver operator characteristic curve (AUC), continuous net reclassification index (cNRI), and incremental discrimination improvement (IDI). Then nomogram was established based on the model with the best performance. This nomogram was validated in the validation cohort in terms of discrimination and calibration. The decision curve analysis (DCA) was performed to evaluate the nomogram's clinical utility.ResultsOf 358 enrolled patients, 232 were in the development cohort (69 AKI), while 126 in the validation cohort (52 AKI). The first clinical model included the APACHE II score, serum creatinine, and vasopressor used at ICU admission. Adding sCysC and uNAG to this model improved the AUC to 0.831. Furthermore, incorporating them significantly improved risk reclassification over the predictive model alone, with cNRI (0.575) and IDI (0.085). A nomogram was then established based on the new model including sCysC and uNAG. Application of this nomogram in the validation cohort yielded fair discrimination with an AUC of 0.784 and good calibration. The DCA revealed good clinical utility of this nomogram.ConclusionsA nomogram that incorporates functional marker (sCysC) and tubular damage marker (uNAG), together with routine clinical factors may be a useful prognostic tool for individualized prediction of AKI in septic patients.

Project description:IntroductionAlbuminuric and nonalbuminuric pathways contribute to diabetic kidney disease. Proximal tubule and inflammation play important roles in these processes. Urinary biomarker(s) to detect early kidney damage and predict progression are needed.MethodsNine urinary biomarkers were measured at baseline in 400 patients with diabetes. Correlation and multivariate logistic and linear regression analyses were performed to assess the association of biomarkers with chronic kidney disease and progression.ResultsIn the albumin/creatinine ratio (ACR) <3 cohort, the only biomarker significantly associated with estimated glomerular filtration rate < 60 ml/min was N-acetyl-β-d-glucosaminidase. A combination of ACR and monocyte chemoattractant protein 1 (MCP1) were significantly associated with stage 2 chronic kidney disease in this cohort. Logistic models showed that in patients with all levels of albuminuria, ACR, retinol binding protein (RBP), and MCP1 were associated with progression. A model including MCP1, interleukin 6, and neutrophil gelatinase-associated lipocalin showed significant association with progression to chronic kidney disease 3/4 in the ACR <3 cohort. Linear mixed-model regression analyses demonstrated MCP1, RBP, and ACR as significant proteins associated with progression to stage 3 or worse, whereas MCP1 was the only significant biomarker in the ACR <3 cohort. Time-to-event and Cox proportional hazard models confirmed significant hazard ratios for progression for ACR, RBP, and MCP1, with significant differences noted between quantiles of biomarkers for ACR, RBP, and MCP1.ConclusionIn this study of diabetic patients with single baseline measurements of urinary biomarkers, albumin, RBP, and MCP1 were significantly associated with chronic kidney disease progression at all levels of albuminuria. Inflammatory cytokines, neutrophil gelatinase-associated lipocalin, and MCP1 were associated with progression in patients without albuminuria. N-acetyl-β-d-glucosaminidase demonstrated a significant association with an estimated glomerular filtration rate < 60 ml/min in the ACR <3 cohort.

Dataset Information

Urinary Biomarkers of Kidney Tubular Damage and Risk of Cardiovascular Disease and Mortality in Elders.

Rationale & objective

Study design

Setting & participants

Predictors

Outcomes

Analytical approach

Results

Limitations

Conclusions

Publications

Urinary Biomarkers of Kidney Tubular Damage and Risk of Cardiovascular Disease and Mortality in Elders.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets