Biomarkers of rapid chronic kidney disease progression in type 2 diabetes (original) (raw)
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Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association, 2014
Diabetic nephropathy imposes a substantial cardiovascular and renal burden contributing to both morbidity and excess mortality. Progression of chronic kidney disease (CKD) in diabetes mellitus is variable, and few biomarkers are available to predict progression accurately. Identification of novel predictive biomarkers may inform clinical care and assist in the design of clinical trials. We hypothesized that urinary and plasma protein biomarkers predict CKD progression independently of the known clinical markers such as albuminuria and estimated glomerular filtration rate (eGFR) in diabetic nephropathy. We studied 67 US veterans with CKD due to type 2 diabetes mellitus and 20 age-matched controls (no CKD, hypertension or cardiovascular disease). After clinical evaluation and the collection of blood and urine specimens for 24 biomarkers, we followed subjects prospectively for the next 2-6 years. CKD progression was defined in three ways: (i) clinically by examining eGFR versus time pl...
Kidney360, 2021
BackgroundWe investigated the predictive value of 11 serum biomarkers for renal and mortality end points in people with CKD.MethodsAdults with CKD (n=139) were enrolled from outpatient clinics between February 2014 and November 2016. Biomarker quantification was performed using two multiplex arrays on a clinical-grade analyzer. Relationships between biomarkers and renal and mortality end points were investigated by random forests and Cox proportional hazards regression.ResultsThe cohort was 56% male. The mean age was 63 years and median (IQR) CKD-EPI eGFR was 33 (24–51) ml/min per BSA. A total of 56 (40%) people developed a composite end point defined as ≥40% decline in eGFR, doubling of serum creatinine, RRT, or death over median (IQR) follow-up of 5.4 (4.7–5.7) years. Prediction of the composite end point was better with random forests trained on serum biomarkers compared with clinical variables (area under the curve of 0.81 versus 0.78). The predictive performance of biomarkers w...
Development of a Biomarker Panel to Distinguish Risk of Progressive Chronic Kidney Disease
Biomedicines
Chronic kidney disease (CKD) patients typically progress to kidney failure, but the rate of progression differs per patient or may not occur at all. Current CKD screening methods are sub-optimal at predicting progressive kidney function decline. This investigation develops a model for predicting progressive CKD based on a panel of biomarkers representing the pathophysiological processes of CKD, kidney function, and common CKD comorbidities. Two patient cohorts are utilised: The CKD Queensland Registry (n = 418), termed the Biomarker Discovery cohort; and the CKD Biobank (n = 62), termed the Predictive Model cohort. Progression status is assigned with a composite outcome of a ≥30% decline in eGFR from baseline, initiation of dialysis, or kidney transplantation. Baseline biomarker measurements are compared between progressive and non-progressive patients via logistic regression. In the Biomarker Discovery cohort, 13 biomarkers differed significantly between progressive and non-progres...
Kidney Biomarkers and Decline in eGFR in Patients with Type 2 Diabetes
Clinical journal of the American Society of Nephrology : CJASN, 2018
Biomarkers may improve identification of individuals at risk of eGFR decline who may benefit from intervention or dialysis planning. However, available biomarkers remain incompletely validated for risk stratification and prediction modeling. We examined serum cystatin C, urinary kidney injury molecule-1 (uKIM-1), and urinary neutrophil gelatinase-associated lipocalin (UNGAL) in 5367 individuals with type 2 diabetes mellitus and recent acute coronary syndromes enrolled in the Examination of Cardiovascular Outcomes with Alogliptin versus Standard of Care (EXAMINE) trial. Baseline concentrations and 6-month changes in biomarkers were also evaluated. Cox proportional regression was used to assess associations with a 50% decrease in eGFR, stage 5 CKD (eGFR<15 ml/min per 1.73 m), or dialysis. eGFR decline occurred in 98 patients (1.8%) over a median of 1.5 years. All biomarkers individually were associated with higher risk of eGFR decline (<0.001). However, when adjusting for baseli...
Diabetes care, 2017
Chronic kidney disease (CKD) in diabetes has a complex molecular and likely multifaceted pathophysiology. We aimed to validate a panel of biomarkers identified using a systems biology approach to predict the individual decline of estimated glomerular filtration rate (eGFR) in a large group of patients with type 2 diabetes and CKD at various stages. We used publicly available "omics" data to develop a molecular process model of CKD in diabetes and identified a representative parsimonious set of nine molecular biomarkers: chitinase 3-like protein 1, growth hormone 1, hepatocyte growth factor, matrix metalloproteinase (MMP) 2, MMP7, MMP8, MMP13, tyrosine kinase, and tumor necrosis factor receptor-1. These biomarkers were measured in baseline serum samples from 1,765 patients recruited into two large clinical trials. eGFR decline was predicted based on molecular markers, clinical risk factors (including baseline eGFR and albuminuria), and both combined, and these predictions w...
Contribution of Predictive and Prognostic Biomarkers to Clinical Research on Chronic Kidney Disease
International Journal of Molecular Sciences, 2020
Chronic kidney disease (CKD), defined as the presence of albuminuria and/or reduction in estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2, is considered a growing public health problem, with its prevalence and incidence having almost doubled in the past three decades. The implementation of novel biomarkers in clinical practice is crucial, since it could allow earlier diagnosis and lead to an improvement in CKD outcomes. Nevertheless, a clear guidance on how to develop biomarkers in the setting of CKD is not yet available. The aim of this review is to report the framework for implementing biomarkers in observational and intervention studies. Biomarkers are classified as either prognostic or predictive; the first type is used to identify the likelihood of a patient to develop an endpoint regardless of treatment, whereas the second type is used to determine whether the patient is likely to benefit from a specific treatment. Many single assays and complex biomarkers we...
Scientific Reports, 2020
Studies reporting on biomarkers aiming to predict adverse renal outcomes in patients with type 2 diabetes and kidney disease (DKD) conventionally define a surrogate endpoint either as a percentage of decrease of eGFR (e.g. ≥ 30%) or an absolute decline (e.g. ≥ 5 ml/min/year). The application of those study results in clinical practise however relies on the assumption of a linear and intra-individually stable progression of DKD. We studied 860 patients of the PROVALID study and 178 of an independent population with a relatively preserved eGFR at baseline and at least 5 years of follow up. Individuals with a detrimental prognosis were identified using various thresholds of a percentage or absolute decline of eGFR after each year of follow up. Next, we determined how many of the patients met the same criteria at other points in time. Interindividual eGFR decline was highly variable but in addition intra-individual eGFR trajectories also were frequently non-linear. For example, of all s...