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Kidney Biomarkers and Decline in eGFR in Patients with Type 2 Diabetes.

ABSTRACT: BACKGROUND AND OBJECTIVES: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. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: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 m2), or dialysis. RESULTS: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 (P<0.001). However, when adjusting for baseline eGFR, proteinuria, and clinical factors, only baseline cystatin C (adjusted hazard ratio per 1 SD change, 1.66; 95% confidence interval, 1.41 to 1.96; P<0.001) and 6-month change in urinary neutrophil gelatinase-associated lipocalin (adjusted hazard ratio per 1 SD change, 1.07; 95% confidence interval, 1.02 to 1.12; P=0.004) independently associated with CKD progression. A base model for predicting kidney function decline with nine standard risk factors had strong discriminative ability (C-statistic 0.93). The addition of baseline cystatin C improved discrimination (C-statistic 0.94), but it failed to reclassify risk categories of individuals with and without eGFR decline. CONCLUSIONS:The addition of cystatin C or biomarkers of tubular injury did not meaningfully improve the prediction of eGFR decline beyond common clinical factors and routine laboratory data in a large cohort of patients with type 2 diabetes and recent acute coronary syndrome. PODCAST:This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2018_01_16_CJASNPodcast_18_3_G.mp3.

SUBMITTER: Garlo KG

PROVIDER: S-EPMC5967667 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Kidney Biomarkers and Decline in eGFR in Patients with Type 2 Diabetes.

Garlo Katherine G KG White William B WB Bakris George L GL Zannad Faiez F Wilson Craig A CA Kupfer Stuart S Vaduganathan Muthiah M Morrow David A DA Cannon Christopher P CP Charytan David M DM

Clinical journal of the American Society of Nephrology : CJASN 20180116 3

<h4>Background and objectives</h4>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.<h4>Design, setting, participants, & measurements</h4>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 dia ...[more]

PMID: 29339356

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Project description:BackgroundIndividuals with type 1 diabetes (T1D) demonstrate varied trajectories of estimated glomerular filtration rate (eGFR) decline. The molecular pathways underlying rapid eGFR decline in T1D are poorly understood, and individual-level risk of rapid eGFR decline is difficult to predict.MethodsWe designed a case-control study with multiple exposure measurements nested within 4 well-characterized T1D cohorts (FinnDiane, Steno, EDC, and CACTI) to identify biomarkers associated with rapid eGFR decline. Here, we report the rationale for and design of these studies as well as results of models testing associations of clinical characteristics with rapid eGFR decline in the study population, upon which "omics" studies will be built. Cases (n = 535) and controls (n = 895) were defined as having an annual eGFR decline of ≥3 and <1 mL/min/1.73 m2, respectively. Associations of demographic and clinical variables with rapid eGFR decline were tested using logistic regression, and prediction was evaluated using area under the curve (AUC) statistics. Targeted metabolomics, lipidomics, and proteomics are being performed using high-resolution mass-spectrometry techniques.ResultsAt baseline, the mean age was 43 years, diabetes duration was 27 years, eGFR was 94 mL/min/1.73 m2, and 62% of participants were normoalbuminuric. Over 7.6-year median follow-up, the mean annual change in eGFR in cases and controls was -5.7 and 0.6 mL/min/1.73 m2, respectively. Younger age, longer diabetes duration, and higher baseline HbA1c, urine albumin-creatinine ratio, and eGFR were significantly associated with rapid eGFR decline. The cross-validated AUC for the predictive model incorporating these variables plus sex and mean arterial blood pressure was 0.74 (95% CI: 0.68-0.79; p < 0.001).ConclusionKnown risk factors provide moderate discrimination of rapid eGFR decline. Identification of blood and urine biomarkers associated with rapid eGFR decline in T1D using targeted omics strategies may provide insight into disease mechanisms and improve upon clinical predictive models using traditional risk factors.

Project description:Introduction: Type 2 diabetes mellitus (T2DM) is an independent risk factor of Alzheimer's disease (AD), and populations with mild cognitive impairment (MCI) have high incidence to suffer from AD. Therefore, discerning who may be more vulnerable to MCI, among the increasing T2DM populations, is important for early intervention and eventually decreasing the prevalence rate of AD. This study was to explore whether the change of plasma β-amyloid (Aβ) could be a biomarker to distinguish MCI (T2DM-MCI) from non-MCI (T2DM-nMCI) in T2DM patients. Methods: Eight hundred fifty-two T2DM patients collected from five medical centers were assigned randomly to training and validation cohorts. Plasma Aβ, platelet glycogen synthase kinase-3β (GSK-3β), apolipoprotein E (ApoE) genotypes, and olfactory and cognitive functions were measured by ELISA, dot blot, RT-PCR, Connecticut Chemosensory Clinical Research Center (CCCRC) olfactory test based on the diluted butanol, and Minimum Mental State Examination (MMSE) test, respectively, and multivariate logistic regression analyses were applied. Results: Elevation of plasma Aβ1-42/Aβ1-40 is an independent risk factor of MCI in T2DM patients. Although using Aβ1-42/Aβ1-40 alone only reached an AUC of 0.631 for MCI diagnosis, addition of the elevated Aβ1-42/Aβ1-40 to our previous model (i.e., activated platelet GSK-3β, ApoE ε4 genotype, olfactory decline, and aging) significantly increased the discriminating efficiency of T2DM-MCI from T2DM-nMCI, with an AUC of 0.846 (95% CI: 0.794-0.897) to 0.869 (95% CI: 0.822-0.916) in the training cohort and an AUC of 0.848 (95% CI: 0.815-0.882) to 0.867 (95% CI: 0.835-0.899) in the validation cohort, respectively. Conclusion: A combination of the elevated plasma Aβ1-42/Aβ1-40 with activated platelet GSK-3β, ApoE ε4 genotype, olfactory decline, and aging could efficiently diagnose MCI in T2DM patients. Further longitudinal studies may consummate the model for early prediction of AD.

Project description:BackgroundImpaired kidney function and albuminuria are associated with increased risk of heart failure (HF) in patients with type 2 diabetes (T2D). We investigated whether rapid kidney function decline over time is an additional determinant of increased HF risk in patients with T2D, independent of baseline kidney function, albuminuria, and other HF predictors.MethodsIncluded in the study were 7,539 participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study with baseline urinary albumin-to-creatinine ratio (UACR) data, who had completed 4 years of follow-up and had ≥ 3 eGFR measurements during that period (median eGFR/year = 1.9, IQR 1.7-3.2). The association between rapid kidney function decline (eGFR loss ≥ 5 ml/min/1.73 m2/year) and odds of HF hospitalization or HF death during the first 4 years of follow-up was estimated by logistic regression. The improvement in risk discrimination provided by adding rapid kidney function decline to other HF risk factors was evaluated as the increment in the area under the Receiving Operating Characteristics curve (ROC AUC) and integrated discrimination improvement (IDI).ResultsOver 4 years of follow-up, 1,573 participants (20.9%) experienced rapid kidney function decline and 255 (3.4%) experienced a HF event. Rapid kidney function decline was associated with a ~ 3.2-fold increase in HF odds (3.23, 95% CI, 2.51-4.16, p < 0.0001), independent of baseline CVD history. This estimate was not attenuated by adjustment for potential confounders, including eGFR and UACR at baseline as well as at censoring (3.74; 95% CI 2.63-5.31). Adding rapid kidney function decline during follow-up to other clinical predictors (WATCH-DM score, eGFR, and UACR at study entry and end of follow-up) improved HF risk classification (ROC AUC = + 0.02, p = 0.027; relative IDI = + 38%, p < 0.0001).ConclusionsIn patients with T2D, rapid kidney function decline is associated with a marked increase in HF risk, independent of starting kidney function and/or albuminuria. These findings highlight the importance of serial eGFR measurements over time to improve HF risk estimation in T2D.

Dataset Information

Kidney Biomarkers and Decline in eGFR in Patients with Type 2 Diabetes.

Publications

Kidney Biomarkers and Decline in eGFR in Patients with Type 2 Diabetes.

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