Dataset Information

Urinary metabolites associate with the rate of kidney function decline in patients with autosomal dominant polycystic kidney disease.

ABSTRACT: BACKGROUND:The variable course of autosomal dominant polycystic kidney disease (ADPKD), and the advent of renoprotective treatment require early risk stratification. We applied urinary metabolomics to explore differences associated with estimated glomerular filtration rate (eGFR; CKD-EPI equation) and future eGFR decline. METHODS:Targeted, quantitative metabolic profiling (1H NMR-spectroscopy) was performed on baseline spot urine samples obtained from 501 patients with ADPKD. The discovery cohort consisted of 338 patients (56% female, median values for age 46 [IQR 38 to 52] years, eGFR 62 [IQR 45 to 85] ml/min/1.73m2, follow-up time 2.5 [range 1 to 3] years, and annual eGFR slope -3.3 [IQR -5.3 to -1.3] ml/min/1.73m2/year). An independent cohort (n = 163) was used for validation. Multivariate modelling and linear regression were used to analyze the associations between urinary metabolites and eGFR, and eGFR decline over time. RESULTS:Twenty-nine known urinary metabolites were quantified from the spectra using a semi-automatic quantification routine. The model optimization routine resulted in four metabolites that most strongly associated with actual eGFR in the discovery cohort (F = 128.9, P = 7×10-54, R2 = 0.724). A model using the ratio of two other metabolites, urinary alanine/citrate, showed the best association with future annual change in eGFR (F = 51.07, P = 7.26×10-12, R2 = 0.150). This association remained significant after adjustment for clinical risk markers including height-adjusted total kidney volume (htTKV). Results were confirmed in the validation cohort. CONCLUSIONS:Quantitative NMR profiling identified urinary metabolic markers that associated with actual eGFR and future rate of eGFR decline. The urinary alanine/citrate ratio showed additional value beyond conventional risk markers.

SUBMITTER: Dekker SEI

PROVIDER: S-EPMC7244119 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Urinary metabolites associate with the rate of kidney function decline in patients with autosomal dominant polycystic kidney disease.

Dekker Shosha E I SEI Verhoeven Aswin A Soonawala Darius D Peters Dorien J M DJM de Fijter Johan W JW Mayboroda Oleg A OA

PloS one 20200522 5

<h4>Background</h4>The variable course of autosomal dominant polycystic kidney disease (ADPKD), and the advent of renoprotective treatment require early risk stratification. We applied urinary metabolomics to explore differences associated with estimated glomerular filtration rate (eGFR; CKD-EPI equation) and future eGFR decline.<h4>Methods</h4>Targeted, quantitative metabolic profiling (1H NMR-spectroscopy) was performed on baseline spot urine samples obtained from 501 patients with ADPKD. The ...[more]

PMID: 32442208

Similar Datasets

Project description:BACKGROUND:Markers currently used to predict the likelihood of rapid disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD) are expensive and time consuming to assess and often have limited sensitivity. New, easy-to-measure markers are therefore needed that alone or in combination with conventional risk markers can predict the rate of disease progression. In the present study, we investigated the ability of tubular damage and inflammation markers to predict kidney function decline. METHODS:At baseline, albumin, immunoglobulin G, kidney injury molecule 1, ?2 microglobulin (?2MG), heart-type fatty acid-binding protein, neutrophil gelatinase-associated lipocalin, and monocyte chemotactic protein-1 -(MCP-1) were measured in 24-h urine samples of patients participating in a study investigating the therapeutic efficacy of lanreotide in ADPKD. Individual change in estimated glomerular filtration rate (eGFR) during follow-up was calculated using mixed-model analysis taking into account 13 -eGFRs (chronic kidney disease EPIdemiology) per patient. Logistic regression analysis was used to select urinary biomarkers that had the best association with rapidly progressive disease. The predictive value of these selected urinary biomarkers was compared to other risk scores using C-statistics. RESULTS:Included were 302 patients of whom 53.3% were female, with an average age of 48 ± 7 years, eGFR of 52 ± 12 mL/min/1.73 m2, and a height-adjusted total kidney volume (htTKV) of 1,082 (736-1,669) mL/m. At baseline, all urinary damage and inflammation markers were associated with baseline eGFR, also after adjustment for age, sex and baseline htTKV. For longitudinal analyses only patients randomized to standard care were considered (n = 152). A stepwise backward analysis revealed that ?2MG and MCP-1 showed the strongest association with rapidly progressive disease. A urinary biomarker score was created by summing the ranking of tertiles of ?2MG and MCP-1 excretion. The predictive value of this urinary biomarker score was higher compared to that of the Mayo htTKV classification (area under the curve [AUC] 0.73 [0.64-0.82] vs. 0.61 [0.51-0.71], p = 0.04) and comparable to that of the predicting renal outcomes in -ADPKD score (AUC 0.73 [0.64-0.82] vs. 0.65 [0.55-0.75], p = 0.18). In a second independent cohort with better kidney function, similar results were found for the urinary biomarker score. CONCLUSION:Measurement of urinary ?2MG and MCP-1 excretion allows selection of ADPKD patients with rapidly progressive disease, with a predictive value comparable to or even higher than that of TKV or PKD mutation. Easy and inexpensive to measure urinary markers therefore hold promise to help predict prognosis in ADPKD.

Project description:BackgroundPrevious clinical studies of autosomal dominant polycystic kidney disease (ADPKD) reported that loss of kidney function usually follows a steep and relentless course. A detailed examination of individual patterns of decline in estimated glomerular filtration rate (eGFR) has not been performed.Study designLongitudinal post hoc analysis of data collected during the Halt Progression of Polycystic Kidney Disease (HALT-PKD) trials.Setting & participants494 HALT-PKD Study A participants (younger; preserved eGFR) and 435 Study B participants (older; reduced eGFR) who had more than 3 years of follow-up and 7 or more eGFR assessments.MeasurementsLongitudinal eGFR assessments using the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) creatinine equation.PredictorsDemographic, clinical, laboratory, and imaging features of participants.OutcomesProbability of linear and nonlinear decline patterns or of stable eGFR calculated for each participant from a Bayesian model of individual eGFR trajectories.ResultsMost (62.5% in Study A and 81% in Study B) participants had a linear decline in eGFR during up to 8 years of follow-up. A proportion (22% in Study A and 13% in Study B) of progressors had a nonlinear pattern. 15.5% of participants in Study A and 6% in Study B had a prolonged (≥4.5 years) period of stable eGFRs. These individuals (Study A) had significantly smaller total kidney volumes, higher renal blood flows, lower urinary albumin excretion, and lower body mass index at baseline and study end. In Study B, participants with reduced but stable eGFRs were older than the progressors. Two-thirds of nonprogressors in both studies had PKD1 mutations, with enrichment for weak nontruncating mutations.LimitationsRelatively short follow-up of a clinical trial population.ConclusionsAlthough many individuals with ADPKD have a linear decline in eGFR, prolonged intervals of stable GFRs occur in a substantial fraction. Lower body mass index was associated with more stable kidney function in early ADPKD.

Project description:Background and objectivesIt is assumed that in autosomal dominant polycystic kidney disease (ADPKD), kidney function remains in the normal range for several decades because of hyperfiltration of remnant nephrons. In this study, we investigate the extent to which patients with ADPKD hyperfilter.Design, setting, participants, & measurementsIn this cross-sectional study, we measured GFR as urinary clearance using continuous infusion of 125I-iothalamate. Kidney function reserve capacity was determined as increase in measured GFR after adding a dopamine infusion of 4.4-6 mg/h. Potential kidney donors were used as healthy controls and matched by age and sex to patients with ADPKD for comparisons across age groups and CKD stages. Hyperfiltration was defined by a loss of kidney function reserve capacity compared with healthy controls.ResultsA total of 300 participants were studied. In the youngest age group (18-29 years), measured GFR was not different between patients with ADPKD and healthy controls (103±21 versus 111±9 ml/min per 1.73 m2; P=0.14). In this age group kidney function reserve capacity was higher compared with healthy controls (11.1%±8.3% versus 5.3%±6.5%; P=0.04). Moreover, kidney function reserve capacity was similar to healthy controls in patients with ADPKD with early-stage disease (eGFR?60 ml/min per 1.73 m2), either overall or when divided into fast or slow progressors according to their Mayo height-adjusted total kidney volume class. However, in patients with ADPKD, lower measured GFR was associated with lower kidney function reserve capacity (?=1.0 [95% confidence interval, 0.5 to 1.5] % per 10 ml/min per 1.73 m2; P<0.001). Kidney function reserve capacity was therefore lower compared with healthy controls at older age and later CKD stages.ConclusionsPatients with early-stage ADPKD, either classified as having rapidly or slowly progressive disease, are able to increase their GFR in response to dopamine. Hyperfiltration, defined by a loss of kidney function reserve capacity, may therefore not be an early phenomenon in ADPKD.

Dataset Information

Urinary metabolites associate with the rate of kidney function decline in patients with autosomal dominant polycystic kidney disease.

Publications

Urinary metabolites associate with the rate of kidney function decline in patients with autosomal dominant polycystic kidney disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets