Metabolomic Alterations Associated with Cause of CKD

Clinical Journal of the American Society of Nephrology, Journal Year: 2017, Volume and Issue: 12(11), P. 1787 - 1794

Published: Sept. 28, 2017

Causes of CKD differ in prognosis and treatment. Metabolomic indicators cause may provide clues regarding the different physiologic processes underlying development progression.Metabolites were quantified from serum samples participants Modification Diet Renal Disease (MDRD) Study, a randomized controlled trial dietary protein restriction BP control, using untargeted reverse phase ultraperformance liquid chromatography tandem mass spectrometry quantification. Known, nondrug metabolites (n=687) log-transformed analyzed to discover associations with (polycystic kidney disease, glomerular other cause). Discovery was performed Study B, substudy MDRD low GFR (n=166), replication A, higher (n=423).Overall MDRD, average participant age 51 years 61% men. In discovery study (Study B), 29% had polycystic 28% 43% another cause; A), percentages 28%, 24%, 48%, respectively. analysis, adjusted for demographics, randomization group, body index, hypertensive medications, measured GFR, proteinuria, estimated intake, seven (16-hydroxypalmitate, kynurenate, homovanillate sulfate, N2,N2-dimethylguanosine, hippurate, homocitrulline, 1,5-anhydroglucitol) associated after correction multiple comparisons (P<0.0008). Five these metabolite hippurate) replicated A (P<0.007), all exhibiting levels disease lower compared causes.Metabolomic profiling identified several strongly CKD.

Language: Английский

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Plasma metabolites associated with chronic kidney disease and renal function in adults from the Baltimore Longitudinal Study of Aging

Metabolomics, Journal Year: 2021, Volume and Issue: 17(1)

Published: Jan. 1, 2021

Language: Английский

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Exposome and Metabolome Analysis of Sugarcane Workers Reveals Predictors of Kidney Injury

Kidney International Reports, Journal Year: 2024, Volume and Issue: 9(5), P. 1458 - 1472

Published: Feb. 6, 2024

IntroductionSugarcane workers are exposed to potentially hazardous agrochemicals, including pesticides, heavy metals, and silica. Such occupational exposures present health risks have been implicated in a high rate of kidney disease seen these workers.MethodsTo investigate potential biomarkers mechanisms that could explain chronic (CKD) among this worker population, paired urine samples were collected from sugarcane cutters at the beginning end harvest season Guatemala. Workers then separated into 2 groups, namely those with or without function decline (KFD) across season. Urine groups underwent elemental analysis untargeted metabolomics.ResultsUrine profiles demonstrated increases silicon, certain phosphorus levels all workers, whereas metals remained low. The KFD group had reduction estimated glomerular filtration (eGFR) season; however, injury marker 1 did not significantly change. Cross-harvest metabolomic found trends fatty acid accumulation, perturbed amino metabolism, presence other known signs impaired function.ConclusionSilica pesticides elevated KFD. Future work should determine whether long-term exposure silica multiple seasons contributes CKD workers. Overall, results confirmed occurring may provide insight early warning help increased incidence agricultural

Language: Английский

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The metabolomic quest for a biomarker in chronic kidney disease

Clinical Kidney Journal, Journal Year: 2018, Volume and Issue: 11(5), P. 694 - 703

Published: April 18, 2018

Chronic kidney disease (CKD) is a growing burden on people and healthcare for which the diagnostics are niether disease-specific nor indicative of progression. Biomarkers sought to enable clinicians offer more appropriate patient-centred treatments, could come fruition by using metabolomics approach. This mini-review highlights current literature CKD, suggests additional factors that need be considered in this quest biomarker, namely diet gut microbiome, meaningful advances made.

Language: Английский

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Variability of Two Metabolomic Platforms in CKD

Clinical Journal of the American Society of Nephrology, Journal Year: 2018, Volume and Issue: 14(1), P. 40 - 48

Published: Dec. 20, 2018

Nontargeted metabolomics can measure thousands of low-molecular-weight biochemicals, but important gaps limit its utility for biomarker discovery in CKD. These include the need to characterize technical and intraperson analyte variation, pool data across platforms, outline relationships with eGFR.Plasma samples from 49 individuals CKD (eGFR<60 ml/min per 1.73 m2 and/or ≥1 g proteinuria) were examined two study visits; 20 repeated as blind replicates. To enable comparison nontargeted profiled at Metabolon Broad Institute.The platform reported 837 known metabolites 483 unnamed compounds (selected 44,953 unknown ion features). The Institute 594 26,106 features. Median coefficients variation (CVs) replicates 14.6% (Metabolon) 6.3% (Broad Institute) metabolites, 18.9% 24.5% CVs day-to-day variability 29.0% 24.9% 41.8% 40.9% A total 381 shared platforms (median correlation 0.89). Many negatively correlated eGFR P<0.05, including 35.7% metabolites.Nontargeted quantifies >1000 analytes low CVs, agreement overlapping leading is excellent. demonstrate substantial eGFR.

Language: Английский

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Indoxyl sulfate associates with cardiovascular phenotype in children with chronic kidney disease

Pediatric Nephrology, Journal Year: 2019, Volume and Issue: 34(12), P. 2571 - 2582

Published: Aug. 19, 2019

Language: Английский

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Metabolite Biomarkers of CKD Progression in Children

Clinical Journal of the American Society of Nephrology, Journal Year: 2021, Volume and Issue: 16(8), P. 1178 - 1189

Published: Aug. 1, 2021

Metabolomics facilitates the discovery of biomarkers and potential therapeutic targets for CKD progression.We evaluated an untargeted metabolomics quantification stored plasma samples from 645 Chronic Kidney Disease in Children (CKiD) participants. Metabolites were standardized logarithmically transformed. Cox proportional hazards regression examined association between 825 nondrug metabolites progression to composite outcome KRT or 50% reduction eGFR, adjusting age, sex, race, body mass index, hypertension, glomerular versus nonglomerular diagnosis, proteinuria, baseline eGFR. Stratified analyses performed within subgroups glomerular/nonglomerular diagnosis eGFR.Baseline characteristics 391 (61%) male; median age 12 years; eGFR 54 ml/min per 1.73 m2; 448 (69%) diagnosis. Over a follow-up 4.8 years, 209 (32%) participants developed outcome. Unique signals identified Among with ≥60 m2, two-fold higher levels seven significantly associated KRT/halving events: three involved purine pyrimidine metabolism (N6-carbamoylthreonyladenosine, hazard ratio, 16; 95% confidence interval, 4 60; 5,6-dihydrouridine, 17; 5 55; pseudouridine, 39; 8 200); two amino acids, C-glycosyltryptophan, 24; interval 6 95 lanthionine, 3; 2 5; tricarboxylic acid cycle intermediate 2-methylcitrate/homocitrate, 4; 7; gulonate, 10; 3 29. those <60 level tetrahydrocortisol sulfate was lower risk (hazard 0.8; 0.7 0.9).Untargeted metabolomic profiling facilitated novel metabolite associations children that independent established clinical predictors highlight role select biologic pathways.

Language: Английский

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A Metabolomics study of metabolites associated with the glomerular filtration rate

BMC Nephrology, Journal Year: 2023, Volume and Issue: 24(1)

Published: April 21, 2023

Abstract Background Chronic kidney disease (CKD) is a global public health issue. The diagnosis of CKD would be considerably enhanced by discovering novel biomarkers used to determine the glomerular filtration rate (GFR). Small molecule metabolites related function that might utilized as measure GFR more accurately could found via metabolomics analysis blood samples taken from individuals with varied rates. Methods An untargeted study 145 plasma was performed using ultrahigh-performance liquid chromatography tandem mass spectrometry (UPLC–MS/MS). were divided into four groups based on patient’s measured rates (mGFRs) determined iohexol clearance rate. data analyzed random forest analyses and six other unique statistical analyses. Principal component (PCA) conducted R software. Results A large number involved in various metabolic pathways changed significantly between different GFRs. These included tryptophan or pyrimidine metabolism. top 30 best distinguished plot 13 amino acids, 9 nucleotides, 3 carbohydrates. panel (including hydroxyaparagine, pseudouridine, C-glycosyltryptophan, erythronate, N-acetylalanine, 7-methylguanidine) for estimating selected future testing targeted combining candidate lists Both hydroxyasparagine N,N-dimethyl-proline-proline are shown inversely associated have not been reported previously. In contrast, 1,5-anhydroglucitol (1,5-AG) decreases impaired renal function. Conclusions This patients degrees identified potential metabolite filtration. provide insight underlying pathophysiologic processes may contribute progression CKD, lead improvements estimation therapeutic targets improve

Language: Английский

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Longitudinal Plasma Metabolome Patterns and Relation to Kidney Function and Proteinuria in Pediatric CKD

Clinical Journal of the American Society of Nephrology, Journal Year: 2024, Volume and Issue: 19(7), P. 837 - 850

Published: May 6, 2024

Key Points Longitudinal untargeted metabolomics. Children with CKD have a circulating metabolome that changes over time. Background Understanding plasma patterns in relation to changing kidney function pediatric is important for continued research identifying novel biomarkers, characterizing biochemical pathophysiology, and developing targeted interventions. There are limited number of studies longitudinal metabolomics virtually none CKD. Methods The study multi-institutional, prospective cohort enrolled children aged 6 months 16 years eGFR 30–90 ml/min per 1.73 m 2 . Untargeted profiling was performed on samples from the baseline, 2-, 4-year visits. were technologic updates metabolomic platform used between baseline follow-up assays. Statistical approaches adopted avoid direct comparison measurements. To identify metabolite associations or urine protein-creatinine ratio (UPCR) among all three time points, we applied linear mixed-effects (LME) models. metabolites associated time, LME models 2- data. We regression analysis examine change level (∆level) (∆eGFR) UPCR (∆UPCR). reported significance basis both false discovery rate (FDR) <0.05 P < 0.05. Results 1156 person-visits ( N : baseline=626, 2-year=254, 4-year=276) included. 622 standardized measurements at points. In modeling, 406 343 FDR <0.05, respectively. Among 530 person-visits, 158 showed differences <0.05. For participants complete data visits n =123), report 35 ∆level–∆eGFR significant no ∆level–∆UPCR 0.05 modeling Conclusions characterized large population. Many these signals been progression, etiology, proteinuria previous Biomarkers Consortium studies. also detected.

Language: Английский

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From Discovery to Translation: Characterization of C-Mannosyltryptophan and Pseudouridine as Markers of Kidney Function

Scientific Reports, Journal Year: 2017, Volume and Issue: 7(1)

Published: Dec. 6, 2017

Using a non-targeted metabolomics platform, we recently identified C-mannosyltryptophan and pseudouridine as non-traditional kidney function markers. The aims of this study were to obtain absolute concentrations both metabolites in blood urine from individuals with without CKD provide reference ranges assess their fractional excretions (FE), the agreement counterparts. In without/with CKD, mean plasma for 0.26/0.72 µmol/L 3.39/4.30 µmol/mmol creatinine, respectively. respective 2.89/5.67 39.7/33.9 creatinine. Median (25th, 75th percentiles) FEs 70.8% (65.6%, 77.8%) 76.0% (68.6%, 82.4%) pseudouridine, indicating partial net reabsorption. Association analyses validated reported associations between single eGFR. Targeted measurements agreed well measurements, especially urine. Agreement composite nephrological measures FE urinary metabolite-to-creatinine ratio was lower, but could be improved by replacing creatinine standard clinical test. summary, targeted quantification additional characterization relevant populations are necessary steps translation biomarkers nephrology discovery application.

Language: Английский

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