Predictive metabolomic signatures of end-stage renal disease: A multivariate analysis of population-based data

Silva, Robson E.; Baldim, João L.; Chagas‐Paula, Daniela Aparecida; Soares, Marisi G.; Lago, João Henrique G.; Gonçalves, Reggiani Vilela; Novaes, Rômulo Dias

doi:10.1016/j.biochi.2018.06.009

Cited by 27 publications

(20 citation statements)

References 61 publications

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“…We found that each type of e-cigarette exposure led to unique metabolite profiles within the circulation of exposed mice. Unique profiles can reveal specific metabolomic signatures that are associated with disease risks; these signatures have been associated with cardiovascular disease and serve as predictors of chronic kidney disease [17,18]. Specifically, JUUL Mango and Vape Pen mice had different plasma levels of eicosanoids, biological molecules that act as activators and suppressors of inflammation [19].…”

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

“…Thus, these data demonstrate that e-device type, chemical components, duration of exposure and sex all play critical roles in altering metabolomic profiles. This is concerning as unique profiles can reveal specific metabolomic signatures associated with disease risks; these signatures have been associated with cardiovascular disease and serve as predictors of chronic kidney disease [ 16 , 17 ]. Future work is needed to fully understand the physiological and pathophysiological effects of these e-cigarette aerosol exposure-related metabolomic changes within humans.…”

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confidence: 99%

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Vaping-induced metabolomic signatures in the circulation of mice are driven by device type, e-liquid, exposure duration and sex

Moshensky

Shin

et al. 2021

ERJ Open Res

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Vaping-induced metabolomic signatures in the circulation of mice are driven by device type, e-liquid, exposure duration and sex

Moshensky

Shin

et al. 2021

ERJ Open Res

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“…It should be noted that KYNA (and possibly KYN) relies on tubular secretion in addition to glomerular filtration for clearance from the serum, which makes them potential markers of non-GFR-related renal function [55]. The potential of KYN to be used as a predictor of CKD across different ethnic populations has been highlighted in a meta-analysis [58]. Out of the 233 metabolites analysed, KYN had the best score as a CKD biomarker.…”

Section: Kp In Ckdmentioning

confidence: 99%

The Kynurenine Pathway in Acute Kidney Injury and Chronic Kidney Disease

et al. 2021

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Background: The kynurenine pathway (KP) is the major catabolic pathway for tryptophan degradation. The KP plays an important role as the sole de novo nicotinamide adenine dinucleotide (NAD+) biosynthetic pathway in normal human physiology and functions as a counter-regulatory mechanism to mitigate immune responses during inflammation. Although the KP has been implicated in a variety of disorders including Huntington’s disease, seizures, cardiovascular disease, and osteoporosis, its role in renal diseases is seldom discussed. Summary: This review summarizes the roles of the KP and its metabolites in acute kidney injury (AKI) and chronic kidney disease (CKD) based on current literature evidence. Metabolomics studies demonstrated that the KP metabolites were significantly altered in patients and animal models with AKI or CKD. The diagnostic and prognostic values of the KP metabolites in AKI and CKD were highlighted in cross-sectional and longitudinal human observational studies. The biological impact of the KP on the pathophysiology of AKI and CKD has been studied in experimental models of different etiologies. In particular, the activation of the KP was found to confer protection in animal models of glomerulonephritis, and its immunomodulatory mechanism may involve the regulation of T cell subsets such as Th17 and regulatory T cells. Manipulation of the KP to increase NAD+ production or diversion toward specific KP metabolites was also found to be beneficial in animal models of AKI. Key Messages: KP metabolites are reported to be dysregulated in human observational and animal experimental studies of AKI and CKD. In AKI, the magnitude and direction of changes in the KP depend on the etiology of the damage. In CKD, KP metabolites are altered with the onset and progression of CKD all the way to advanced stages of the disease, including uremia and its related vascular complications. The activation of the KP and diversion to specific sub-branches are currently being explored as therapeutic strategies in these diseases, especially with regards to the immunomodulatory effects of certain KP metabolites. Further elucidation of the KP may hold promise for the development of biomarkers and targeted therapies for these kidney diseases.

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“…In addition, urine can be used for measuring time-related metabolic alterations-a valuable feature for the study of progression and prognostication of acute and chronic diseases [10]. Urine metabolomics has been successfully applied to understand the mechanism(s) underlying drug toxicity and discover novel biomarkers for detecting kidney disease [11].…”

Section: Introductionmentioning

confidence: 99%

Urinary chemical fingerprint left behind by repeated NSAID administration: Discovery of putative biomarkers using artificial intelligence

et al. 2020

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Prediction and early detection of kidney damage induced by nonsteroidal anti-inflammatories (NSAIDs) would provide the best chances of maximizing the anti-inflammatory effects while minimizing the risk of kidney damage. Unfortunately, biomarkers for detecting NSAIDinduced kidney damage in cats remain to be discovered. To identify potential urinary biomarkers for monitoring NSAID-based treatments, we applied an untargeted metabolomics approach to urine collected from cats treated repeatedly with meloxicam or saline for up to 17 days. Applying multivariate analysis, this study identified a panel of seven metabolites that discriminate meloxicam treated from saline treated cats. Combining artificial intelligence machine learning algorithms and an independent testing urinary metabolome data set from cats with meloxicam-induced kidney damage, a panel of metabolites was identified and validated. The panel of metabolites including tryptophan, tyrosine, taurine, threonic acid, pseudouridine, xylitol and lyxitol, successfully distinguish meloxicam-treated and saline-treated cats with up to 75-100% sensitivity and specificity. This panel of urinary metabolites may prove a useful and non-invasive diagnostic tool for monitoring potential NSAID induced kidney injury in feline patients and may act as the framework for identifying urine biomarkers of NSAID induced injury in other species.

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Predictive metabolomic signatures of end-stage renal disease: A multivariate analysis of population-based data

Cited by 27 publications

References 61 publications

Vaping-induced metabolomic signatures in the circulation of mice are driven by device type, e-liquid, exposure duration and sex

Vaping-induced metabolomic signatures in the circulation of mice are driven by device type, e-liquid, exposure duration and sex

The Kynurenine Pathway in Acute Kidney Injury and Chronic Kidney Disease

Urinary chemical fingerprint left behind by repeated NSAID administration: Discovery of putative biomarkers using artificial intelligence

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