Metabolomic analysis of human plasma from haemodialysis patients

Sato, Emiko; Kohno, Masahiro; Yamamoto, Masanori; Fujisawa, Tatsuya; Fujiwara, Kazutoshi; Tanaka, Noriaki

doi:10.1111/j.1365-2362.2010.02398.x

Cited by 63 publications

(48 citation statements)

References 16 publications

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“…Increasing interest has been directed toward the application of metabolite profiling to plasma from individuals with existing CKD or ESRD. [2][3][4][30][31][32] Here, we profile plasma obtained from individuals up to 8 years before disease onset, on the principle that non-GFR markers of renal metabolite handling may be sensitive indicators of incipient kidney dysfunction. Although metabolite profiling alone may not be sufficiently specific to identify individuals who go on to develop CKD, it may contribute to clinical models of CKD prediction that contain other variables.…”

Section: Discussionmentioning

confidence: 99%

A Combined Epidemiologic and Metabolomic Approach Improves CKD Prediction

Rhee

Clish

Ghorbani

et al. 2013

Journal of the American Society of Nephrology

260

220

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Metabolomic approaches have begun to catalog the metabolic disturbances that accompany CKD, but whether metabolite alterations can predict future CKD is unknown. We performed liquid chromatography/mass spectrometry-based metabolite profiling on plasma from 1434 participants in the Framingham Heart Study (FHS) who did not have CKD at baseline. During the following 8 years, 123 individuals developed CKD, defined by an estimated GFR of ,60 ml/min per 1.73 m 2 . Numerous metabolites were associated with incident CKD, including 16 that achieved the Bonferroni-adjusted significance threshold of P#0.00023. To explore how the human kidney modulates these metabolites, we profiled arterial and renal venous plasma from nine individuals. Nine metabolites that predicted CKD in the FHS cohort decreased more than creatinine across the renal circulation, suggesting that they may reflect non-GFR-dependent functions, such as renal metabolism and secretion. Urine isotope dilution studies identified citrulline and choline as markers of renal metabolism and kynurenic acid as a marker of renal secretion. In turn, these analytes remained associated with incident CKD in the FHS cohort, even after adjustment for eGFR, age, sex, diabetes, hypertension, and proteinuria at baseline. Addition of a multimarker metabolite panel to clinical variables significantly increased the c-statistic (0.77-0.83, P,0.0001); net reclassification improvement was 0.78 (95% confidence interval, 0.60 to 0.95; P,0.0001). Thus, the addition of metabolite profiling to clinical data may significantly improve the ability to predict whether an individual will develop CKD by identifying predictors of renal risk that are independent of estimated GFR.

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Section: Discussionmentioning

confidence: 99%

A Combined Epidemiologic and Metabolomic Approach Improves CKD Prediction

Rhee

Clish

Ghorbani

et al. 2013

Journal of the American Society of Nephrology

260

220

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“…UPLC-based metabonomics was developed to analyze the plasma samples from end-stage renal disease patients. 1-Methylinosine was found to be an effective candidate biomarker to estimate adequacy of a hemodialysis regimen [77]. One study reported that urinary hypoxanthine was the most significant metabolite in children with nephrolithiasis.…”

Section: Chronic Kidney Disease (Ckd)mentioning

confidence: 99%

UPLC-based metabonomic applications for discovering biomarkers of diseases in clinical chemistry

Zhao

Cheng

Vaziri

et al. 2014

Clinical Biochemistry

120

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a b s t r a c t a r t i c l e i n f oObjectives: Metabonomics is a powerful and promising analytic tool that allows assessment of global lowmolecular-weight metabolites in biological systems. It has a great potential for identifying useful biomarkers for early diagnosis, prognosis and assessment of therapeutic interventions in clinical practice. The aim of this review is to provide a brief summary of the recent advances in UPLC-based metabonomic approach for biomarker discovery in a variety of diseases, and to discuss their significance in clinical chemistry.Design and methods: All the available information on UPLC-based metabonomic applications for discovering biomarkers of diseases were collected via a library and electronic search (using Web of Science, Pubmed, ScienceDirect, Springer, Google Scholar, etc.).Results: Metabonomics has been used in clinical chemistry to identify and evaluate potential biomarkers and therapeutic targets in various diseases affecting the liver (hepatocarcinoma and liver cirrhosis), lung (lung cancer and pneumonia), gastrointestinal tract (colorectal cancer) and urogenital tract (prostate cancer, ovarian cancer and chronic kidney disease), as well as metabolic diseases (diabetes) and neuropsychiatric disorders (Alzheimer's disease and schizophrenia), etc.Conclusions: The information provided highlights the potential value of determination of endogenous lowmolecular-weight metabolites and the advantages and potential drawbacks of the application of UPLC-based metabonomics in clinical setting.

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“…High-resolution mass spectrometry has revealed the accumulation of many compounds that do not appear in lists of known metabolites and are characterized only by molecular mass. [11][12][13][14][15][16] With the inclusion of such compounds, the number of reported uremic solutes will soon rise above 500.…”

Section: The Multiplicity Of Uremic Solutesmentioning

confidence: 99%

Approaches to Uremia

Meyer

Hostetter

2014

Journal of the American Society of Nephrology

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The development of dialysis was a dramatic step forward in medicine, allowing people who would soon have died because of lack of kidney function to remain alive for years. We have since found, however, that the "artificial kidney" does not live up fully to its name. Dialysis keeps patients alive but not well. Part of the residual illness that dialysis patients experience is caused by retained waste solutes that dialysis does not remove as well as native kidney function does. New means are available to identify these toxic solutes, about which we currently know remarkably little, and knowledge of these solutes would help us to improve therapy. This review summarizes our current knowledge of toxic solutes and highlights methods being explored to identify additional toxic solutes and to enhance the clearance of these solutes to improve patient outcomes.

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Metabolomic analysis of human plasma from haemodialysis patients

Abstract: 1-Methylinosine and two unknown molecules whose m/z at ESI-positive mode are 257·1033 and 413·1359 were found as effective candidate biomarkers to estimate adequate haemodialysis dose, which has to be confirmed in prospective studies.

Cited by 63 publications

References 16 publications

A Combined Epidemiologic and Metabolomic Approach Improves CKD Prediction

A Combined Epidemiologic and Metabolomic Approach Improves CKD Prediction

UPLC-based metabonomic applications for discovering biomarkers of diseases in clinical chemistry

Approaches to Uremia

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