Discovery of Metabolomics Biomarkers for Early Detection of Nephrotoxicity

Boudonck, Kurt; Mitchell, Matthew; Német, László; Keresztes, Lilla; Nyska, Abraham; Shinar, Doron; Rosenstock, Moti

doi:10.1177/0192623309332992

Cited by 223 publications

(190 citation statements)

References 47 publications

Supporting

Mentioning

172

Contrasting

Unclassified

Order By: Relevance

“…After adjusting for baseline glucose levels and diabetes status, 1,5-AG levels at the baseline examination persisted to show an inverse relationship with higher risk of incident CKD. These results are supported by a recent study suggesting that an increase of urinary carbohydrates, including 1,5-AG, can be an early indicator of renal toxicity (46). Taken together, 1,5-AG is a promising candidate biomarker for incidence CKD whether as a result of hyperglycemia excursions or other pathways.…”

Section: Discussionsupporting

confidence: 74%

Serum Metabolomic Profiling and Incident CKD among African Americans

Zheng

Nettleton

et al. 2014

Clinical Journal of the American Society of Nephrology

101

View full text Add to dashboard Cite

Background and objectives Novel biomarkers that more accurately reflect kidney function and predict future CKD are needed. The human metabolome is the product of multiple physiologic or pathophysiologic processes and may provide novel insight into disease etiology and progression. This study investigated whether estimated kidney function would be associated with multiple metabolites and whether selected metabolomic factors would be independent risk factors for incident CKD.Design, setting, participants, & measurements In total, 1921 African Americans free of CKD with a median of 19.6 years follow-up among the Atherosclerosis Risk in Communities Study were included. A total of 204 serum metabolites quantified by untargeted gas chromatography-mass spectrometry and liquid chromatographymass spectrometry was analyzed by both linear regression for the cross-sectional associations with eGFR (specified by the Chronic Kidney Disease Epidemiology Collaboration equation) and Cox proportional hazards model for the longitudinal associations with incident CKD.Results Forty named and 34 unnamed metabolites were found to be associated with eGFR specified by the Chronic Kidney Disease Epidemiology Collaboration equation with creatine and 3-indoxyl sulfate showing the strongest positive (2.8 ml/min per 1.73 m 2 per +1 SD; 95% confidence interval, 2.1 to 3.5) and negative association (214.2 ml/min per 1.73 m 2 per +1 SD; 95% confidence interval, 217.0 to 211.3), respectively. Two hundred four incident CKD events with a median follow-up time of 19.6 years were included in the survival analyses. Higher levels of 5-oxoproline (hazard ratio, 0.70; 95% confidence interval, 0.60 to 0.82) and 1,5-anhydroglucitol (hazard ratio, 0.68; 95% confidence interval, 0.58 to 0.80) were significantly related to lower risk of incident CKD, and the associations did not appreciably change when mutually adjusted.Conclusions These data identify a large number of metabolites associated with kidney function as well as two metabolites that are candidate risk factors for CKD and may provide new insights into CKD biomarker identification.

show abstract

Section: Discussionsupporting

confidence: 74%

Serum Metabolomic Profiling and Incident CKD among African Americans

Zheng

Nettleton

et al. 2014

Clinical Journal of the American Society of Nephrology

101

View full text Add to dashboard Cite

show abstract

“…Out of the markers elevated with the kidney damages, glucose and branched amino acids have been reported previously for cisplatin induced toxicity (Portilla et al, 2006;Boudonck et al, 2009). Here, we identifi ed additional markers, glycine and taurine.…”

Section: Discussionmentioning

confidence: 55%

“…As statistical differentiation, we used OPLS-DA approach, whereas a previous NMR study used PCA and another MS study used t-test followed by either CART or logistic regression (Portilla et al, 2006;Boudonck et al, 2009). Although each approach has its own merits and shortcomings, our approach gave very good performance in classifying the unknown test set, predicting correctly all the test set data, up to 30% of the entire data set at 3 day time point.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Identification of Urinary Biomarkers Related to Cisplatin-Induced Acute Renal Toxicity Using NMR-Based Metabolomics

He¹,

Yang²,

Choi³

et al. 2011

Biomolecules and Therapeutics

View full text Add to dashboard Cite

Cisplatin is the founding member of the platin-group drugs that has platinum metal and ammonium group. Since its fi rst approval in 1978 by US Food and Drug Administration, it has been widely used for various types of cancer such as lung, ovarian, lymphomas, breast and bladder cancers (Smith and Talbot, 1992;von der Maase et al., 2000;Crino et al., 2001;Muggia, 2009). The mechanism of anticancer effect is cytotoxicity due to DNA cross-linking, oxidative damages and apoptosis (Gong et al., 1999;Pruefer et al., 2008). Due to these cytotoxic effect, cisplatin kills not only cancer cells but also normal cells, resulting in undesirable effects in various tissues including kidney, nerves, ear and gastroenteric ones (Loehrer and Einhorn, 1984). Among these, the nephrotoxicity is most common and can be a cause for the cessation of the drug therapy (Arany and Safi rstein, 2003;Yao et al., 2007). Typically, BloodCisplatin is widely used for various types of cancers. However, its side effects, most notably, renal toxicity often limit its clinical utility. Although previous metabolomic studies reported possible toxicity markers, they used small number of animals and statistical approaches that may not perform best in the presence of intra-group variation. Here, we identifi ed urinary biomarkers associated with renal toxicity induced by cisplatin using NMR-based metabolomics combined with Orthogonal Projections to Latent Structures-Discriminant Analysis (OPLS-DA). Male Sprague-Dawley rats (n=22) were treated with cisplatin (10 mg/kg single dose), and the urines obtained before and after treatment were analyzed by NMR. Multivariable analysis of NMR data presented clear separation between non-treated and treated groups. The OPLS-DA statistical results revealed that 1,3-dimethylurate, taurine, glucose, glycine and branched-chain amino acid (isoleucine, leucine and valine) were signifi cantly elevated in the treated group and that phenylacetylglycine and sarcosine levels were decreased in the treated group. To test the robustness of the approach, we built a prediction model for the toxicity and were able to predict all the unknown samples (n=14) correctly. We believe the proposed NMR-based metabolomics with OPLS-DA approach and the resulting urine markers can be used to augment the currently available blood markers. AbstractUrea Nitrogen (BUN), and blood creatinine are checked to monitor the expression of renal toxicity. In addition, hydration and diuretic measures are taken to minimize possible kidney damages. Still, BUN and creatinine are measured from blood and are late stage kidney functional markers (Hewitt et al.,

show abstract

“…Major changes in 3-hydroxybutyrate concentration, related to the metabolism of plasma lipids, occurs when tissue are exposed to stress (Fukao et al, 2004). A high increase of urinary 3-hydroxybutyrate has been reported as an early biomarker of toxicity (such as in nephrotoxicity, Boudonck et al, 2009, or during surgical trauma, Teague et al, 2007).…”

Section: Identification Of Specific Apap Toxicity Biomarkers In Biochipsmentioning

confidence: 99%

Predictive toxicology using systemic biology and liver microfluidic “on chip” approaches: Application to acetaminophen injury

Prot

Bunescu

Elena-Herrmann

et al. 2012

Toxicology and Applied Pharmacology

View full text Add to dashboard Cite

Snouber, et al.. Predictive toxicology using systemic biology and liver microfluidic "on chip" approaches: Application to acetaminophen injury. Toxicology and Applied Pharmacology, Elsevier, 2012, 259 (3) ABSTRACTWe -analyzed transcriptomic, proteomic and metabolomic profiles of hepatoma cells cultivated inside a microfluidic biochip with or without acetaminophen (APAP).Without APAP, the results show an adaptive cellular response to the microfluidic environment, leading to the induction of anti-oxidative stress and cytoprotective pathways. In presence of APAP, calcium homeostasis perturbation, lipid peroxidation and cell death are observed. These effects can be attributed to APAP metabolism into its highly reactive metabolite, N-acetyl-p-benzoquinone imine (NAPQI). . That toxicity pathway was confirmed by the detection of GSH-APAP, the large production of 2-hydroxybutyrate and 3-hydroxybutyrate, and methionine, cystine, and histidine consumption in the treated biochips. Those metabolites have been reported as specific biomarkers of hepatotoxicity and glutathione depletion in the literature. In addition, the integration of the metabolomic, transcriptomic and proteomic profiles collected allowed a more complete reconstruction of the APAP injury pathways. To our knowledge, this work is the first example of a global integration of microfluidic biochip data in toxicity assessment. Our results demonstrate the potential of that new approach to predictive toxicology.

show abstract

Discovery of Metabolomics Biomarkers for Early Detection of Nephrotoxicity

Cited by 223 publications

References 47 publications

Serum Metabolomic Profiling and Incident CKD among African Americans

Serum Metabolomic Profiling and Incident CKD among African Americans

Identification of Urinary Biomarkers Related to Cisplatin-Induced Acute Renal Toxicity Using NMR-Based Metabolomics

Predictive toxicology using systemic biology and liver microfluidic “on chip” approaches: Application to acetaminophen injury

Contact Info

Product

Resources

About