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Detecting Renal Allograft Inflammation Using Quantitative Urine Metabolomics and CXCL10.

J. Ho,1 A. Sharma,2 R. Mandal,3 D. Wishart,3 C. Wiebe,1 L. Storsley,1 M. Karpinski,1 I. Gibson,4 P. Nickerson,1 D. Rush.1

1Internal Medicine, University of Manitoba, Winnipeg, MB, Canada
2Pediatrics & Child Health, University of Manitoba, Winnipeg, MB, Canada
3Biological Sciences, University of Alberta, Edmonton, AB, Canada
4Pathology, University of Manitoba, Winnipeg, MB, Canada.

Meeting: 2016 American Transplant Congress

Abstract number: 133

Keywords: Kidney transplantation, Monitoring, Protocol biopsy, Rejection

Session Information

Date: Sunday, June 12, 2016

Session Name: Concurrent Session: Kidney Immune Monitoring 1

Session Time: 4:30pm-6:00pm

 Presentation Time: 4:42pm-4:54pm

Location: Ballroom C

Related Abstracts
  • Validation of Urine CXCL10 for Diagnosis of Subclinical and Clinical Rejection in Pediatric Kidney Transplants
  • Urinary CXCL10 Independently Improves the Noninvasive Diagnosis of Antibody-Mediated Kidney Allograft Rejection

Background. We studied urine metabolomics (UM) alone or combined with urine CXCL10 to non-invasively detect cellular infiltrates in renal allograft biopsies.

Methods. Urines (n=137) were obtained prior to biopsy in 113 patients with no (n=66), mild (borderline or subclinical; n=58) or severe (clinical; n=13) rejection. UM was performed with Direct Flow Injection-Tandem Mass Spectrometry (DFI-MS/MS) using multiple reaction monitoring. Urine CXCL10 was measured by ELISA. UM data was analyzed with PLS-DA, validated with leave-one-out cross-validation, and an optimal two-component model was developed. CXCL10 area under the curve (AUC) was determined and a net reclassification index (NRI) and integrated discrimination index (IDI) analyses were performed.

Results. A three-way PLS2 classifier demonstrated that UM discriminated the three groups (Cohen's kappa 0.601, 95%CI 0.46-0.74, p<0.001). UM and CXCL10 demonstrated an AUC 0.81 (95%CI 0.74-0.88) and 0.76 (95%CI 0.68-0.84) respectively; and a combined AUC 0.84 (95%CI 0.78-0.91) for detecting alloimmune inflammation that was improved by NRI and IDI. Urinary CXCL10 was the best discriminator, followed by urine acylcarnitines and hexose.

Conclusions. UM can accurately and non-invasively discriminate non-inflamed biopsies from subclinical and clinical inflammation, and the addition of urine CXCL10 had a modest but significant effect on overall diagnostic performance. These data suggest that UM and CXCL10 may be useful for non-invasive monitoring of alloimmune inflammation in renal transplant patients.

CITATION INFORMATION: Ho J, Sharma A, Mandal R, Wishart D, Wiebe C, Storsley L, Karpinski M, Gibson I, Nickerson P, Rush D. Detecting Renal Allograft Inflammation Using Quantitative Urine Metabolomics and CXCL10. Am J Transplant. 2016;16 (suppl 3).

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To cite this abstract in AMA style:

Ho J, Sharma A, Mandal R, Wishart D, Wiebe C, Storsley L, Karpinski M, Gibson I, Nickerson P, Rush D. Detecting Renal Allograft Inflammation Using Quantitative Urine Metabolomics and CXCL10. [abstract]. Am J Transplant. 2016; 16 (suppl 3). https://atcmeetingabstracts.com/abstract/detecting-renal-allograft-inflammation-using-quantitative-urine-metabolomics-and-cxcl10/. Accessed March 8, 2021.

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