| Literature DB >> 31054449 |
Sun-Young Kim1, Bo Kyung Kim1, Mi-Ri Gwon1, Sook Jin Seong1, Boram Ohk1, Woo Youl Kang1, Hae Won Lee1, Hee-Yeon Jung2, Jang-Hee Cho2, Byung Ha Chung3, Sang-Ho Lee4, Yeong Hoon Kim5, Young-Ran Yoon1, Chan-Duck Kim6, Seungil Cho7.
Abstract
To improve early renal allograft function, it is important to develop a noninvasive diagnostic method for acute T cell-mediated rejection (TCMR). This study aims to explore potential noninvasive urinary biomarkers to screen for acute TCMR in kidney transplant recipients (KTRs) using untargeted metabolomic profiling. Urinary metabolites, collected from KTRs with stable graft function (STA) or acute TCMR episodes, were analyzed using liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analyses were performed to discriminate differences in urinary metabolites between the two groups. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of potential urinary biomarkers. Statistical analysis revealed the differences in urinary metabolites between the two groups and indicated several statistically significant metabolic features suitable for potential biomarkers. By comparing the retention times and mass fragmentation patterns of the chemicals in metabolite databases, samples, and standards, six of these features were clearly identified. ROC curve analysis showed the best performance of the training set (area under the curve value, 0.926; sensitivity, 90.0%; specificity, 84.6%) using a panel of five potential biomarkers: guanidoacetic acid, methylimidazoleacetic acid, dopamine, 4-guanidinobutyric acid, and L-tryptophan. The diagnostic accuracy of this model was 62.5% for an independent test dataset. LC-MS-based untargeted metabolomic profiling is a promising method to discriminate between acute TCMR and STA groups. Our model, based on a panel of five potential biomarkers, needs to be further validated in larger scale studies.Entities:
Keywords: Acute T cell-mediated rejection; Kidney transplantation; Liquid chromatography-tandem mass spectrometry; Metabolomic profiling; Metabolomics; Urine
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Year: 2019 PMID: 31054449 DOI: 10.1016/j.jchromb.2019.04.047
Source DB: PubMed Journal: J Chromatogr B Analyt Technol Biomed Life Sci ISSN: 1570-0232 Impact factor: 3.205