PDF
ePub
Citation
Print
Abstract
Acute and chronic immune injury, drug toxicity, and cardiovascular complications remain a critical challenge following kidney transplantation. Success from these hurdles is closely associated with the ability to monitor patients and responsively adjust their medication. Metabolic and biochemical profiling (metabolomics) may enable detection of early changes in cell signal transduction regulation and biochemistry with high sensitivity and specificity. However, metabolomics have not been studied extensively in the field of kidney transplantation. This review describes the basic principles of metabolomics, summarizes recent studies, and suggests future perspectives.
References
1). Chung BC. Metabolomics in disease research. Mol Cell Biol News. 2006; 18:17–27. (정봉철. 질환연구분야에서의 대사체학. 분자세포생물학뉴스 2006;18: 17–27.).
2). Bouatra S, Aziat F, Mandal R, Guo AC, Wilson MR, Knox C, et al. The human urine metabolome. PLoS One. 2013; 8:e73076.
3). Kim SH, Yang SO, Kim KH, Km YS, Liu KH, Yoon YR, et al. Research trends, applications, and domestic research promotion stratigies of metabolomics. KSBB Journal. 2009; 24:113–21. (김소현, 양승옥, 김경헌, 김영석, 유광현, 윤영란, 등. 대사체학의 연구동향, 응용 및 국내 연구 활성화 방안. KSBB Journal 2009;24: 113–21.).
4). Emwas AHM, Salek RM, Griffin JL, Merzaban J. NMR-based metabolomics in human disease diagnosis: applications, limitations, and recommendations. Metabolomics. 2013; 9:1048–72.
5). Boccard J, Veuthey JL, Rudaz S. Knowledge discovery in metabolomics: an overview of MS data handling. J Sep Sci. 2010; 33(3):290–304.
6). Sugimoto M, Kawakami M, Robert M, Soga T, Tomita M. Bioinformatics Tools for Mass Spectroscopy-Based Metabo-lomic Data Processing and Analysis. Curr Bioinform. 2012; 7(1):96–108.
7). Kim CD, Kim EY, Yoo H, Lee JW, Ryu do H, Noh DW, et al. Metabonomic analysis of serum metabolites in kidney transplant recipients with cyclosporine A- or tacrolimus-based immunosuppression. Transplantation. 2010; 90:748–56.
8). Li L, Sui W, Che W, Li W, Chen J, Li H, et al. 1H NMR-based metabolic profiling of human serum before and after renal transplantation. ASAIO J. 2013; 59:286–93.
9). Sui W, Huang L, Dai Y, Chen J, Yan Q, Huang H. Proteomic profiling of renal allograft rejection in serum using magnetic bead-based sample fractionation and MALDI-TOF MS. Clin Exp Med. 2010; 10:259–68.
10). Wang J, Zhou Y, Xu M, Rong R, Guo Y, Zhu T. Urinary metabolomics in monitoring acute tubular injury of renal allografts: a preliminary report. Transplant Proc. 2011; 43:3738–42.
11). Blydt-Hansen TD, Sharma A, Gibson IW, Mandal R, Wishart DS. Urinary metabolomics for noninvasive detection of borderline and acute T cell-mediated rejection in children after kidney transplantation. Am J Transplant. 2014; 14:2339–49.
12). Zhao X, Chen J, Ye L, Xu G. Serum metabolomics study of the acute graft rejection in human renal transplantation based on liquid chromatography-mass spectrometry. J Proteome Res. 2014; 13:2659–67.
13). Moers C, Varnav OC, van Heurn E, Jochmans I, Kirste GR, Rahmel A, et al. The value of machine perfusion perfusate biomarkers for predicting kidney transplant outcome. Transplantation. 2010; 90:966–73.
14). Hoogland ER, de Vries EE, Christiaans MH, Winkens B, Snoeijs MG, van Heurn LW. The value of machine perfusion biomarker concentration in DCD kidney transplantations. Transplantation. 2013; 95:603–10.
15). Bon D, Billault C, Thuillier R, Hebrard W, Boildieu N, Celhay O, et al. Analysis of perfusates during hypothermic machine perfusion by NMR spectroscopy: a potential tool for predicting kidney graft outcome. Transplantation. 2014; 97:810–6.
16). Dié mé B, Halimi JM, Emond P, Bü chler M, Nadal-Desbarat L, Blasco H, et al. Assessing the metabolic effects of calcineurin inhibitors in renal transplant recipients by urine metabolic profiling. Transplantation. 2014; 98:195–201.
Table 1.
신장이식 분야의 주요 대사체 연구
XML Download