Literature DB >> 20842074

Metabonomic analysis of serum metabolites in kidney transplant recipients with cyclosporine A- or tacrolimus-based immunosuppression.

Chan-Duck Kim1, Eun-Young Kim, Hanna Yoo, Jae Won Lee, Do Hyun Ryu, Dong Woo Noh, Sun-Hee Park, Yong-Lim Kim, Geum-Sook Hwang, Tae-Hwan Kwon.   

Abstract

BACKGROUND: Cyclosporine A (CsA) and tacrolimus (TAC) affect the body metabolism of renal transplant recipients differently. We applied a novel method of H-nuclear magnetic resonance-based metabonomics to integrate the serum metabolic profiles of transplant recipients with normal allograft function and identify time-dependent changes in the levels of serum metabolites in response to CsA- or TAC-based immunosuppression after kidney transplantation (KT).
METHODS: Fifty-seven consecutive renal transplant recipients were treated with CsA-based (CsA, mycophenolate mofetil, and steroid, n=27) or TAC-based (TAC, mycophenolate mofetil, and steroid, n=30) regimens. Serum samples were analyzed at baseline (pretransplant) and 1, 3, and 6 months after KT.
RESULTS: The Partial Least Squares-Discriminant Analysis score plots showed a clear separation between levels at baseline and at 1, 3, and 6 months after KT in both groups. The levels of lipid metabolites were increased after KT in both groups, and importantly, CsA group demonstrated higher levels than TAC group. The metabolites for which the levels differed between the CsA and TAC groups and that changed according to treatment duration were glucose, hypoxanthine, lactate, succinate, and taurine. In contrast, trimethylamine-N-oxide levels, known to be associated with graft dysfunction, did not differ between the two groups.
CONCLUSIONS: These data indicate that CsA- and TAC-based immunosuppressions elicit unique changes in serum metabolic profiles after KT. H-nuclear magnetic resonance-based metabonomics could provide new insights regarding the side effects of immunosuppressive regimens.

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Year:  2010        PMID: 20842074     DOI: 10.1097/TP.0b013e3181edd69a

Source DB:  PubMed          Journal:  Transplantation        ISSN: 0041-1337            Impact factor:   4.939


  10 in total

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2.  Urinary Concentration Defect and Renal Glycosuria in Cyclosporine-treated Rats.

Authors:  Jun Han Lee; Su A Kim; Chor Ho Jo; Chang Hwa Lee; Gheun-Ho Kim
Journal:  Electrolyte Blood Press       Date:  2020-06-18

3.  The Use of Machine Learning Algorithms and the Mass Spectrometry Lipidomic Profile of Serum for the Evaluation of Tacrolimus Exposure and Toxicity in Kidney Transplant Recipients.

Authors:  Dan Burghelea; Tudor Moisoiu; Cristina Ivan; Alina Elec; Adriana Munteanu; Ștefania D Iancu; Anamaria Truta; Teodor Paul Kacso; Oana Antal; Carmen Socaciu; Florin Ioan Elec; Ina Maria Kacso
Journal:  Biomedicines       Date:  2022-05-17

4.  A pilot metabolic profiling study in serum of patients with chronic kidney disease based on (1) H-NMR-spectroscopy.

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Review 5.  Metabolic phenotyping in clinical and surgical environments.

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Review 6.  The Personalization of Clopidogrel Antiplatelet Therapy: The Role of Integrative Pharmacogenetics and Pharmacometabolomics.

Authors:  Arwa M Amin; Lim Sheau Chin; Dzul Azri Mohamed Noor; Muhamad Ali Sk Abdul Kader; Yuen Kah Hay; Baharudin Ibrahim
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7.  Metabolomic Profiling in Individuals with a Failing Kidney Allograft.

Authors:  Roberto Bassi; Monika A Niewczas; Luigi Biancone; Stefania Bussolino; Sai Merugumala; Sara Tezza; Francesca D'Addio; Moufida Ben Nasr; Alessandro Valderrama-Vasquez; Vera Usuelli; Valentina De Zan; Basset El Essawy; Massimo Venturini; Antonio Secchi; Francesco De Cobelli; Alexander Lin; Anil Chandraker; Paolo Fiorina
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8.  1H NMR-based metabolite profiling of plasma in a rat model of chronic kidney disease.

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Journal:  PLoS One       Date:  2014-01-20       Impact factor: 3.240

9.  Patients with Treatment-Requiring Chronic Graft versus Host Disease after Allogeneic Stem Cell Transplantation Have Altered Metabolic Profiles due to the Disease and Immunosuppressive Therapy: Potential Implication for Biomarkers.

Authors:  Håkon Reikvam; Ida-Sofie Grønningsæter; Knut Anders Mosevoll; Roald Lindås; Kimberley Hatfield; Øystein Bruserud
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10.  Novel Filtration Markers for GFR Estimation.

Authors:  Amy B Karger; Lesley A Inker; Josef Coresh; Andrew S Levey; John H Eckfeldt
Journal:  EJIFCC       Date:  2017-12-19
  10 in total

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