ABSTRACT: Effective non-invasive monitoring method to tell histopathology is a big challenge in renal transplantation.
We used 70-mer long oligonucleotide array with 449 immune related genes to determine gene expression profiles of peripheral blood mononuclear cells (PBMCs) under different immune status including stable renal function (TX), acute tubular necrosis (ATN), biopsy conformed acute rejection (AR), clinical rejection with pathology of borderline changes (BL), clinical rejection without biopsy proven/presumed rejection (PR) and renal dysfunction without rejection (NR).
Distinct molecular expression signatures in each group were found to correlate with histopathology. And we concluded that B cell chemokine CXCL13 and mast cell may play a role in renal allograft rejection through significant difference analysis and functional pathway analysis.
It provides a potential non-invasive method for monitoring renal allograft function and immune status of renal transplant recipients.
Transplant Immunology 04/2011; 24(3):172-80. · 1.46 Impact Factor
Chinese medical journal 03/2011; 124(5):646-8. · 0.86 Impact Factor
ABSTRACT: To prepare a novel MRI targeted contrast agent Gd-DTPA-Granzyme B monoclonal antibody (mAb) and to test its reaction conditions.
The Granzyme B mAb was coupled with DTPA,and then conjugated with Gd. The Gd-DTPA antibody was characterized using MALDI-TOF-MS. Cytotoxicity test was performed with MTT assay, and immune activation was examined with immunohistochemistry.
MALDI-TOF-MS demonstrated that the molecular weight shifted from granzyme B mAb (133986) to Gd-DTPA-GB mAb (139736), which indicated the conjugation of the antibody with Gd-DTPA. The molar ratio of Gd per IgG molecule was about 20. MTT assay showed that Gd, DTPA, Gd-DTPA and Gd-DTPA-GB mAb groups did not make an impact on cell viability, and there were no significant differences among 4 groups (P>0.05). Immunohistochemistry results showed that compared with the positive control group the targeted contrast agent had a high immune activity.
The novel contrast agent Gd-DTPA-Granzyme B mAb prepared in this study keeps a good immune activity and has no significant cytotoxicity.
Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences 05/2010; 39(3):290-5.
ABSTRACT: Acute allograft rejection is one of the important complications after renal transplantation, and it is a deleterious factor for long-term graft survival. Rejection is a complex pathophysiologic process, which has been explained by transcriptome and proteome in RNA transcripts and proteins level respectively. How are serum metabolite levels in response to acute rejection? Can metabolite levels in serum be used to diagnose and explain acute renal allograft rejection?
Gas chromatograph-mass spectrometry (GC-MS) was used to analyze serum metabolome in 22 recipients of acute rejection and 15 stable renal transplant recipients.
46 endogenous metabolites included amino acid, fatty acid, carbohydrate and other intermediate metabolites were identified in 37 recipients. Principal component analysis based on these metabolites discriminated acute rejection group from stable recipients. Among these metabolites, the levels of 17 metabolites were significant higher in rejection group than those in stable group. These included amino acid (phenylalanine, serine, glycine, threonine, valine), carbohydrate (galactose oxime, glycose, fructose), carboxylic acid, lipids and other metabolite such as lactate, urea and myo-inositol. The levels of 5 metabolites of alanine, lysine, leucine, aminomalonic acid and tetradecanoic acid were low in rejection group compared to stable group. The prediction accuracy of acute rejection was 77.3% and stable function was 100% by supervised clustering based on these 22 metabolites.
This study demonstrated that metabolic profile was changed in response to rejection process and renal function can be reflected by serum metabolite levels. This study showed potential capability to diagnose acute rejection by metabolome analysis.
Transplant Immunology 05/2008; 19(1):74-80. · 1.46 Impact Factor