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Peripheral blood transcriptome sequencing reveals rejection-relevant genes in long-term heart transplantation.

Authors :
Chen, Yan
Zhang, Haibo
Xiao, Xue
Jia, Yixin
Wu, Weili
Liu, Licheng
Jiang, Jun
Zhu, Baoli
Meng, Xu
Chen, Weijun
Source :
International Journal of Cardiology. Oct2013, Vol. 168 Issue 3, p2726-2733. 8p.
Publication Year :
2013

Abstract

Abstract: Background: Peripheral blood-based gene expression patterns have been investigated as biomarkers to monitor the immune system and rule out rejection after heart transplantation. Recent advances in the high-throughput deep sequencing (HTS) technologies provide new leads in transcriptome analysis. Methods: By performing Solexa/Illumina's digital gene expression (DGE) profiling, we analyzed gene expression profiles of PBMCs from 6 quiescent (grade 0) and 6 rejection (grade 2R&3R) heart transplant recipients at more than 6months after transplantation. Subsequently, quantitative real-time polymerase chain reaction (qRT-PCR) was carried out in an independent validation cohort of 47 individuals from three rejection groups (ISHLT, grade 0,1R, 2R&3R). Results: Through DGE sequencing and qPCR validation, 10 genes were identified as informative genes for detection of cardiac transplant rejection. A further clustering analysis showed that the 10 genes were not only effective for distinguishing patients with acute cardiac allograft rejection, but also informative for discriminating patients with renal allograft rejection based on both blood and biopsy samples. Moreover, PPI network analysis revealed that the 10 genes were connected to each other within a short interaction distance. Conclusions: We proposed a 10-gene signature for heart transplant patients at high-risk of developing severe rejection, which was found to be effective as well in other organ transplant. Moreover, we supposed that these genes function systematically as biomarkers in long-time allograft rejection. Further validation in broad transplant population would be required before the non-invasive biomarkers can be generally utilized to predict the risk of transplant rejection. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
01675273
Volume :
168
Issue :
3
Database :
Academic Search Index
Journal :
International Journal of Cardiology
Publication Type :
Academic Journal
Accession number :
90627907
Full Text :
https://doi.org/10.1016/j.ijcard.2013.03.095