Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation
Abstract Background Kidney transplantation is the most effective treatment for end-stage renal disease. Allograft rejections severely affect survivals of allograft kidneys and recipients. Methods Using bioinformatics approaches, the present study was designed to investigate immune status in renal tr...
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doaj-1310d08f571e449886805d699114a68d2021-04-02T19:08:30ZengBMCBMC Medical Genomics1755-87942020-02-0113111110.1186/s12920-020-0673-6Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantationMei Meng0Weitao Zhang1Qunye Tang2Baixue Yu3Tingting Li4Ruiming Rong5Tongyu Zhu6Ming Xu7Yi Shi8Shanghai Key Laboratory of Organ TransplantationShanghai Key Laboratory of Organ TransplantationShanghai Key Laboratory of Organ TransplantationShanghai Key Laboratory of Organ TransplantationShanghai Key Laboratory of Organ TransplantationShanghai Key Laboratory of Organ TransplantationShanghai Key Laboratory of Organ TransplantationShanghai Key Laboratory of Organ TransplantationShanghai Key Laboratory of Organ TransplantationAbstract Background Kidney transplantation is the most effective treatment for end-stage renal disease. Allograft rejections severely affect survivals of allograft kidneys and recipients. Methods Using bioinformatics approaches, the present study was designed to investigate immune status in renal transplant recipients. Fifteen datasets from Gene Expression Omnibus (GEO) were collected and analysed. Analysis of gene enrichment and protein-protein interactions were also used. Results There were 40 differentially expressed genes (DEGs) identified in chronic rejection group when compared with stable recipients, which were enriched in allograft rejection module. There were 135 DEGs identified in acute rejection patients, compared with stable recipients, in which most genes were enriched in allograft rejection and immune deficiency. There were 288 DEGs identified in stable recipients when compared to healthy subjects. Most genes were related to chemokine signalling pathway. In integrated comparisons, expressions of MHC molecules and immunoglobulins were increased in both acute and chronic rejection; expressions of LILRB and MAP 4 K1 were increased in acute rejection patients, but not in stable recipients. There were no overlapping DEGs in blood samples of transplant recipients. Conclusion By performing bioinformatics analysis on the immune status of kidney transplant patients, the present study reports several DEGs in the renal biopsy of transplant recipients, which are requested to be validated in clinical practice.https://doi.org/10.1186/s12920-020-0673-6BioinformaticsKidney transplantationImmune regulation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mei Meng Weitao Zhang Qunye Tang Baixue Yu Tingting Li Ruiming Rong Tongyu Zhu Ming Xu Yi Shi |
spellingShingle |
Mei Meng Weitao Zhang Qunye Tang Baixue Yu Tingting Li Ruiming Rong Tongyu Zhu Ming Xu Yi Shi Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation BMC Medical Genomics Bioinformatics Kidney transplantation Immune regulation |
author_facet |
Mei Meng Weitao Zhang Qunye Tang Baixue Yu Tingting Li Ruiming Rong Tongyu Zhu Ming Xu Yi Shi |
author_sort |
Mei Meng |
title |
Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation |
title_short |
Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation |
title_full |
Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation |
title_fullStr |
Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation |
title_full_unstemmed |
Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation |
title_sort |
bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation |
publisher |
BMC |
series |
BMC Medical Genomics |
issn |
1755-8794 |
publishDate |
2020-02-01 |
description |
Abstract Background Kidney transplantation is the most effective treatment for end-stage renal disease. Allograft rejections severely affect survivals of allograft kidneys and recipients. Methods Using bioinformatics approaches, the present study was designed to investigate immune status in renal transplant recipients. Fifteen datasets from Gene Expression Omnibus (GEO) were collected and analysed. Analysis of gene enrichment and protein-protein interactions were also used. Results There were 40 differentially expressed genes (DEGs) identified in chronic rejection group when compared with stable recipients, which were enriched in allograft rejection module. There were 135 DEGs identified in acute rejection patients, compared with stable recipients, in which most genes were enriched in allograft rejection and immune deficiency. There were 288 DEGs identified in stable recipients when compared to healthy subjects. Most genes were related to chemokine signalling pathway. In integrated comparisons, expressions of MHC molecules and immunoglobulins were increased in both acute and chronic rejection; expressions of LILRB and MAP 4 K1 were increased in acute rejection patients, but not in stable recipients. There were no overlapping DEGs in blood samples of transplant recipients. Conclusion By performing bioinformatics analysis on the immune status of kidney transplant patients, the present study reports several DEGs in the renal biopsy of transplant recipients, which are requested to be validated in clinical practice. |
topic |
Bioinformatics Kidney transplantation Immune regulation |
url |
https://doi.org/10.1186/s12920-020-0673-6 |
work_keys_str_mv |
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