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Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation

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 transplan...

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Autores principales: Meng, Mei, Zhang, Weitao, Tang, Qunye, Yu, Baixue, Li, Tingting, Rong, Ruiming, Zhu, Tongyu, Xu, Ming, Shi, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014750/
https://www.ncbi.nlm.nih.gov/pubmed/32046717
http://dx.doi.org/10.1186/s12920-020-0673-6
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author Meng, Mei
Zhang, Weitao
Tang, Qunye
Yu, Baixue
Li, Tingting
Rong, Ruiming
Zhu, Tongyu
Xu, Ming
Shi, Yi
author_facet Meng, Mei
Zhang, Weitao
Tang, Qunye
Yu, Baixue
Li, Tingting
Rong, Ruiming
Zhu, Tongyu
Xu, Ming
Shi, Yi
author_sort Meng, Mei
collection PubMed
description 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.
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spelling pubmed-70147502020-02-20 Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation Meng, Mei Zhang, Weitao Tang, Qunye Yu, Baixue Li, Tingting Rong, Ruiming Zhu, Tongyu Xu, Ming Shi, Yi BMC Med Genomics Research Article 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. BioMed Central 2020-02-11 /pmc/articles/PMC7014750/ /pubmed/32046717 http://dx.doi.org/10.1186/s12920-020-0673-6 Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Meng, Mei
Zhang, Weitao
Tang, Qunye
Yu, Baixue
Li, Tingting
Rong, Ruiming
Zhu, Tongyu
Xu, Ming
Shi, Yi
Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation
title 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_short 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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014750/
https://www.ncbi.nlm.nih.gov/pubmed/32046717
http://dx.doi.org/10.1186/s12920-020-0673-6
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