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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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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. |
format | Online Article Text |
id | pubmed-7014750 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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