ArticleBMC medical genomics2020
Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation.
Article in BMC medical genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Article
- Multiplexed droplet single-cell sequencing (Mux-Seq) of normal and transplant kidney.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2022Article
- Noxa and Puma genes regulated by hTERT promoter can mitigate growth and induce apoptosis in hepatocellular carcinoma mouse model.Journal of Cancer · 2022Article
- Screening and identification of key regulatory connections and immune cell infiltration characteristics for lung transplant rejection using mucosal biopsies.International immunopharmacology · 2020Article
- A Machine Learning Analysis of Prognostic Genes Associated With Allograft Tolerance After Renal Transplantation.Cell transplantationArticle
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundKidney transplantation is the most effective treatment for end-stage renal disease. Allograft rejections severely affect survivals of allograft kidneys and recipients.
methodsUsing 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.
resultsThere 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.
conclusionBy 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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