Dataset Information

Identification of Candidate Genes Involved in Renal Ischemia/Reperfusion Injury.

ABSTRACT: Renal ischemia/reperfusion injury (IRI) is a main risk factor for the occurrence of delayed graft function or primary graft nonfunction of kidney transplantation. However, it lacks ideal molecular markers for indicating IRI in kidney transplantation. The present study is to explore novel candidate genes involved in renal IRI. Experimental renal IRI mouse models were constructed, and the differentially expressed genes were screened using a microarray assay. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed. The expression of genes was detected using real-time qPCR assay. Western blotting and immunohistochemistry staining assays were performed for protein determination. We identified that renal IRI induced the upregulation of SPRR2F, SPRR1A, MMP-10, and long noncoding RNA (lncRNA) Malat1 in kidney tissues for 479.3-, 4.98-, 238.1-, and 3.79-fold, respectively. The expression of miR-139-5p in kidney tissues of IRI-treated mice was decreased to 40.4% compared with the sham-operated mice. These genes are associated with keratinocyte differentiation, regeneration and repair of kidney tissues, extracellular matrix degradation and remodeling, inflammation, and cell proliferation in renal IRI. Identification of novel biomarkers involved in renal IRI may provide evidences for the diagnosis and treatment of renal IRI.

SUBMITTER: Su M

PROVIDER: S-EPMC6434600 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Identification of Candidate Genes Involved in Renal Ischemia/Reperfusion Injury.

Su Ming M Hu Xinyi X Lin Jun J Zhang Lei L Sun Wen W Zhang Jian J Tian Ye Y Qiu Wei W

DNA and cell biology 20190122 3

Renal ischemia/reperfusion injury (IRI) is a main risk factor for the occurrence of delayed graft function or primary graft nonfunction of kidney transplantation. However, it lacks ideal molecular markers for indicating IRI in kidney transplantation. The present study is to explore novel candidate genes involved in renal IRI. Experimental renal IRI mouse models were constructed, and the differentially expressed genes were screened using a microarray assay. Gene Ontology and Kyoto Encyclopedia of ...[more]

PMID: 30668132

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Project description:BackgroundOxidative stress is the primary cause of ischemia-reperfusion injury (IRI) in kidney transplantation, leading to delayed graft function (DGF) and implications on patient health. Necroptosis is believed to play a role in renal IRI. This research presents a comprehensive analysis of necroptosis-related genes and their functional implications in the context of IRI in renal transplantation.MethodsThe necroptosis-related differentially expressed genes (NR-DEGs) were identified using gene expression data from pre- and post-reperfusion renal biopsies, and consensus clustering analysis was performed to distinguish necroptosis-related clusters. A predictive model for DGF was developed based on the NR-DEGs and patients were divided into high- and low-risk groups. We investigated the differences in functional enrichment and immune infiltration between different clusters and risk groups and further validated them in single-cell RNA-sequencing (scRNA-seq) data. Finally, we verified the expression changes of NR-DEGs in an IRI mouse model.ResultsFive NR-DEGs were identified and were involved in various biological processes. The renal samples were further stratified into two necroptosis-related clusters (C1 and C2) showing different occurrences of DGF. The predictive model had a reliable performance in identifying patients at higher risk of DGF with the area under the curve as 0.798. Additionally, immune infiltration analysis indicated more abundant proinflammatory cells in the high-risk group, which was also found in C2 cluster with more DGF patients. Validation of NR-DEG in scRNA-seq data further supported their involvement in immune cells. Lastly, the mouse model validated the up-regulation of NR-DEGs after IR and indicated the correlations with kidney function markers.ConclusionsOur research provides valuable insights into the identification and functional characterization of NR-DEGs in the context of renal transplantation and sheds light on their involvement in immune responses and the progression of IRI and DGF.

Project description:BACKGROUND: Accumulated to-date microarray data on ischemia reperfusion injury (IRI) of kidney represent a powerful source for identifying new targets and mechanisms of kidney IRI. In this study, we conducted a meta-analysis of gene expression profiles of kidney IRI in human, pig, rat, and mouse models, using a new scoring method to correct for the bias of overrepresented species. The gene expression profiles were obtained from the public repositories for 24 different models. After filtering against inclusion criteria 21 experimental settings were selected for meta-analysis and were represented by 11 rat models, 6 mouse models, and 2 models each for pig and human, with a total of 150 samples. Meta-analysis was conducted using expression-based genome-wide association study (eGWAS). The eGWAS results were corrected for a rodent species bias using a new weighted scoring algorithm, which favors genes with unidirectional change in expression in all tested species. RESULTS: Our meta-analysis corrected for a species bias, identified 46 upregulated and 1 downregulated genes, of which 26 (55%) were known to be associated with kidney IRI or kidney transplantation, including LCN2, CCL2, CXCL1, HMOX1, ICAM1, ANXA1, and TIMP1, which justified our approach. Pathway analysis of our candidates identified "Acute renal failure panel" as the most implicated pathway, which further validates our new method. Among new IRI candidates were 10 novel (<5 published reports related to kidney IRI) and 11 new candidates (0 reports related to kidney IRI) including the most prominent candidates ANXA2, CLDN4, and TYROBP. The cross-species expression pattern of these genes allowed us to generate three workable hypotheses of kidney IRI, one of which was confirmed by an additional study. CONCLUSIONS: Our first in the field kidney IRI meta-analysis of 150 microarray samples, corrected for a species bias, identified 10 novel and 11 new candidate genes. Moreover, our new meta-analysis correction method improved gene candidate selection by identifying genes that are model and species independent, as a result, function of these genes can be directly extrapolated to the disease state in human and facilitate translation of potential diagnostic or therapeutic properties of these candidates to the bedside.

Project description:BackgroundRenal ischemia-reperfusion injury (IRI) is a disease with high incidence rate in kidney related surgery. Micro RNA (miRNA) and transcription factors (TFs) are widely involved in the process of renal IRI through regulation of their target genes. However, the regulatory relationships and functional roles of TFs, miRNAs and mRNAs in the progression of renal IRI are insufficiently understood. The present study aimed to clarify the underlying mechanism of regulatory relationships in renal IRI.MethodsSix gene expression profiles were downloaded from Gene Expression Omnibus (GEO). Differently expressed genes (DEGs) and differently expressed miRNAs (DEMs) were identified through RRA integrated analysis of mRNA datasets (GSE39548, GSE87025, GSE52004, GSE71647, and GSE131288) and miRNA datasets (GSE29495). miRDB and TransmiR v2.0 database were applied to predict target genes of miRNA and TFs, respectively. DEGs were applied for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, followed with construction of protein-protein interaction (PPI) network. Then, the TF-miRNA-mRNA network was constructed. Correlation coefficient and ROC analysis were used to verify regulatory relationship between genes and their diagnostic value in GSE52004. Furthermore, in independent mouse RNA-seq datasets GSE98622, human RNA-seq GSE134386 and in vitro, the expression of hub genes and genes from the network were observed and correlation coefficient and ROC analysis were validated.ResultsA total of 21 DEMs and 187 DEGs were identified in renal IRI group compared to control group. The results of PPI analysis showed 15 hub genes. The TF-miRNA-mRNA regulatory network was constructed and several important pathways were identified and further verified, including Junb-miR-223-Ranbp3l, Cebpb-miR-223-Ranbp3l, Cebpb-miR-21-Ranbp3l and Cebpb-miR-181b-Bsnd. Four regulatory loops were identified, including Fosl2-miR-155, Fosl2-miR-146a, Cebpb-miR-155 and Mafk-miR-25. The hub genes and genes in the network showed good diagnostic value in mice and human.ConclusionsIn this study, we found 15 hub genes and several TF-miRNA-mRNA pathways, which are helpful for understanding the molecular and regulatory mechanisms in renal IRI. Junb-miR-223-Ranbp3l, Cebpb-miR-223-Ranbp3l, Cebpb-miR-21-Ranbp3l and Cebpb-miR-181b-Bsnd were the most important pathways, while Spp1, Fos, Timp1, Tnc, Fosl2 and Junb were the most important hub genes. Fosl2-miR-155, Fosl2-miR-146a, Cebpb-miR-155 and Mafk-miR-25 might be the negative feedback loops in renal IRI.

Project description:BackgroundIschemia-reperfusion injury (IRI) remains an inevitable and major challenge in renal transplantation. The current study aims to obtain deep insights into underlying mechanisms and seek prognostic genes as potential therapeutic targets for renal IRI (RIRI).MethodsAfter systematically screening the Gene Expression Omnibus (GEO) database, we collected gene expression profiles of over 1,000 specimens from 11 independent cohorts. Differentially expressed genes (DEGs) were identified by comparing allograft kidney biopsies taken before and after reperfusion in the discovery cohort and further validated in another two independent transplant cohorts. Then, graft survival analysis and immune cell analysis of DEGs were performed in another independent renal transplant cohort with long-term follow-ups to further screen out prognostic genes. Cell type and time course analyses were performed for investigating the expression pattern of prognostic genes in more dimensions utilizing a mouse RIRI model. Finally, two novel genes firstly identified in RIRI were verified in the mouse model and comprehensively analyzed to investigate potential mechanisms.ResultsTwenty DEGs upregulated in the process of RIRI throughout different donor types (living donors, cardiac and brain death donors) were successfully identified and validated. Among them, upregulation of 10 genes was associated with poor long-term allograft outcomes and exhibited strong correlations with prognostic immune cells, like macrophages. Furthermore, certain genes were found to be only differentially expressed in specific cell types and remained with high expression levels even months after RIRI in the mouse model, which processed the potential to serve as therapeutic targets. Importantly, two newly identified genes in RIRI, Btg2 and Rhob, were successfully confirmed in the mouse model and found to have strong connections with NF-κB signaling.ConclusionsWe successfully identified and validated 10 IRI-associated prognostic genes in renal transplantation across different donor types, and two novel genes with crucial roles in RIRI were recognized for the first time. Our findings offered promising potential therapeutic targets for RIRI in renal transplantation.

Dataset Information

Identification of Candidate Genes Involved in Renal Ischemia/Reperfusion Injury.

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Identification of Candidate Genes Involved in Renal Ischemia/Reperfusion Injury.

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