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Research article
Wanxin Tang
Sichuan University West China Hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0001-6709-5591
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. In the present study, we used CIBERSORT and gene set enrichment analysis (GSEA) of gene expression profiles to identify immune cell infiltration characteristics and related core genes in LN. Results Datasets from the Gene Expression Omnibus, GSE32591 and GSE113342, were downloaded for further analysis. The GSE32591 dataset, which included 32 LN glomerular biopsy tissues and 14 glomerular tissues from living donors, was analyzed by CIBERSORT. Different immune cell types in LN were analyzed by the Limma software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis based on GSEA were performed by clusterProfiler software. Lists of core genes were derived from Spearman correlation between the most significant GO term and differentially expressed immune cell gene from CIBERSORT. GSE113342 was employed to validate the association between selected core genes and clinical manifestation. Five types of immune cells revealed important associations with LN, and monocytes emerged as having the most prominent differences. GO and KEGG analyses indicated that immune response pathways are significantly enriched in LN. The Spearman correlation indicated that 15 genes, including FCER1G, CLEC7A, MARCO, CLEC7A, PSMB9, and PSMB8 , were closely related to clinical features. Conclusions This study is the first to identify immune cell infiltration with microarray data of glomeruli in LN by using CIBERSORT analysis and provides novel evidence and clues for further research of the molecular mechanisms of LN.
Keywords
Systemic lupus erythematosus, Lupus nephritis, CIBERSORT, GSEA, Immune infiltration
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CURRENT STATUS: Published
View the published article at BMC Immunology.
No community comments so far
Submission checks complete
On 06 Nov, 2019
Editorial decision: Accept
On 11 Sep, 2019
Version 2
Posted 24 Sep, 2019
No comments provided
Editorial decision: Minor revision
On 05 Sep, 2019
Reviewer #2 agreed
On 27 Aug, 2019
Review #2 received
Received 27 Aug, 2019
Reviewers invited
Invitations sent on 26 Aug, 2019
Reviewer #1 agreed
On 26 Aug, 2019
Review #1 received
Received 26 Aug, 2019
Editor assigned
On 25 Aug, 2019
Submission checks complete
On 24 Aug, 2019
Editor invited
On 24 Aug, 2019
No comments provided
Editorial decision: Minor revision
On 17 Aug, 2019
Review #1 received
Received 14 Aug, 2019
Review #2 received
Received 14 Aug, 2019
Reviewers invited
Invitations sent on 02 Aug, 2019
Reviewer #1 agreed
On 02 Aug, 2019
Reviewer #2 agreed
On 02 Aug, 2019
Submission checks complete
On 26 Jul, 2019
Editor assigned
On 19 Jul, 2019
Editor invited
On 18 Jul, 2019
First submitted
On 17 Jul, 2019
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A new preprint design is coming!
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See the published version of this preprint at BMC Immunology.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Wanxin Tang
Sichuan University West China Hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0001-6709-5591
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Immunology.
No community comments so far
Submission checks complete
On 06 Nov, 2019
Editorial decision: Accept
On 11 Sep, 2019
Version 2
Posted 24 Sep, 2019
No comments provided
Editorial decision: Minor revision
On 05 Sep, 2019
Reviewer #2 agreed
On 27 Aug, 2019
Review #2 received
Received 27 Aug, 2019
Reviewers invited
Invitations sent on 26 Aug, 2019
Reviewer #1 agreed
On 26 Aug, 2019
Review #1 received
Received 26 Aug, 2019
Editor assigned
On 25 Aug, 2019
Submission checks complete
On 24 Aug, 2019
Editor invited
On 24 Aug, 2019
No comments provided
Editorial decision: Minor revision
On 17 Aug, 2019
Review #1 received
Received 14 Aug, 2019
Review #2 received
Received 14 Aug, 2019
Reviewers invited
Invitations sent on 02 Aug, 2019
Reviewer #1 agreed
On 02 Aug, 2019
Reviewer #2 agreed
On 02 Aug, 2019
Submission checks complete
On 26 Jul, 2019
Editor assigned
On 19 Jul, 2019
Editor invited
On 18 Jul, 2019
First submitted
On 17 Jul, 2019
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Immunology.
Background Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. In the present study, we used CIBERSORT and gene set enrichment analysis (GSEA) of gene expression profiles to identify immune cell infiltration characteristics and related core genes in LN. Results Datasets from the Gene Expression Omnibus, GSE32591 and GSE113342, were downloaded for further analysis. The GSE32591 dataset, which included 32 LN glomerular biopsy tissues and 14 glomerular tissues from living donors, was analyzed by CIBERSORT. Different immune cell types in LN were analyzed by the Limma software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis based on GSEA were performed by clusterProfiler software. Lists of core genes were derived from Spearman correlation between the most significant GO term and differentially expressed immune cell gene from CIBERSORT. GSE113342 was employed to validate the association between selected core genes and clinical manifestation. Five types of immune cells revealed important associations with LN, and monocytes emerged as having the most prominent differences. GO and KEGG analyses indicated that immune response pathways are significantly enriched in LN. The Spearman correlation indicated that 15 genes, including FCER1G, CLEC7A, MARCO, CLEC7A, PSMB9, and PSMB8 , were closely related to clinical features. Conclusions This study is the first to identify immune cell infiltration with microarray data of glomeruli in LN by using CIBERSORT analysis and provides novel evidence and clues for further research of the molecular mechanisms of LN.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
This is a list of supplementary files associated with this preprint. Click to download.
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