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pmid:35592524

Integrated Analysis of Multiple Microarray Studies to Identify Core Gene-Expression Signatures Involved in Tubulointerstitial Injury in Diabetic Nephropathy.

Huandi Zhou · Zhifen Yang · Lin Mu · Yonghong Shi

BioMed research international · 2022 doi:10.1155/2022/9554658

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title
Integrated Analysis of Multiple Microarray Studies to Identify Core Gene-Expression Signatures Involved in Tubulointerstitial Injury in Diabetic Nephropathy.
doi
10.1155/2022/9554658
pmid
35592524
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Huandi Zhou
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Zhifen Yang
[2]
Lin Mu
[3]
Yonghong Shi
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BioMed research international
year
2022
abstract
Diabetic nephropathy is a leading cause of end-stage renal disease in both developed and developing countries. It is lack of specific diagnosis, and the pathogenesis remains unclarified in diabetic nephropathy, following the unsatisfactory effects of existing treatments. Therefore, it is very meaningful to find biomarkers with high specificity and potential targets. Two datasets, GSE30529 and GSE47184 from GEO based on diabetic nephropathy tubular samples, were downloaded and merged after batch effect removal. A total of 545 different expression genes screened with log2FC > 0.5 were weighted gene coexpression correlation network analysis, and green module and blue module were identified. The results of KEGG analyses both in green module and GSEA analysis showed the same two enriched pathway, focal adhesion and viral myocarditis. Based on the intersection among WGCNA focal adhesion/Viral myocarditis, GSEA focal adhesion/viral myocarditis, and PPI network, 17 core genes, ACTN1, CAV1, PRKCB, PDGFRA, COL1A2, COL6A3, RHOA, VWF, FN1, HLA-F, HLA-DPB1, ITGB2, HLA-DRA, HLA-DMA, HLA-DPA1, HLA-B, and HLA-DMB, were identified as potential biomarkers in diabetic tubulointerstitial injury and were further validated externally for expression at GSE99325 and GSE104954 and clinical feature at nephroseq V5 online platform. CMap analysis suggested that two compounds, LY-294002 and bufexamac, may be new insights for therapeutics of diabetic tubulointerstitial injury. Conclusively, it was raised that a series of core genes may be as potential biomarkers for diagnosis and two prospective compounds.
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After batch normalization, 545 DEGs were filtered out by the limma R package (adjusted P < 0.05 and |log2FC| > 0.5), in which 375 genes were upregulated, and 170 were downregulated (Figure 2(e)).
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sections[13] "3.1. Identification of DEGs Specifically Involved in Tubulointerstitial Injury in DN" paragraph 4
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After batch normalization, 545 DEGs were filtered out by the limma R package (adjusted P < 0.05 and |log2FC| > 0.5), in which 375 genes were upregulated, and 170 were downregulated (Figure 2(e)).
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The datasets generated during and/or analyzed during the current study are presented in the main file. Additional data are available from the corresponding author on reasonable request.
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After batch normalization, 545 DEGs were filtered out by the limma R package (adjusted P < 0.05 and |log2FC| > 0.5), in which 375 genes were upregulated, and 170 were downregulated (Figure 2(e)).
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sections[13] "3.1. Identification of DEGs Specifically Involved in Tubulointerstitial Injury in DN" paragraph 4
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After batch normalization, 545 DEGs were filtered out by the limma R package (adjusted P < 0.05 and |log2FC| > 0.5), in which 375 genes were upregulated, and 170 were downregulated (Figure 2(e)).
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A total of 545 different expression genes screened with log2FC > 0.5 were weighted gene coexpression correlation network analysis, and green module and blue module were identified.
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sample_count
175
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null
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null
platform
19109;19184
taxon
Homo sapiens
title
Transcriptome-based network analysis reveals renal cell type-specific dysregulation of hypoxia-associated transcripts [Tub-FE]
resolution_checked_at
2026-11-01T15:39:55Z
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identifier_resolution_only_no_download_no_licence_read
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[6]
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After batch normalization, 545 DEGs were filtered out by the limma R package (adjusted P < 0.05 and |log2FC| > 0.5), in which 375 genes were upregulated, and 170 were downregulated (Figure 2(e)).
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Correlation analysis
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[0]
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evidence object · 3 fields
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evidence object · 3 fields
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claim-target-result
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The threshold the paper applied to its own result, as the paper states it. A run that reproduces the effect is judged against this threshold.
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complete
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Automated Assays Laravel application and simulated adapters
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The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom.
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tier
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availability_state
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
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reachable
true
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[0]
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[1]
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GSE30529
[1]
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[2]
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[3]
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[0]
The datasets generated during and/or analyzed during the current study are presented in the main file. Additional data are available from the corresponding author on reasonable request.
basis
The paper names GSE30529, GSE47184, GSE99325, GSE104954 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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minimax
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minimax
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single_reader
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verbatim
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verbatim
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5
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extraction
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source:pmid:35592524
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data:geo:GSE104954
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GEO GSE104954
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classification
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Integrated Analysis of Multiple Microarray Studies to Identify Core Gene-Expression Sig
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After batch normalization, 545 DEGs were filtered out by the limma R package (adjusted P < 0.05 and |log2FC| > 0.5), in which 375 genes were upregulated, and 170 were downregulated (Figure 2(e)).
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35592524", "kind": "science-record", "revision": 5, "content_hash": "sha256:94234c52397f34f1e43d4f31d0bb6fe16cc7c92eac2c2c2ab3395385e67a8e16", "created_at": "2026-11-01T18:14:29Z", "updated_at": "2026-11-01T22:49:05Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrated Analysis of Multiple Microarray Studies to Identify Core Gene-Expression Signatures Involved in Tubulointerstitial Injury in Diabetic Nephropathy.", "doi": "10.1155/2022/9554658", "pmid": "35592524", "authors": ["Huandi Zhou", "Zhifen Yang", "Lin Mu", "Yonghong Shi"], "journal": "BioMed research international", "year": 2022, "abstract": "Diabetic nephropathy is a leading cause of end-stage renal disease in both developed and developing countries. It is lack of specific diagnosis, and the pathogenesis remains unclarified in diabetic nephropathy, following the unsatisfactory effects of existing treatments. Therefore, it is very meaningful to find biomarkers with high specificity and potential targets. Two datasets, GSE30529 and GSE47184 from GEO based on diabetic nephropathy tubular samples, were downloaded and merged after batch effect removal. A total of 545 different expression genes screened with log2FC > 0.5 were weighted gene coexpression correlation network analysis, and green module and blue module were identified. The results of KEGG analyses both in green module and GSEA analysis showed the same two enriched pathway, focal adhesion and viral myocarditis. Based on the intersection among WGCNA focal adhesion/Viral myocarditis, GSEA focal adhesion/viral myocarditis, and PPI network, 17 core genes, ACTN1, CAV1, PRKCB, PDGFRA, COL1A2, COL6A3, RHOA, VWF, FN1, HLA-F, HLA-DPB1, ITGB2, HLA-DRA, HLA-DMA, HLA-DPA1, HLA-B, and HLA-DMB, were identified as potential biomarkers in diabetic tubulointerstitial injury and were further validated externally for expression at GSE99325 and GSE104954 and clinical feature at nephroseq V5 online platform. CMap analysis suggested that two compounds, LY-294002 and bufexamac, may be new insights for therapeutics of diabetic tubulointerstitial injury. 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