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pmid:35559414

Screening of key genes associated with m6A methylation in diabetic nephropathy patients by CIBERSORT and weighted gene coexpression network analysis.

Shaohua Yin · Wen Li · Junjie Wang · Han Wu · Ji Hu · Yu Feng

American journal of translational research · 2022

Paper

partial

Experiment

complete

Data

partial

Analysis

partial

Execution

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Screening of key genes associated with m6A methylation in diabetic nephropathy patients by CIBERSORT and weighted gene coexpression network analysis.
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Shaohua Yin
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Wen Li
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Junjie Wang
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Han Wu
[4]
Ji Hu
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Yu Feng
journal
American journal of translational research
year
2022
abstract
Diabetic nephropathy (DN) is a common complication of diabetes. Due to its complex pathogenesis, there is no effective treatment. M6A is a newly discovered epigenetic mechanism that may be involved in the development of diabetic nephropathy. In this study, we analyzed differentially expressed genes (DEG) in the GEO database (GSE96804) and paid attention to genes with m6A methylation. 623 DEGs in glomerular tissue were identified by comparing diabetic nephropathy with normal. Correlation analysis with 21 genes involved in m6A modification showed that 492 genes were associated with m6A methylation. According to the CIBERSORT algorithm, the infiltration of M1 macrophages in DN patients was significantly higher than that in normal samples. Weighted gene coexpression network analysis (WGCNA) was used to screen for the modules most correlated with the clinical features of M1 macrophages. The genes in the selected modules and 492 m6A-related DEGs were intersected by a Venn diagram, and 43 key genes were obtained. GO and KEGG analyses showed that these genes were mainly related to the positive regulation of protein aggregation and the transforming growth factor β receptor signaling pathway. According to a literature review, among the top 10 genes, HSPA1A, HSPA1B, CHI3L1, TYRO3 and PTH1R are markers in diabetic nephropathy, and their abnormal expression is associated with renal hypertrophy, proteinuria and glomerulosclerosis. These findings may provide evidence for the diagnosis and treatment of diabetic nephropathy.
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According to the CIBERSORT algorithm, the infiltration of M1 macrophages in DN patients was significantly higher than that in normal samples. Weighted gene coexpression network analysis (WGCNA) was used to screen for the modules most correlated with the clinical features of M1 macrophages.
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In this study, we analyzed differentially expressed genes (DEG) in the GEO database (GSE96804) and paid attention to genes with m6A methylation. 623 DEGs in glomerular tissue were identified by comparing diabetic nephropathy with normal.
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623 DEGs in glomerular tissue were identified by comparing diabetic nephropathy with normal.
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Correlation analysis with 21 genes involved in m6A modification showed that 492 genes were associated with m6A methylation.
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