The unique molecular mechanism of diabetic nephropathy: a bioinformatics analysis of over 250 microarray datasets Article Swipe
Le‐Ting Zhou
,
Zhijian Zhang
,
Jing-Yuan Cao
,
Hanzhi Chen
,
Yushan Zhu
,
Xi Wu
,
Abdul Qadir Nawabi
,
Xiaobin Liu
,
Weiwei Shan
,
Yue Zhang
,
Xiran Zhang
,
Jing Xue
,
Ling Hu
,
Sisi Wang
,
Liang Wang
,
Zhuxing Sun
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1093/ckj/sfaa190
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1093/ckj/sfaa190
Background/Aims Diabetic nephropathy (DN) is one of the main causes of end-stage kidney disease worldwide. Emerging studies have suggested that its pathogenesis is distinct from nondiabetic renal diseases in many aspects. However, it still lacks a comprehensive understanding of the unique molecular mechanism of DN. Methods A total of 255 Affymetrix U133 microarray datasets (Affymetrix, Santa Calra, CA, USA) of human glomerular and tubulointerstitial tissues were collected. The 22 215 Affymetrix identifiers shared by the Human Genome U133 Plus 2.0 and U133A Array were extracted to facilitate dataset pooling. Next, a linear model was constructed and the empirical Bayes method was used to select the differentially expressed genes (DEGs) of each kidney disease. Based on these DEG sets, the unique DEGs of DN were identified and further analyzed using gene ontology and pathway enrichment analysis. Finally, the protein–protein interaction networks (PINs) were constructed and hub genes were selected to further refine the results. Results A total of 129 and 1251 unique DEGs were identified in the diabetic glomerulus (upregulated n = 83 and downregulated n = 203) and the diabetic tubulointerstitium (upregulated n = 399 and downregulated n = 874), respectively. Enrichment analysis revealed that the DEGs in the diabetic glomerulus were significantly associated with the extracellular matrix, cell growth, regulation of blood coagulation, cholesterol homeostasis, intrinsic apoptotic signaling pathway and renal filtration cell differentiation. In the diabetic tubulointerstitium, the significantly enriched biological processes and pathways included metabolism, the advanced glycation end products–receptor for advanced glycation end products signaling pathway in diabetic complications, the epidermal growth factor receptor (EGFR) signaling pathway, the FoxO signaling pathway, autophagy and ferroptosis. By constructing PINs, several nodes, such as AGR2, CSNK2A1, EGFR and HSPD1, were identified as hub genes, which might play key roles in regulating the development of DN. Conclusions Our study not only reveals the unique molecular mechanism of DN but also provides a valuable resource for biomarker and therapeutic target discovery. Some of our findings are promising and should be explored in future work.
Related Topics
Concepts
Diabetic nephropathy
Microarray
Microarray analysis techniques
Biology
Computational biology
Downregulation and upregulation
Glycation
Bioinformatics
Gene expression profiling
Diabetes mellitus
Gene
Gene expression
Genetics
Endocrinology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/ckj/sfaa190
- https://academic.oup.com/ckj/article-pdf/14/6/1626/38375675/sfaa190.pdf
- OA Status
- gold
- Cited By
- 47
- References
- 28
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3139367066
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3139367066Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/ckj/sfaa190Digital Object Identifier
- Title
-
The unique molecular mechanism of diabetic nephropathy: a bioinformatics analysis of over 250 microarray datasetsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2020Year of publication
- Publication date
-
2020-08-29Full publication date if available
- Authors
-
Le‐Ting Zhou, Zhijian Zhang, Jing-Yuan Cao, Hanzhi Chen, Yushan Zhu, Xi Wu, Abdul Qadir Nawabi, Xiaobin Liu, Weiwei Shan, Yue Zhang, Xiran Zhang, Jing Xue, Ling Hu, Sisi Wang, Liang Wang, Zhuxing SunList of authors in order
- Landing page
-
https://doi.org/10.1093/ckj/sfaa190Publisher landing page
- PDF URL
-
https://academic.oup.com/ckj/article-pdf/14/6/1626/38375675/sfaa190.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://academic.oup.com/ckj/article-pdf/14/6/1626/38375675/sfaa190.pdfDirect OA link when available
- Concepts
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Diabetic nephropathy, Microarray, Microarray analysis techniques, Biology, Computational biology, Downregulation and upregulation, Glycation, Bioinformatics, Gene expression profiling, Diabetes mellitus, Gene, Gene expression, Genetics, EndocrinologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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47Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4, 2024: 32, 2023: 5, 2022: 5, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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28Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| publication_date | 2020-08-29 |
| publication_year | 2020 |
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