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Network-based identification and prioritization of key transcriptional factors of diabetic kidney disease

Diabetic nephropathy (DN) is one of the most established microvascular complications of diabetes and a key cause of end-stage renal disease. It is well established that gene susceptibility to DN plays a critical role in disease pathophysiology. Therefore, many genetic studies have been performed to...

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Autores principales: Ahmed, Ikhlak, Ziab, Mubarak, Da’as, Sahar, Hasan, Waseem, Jeya, Sujitha P., Aliyev, Elbay, Nisar, Sabah, Bhat, Ajaz A., Fakhro, Khalid Adnan, Alshabeeb Akil, Ammira S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2023
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9827363/
https://www.ncbi.nlm.nih.gov/pubmed/36659918
http://dx.doi.org/10.1016/j.csbj.2022.12.054
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author Ahmed, Ikhlak
Ziab, Mubarak
Da’as, Sahar
Hasan, Waseem
Jeya, Sujitha P.
Aliyev, Elbay
Nisar, Sabah
Bhat, Ajaz A.
Fakhro, Khalid Adnan
Alshabeeb Akil, Ammira S.
author_facet Ahmed, Ikhlak
Ziab, Mubarak
Da’as, Sahar
Hasan, Waseem
Jeya, Sujitha P.
Aliyev, Elbay
Nisar, Sabah
Bhat, Ajaz A.
Fakhro, Khalid Adnan
Alshabeeb Akil, Ammira S.
author_sort Ahmed, Ikhlak
collection PubMed
description Diabetic nephropathy (DN) is one of the most established microvascular complications of diabetes and a key cause of end-stage renal disease. It is well established that gene susceptibility to DN plays a critical role in disease pathophysiology. Therefore, many genetic studies have been performed to categorize candidate genes in prominent diabetic cohorts, aiming to investigate DN pathogenesis and etiology. In this study, we performed a meta-analysis on the expression profiles of GSE1009, GSE30122, GSE96804, GSE99340, GSE104948, GSE104954, and GSE111154 to identify critical transcriptional factors associated with DN progression. The analysis was conducted for all individual datasets for each kidney tissue (glomerulus, tubules, and kidney cortex). We identified distinct clusters of susceptibility genes that were dysregulated in a renal compartment-specific pattern. Further, we recognized a small but a closely connected set of these susceptibility genes enriched for podocyte differentiation, several of which were characterized as genes encoding critical transcriptional factors (TFs) involved in DN development and podocyte function. To validate the role of identified TFs in DN progression, we functionally validated the three main TFs (DACH1, LMX1B, and WT1) identified through differential gene expression and network analysis using the hyperglycemic zebrafish model. We report that hyperglycemia-induced altered gene expression of the key TF genes leads to morphological abnormalities in zebrafish glomeruli, pronephric tubules, proximal and distal ducts. This study demonstrated that altered expression of these TF genes could be associated with hyperglycemia-induced nephropathy and, thus, aids in understanding the molecular drivers, essential genes, and pathways that trigger DN initiation and development.
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spelling pubmed-98273632023-01-18 Network-based identification and prioritization of key transcriptional factors of diabetic kidney disease Ahmed, Ikhlak Ziab, Mubarak Da’as, Sahar Hasan, Waseem Jeya, Sujitha P. Aliyev, Elbay Nisar, Sabah Bhat, Ajaz A. Fakhro, Khalid Adnan Alshabeeb Akil, Ammira S. Comput Struct Biotechnol J Research Article Diabetic nephropathy (DN) is one of the most established microvascular complications of diabetes and a key cause of end-stage renal disease. It is well established that gene susceptibility to DN plays a critical role in disease pathophysiology. Therefore, many genetic studies have been performed to categorize candidate genes in prominent diabetic cohorts, aiming to investigate DN pathogenesis and etiology. In this study, we performed a meta-analysis on the expression profiles of GSE1009, GSE30122, GSE96804, GSE99340, GSE104948, GSE104954, and GSE111154 to identify critical transcriptional factors associated with DN progression. The analysis was conducted for all individual datasets for each kidney tissue (glomerulus, tubules, and kidney cortex). We identified distinct clusters of susceptibility genes that were dysregulated in a renal compartment-specific pattern. Further, we recognized a small but a closely connected set of these susceptibility genes enriched for podocyte differentiation, several of which were characterized as genes encoding critical transcriptional factors (TFs) involved in DN development and podocyte function. To validate the role of identified TFs in DN progression, we functionally validated the three main TFs (DACH1, LMX1B, and WT1) identified through differential gene expression and network analysis using the hyperglycemic zebrafish model. We report that hyperglycemia-induced altered gene expression of the key TF genes leads to morphological abnormalities in zebrafish glomeruli, pronephric tubules, proximal and distal ducts. This study demonstrated that altered expression of these TF genes could be associated with hyperglycemia-induced nephropathy and, thus, aids in understanding the molecular drivers, essential genes, and pathways that trigger DN initiation and development. Research Network of Computational and Structural Biotechnology 2023-01-02 /pmc/articles/PMC9827363/ /pubmed/36659918 http://dx.doi.org/10.1016/j.csbj.2022.12.054 Text en © 2023 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Ahmed, Ikhlak
Ziab, Mubarak
Da’as, Sahar
Hasan, Waseem
Jeya, Sujitha P.
Aliyev, Elbay
Nisar, Sabah
Bhat, Ajaz A.
Fakhro, Khalid Adnan
Alshabeeb Akil, Ammira S.
Network-based identification and prioritization of key transcriptional factors of diabetic kidney disease
title Network-based identification and prioritization of key transcriptional factors of diabetic kidney disease
title_full Network-based identification and prioritization of key transcriptional factors of diabetic kidney disease
title_fullStr Network-based identification and prioritization of key transcriptional factors of diabetic kidney disease
title_full_unstemmed Network-based identification and prioritization of key transcriptional factors of diabetic kidney disease
title_short Network-based identification and prioritization of key transcriptional factors of diabetic kidney disease
title_sort network-based identification and prioritization of key transcriptional factors of diabetic kidney disease
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9827363/
https://www.ncbi.nlm.nih.gov/pubmed/36659918
http://dx.doi.org/10.1016/j.csbj.2022.12.054
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