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Mapping the dynamics of insulin-responsive pathways in the blood–brain barrier endothelium using time-series transcriptomics data
Critical functions of the blood–brain barrier (BBB), including cerebral blood flow, energy metabolism, and immunomodulation, are regulated by insulin signaling pathways. Therefore, endothelial insulin resistance could lead to BBB dysfunction, which is associated with neurodegenerative diseases such...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9381797/ https://www.ncbi.nlm.nih.gov/pubmed/35974022 http://dx.doi.org/10.1038/s41540-022-00235-8 |
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author | Wang, Zengtao Tang, Xiaojia Swaminathan, Suresh K. Kandimalla, Karunya K. Kalari, Krishna R. |
author_facet | Wang, Zengtao Tang, Xiaojia Swaminathan, Suresh K. Kandimalla, Karunya K. Kalari, Krishna R. |
author_sort | Wang, Zengtao |
collection | PubMed |
description | Critical functions of the blood–brain barrier (BBB), including cerebral blood flow, energy metabolism, and immunomodulation, are regulated by insulin signaling pathways. Therefore, endothelial insulin resistance could lead to BBB dysfunction, which is associated with neurodegenerative diseases such as Alzheimer’s disease (AD). The current study aims to map the dynamics of insulin-responsive pathways in polarized human cerebral microvascular endothelial cell (hCMEC/D3) monolayers. RNA-Sequencing was performed on hCMEC/D3 monolayers with and without insulin treatment at various time points. The Short Time-series Expression Miner (STEM) method was used to identify gene clusters with distinct and representative expression patterns. Functional annotation and pathway analysis of genes from selected clusters were conducted using Webgestalt and Ingenuity Pathway Analysis (IPA) software. Quantitative expression differences of 16,570 genes between insulin-treated and control monolayers were determined at five-time points. The STEM software identified 12 significant clusters with 6880 genes that displayed distinct temporal patterns upon insulin exposure, and the clusters were further divided into three groups. Gene ontology (GO) enrichment analysis demonstrated that biological processes protecting BBB functions such as regulation of vascular development and actin cytoskeleton reorganization were upregulated after insulin treatment (Group 1 and 2). In contrast, GO pathways related to inflammation, such as response to interferon-gamma, were downregulated (Group 3). The IPA analyses further identified insulin-responsive cellular and molecular pathways that are associated with AD pathology. These findings unravel the dynamics of insulin action on the BBB endothelium and inform about downstream signaling cascades that are potentially disrupted due to brain insulin resistance prevalent in AD. |
format | Online Article Text |
id | pubmed-9381797 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93817972022-08-18 Mapping the dynamics of insulin-responsive pathways in the blood–brain barrier endothelium using time-series transcriptomics data Wang, Zengtao Tang, Xiaojia Swaminathan, Suresh K. Kandimalla, Karunya K. Kalari, Krishna R. NPJ Syst Biol Appl Article Critical functions of the blood–brain barrier (BBB), including cerebral blood flow, energy metabolism, and immunomodulation, are regulated by insulin signaling pathways. Therefore, endothelial insulin resistance could lead to BBB dysfunction, which is associated with neurodegenerative diseases such as Alzheimer’s disease (AD). The current study aims to map the dynamics of insulin-responsive pathways in polarized human cerebral microvascular endothelial cell (hCMEC/D3) monolayers. RNA-Sequencing was performed on hCMEC/D3 monolayers with and without insulin treatment at various time points. The Short Time-series Expression Miner (STEM) method was used to identify gene clusters with distinct and representative expression patterns. Functional annotation and pathway analysis of genes from selected clusters were conducted using Webgestalt and Ingenuity Pathway Analysis (IPA) software. Quantitative expression differences of 16,570 genes between insulin-treated and control monolayers were determined at five-time points. The STEM software identified 12 significant clusters with 6880 genes that displayed distinct temporal patterns upon insulin exposure, and the clusters were further divided into three groups. Gene ontology (GO) enrichment analysis demonstrated that biological processes protecting BBB functions such as regulation of vascular development and actin cytoskeleton reorganization were upregulated after insulin treatment (Group 1 and 2). In contrast, GO pathways related to inflammation, such as response to interferon-gamma, were downregulated (Group 3). The IPA analyses further identified insulin-responsive cellular and molecular pathways that are associated with AD pathology. These findings unravel the dynamics of insulin action on the BBB endothelium and inform about downstream signaling cascades that are potentially disrupted due to brain insulin resistance prevalent in AD. Nature Publishing Group UK 2022-08-16 /pmc/articles/PMC9381797/ /pubmed/35974022 http://dx.doi.org/10.1038/s41540-022-00235-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wang, Zengtao Tang, Xiaojia Swaminathan, Suresh K. Kandimalla, Karunya K. Kalari, Krishna R. Mapping the dynamics of insulin-responsive pathways in the blood–brain barrier endothelium using time-series transcriptomics data |
title | Mapping the dynamics of insulin-responsive pathways in the blood–brain barrier endothelium using time-series transcriptomics data |
title_full | Mapping the dynamics of insulin-responsive pathways in the blood–brain barrier endothelium using time-series transcriptomics data |
title_fullStr | Mapping the dynamics of insulin-responsive pathways in the blood–brain barrier endothelium using time-series transcriptomics data |
title_full_unstemmed | Mapping the dynamics of insulin-responsive pathways in the blood–brain barrier endothelium using time-series transcriptomics data |
title_short | Mapping the dynamics of insulin-responsive pathways in the blood–brain barrier endothelium using time-series transcriptomics data |
title_sort | mapping the dynamics of insulin-responsive pathways in the blood–brain barrier endothelium using time-series transcriptomics data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9381797/ https://www.ncbi.nlm.nih.gov/pubmed/35974022 http://dx.doi.org/10.1038/s41540-022-00235-8 |
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