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.
Bibliographical noteFunding Information:
The data generation and analysis of the RNA-Seq data were supported by meritorious research awards (KRK) provided by the Division of Biostatistics and Informatics, Department of Health Sciences Research (Mayo Clinic, Rochester, MN). This work was supported by Minnesota Partnership for Biotechnology and Medical Genomics (Grant #00056030) and the National Institutes of Health/National Institute of Neurological Disorders and Stroke R01NS125437.
© 2022, The Author(s).
PubMed: MeSH publication types
- Journal Article
- Research Support, N.I.H., Extramural
- Research Support, Non-U.S. Gov't