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Identification of dynamic molecular networks in peripheral blood mononuclear cells in type 1 diabetes mellitus
BACKGROUND: Type 1 diabetes mellitus (T1DM) is an autoimmune disease caused by the immune destruction of islet β cells. Gene expression in peripheral blood mononuclear cells (PBMCs) could offer new disease and treatment markers in T1DM. The objective of this study was to explore the coexpression and...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Dove
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6601337/ https://www.ncbi.nlm.nih.gov/pubmed/31417297 http://dx.doi.org/10.2147/DMSO.S207021 |
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author | Li, Lu Pan, Zongfu Yang, Xi |
author_facet | Li, Lu Pan, Zongfu Yang, Xi |
author_sort | Li, Lu |
collection | PubMed |
description | BACKGROUND: Type 1 diabetes mellitus (T1DM) is an autoimmune disease caused by the immune destruction of islet β cells. Gene expression in peripheral blood mononuclear cells (PBMCs) could offer new disease and treatment markers in T1DM. The objective of this study was to explore the coexpression and dynamic molecular networks in PBMCs of T1DM patients. METHODS: Dataset GSE9006 contains PBMC samples of healthy volunteers, newly diagnosed T1DM patients, T1DM patients after insulin treatment, and newly diagnosed type 2 diabetes mellitus (T2DM) patients. Weighted correlation network analysis (WGCNA) was used to generate coexpression networks in T1DM and T2DM. Functional pathways in highly correlated modules of T1DM were enriched by gene set enrichment analysis (GSEA). We next filtered the differentially expressed genes (DEGs) and revealed their dynamic expression profiles in T1DM with or without insulin treatment. Furthermore, dynamic clusters and dynamic protein–protein interaction networks were identified. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was developed in dynamic clusters. RESULTS: WGCNA disclosed 12 distinct gene modules, and distinguished between correlated networks in T1DM and T2DM. Two modules were closely associated with T1DM. GSEA showed that the immune response and response to cytokines were enriched in the T1DM highly correlated module. Next, we screened 44 DEGs in newly diagnosed T1DM compared with healthy donors, and 71 DEGs in 1-month and 97 DEGs in 4-month insulin treatment groups compared with newly diagnosed T1DM. Dynamic expression profiles of DEGs indicated the potential targets for T1DM treatment. Moreover, four molecular dynamic clusters were analyzed in newly diagnosed and insulin-treated T1DM. Functional annotation showed that these clusters were mainly enriched in the IL-17 signaling pathway, nuclear factor-ϰB signaling pathway, and tumor necrosis factor signaling pathway. CONCLUSION: The results indicate potential drug targets or clinical efficacy markers, as well as demonstrating the underlying molecular mechanisms of T1DM treatment. |
format | Online Article Text |
id | pubmed-6601337 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-66013372019-08-15 Identification of dynamic molecular networks in peripheral blood mononuclear cells in type 1 diabetes mellitus Li, Lu Pan, Zongfu Yang, Xi Diabetes Metab Syndr Obes Original Research BACKGROUND: Type 1 diabetes mellitus (T1DM) is an autoimmune disease caused by the immune destruction of islet β cells. Gene expression in peripheral blood mononuclear cells (PBMCs) could offer new disease and treatment markers in T1DM. The objective of this study was to explore the coexpression and dynamic molecular networks in PBMCs of T1DM patients. METHODS: Dataset GSE9006 contains PBMC samples of healthy volunteers, newly diagnosed T1DM patients, T1DM patients after insulin treatment, and newly diagnosed type 2 diabetes mellitus (T2DM) patients. Weighted correlation network analysis (WGCNA) was used to generate coexpression networks in T1DM and T2DM. Functional pathways in highly correlated modules of T1DM were enriched by gene set enrichment analysis (GSEA). We next filtered the differentially expressed genes (DEGs) and revealed their dynamic expression profiles in T1DM with or without insulin treatment. Furthermore, dynamic clusters and dynamic protein–protein interaction networks were identified. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was developed in dynamic clusters. RESULTS: WGCNA disclosed 12 distinct gene modules, and distinguished between correlated networks in T1DM and T2DM. Two modules were closely associated with T1DM. GSEA showed that the immune response and response to cytokines were enriched in the T1DM highly correlated module. Next, we screened 44 DEGs in newly diagnosed T1DM compared with healthy donors, and 71 DEGs in 1-month and 97 DEGs in 4-month insulin treatment groups compared with newly diagnosed T1DM. Dynamic expression profiles of DEGs indicated the potential targets for T1DM treatment. Moreover, four molecular dynamic clusters were analyzed in newly diagnosed and insulin-treated T1DM. Functional annotation showed that these clusters were mainly enriched in the IL-17 signaling pathway, nuclear factor-ϰB signaling pathway, and tumor necrosis factor signaling pathway. CONCLUSION: The results indicate potential drug targets or clinical efficacy markers, as well as demonstrating the underlying molecular mechanisms of T1DM treatment. Dove 2019-06-25 /pmc/articles/PMC6601337/ /pubmed/31417297 http://dx.doi.org/10.2147/DMSO.S207021 Text en © 2019 Li et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Li, Lu Pan, Zongfu Yang, Xi Identification of dynamic molecular networks in peripheral blood mononuclear cells in type 1 diabetes mellitus |
title | Identification of dynamic molecular networks in peripheral blood mononuclear cells in type 1 diabetes mellitus |
title_full | Identification of dynamic molecular networks in peripheral blood mononuclear cells in type 1 diabetes mellitus |
title_fullStr | Identification of dynamic molecular networks in peripheral blood mononuclear cells in type 1 diabetes mellitus |
title_full_unstemmed | Identification of dynamic molecular networks in peripheral blood mononuclear cells in type 1 diabetes mellitus |
title_short | Identification of dynamic molecular networks in peripheral blood mononuclear cells in type 1 diabetes mellitus |
title_sort | identification of dynamic molecular networks in peripheral blood mononuclear cells in type 1 diabetes mellitus |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6601337/ https://www.ncbi.nlm.nih.gov/pubmed/31417297 http://dx.doi.org/10.2147/DMSO.S207021 |
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