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Identification of Key LncRNAs and Pathways in Prediabetes and Type 2 Diabetes Mellitus for Hypertriglyceridemia Patients Based on Weighted Gene Co-Expression Network Analysis
AIMS: Prevalence of prediabetes and type 2 diabetes mellitus(T2DM) are increasing worldwide. Key lncRNAs were detected to provide a reference for searching potential biomarkers of prediabetes and T2DM in hypertriglyceridemia patients. METHODS: The study included 18 hypertriglyceridemia patients: 6 n...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818867/ https://www.ncbi.nlm.nih.gov/pubmed/35140684 http://dx.doi.org/10.3389/fendo.2021.800123 |
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author | Yan, Shoumeng Sun, Mengzi Gao, Lichao Yao, Nan Feng, Tianyu Yang, Yixue Li, Xiaotong Hu, Wenyu Cui, Weiwei Li, Bo |
author_facet | Yan, Shoumeng Sun, Mengzi Gao, Lichao Yao, Nan Feng, Tianyu Yang, Yixue Li, Xiaotong Hu, Wenyu Cui, Weiwei Li, Bo |
author_sort | Yan, Shoumeng |
collection | PubMed |
description | AIMS: Prevalence of prediabetes and type 2 diabetes mellitus(T2DM) are increasing worldwide. Key lncRNAs were detected to provide a reference for searching potential biomarkers of prediabetes and T2DM in hypertriglyceridemia patients. METHODS: The study included 18 hypertriglyceridemia patients: 6 newly diagnosed type 2 diabetes patients, 6 samples with prediabetes and 6 samples with normal blood glucose. Weighted gene co-expression network analysis (WGCNA) was conducted to construct co‐expression network and obtain modules related to blood glucose, thus detecting key lncRNAs. RESULTS: The green, yellow and yellow module was significantly related to blood glucose in T2DM versus normal controls, T2DM versus prediabetes, prediabetes versus normal controls, respectively. ENST00000503273, ENST00000462720, ENST00000480633 and ENST00000485392 were detected as key lncRNAs for the above three groups, respectively. CONCLUSIONS: For hypertriglyceridemia patients with different blood glucose levels, ENST00000503273, ENST00000462720 and ENST00000480633 could be potential biomarkers of T2DM. |
format | Online Article Text |
id | pubmed-8818867 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88188672022-02-08 Identification of Key LncRNAs and Pathways in Prediabetes and Type 2 Diabetes Mellitus for Hypertriglyceridemia Patients Based on Weighted Gene Co-Expression Network Analysis Yan, Shoumeng Sun, Mengzi Gao, Lichao Yao, Nan Feng, Tianyu Yang, Yixue Li, Xiaotong Hu, Wenyu Cui, Weiwei Li, Bo Front Endocrinol (Lausanne) Endocrinology AIMS: Prevalence of prediabetes and type 2 diabetes mellitus(T2DM) are increasing worldwide. Key lncRNAs were detected to provide a reference for searching potential biomarkers of prediabetes and T2DM in hypertriglyceridemia patients. METHODS: The study included 18 hypertriglyceridemia patients: 6 newly diagnosed type 2 diabetes patients, 6 samples with prediabetes and 6 samples with normal blood glucose. Weighted gene co-expression network analysis (WGCNA) was conducted to construct co‐expression network and obtain modules related to blood glucose, thus detecting key lncRNAs. RESULTS: The green, yellow and yellow module was significantly related to blood glucose in T2DM versus normal controls, T2DM versus prediabetes, prediabetes versus normal controls, respectively. ENST00000503273, ENST00000462720, ENST00000480633 and ENST00000485392 were detected as key lncRNAs for the above three groups, respectively. CONCLUSIONS: For hypertriglyceridemia patients with different blood glucose levels, ENST00000503273, ENST00000462720 and ENST00000480633 could be potential biomarkers of T2DM. Frontiers Media S.A. 2022-01-24 /pmc/articles/PMC8818867/ /pubmed/35140684 http://dx.doi.org/10.3389/fendo.2021.800123 Text en Copyright © 2022 Yan, Sun, Gao, Yao, Feng, Yang, Li, Hu, Cui and Li https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Yan, Shoumeng Sun, Mengzi Gao, Lichao Yao, Nan Feng, Tianyu Yang, Yixue Li, Xiaotong Hu, Wenyu Cui, Weiwei Li, Bo Identification of Key LncRNAs and Pathways in Prediabetes and Type 2 Diabetes Mellitus for Hypertriglyceridemia Patients Based on Weighted Gene Co-Expression Network Analysis |
title | Identification of Key LncRNAs and Pathways in Prediabetes and Type 2 Diabetes Mellitus for Hypertriglyceridemia Patients Based on Weighted Gene Co-Expression Network Analysis |
title_full | Identification of Key LncRNAs and Pathways in Prediabetes and Type 2 Diabetes Mellitus for Hypertriglyceridemia Patients Based on Weighted Gene Co-Expression Network Analysis |
title_fullStr | Identification of Key LncRNAs and Pathways in Prediabetes and Type 2 Diabetes Mellitus for Hypertriglyceridemia Patients Based on Weighted Gene Co-Expression Network Analysis |
title_full_unstemmed | Identification of Key LncRNAs and Pathways in Prediabetes and Type 2 Diabetes Mellitus for Hypertriglyceridemia Patients Based on Weighted Gene Co-Expression Network Analysis |
title_short | Identification of Key LncRNAs and Pathways in Prediabetes and Type 2 Diabetes Mellitus for Hypertriglyceridemia Patients Based on Weighted Gene Co-Expression Network Analysis |
title_sort | identification of key lncrnas and pathways in prediabetes and type 2 diabetes mellitus for hypertriglyceridemia patients based on weighted gene co-expression network analysis |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818867/ https://www.ncbi.nlm.nih.gov/pubmed/35140684 http://dx.doi.org/10.3389/fendo.2021.800123 |
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