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Identifying critical genes associated with aneurysmal subarachnoid hemorrhage by weighted gene co-expression network analysis
Aneurysmal subarachnoid hemorrhage (aSAH) is a life-threatening medical condition with a high mortality and disability rate. aSAH has an unclear pathogenesis, and limited treatment options are available. Here, we aimed to identify critical genes involved in aSAH pathogenesis using peripheral blood g...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8507255/ https://www.ncbi.nlm.nih.gov/pubmed/34542421 http://dx.doi.org/10.18632/aging.203542 |
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author | Yan, Zhizhong Wu, Qi Cai, Wei Xiang, Haitao Wen, Lili Zhang, An Peng, Yaonan Zhang, Xin Wang, Handong |
author_facet | Yan, Zhizhong Wu, Qi Cai, Wei Xiang, Haitao Wen, Lili Zhang, An Peng, Yaonan Zhang, Xin Wang, Handong |
author_sort | Yan, Zhizhong |
collection | PubMed |
description | Aneurysmal subarachnoid hemorrhage (aSAH) is a life-threatening medical condition with a high mortality and disability rate. aSAH has an unclear pathogenesis, and limited treatment options are available. Here, we aimed to identify critical genes involved in aSAH pathogenesis using peripheral blood gene expression data of 43 patients with aSAH due to ruptured intracranial aneurysms and 18 controls with headache, downloaded from Gene Expression Omnibus. These data were used to construct a co-expression network using weighted gene co-expression network analysis (WGCNA). The biological functions of the hub genes were explored, and critical genes were selected by combining with differentially expressed genes analysis. Fourteen modules were identified by WGCNA. Among those modules, red, blue, brown and cyan modules were closely associated with aSAH. Moreover, 364 hub genes in the significant modules were found to play important roles in aSAH. Biological function analysis suggested that protein biosynthesis-related processes and inflammatory responses-related processes were involved in the pathology of aSAH pathology. Combined with differentially expressed genes analysis and validation in 35 clinical samples, seven gene (CD27, ANXA3, ACSL1, PGLYRP1, ALPL, ARG1, and TPST1) were identified as potential biomarkers for aSAH, and three genes (ANXA3, ALPL, and ARG1) were changed with disease development, that may provide new insights into potential molecular mechanisms for aSAH. |
format | Online Article Text |
id | pubmed-8507255 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-85072552021-10-14 Identifying critical genes associated with aneurysmal subarachnoid hemorrhage by weighted gene co-expression network analysis Yan, Zhizhong Wu, Qi Cai, Wei Xiang, Haitao Wen, Lili Zhang, An Peng, Yaonan Zhang, Xin Wang, Handong Aging (Albany NY) Research Paper Aneurysmal subarachnoid hemorrhage (aSAH) is a life-threatening medical condition with a high mortality and disability rate. aSAH has an unclear pathogenesis, and limited treatment options are available. Here, we aimed to identify critical genes involved in aSAH pathogenesis using peripheral blood gene expression data of 43 patients with aSAH due to ruptured intracranial aneurysms and 18 controls with headache, downloaded from Gene Expression Omnibus. These data were used to construct a co-expression network using weighted gene co-expression network analysis (WGCNA). The biological functions of the hub genes were explored, and critical genes were selected by combining with differentially expressed genes analysis. Fourteen modules were identified by WGCNA. Among those modules, red, blue, brown and cyan modules were closely associated with aSAH. Moreover, 364 hub genes in the significant modules were found to play important roles in aSAH. Biological function analysis suggested that protein biosynthesis-related processes and inflammatory responses-related processes were involved in the pathology of aSAH pathology. Combined with differentially expressed genes analysis and validation in 35 clinical samples, seven gene (CD27, ANXA3, ACSL1, PGLYRP1, ALPL, ARG1, and TPST1) were identified as potential biomarkers for aSAH, and three genes (ANXA3, ALPL, and ARG1) were changed with disease development, that may provide new insights into potential molecular mechanisms for aSAH. Impact Journals 2021-09-20 /pmc/articles/PMC8507255/ /pubmed/34542421 http://dx.doi.org/10.18632/aging.203542 Text en Copyright: © 2021 Yan et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Yan, Zhizhong Wu, Qi Cai, Wei Xiang, Haitao Wen, Lili Zhang, An Peng, Yaonan Zhang, Xin Wang, Handong Identifying critical genes associated with aneurysmal subarachnoid hemorrhage by weighted gene co-expression network analysis |
title | Identifying critical genes associated with aneurysmal subarachnoid hemorrhage by weighted gene co-expression network analysis |
title_full | Identifying critical genes associated with aneurysmal subarachnoid hemorrhage by weighted gene co-expression network analysis |
title_fullStr | Identifying critical genes associated with aneurysmal subarachnoid hemorrhage by weighted gene co-expression network analysis |
title_full_unstemmed | Identifying critical genes associated with aneurysmal subarachnoid hemorrhage by weighted gene co-expression network analysis |
title_short | Identifying critical genes associated with aneurysmal subarachnoid hemorrhage by weighted gene co-expression network analysis |
title_sort | identifying critical genes associated with aneurysmal subarachnoid hemorrhage by weighted gene co-expression network analysis |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8507255/ https://www.ncbi.nlm.nih.gov/pubmed/34542421 http://dx.doi.org/10.18632/aging.203542 |
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