Research Paper Volume 13, Issue 18 pp 22345—22360
Identifying critical genes associated with aneurysmal subarachnoid hemorrhage by weighted gene co-expression network analysis
- 1 The First School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
- 2 Department of Neurosurgery, Jinling Hospital, Nanjing 210002, China
- 3 Department of Neurosurgery, The 904th Hospital of The Joint Logistics Support Force of Chinese People's Liberation Army, Wuxi 214000, China
- 4 Department of Neurosurgery, The Affiliated Suqian First People’s Hospital of Nanjing Medical University, Suqian 223800, China
- 5 Department of Neurosurgery, Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou 215028, China
Received: February 22, 2021 Accepted: August 11, 2021 Published: September 20, 2021https://doi.org/10.18632/aging.203542
How to Cite
Copyright: © 2021 Yan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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.