Integrative network analysis of N<sup>6</sup> methylation-related genes reveal potential therapeutic targets for spinal cord injury

<abstract> <p>The diagnosis of the severity of spinal cord injury (SCI) and the revelation of potential therapeutic targets are crucial for urgent clinical care and improved patient outcomes. Here, we analyzed the overall gene expression data in peripheral blood leukocytes during the acute injury phase collected from Gene Expression Omnibus (GEO) and identified six m6A regulators specifically expressed in SCI compared to normal samples. LncRNA-mRNA network analysis identified AKT2/3 and PIK3R1 related to m6A methylation as potential therapeutic targets for SCI and constructed a classifier to identify patients of SCI to assist clinical diagnosis. Moreover, FTO (eraser) and RBMX (reader) were found to be significantly down-regulated in SCI and the functional gene co-expressed with them was found to be involved in the signal transduction of multiple pathways related to nerve injury. Through the construction of the drug-target gene network, eight key genes were identified as drug targets and it was emphasized that fostamatinib can be used as a potential drug for the treatment of SCI. Taken together, our study characterized the pathogenesis and identified a potential therapeutic target of SCI providing theoretical support for the development of precision medicine.</p> </abstract>

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Diagnostic blood RNA profiles for human acute spinal cord injury

Journal of Experimental Medicine ◽

10.1084/jem.20201795 ◽

2021 ◽

Vol 218 (3) ◽

Author(s):

Nikos Kyritsis ◽

Abel Torres-Espín ◽

Patrick G. Schupp ◽

J. Russell Huie ◽

Austin Chou ◽

...

Keyword(s):

Spinal Cord ◽

Spinal Cord Injury ◽

Clinical Trials ◽

Blood Cells ◽

Immune Cell ◽

Clinical Care ◽

White Blood Cells ◽

Acute Injury ◽

Specificity And Sensitivity ◽

Cord Injury

Diagnosis of spinal cord injury (SCI) severity at the ultra-acute stage is of great importance for emergency clinical care of patients as well as for potential enrollment into clinical trials. The lack of a diagnostic biomarker for SCI has played a major role in the poor results of clinical trials. We analyzed global gene expression in peripheral white blood cells during the acute injury phase and identified 197 genes whose expression changed after SCI compared with healthy and trauma controls and in direct relation to SCI severity. Unsupervised coexpression network analysis identified several gene modules that predicted injury severity (AIS grades) with an overall accuracy of 72.7% and included signatures of immune cell subtypes. Specifically, for complete SCIs (AIS A), ROC analysis showed impressive specificity and sensitivity (AUC: 0.865). Similar precision was also shown for AIS D SCIs (AUC: 0.938). Our findings indicate that global transcriptomic changes in peripheral blood cells have diagnostic and potentially prognostic value for SCI severity.

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Bioinformatic analysis of the gene expression profile in muscle atrophy after spinal cord injury

Scientific Reports ◽

10.1038/s41598-021-01302-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hui Huang ◽

Jinju Xue ◽

Jiaxuan Zheng ◽

Haiquan Tian ◽

Yehan Fang ◽

...

Keyword(s):

Gene Expression ◽

Spinal Cord ◽

Spinal Cord Injury ◽

Network Analysis ◽

Gene Expression Profile ◽

Muscle Atrophy ◽

Expression Profile ◽

Pathway Network ◽

Cord Injury ◽

Signal Network

AbstractSpinal cord injury (SCI) is often accompanied by muscle atrophy; however, its underlying mechanisms remain unclear. Here, the molecular mechanisms of muscle atrophy following SCI were investigated. The GSE45550 gene expression profile of control (before SCI) and experimental (14 days following SCI) groups, consisting of Sprague–Dawley rat soleus muscle (n = 6 per group), was downloaded from the Gene Expression Omnibus database, and then differentially expressed gene (DEG) identification and Gene Ontology, pathway, pathway network, and gene signal network analyses were performed. A total of 925 differentially expressed genes, 149 biological processes, and 55 pathways were screened. In the pathway network analysis, the 10 most important pathways were citrate cycle (TCA cycle), pyruvate metabolism, MAPK signalling pathway, fatty acid degradation, propanoate metabolism, apoptosis, focal adhesion, synthesis and degradation of ketone bodies, Wnt signalling, and cancer pathways. In the gene signal network analysis, the 10 most important genes were Acat1, Acadvl, Acaa2, Hadhb, Acss1, Oxct1, Hadha, Hadh, Acaca, and Cpt1b. Thus, we screened the key genes and pathways that may be involved in muscle atrophy after SCI and provided support for finding valuable markers for this disease.

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