Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Neuromyelitis optica spectrum disorder (NMOSD) is a severe central nervous system disease primarily characterized by optic neuritis and myelitis, which can result in vision loss and limb paralysis. Current treatment options are limited in their ability to prevent relapses and mitigate disease progression, underscoring the urgent need for new drug targets to develop more effective therapies. The objective of this study is to identify potential drug targets associated with a reduced risk of NMOSD attacks or relapses through Mendelian randomization (MR) analysis, thereby addressing the limitations of existing treatment methods and providing better clinical options for patients. To identify therapeutic targets for NMOSD, a MR analysis was conducted. The cis-expression quantitative trait loci (cis-eQTL, exposure) data were sourced from the eQTLGen consortium, which included a sample size of 31,684. NMOSD (outcome) summary data were obtained from two of the largest independent cohorts: one cohort consisted of 86 NMOSD cases and 460 controls derived from whole-genome sequencing data, while the other cohort included 129 NMOSD patients and 784 controls. We performed a two-sample MR analysis to evaluate the association between single nucleotide polymorphisms (SNPs) and copy number variations with NMOSD. The MR analysis utilized the inverse variance weighted (IVW) method, supplemented by MR-Egger, weighted median, simple mode, and weighted mode methods. Sensitivity analyses were conducted to assess the presence of horizontal pleiotropy and heterogeneity. Colocalization analysis was employed to test whether NMOSD risk and gene expression are driven by common SNPs. Additionally, a phenome-wide association study (PheWAS) was performed to detect disease outcomes associated with NEU1. Supplementary analyses included single-nucleus RNA sequencing (snRNA-seq) data analysis, protein-protein interaction (PPI) networks, and drug feasibility assessments to prioritize potential therapeutic targets. Two drug targets, COL4A1 and NEU1, demonstrated significant MR results in two independent datasets. Notably, NEU1 showed substantial evidence of colocalization with NMOSD. Additionally, apart from the association between NEU1 and NMOSD, no other associations were observed between gene-proxied NEU1 inhibition and the increased risk of other NMOSD-related diseases. This study supports the potential of targeting NEU1 for drug inhibition to reduce the risk of NMOSD. Further preclinical research and drug development are warranted to validate the efficacy and safety of NEU1 as a therapeutic target and to explore its potential in NMOSD treatment.
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http://dx.doi.org/10.1007/s12035-024-04612-8 | DOI Listing |
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