Identification of Exercise-Related Signature Genes Potentially Associated with Cocaine Addiction by Integrating Bioinformatics and Mendelian Randomization Analysis

通过整合生物信息学和孟德尔随机化分析,鉴定可能与可卡因成瘾相关的运动相关特征基因

阅读:2

Abstract

Background: Exercise is a promising non-pharmacological intervention for cocaine addiction but molecular mechanisms of exercise-related genes in addiction remain unclear. This study aimed to identify exercise-related signature genes for cocaine addiction and to assess the potential causal relationship between exercise and cocaine addiction using two-sample Mendelian randomization (MR) analysis. Methods: Midbrain transcriptomic data were analyzed for differentially expressed genes (DEGs) and intersected with exercise-related genes. Functional enrichment, protein-protein interaction (PPI) and immune infiltration analyses explored their roles while signature genes were screened via LASSO/Random Forest and validated by ROC curves. GSEA explored pathways and MR confirmed exercise's causal effect. Results: A total of 244 DEGs were identified, including 27 exercise-related, and six signature genes (CALM3, CCL2, CD44, CLIC1, JUN, VCAM1) showed AUC values between 0.714 and 0.868 in distinguishing cocaine-addicted individuals from controls. Functional analyses revealed enrichment in immune-inflammatory pathways, metabolic processes and neuro-immune interactions and immune infiltration analysis showed cocaine addicts had elevated pro-inflammatory cells, reduced regulatory cells and signature genes correlated with immune dysregulations. MR analysis suggested a statistically significant protective association between genetically proxied higher levels of exercise and cocaine addiction risk (p < 0.05). Conclusions: These six genes may be potential biomarkers and therapeutic targets, and exercise may protect against cocaine addiction by regulating immune-inflammatory responses, metabolic pathways and neuroplasticity, although further validation in larger, independent cohorts and experimental models is required.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。