生物信息学和系统生物学方法用于识别COVID-19感染和骨关节炎的潜在常见病原体
Ziyi Chen1, Wenjuan Wang1, Hao Jue1
1Department of Sports Medicine, Huashan Hospital, Fudan University, No. 12, Wulumuqi Zhong Road, Shanghai, 200040, People's Republic of China.
Scientific reports
|June 8, 2023
概括
患有骨关节炎 (OA) 和冠状病毒2019 (COVID-19) 的患者有共同的疾病途径和枢纽基因. 这项研究确定了潜在的诊断标记物和候选药物,用于治疗COVID-19的OA患者.
科学领域:
- 基因组学就是基因组学.
- 传染性疾病 传染性疾病
- 类风湿病学 类风湿病学
背景情况:
- 骨关节炎 (OA) 患者的冠状病毒2019 (COVID-19) 感染率增加和预后更差.
- COVID-19 感染可能会诱导肌肉骨病理变化,但潜在的机制尚不清楚.
研究的目的:
- 调查OA和COVID-19之间的共享病原体.
- 识别常见的差异表达基因 (DEGs) 和枢纽基因.
- 为了预测COVID-19的OA患者的候选药物.
主要方法:
- 从基因表达综合 (GEO) 数据库中获得的OA (GSE51588) 和COVID-19 (GSE147507) 基因表达概况.
- 识别了重叠的DEG,构建了监管和关联网络 (PPI,TF基因,TF-miRNA,基因疾病).
- 使用DSigDB进行药物预测和ROC曲线用于诊断标记物评估.
主要成果:
- 在OA和COVID-19之间确定了83个重叠的DEG.
- 选了14个枢纽基因 (例如,CXCR4,EGR2,ENO1,FASN) 对这两种疾病都有诊断潜力.
- 预测的候选分子药物针对这些枢纽基因.
结论:
- 共享的路径和枢纽基因为OA和COVID-19病原体提供了洞察力.
- 确定了COVID-19感染的OA患者的潜在诊断标志物和治疗点.
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