PDF(Pubmed)
Abstract：
Sarcopenia is a condition characterized by age-related loss of muscle mass and strength. Increasing evidence suggests that patients with sarcopenia have higher rates of coronavirus 2019 (COVID-19) infection and poorer post-infection outcomes. However, the exact mechanism and connections between the two is unknown. In this study, we used high-throughput data from the GEO database for sarcopenia (GSE111016) and COVID-19 (GSE171110) to identify common differentially expressed genes (DEGs). We conducted GO and KEGG pathway analyses, as well as PPI network analysis on these DEGs. Using seven algorithms from the Cytoscape plug-in cytoHubba, we identified 15 common hub genes. Further analyses included enrichment, PPI interaction, TF-gene and miRNA-gene regulatory networks, gene-disease associations, and drug prediction. Additionally, we evaluated immune cell infiltration with CIBERSORT and assessed the diagnostic accuracy of hub genes for sarcopenia and COVID-19 using ROC curves. In total, we identified 66 DEGs (34 up-regulated and 32 down-regulated) and 15 hub genes associated with sarcopenia and COVID-19. GO and KEGG analyses revealed functions and pathways between the two diseases. TF-genes and TF-miRNA regulatory network suggest that FOXOC1 and hsa-mir-155-5p may be identified as key regulators, while gene-disease analysis showed strong correlations with hub genes in schizophrenia and bipolar disorder. Immune infiltration showed a correlation between the degree of immune infiltration and the level of infiltration of different immune cell subpopulations of hub genes in different datasets. The ROC curves for ALDH1L2 and KLF5 genes demonstrated their potential as diagnostic markers for both sarcopenia and COVID-19. This study suggests that sarcopenia and COVID-19 may share pathogenic pathways, and these pathways and hub genes offer new targets and strategies for early diagnosis, effective treatment, and tailored therapies for sarcopenia patients with COVID-19.
摘要：
肌肉减少症是一种以年龄相关的肌肉质量和力量损失为特征的病症。越来越多的证据表明，肌肉减少症患者2019年冠状病毒(COVID-19)感染率更高，感染后结局更差。然而,两者之间的确切机制和联系是未知的。在这项研究中,我们使用GEO数据库中的关于肌肉减少症(GSE111016)和COVID-19(GSE171110)的高通量数据来鉴定常见差异表达基因(DEGs).我们进行了GO和KEGG通路分析，以及这些DEG的PPI网络分析。使用Cytoscape插件cytoHubba的七个算法，我们确定了15个常见的hub基因.进一步的分析包括浓缩，PPI相互作用，TF-基因和miRNA-基因调控网络，基因-疾病关联，和药物预测。此外,我们使用CIBERSORT评估了免疫细胞浸润,并使用ROC曲线评估了hub基因对肌肉减少症和COVID-19的诊断准确性.总的来说,我们鉴定了66个DEGs(34个上调和32个下调)和15个与肌肉减少症和COVID-19相关的hub基因。GO和KEGG分析揭示了两种疾病之间的功能和途径。TF-基因和TF-miRNA调控网络表明FOXOC1和hsa-mir-155-5p可能被确定为关键调控因子,而基因-疾病分析显示与精神分裂症和双相情感障碍的hub基因有很强的相关性。免疫浸润显示不同数据集hub基因不同免疫细胞亚群的免疫浸润程度与浸润水平之间存在相关性。ALDH1L2和KLF5基因的ROC曲线证明了它们作为肌肉减少症和COVID-19诊断标志物的潜力。这项研究表明，肌肉减少症和COVID-19可能具有共同的致病途径，这些通路和枢纽基因为早期诊断提供了新的目标和策略，有效治疗,并为COVID-19患者提供量身定制的治疗方法。
