Identification of Key Genes Involved in Acute Myocardial Infarction by Comparative Transcriptome Analysis
المؤلفون المشاركون
Fan, Tao
Sheng, Xiaodong
Jin, Xiaoqi
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-10-06
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
Background.
Acute myocardial infarction (AMI) is regarded as an urgent clinical entity, and identification of differentially expressed genes, lncRNAs, and altered pathways shall provide new insight into the molecular mechanisms behind AMI.
Materials and Methods.
Microarray data was collected to identify key genes and lncRNAs involved in AMI pathogenesis.
The differential expression analysis and gene set enrichment analysis (GSEA) were employed to identify the upregulated and downregulated genes and pathways in AMI.
The protein-protein interaction network and protein-RNA interaction analysis were utilized to reveal key long noncoding RNAs.
Results.
In the present study, we utilized gene expression profiles of circulating endothelial cells (CEC) from 49 patients of AMI and 50 controls and identified a total of 552 differentially expressed genes (DEGs).
Based on these DEGs, we also observed that inflammatory response-related genes and pathways were highly upregulated in AMI.
Mapping the DEGs to the protein-protein interaction (PPI) network and identifying the subnetworks, we found that OMD and WDFY3 were the hub nodes of two subnetworks with the highest connectivity, which were found to be involved in circadian rhythm and organ- or tissue-specific immune response.
Furthermore, 23 lncRNAs were differentially expressed between AMI and control groups.
Specifically, we identified some functional lncRNAs, including XIST and its antisense RNA, TSIX, and three lncRNAs (LINC00528, LINC00936, and LINC01001), which were predicted to be interacting with TLR2 and participate in Toll-like receptor signaling pathway.
In addition, we also employed the MMPC algorithm to identify six gene signatures for AMI diagnosis.
Particularly, the multivariable SVM model based on the six genes has achieved a satisfying performance (AUC=0.97).
Conclusion.
In conclusion, we have identified key regulatory lncRNAs implicated in AMI, which not only deepens our understanding of the lncRNA-related molecular mechanism of AMI but also provides computationally predicted regulatory lncRNAs for AMI researchers.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Sheng, Xiaodong& Fan, Tao& Jin, Xiaoqi. 2020. Identification of Key Genes Involved in Acute Myocardial Infarction by Comparative Transcriptome Analysis. BioMed Research International،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1131660
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Sheng, Xiaodong…[et al.]. Identification of Key Genes Involved in Acute Myocardial Infarction by Comparative Transcriptome Analysis. BioMed Research International No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1131660
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Sheng, Xiaodong& Fan, Tao& Jin, Xiaoqi. Identification of Key Genes Involved in Acute Myocardial Infarction by Comparative Transcriptome Analysis. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1131660
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1131660
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر