Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019

• Main Authors: Hui Liu, Shujin Lin, Xiulan Ao, Xiangwen Gong, Chunyun Liu, Dechang Xu, Yumei Huang, Zhiqiang Liu, Bixing Zhao, Xiaolong Liu, Xiao Han, Hanhui Ye
• Format: Article
• Language: English
• Published: Elsevier 2021-01-01
• Series: Computational and Structural Biotechnology Journal
• Subjects: IL-6; Meta-analysis; Transcriptome; Respiratory disease; Cardiovasculardisease; Resveratrol
• Online Access: http://www.sciencedirect.com/science/article/pii/S2001037020305353

In coronavirus disease 2019 (COVID-19) patients, interleukin (IL)-6 is one of the leading factors causing death through cytokine release syndrome. Hence, identification of IL-6 downstream from clinical patients’ transcriptome is very valid for analyses of its mechanism. However, clinical study is conditional and time consuming to collect optional size of samples, as patients have the clinical heterogeneity. A possible solution is to deeply mine the relative existing data. Several transcriptome-based studies on other diseases or treatments have revealed different genes to be regulated by IL-6. Through our meta-analysis of these transcriptome datasets, 352 genes were suggested to be regulated by IL-6 in different biological conditions, some of which were related to virus infection and cardiovascular disease. Among them, 232 genes were not identified by current transcriptome studies from clinical research. ICAM1 and PFKFB3 were the most significantly upregulated genes in our meta-analysis and could be employed as biomarkers in patients with severe COVID-19. In general, a meta-analysis of transcriptome datasets could be an alternative way to analyze the immune response and complications of patients suffering from severe COVID-19 and other emergency diseases.