Presentation Information
[OE5-2]The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force
○Qingbo Wang1,2, Ryuya Edahiro1,3, Namkoong Ho4, Takanori Hasegawa5, Makoto Ishii6, Ryuji Koike7, Akinori Kimura8, Seiya Imoto9, Satoru Miyano5, Seishi Ogawa10,11,12, Takanori Kanai13,14, Koichi Fukunaga6, Yukinori Okada1,2,15,16,17,18, Japan Covid-19 Task Force Project4 (1.Department of Statistical Genetics, Graduate School of Medicine, Osaka University, Osaka, Japan, 2.Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan., 3.Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita, Japan., 4.Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan., 5.M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan, 6.Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan, 7.Medical Innovation Promotion Center, Tokyo Medical and Dental University, Tokyo, Japan, 8.Institute of Research, Tokyo Medical and Dental University, Tokyo, Japan, 9.Division of Health Medical Intelligence, Human Genome Center, the Institute of Medical Science, the University of Tokyo, Tokyo, Japan, 10.Department of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan, 11.Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan, 12.Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institute, Stockholm, Sweden, 13.Division of Gastroenterology and Hepatology, Department of Medicine, Keio University School of Medicine, Tokyo, Japan, 14.AMED-CREST, Japan Agency for Medical Research and Development, Tokyo, Japan, 15.Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan, 16.Center for Infectious Disease Education and Research (CiDER), Osaka University, Suita, Japan, 17.Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan, 18.Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan)
Here we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force (359 severe and 106 non-severe COVID-19 cases). We discovered 1,169 putative causal (0.9 ＜ posterior inclusion probability = PIP) expression quantitative trait loci (p-causal eQTLs) including 34 possible colocalizations with fine-mapped variants in Biobank Japan (BBJ), 1,549 p-causal splice QTLs (sQTLs), as well as trans-eQTLs (e.g., REST and STING1).We validated our cis-eQTL fine-mapping by comparing it with that of GTEx and observing 46％ replication rate of p-causal eQTLs, as well as 100％ concordance in the effect size direction when replicated. We also show a refinement of fine-mapping by integrating results from two cohorts (e.g., 396 additional p-causal eQTLs). Differential gene expression elucidated 198 genes with increased expression in severe COVID-19 cases, enriched for innate immune-related functions (adjusted p＜10e-10). 13 genes, including the ones relevant to viral infection (e.g. CLEC4C), showed eQTL effects of different magnitudes by disease severity (FDR＜0.05). We characterized such COVID-19 severity interaction-eQTLs (ieQTLs) with dynamics of cell type composition, for instance, an increase in neutrophils along with the COVID-19 severity (10/13 genes; Bonferroni p＜0.05). Our study overall provides a reference for transcriptional landscapes in COVID-19 infection such as the presence of ieQTLs, and highlights an improvement of eQTL fine-mapping by including ＞1 populations.