13073_2021_866_MOESM2_ESM.xlsx (6.92 MB)
Additional file 2 of Genetic and non-genetic factors affecting the expression of COVID-19-relevant genes in the large airway epithelium
dataset
posted on 2021-04-22, 03:40 authored by Silva Kasela, Victor E. Ortega, Molly Martorella, Suresh Garudadri, Jenna Nguyen, Elizabeth Ampleford, Anu Pasanen, Srilaxmi Nerella, Kristina L. Buschur, Igor Z. Barjaktarevic, R. Graham Barr, Eugene R. Bleecker, Russell P. Bowler, Alejandro P. Comellas, Christopher B. Cooper, David J. Couper, Gerard J. Criner, Jeffrey L. Curtis, MeiLan K. Han, Nadia N. Hansel, Eric A. Hoffman, Robert J. Kaner, Jerry A. Krishnan, Fernando J. Martinez, Merry-Lynn N. McDonald, Deborah A. Meyers, Robert Paine, Stephen P. Peters, Mario Castro, Loren C. Denlinger, Serpil C. Erzurum, John V. Fahy, Elliot Israel, Nizar N. Jarjour, Bruce D. Levy, Xingnan Li, Wendy C. Moore, Sally E. Wenzel, Joe Zein, Charles Langelier, Prescott G. Woodruff, Tuuli Lappalainen, Stephanie A. ChristensonAdditional file 2: Table S1. Differential expression analysis of ACE2 in relation to clinical variables (A) and genomic signatures (B) in SPIROMICS, SARP, and MAST. Table S2. Top 100 genes co-expressed with ACE2 after adjustments in SPIROMICS (A), SARP (B), and MAST (C). The genes in the IL-17 signature are highlighted in yellow. Table S3. Canonical pathway gene sets based on differentially downregulated genes between SARS-CoV-2 infection and other viral illness using the Ingenuity Pathway Analysis canonical pathway function. Table S4. Association between canonical pathway gene sets from Table S3 and comorbidities in SPIROMICS (A), SARP (B), and MAST (C). Leading edge genes are enriched in association with the given comorbidity. Table S5. Canonical pathway gene sets based on genes enriched in association with each comorbidity using the Ingenuity Pathway Analysis canonical pathway function. A – cardiovascular condition in SPIROMICS, B – hypertension in SPIROMICS, C – obesity in SPIROMICS, D - hypertension in SARP, E – obesity in SARP. Table S6. COVID-19-related genes from Blanco-Melo et al. 2020, Gassen et al. 2020, Gordon et al. 2020, Hoffmann et al. 2020, Wang et al. 2020, and COVID-19 Cell Atlas. Table S7. Summary statistics of eQTL mapping in bronchial epithelium in SPIROMICS, including eQTL effect sizes, and lookup analysis from GTEx and eQTLGen Consortium. Table S8. Lookup of COVID-19-related genes with cis-eQTLs in bronchial epithelium from GTEx v8. Effect size measured as allelic fold change (log2) is given for every gene with FDR < 0.05 in GTEx v8 and its lead eQTL, or set to NA otherwise. Table S9. Pathway analysis of 492 eGenes from SPIROMICS not tested in GTEx Lung. Table S10. pheWAS of eQTLs for COVID-19-related genes in bronchial epithelium with Phenoscanner v2. Table S11. pheWAS of eQTLs for COVID-19-related genes in bronchial epithelium in (A) non-Hispanic White individuals (N = 1980) and (B) Hispanic and non-Hispanic, non-White individuals (N = 696) in SPIROMICS for 20 phenotypes. Table S12. Results of the colocalization analysis of the eQTLs in bronchial epithelium and COVID-19-relevant phenotypes.
