Additional file 1: of Integrative genomics identifies new genes associated with severe COPD and emphysema

Supplementary Methods. Table S1. Colocalization probability and regulatory annotations for colocalized variants using corresponding GWAS and Lung-eQTL consortium datasets (see Excel file). Table S2. Colocalization probability and regulatory annotations for colocalized variants using corresponding GWAS and GTEx eQTL (blood and lung) datasets (see Excel file). Table S3. Additional imputed gene expression association results at previously described GWAS significant loci. Table S4. Result of association analysis between imputed gene expression and moderate to severe COPD of reported genes from severe COPD. Table S5. Differential expression analysis between COPD and controls using blood RNA-seq in COPDGene. Table S6. Differential expression analysis of quantitative emphysema using blood RNA-seq in COPDGene. Table S7. Differential expression analysis between severe COPD and controls using lung tissues. Table S8. Differential expression analysis of %LAA-950 and Perc15 using lung tissues. Table S9. T-cell-associated gene sets from Reactome using a ranked gene list from associations of %LAA-950 (DGN-Blood). Table S10. Covariate adjustments for differential expression analysis. Figure S1. Regional association plots within 50kb of LILRA3. GWAS of %LAA-950 and blood eQTL were shown in upper panel. Chromatin states and epigenomic marks of normal human lung fibroblast were shown in lower panel (see Supplementary Methods). Figure S2. Regional association plots within 50kb of DCBLD1. GWAS of %LAA-950 and lung eQTL were shown in upper panel. Chromatin states and epigenomic marks of normal human lung fibroblast were shown in lower panel (see Supplementary Methods). Figure S3. Scatter plot of effect size of significant SNPs from eQTL studies of blood and lung tissue for FAM13A. Figure S4. Contribution of each FAM13A SNP in prediction models to overall association statistics. (ZIP 758 kb)