Additional file 2: Table S2. Summary of different models tested for estimating differences between controls and COVID-19 patients for immune cell proportions. Adjusted R2, residual standard error (sigma), AIC, and p.value for each tested model for each cell type are shown. The following models were tested, mod1; Age and ethnicity as covariates, mod2; age as a covariate, mod3; ethnicity as a covariate, mod4; no covariates.

Additional file 3: Table S3. Summary of identified differentially methylated CpGs between COVID-19 patients and controls. A. All significant CpGs B. Variable description from Table S2A. C. Significant CpGs from genes previously described as COVID-19 important [1]. D. Functional annotation of genes from Supplemental table 3C.

Additional file 9: Table S9. Summary of univariate Cox proportional hazard analysis of the previously identified CpGs. Column variables represent Name; chr; chromosome number, pos; position, CpG name, relation_to_Island; where is CpG located in relationship to island, UCSC RefGene Name; UCSC gene name, UCSC RefGene Accession; UCSC gene accession, UCSC RefGene Group; where in respect to gene is CpG located, Beta; estimated coefficient beta from the model, StandardError; standard error, Z; z-score, LRT; likelihood ratio...

Additional file 1. Stage one database. Include the participants who met the inclusion criteria for stage one.

Additional file 1. Stage one database. Include the participants who met the inclusion criteria for stage one.

Additional file 3: Propagation walkscores of 127 proxy protein-coding genes in the TCGA-BRCA cohort.

Additional file 7: Akaike information criterion (AIC), delta AIC, and HRs for death (overall survival) and corresponding 95%-confidence interval for ICR and 3 ir-lncRNA signature in 18 solid cancer TCGA datasets and RAQA cohort.

Additional file 3: Propagation walkscores of 127 proxy protein-coding genes in the TCGA-BRCA cohort.

Additional file 4: Canonical pathways, diseases and functions associated with the 127 proxy protein-coding genes.

Additional file 7: Akaike information criterion (AIC), delta AIC, and HRs for death (overall survival) and corresponding 95%-confidence interval for ICR and 3 ir-lncRNA signature in 18 solid cancer TCGA datasets and RAQA cohort.

Additional file 7: Table S7. Summary of immune cell changes and differentially methylated CpGs between recovered and dead patients over four time points 7A. Immune cell changes between recovered and dead patients over four time points, 7B. Differential methylation of CpGs between recovered and died patients over four time points. The b_0, b_1, b_2, and b_3 coefficients correspond to the reference model parameters, where survival phenotype is used as a reference. The d_0, d_1, d_2,...

Additional file 2. Stage two database. Include the cases and controls that were analyzed in stage two.

Additional file 5: Spearman correlation coefficients of ir-lncRNAs with immune checkpoint expression in TCGA-BRCA.

Additional file 2. Stage two database. Include the cases and controls that were analyzed in stage two.

Additional file 9: Table S9. Summary of univariate Cox proportional hazard analysis of the previously identified CpGs. Column variables represent Name; chr; chromosome number, pos; position, CpG name, relation_to_Island; where is CpG located in relationship to island, UCSC RefGene Name; UCSC gene name, UCSC RefGene Accession; UCSC gene accession, UCSC RefGene Group; where in respect to gene is CpG located, Beta; estimated coefficient beta from the model, StandardError; standard error, Z; z-score, LRT; likelihood ratio...

Additional file 4: Supplemental results.1. README. 2. Prevalence range across districts. 3. Prevalence range between sexes. 4. Prevalence range between ages. 5. Age-specific district ranges.

Additional file 5: Spearman correlation coefficients of ir-lncRNAs with immune checkpoint expression in TCGA-BRCA.

Additional file 5: Table S5. Summary of differentially methylated CpGs in recovered and died COVID-19 patients. A. Immune cell comparison between baseline and recovered pairs, B. Significant CpGs between baseline and recovered pairs, C. CpG pathways between baseline and recovered pairs, D. Immune cell comparison between baseline and died pairs, E. Significant CpGs between baseline and died pairs, F. CpG pathways between baseline and died pairs.

Additional file 5: Table S5. Summary of differentially methylated CpGs in recovered and died COVID-19 patients. A. Immune cell comparison between baseline and recovered pairs, B. Significant CpGs between baseline and recovered pairs, C. CpG pathways between baseline and recovered pairs, D. Immune cell comparison between baseline and died pairs, E. Significant CpGs between baseline and died pairs, F. CpG pathways between baseline and died pairs.

Additional file 6: Table S6. Analysis of dead and recovered+A3 COVID-19 patients for immune cell proportions. A. Summary of different models tested for immune cell proportions. Adjusted R2, residual standard error (sigma), AIC, and p-value for each tested model for each cell type are shown. The following models were tested, mod1; Age + MV days + Gender + ICU LoS + ECMO + Nosocomial infections, mod2; Age + Gender + ICU LoS + ECMO +...

Additional file 7: Table S7. Summary of immune cell changes and differentially methylated CpGs between recovered and dead patients over four time points 7A. Immune cell changes between recovered and dead patients over four time points, 7B. Differential methylation of CpGs between recovered and died patients over four time points. The b_0, b_1, b_2, and b_3 coefficients correspond to the reference model parameters, where survival phenotype is used as a reference. The d_0, d_1, d_2,...

Additional file 4: Supplemental results.1. README. 2. Prevalence range across districts. 3. Prevalence range between sexes. 4. Prevalence range between ages. 5. Age-specific district ranges.

Additional file 2: Table S1: List of significantly upregulated miRNAs in OBM compared to OBO. Here RQ refers to Relative Quantification measure using the standard formula [24]. An RQ value showcases the fold-change (FC) of a specific miRNA in two populations. An RQ=1 indicated that a specific miRNA was not differentially expressed in OBM versus OBO samples. Only those miRNAs were considered which were above the limit of quantification (LOQ). Table S2. List of significantly...

Additional file 2: Table S1: List of significantly upregulated miRNAs in OBM compared to OBO. Here RQ refers to Relative Quantification measure using the standard formula [24]. An RQ value showcases the fold-change (FC) of a specific miRNA in two populations. An RQ=1 indicated that a specific miRNA was not differentially expressed in OBM versus OBO samples. Only those miRNAs were considered which were above the limit of quantification (LOQ). Table S2. List of significantly...

Additional file 2: Table S2. Summary of different models tested for estimating differences between controls and COVID-19 patients for immune cell proportions. Adjusted R2, residual standard error (sigma), AIC, and p.value for each tested model for each cell type are shown. The following models were tested, mod1; Age and ethnicity as covariates, mod2; age as a covariate, mod3; ethnicity as a covariate, mod4; no covariates.