Multi-omics analyses of the complex interplay between genetic variants, DNA methylation, and gene expression in COVID-19
Background: SARS-CoV-2, which drove the 2019 COVID-19 pandemic, continues to engender inquiries into the role of host genetic factors in disease susceptibility. Despite the identification of over 1,000 genes potentially associated with SARS-CoV-2 and COVID-19, the mechanisms connecting genetic variants to phenotype remain elusive. To shed light on these mechanisms, we undertook an integrated analysis, merging data from whole-genome association analyses of COVID-19 with methylome and transcriptomic.
Methods: Study includes African American adults from the GENE-FORECAST study, encompassing 371 individuals with whole genome sequencing (WGS), 203 with DNA methylation, and 321 with RNA sequencing (RNA-Seq). 53.3% of participants reported COVID-19. Significant loci associated with COVID-19 were examined within the framework of methylation quantitative trait loci (mQTL) which located near the gene-of-original (cis-mQTL) and expression quantitative trait loci (eQTL) which located near the gene-of-origin (cis-eQTL), enabling analysis to assess mediators between genetic variants and COVID-19 status.
Results: Our analysis identified four intronic variants and confirmed a missense variant, rs1052067, in PMF1 associated with COVID-19. Within the PMF region, we identified six cis-eQTLs and twenty cis-mQTLs. Mediation analysis revealed that genetic variants within PMF1 influenced COVID-19 status through two mediators: one cis-eQTL (GLMP) and three cis-mQTLs (ARHGEF2, TMEM79, and MEX3A).
Conclusions: Through integrated multi-omics analyses, we identified genetic variants whose effects on COVID-19 susceptibility are mediated by changes in DNA methylation and mRNA expression. These findings offer insights into potential mechanistic pathways that merit further exploration.
