Integrative genomics analysis reveals a 21q22.11 locus contributing risk to COVID-19

Abstract

The systematic identification of host genetic risk factors is essential for the understanding and treatment of coronavirus disease 2019 (COVID-19). By performing a meta-analysis of two independent genome-wide association summary datasets (N = 680 128), a novel locus at 21q22.11 was identified to be associated with COVID-19 infection (rs9976829 in IFNAR2-IL10RB, odds ratio = 1.16, 95% confidence interval = 1.09–1.23, P = 2.57 × 10−6). The rs9976829 represents a strong splicing quantitative trait locus for both IFNAR2 and IL10RB genes, especially in lung tissue (P = 1.8 × 10−24). Integrative genomics analysis of combining genome-wide association study with expression quantitative trait locus data showed the expression variations of IFNAR2 and IL10RB have prominent effects on COVID-19 in various types of tissues, especially in lung tissue. The majority of IFNAR2-expressing cells were dendritic cells (40%) and plasmacytoid dendritic cells (38.5%), and IL10RB-expressing cells were mainly nonclassical monocytes (29.6%). IFNAR2 and IL10RB are targeted by several interferons-related drugs. Together, our results uncover 21q22.11 as a novel susceptibility locus for COVID-19, in which individuals with G alleles of rs9976829 have a higher probability of COVID-19 susceptibility than those with non-G alleles.

Single cell sequencing analysis uncovers genetics-influenced CD16+monocytes and memory CD8+T cells involved in severe COVID-19

“…Furthermore, the index SNP of rs505922 (P = 2.24×10 −9 ) in the 9q34.2 locus is highly LD with the reported SNP of rs657152 (R 2 = 0.874) [27] and rs8176719 (R 2 = 0.876) [25]. Based on the top-ranked V2G score for rs505922, we prioritized ABO as a potential causal gene contributing susceptibility to severe COVID-19.…”

“…The result of a network-based enrichment analysis suggested that 22 of 34 risk genes were significantly enriched in a PPI subnetwork (P = 2.85×10 −13 , Figure 2D), which is consistent with the consensus that disease-related genes are more densely connected [50, 51]. To functionally characterize the drug targets of these genes, we conducted a drug-gene interaction analysis and identified 11 genes including CCR1, IFNAR2, IL10RB , and OAS1 were targeted by at least one known drug (Figure 2D and Supplemental Figure S14), of which some genes including CCR1, IFNAR2 , and IL10RB have been reported to be drug targets for treating severe COVID-19 patients [25, 26]. Furthermore, these 34 genes were significantly enriched in a functional module consisting of 10 biological pathways (Figure 2E, Supplemental Table S8 and Figure S13), among which two top-ranked ones being cytokine-cytokine receptor interaction and chemokine signaling pathway (FDR < 0.05).…”

“…Furthermore, these 34 genes were significantly enriched in a functional module consisting of 10 biological pathways (Figure 2E, Supplemental Table S8 and Figure S13), among which two top-ranked ones being cytokine-cytokine receptor interaction and chemokine signaling pathway (FDR < 0.05). Most of these enriched pathways have been reported to be implicated in COVID-19 [25, 52, 53].…”

“…Ellinghaus et al [27] performed a meta-analysis of two independent GWAS datasets with 1,610 severe COVID-19 patients and 2,205 matched controls at seven hospitals in the Italian and Spanish epicenters, and identified two susceptibility loci of 3p21.31 and 9q34.2 to be significantly associated with severe COVID-19 at the genome-wide level. Based on a large-scale meta-analysis (N = 680,128), our group found that the IFNAR2-IL10RB gene cluster were significantly associated with COVID-19 susceptibility, and suggested that IFNAR2 and IL10RB might have regulatory roles in the pulmonary immune response based on scRNA-seq data [25]. Consistently, Pairo-Gastineira et al [24] conducted a GWAS study based on 2,244 critically ill COVID-19 patients and highlighted that several genes including IFNAR2, DPP9 , and OAS1 were significantly associated with severe COVID-19 at a genome-wide significance.…”

Bench Research Informed by GWAS Results

“…These methods provide an interface between genetic epidemiological data and molecular phenotypes, such as cell-specific gene expression, active chromatin markers, DNA methylation and chromosome interactions, and allow one to assess the enrichment of genetic associations with various functional ontologies. These methods can be used to demonstrate enrichment of specific gene ontologies, like neurogenesis and locomotor behaviour in restless legs syndrome [2], cytokine signalling pathways for COVID-19 [138], cell growth and synapse organisation for volume of lateral nuclei [139] and cell adhesion and transsynaptic signalling for Tourette syndrome [140]. Hormozdiari et al, applied S-LDSC on sets of functional SNPs (eQTLs, etc.,) and found that they are indeed enriched for heritability in an expected, cell type-specific manner [141].…”