Mapping the human genetic architecture of COVID-19 by worldwide meta-analysis

Abstract

The genetic makeup of an individual contributes to susceptibility and response to viral infection. While environmental, clinical and social factors play a role in exposure to SARS-CoV-2 and COVID-19 disease severity, host genetics may also be important. Identifying host-specific genetic factors indicate biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-COV-2 infection and COVID-19 severity. We describe the results of three genome-wide association meta-analyses comprising 49,562 COVID-19 patients from 46 studies across 19 countries worldwide. We reported 15 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases. They also represent potentially actionable mechanisms in response to infection. We further identified smoking and body mass index as causal risk factors for severe COVID-19. The identification of novel host genetic factors associated with COVID-19, with unprecedented speed, was enabled by prioritization of shared resources and analytical frameworks. This working model of international collaboration a blue-print for future genetic discoveries in the event of pandemics or for any complex human disease.

Japan COVID-19 Task Force: a nation-wide consortium to elucidate host genetics of COVID-19 pandemic in Japan

“…The most significant replication was observed at the FOXP4 locus, where the risk allele was known to be more prevalent in East Asians than in Europeans, and expected to have a higher power to be detected in East Asians 16…”

“…We then looked up the MR results in Europeans by using publicly released GWAS summary statistics of COVID-19 Host Genetics Initiative (release 5) 16 . We observed significant causal inferences of obesity consistent with those in Japanese.…”

Insights into genetic factors contributing to variability in SARS-CoV-2 susceptibility and COVID-19 disease severity

“…For each phenotype, four distinct GWASs were performed by either including only individuals from European descent (referred to as European-only hereafter) or individuals from multiple ethnicities (referred to as multi-ethnic hereafter), and using two sets of control individuals either from both the 23andMe and UK Biobank resources or only from 23andMe. Overall, these 16 GWASs identified 15 genomic loci that are significantly associated with SARS-CoV-2 infection and/or COVID-19 severity 12 , confirming that this disease has a strong underlying genetic component. For several of these loci likely causal variants and their associated target genes have been described and replicated in multiple studies, suggesting that genetic variation contributing to COVID-19 disease is present multiple populations.…”

“…Most of these risk factors have a well-known genetic component [9][10][11] , suggesting that risk of SARS-CoV-2 infection and/or disease severity may also be influenced by the genetic background of an individual. The COVID-19 Host Genetics Initiative (COVID-19 HGI, https://www.covid19hg.org/) is currently leading a public effort worldwide to analyze COVID-19 information for millions of individuals in conjunction with genotype data in order to identify genetic variants associated with SARS-CoV-2 infection as well as COVID-19 hospitalization and disease severity 12,13 . To date the COVID-19 HGI has conducted a meta-analysis on four phenotypes (very severe respiratory confirmed COVID-19 vs. population, A2; hospitalized vs. non-hospitalized COVID-19 patients, B1; hospitalized vs. population, B2; and COVID-19 patients vs. population, C2) by combining 46 studies worldwide.…”

Older biological age is associated with adverse COVID-19 outcomes: A cohort study in UK Biobank

“…Our one-sample Mendelian randomisation analysis in UKB had limited power to reliably estimate causal effects as fewer than one thousand participants had been hospitalised after a positive SARS-CoV-2 test and our genetic instrument of 131 variants, while using the most up to date information on LTL-associated variants, accounts for only ~4% of inter-individual variation in LTL. 11 While there are data from large genetic studies of COVID-19 24 , they could not be used in our analysis because the outcome definitions differed substantially from those we used, and because of their inclusion of within hospital testing that is potentially a collider with LTL and COVID-19 outcomes. Larger sample sizes with comparable disease phenotypes should, therefore, enable more precise evaluation of a potential causal association between shorter LTL and adverse COVID-19 outcomes.…”