| Title: | Genome-wide epistasis study highlights genetic interactions influencing severity of COVID-19 |
| Journal: | European Journal of Epidemiology |
| Published: | 26 Jun 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37358671/ |
| DOI: | https://doi.org/10.1007/s10654-023-01020-5 |
Publication 10927
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Abstract
Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may lead to life-threatening respiratory symptoms. Understanding the genetic basis of the prognosis of COVID-19 is important for risk profiling of potentially severe symptoms. Here, we conducted a genome-wide epistasis study of COVID-19 severity in 2243 patients with severe symptoms and 12,612 patients with no or mild symptoms from the UK Biobank, followed by a replication study in an independent Spanish cohort (1416 cases, 4382 controls). Our study highlighted 3 interactions with genome-wide significance in the discovery phase, nominally significant in the replication phase, and enhanced significance in the meta-analysis. For example, the lead interaction was found between rs9792388 upstream of PDGFRL and rs3025892 downstream of SNAP25, where the composite genotype of rs3025892 CT and rs9792388 CA/AA showed higher risk of severe disease than any other genotypes (P = 2.77 × 10-12, proportion of severe cases = 0.24 ~ 0.29 vs. 0.09 ~ 0.18, genotypic OR = 1.96 ~ 2.70). This interaction was replicated in the Spanish cohort (P = 0.002, proportion of severe cases = 0.30 ~ 0.36 vs. 0.14 ~ 0.25, genotypic OR = 1.45 ~ 2.37) and showed enhanced significance in the meta-analysis (P = 4.97 × 10-14). Notably, these interactions indicated a possible molecular mechanism by which SARS-CoV-2 affects the nervous system. The first exhaustive genome-wide screening for epistasis improved our understanding of genetic basis underlying the severity of COVID-19.</p>
17 Authors
- Shiqi Lin
- Xingjian Gao
- Frauke Degenhardt
- Yu Qian
- Tianzi Liu
- Xavier Farre Ramon
- Syed Sibte Hadi
- Manuel Romero-Gómez
- Javier Fernández
- Agustín Albillos
- Maria Buti Ferret
- Luis Bujanda
- Antonio Julià
- Rafael de Cid
- Rosanna Asselta
- Andre Franke
- Fan Liu
1 Application
| Application ID | Title |
|---|---|
| 67076 | Estimating the correlation of various genetic and non-genetic factors with severity and outcome of COVID-19. |
Enabling scientific discoveries that improve human health