Esimating the shared genetic eitology and the causal association of potentially modifiable risk factors on SARS-CoV-2 infection and COVID-19 severity using genetic correlation (rg) and Mendelian randomization (MR).
Citation: The COVID-19 Host Genetics Initative. 2021. Mapping the human genetic architecture of COVID-19 by worldwide meta-analysis. MedRxiv. doi:10.1101/2021.03.10.21252820.
A set of 38 disease, health and neuropsychiatric phenotypes were selected as potential COVID-19 risk factors based on their putative relevance to the disease susceptibility, severity, or mortality. Initial risk factors were selected based on guidelines from the CDC and OpenSafely.
docs/mrcovid_exposures.xlsx: excel file listing the traits and respective GWAS used as exposures.
Genome-wide assocations studies for COIVD-19 susceptibility and severity were obtained from Release 5 of the COVID-19 host genetics initiative.
Outcomes included:
- SARS-CoV-2 reported infection
- COVID-19 Hospitalization
- COVID-19 Critical Illness
The Snakemake workflow management system was used to implement pipelines for the rg and MR anlaysis. Rules defineding the snakemake workflows for the rg and MR analyses are avliable in workflow/rules/rg.smk and workflow/rules/mr.smk. Scripts for implementing polygenic risk score analyses were not utlized in this analysis. This pipeline is a adapted from Andrews et al (2020) Annals of Neurology.
Final output files used in the current publication are avaliable in docs/20210224.
Genetic correlations between the exposures and outcomes was estimated using LD Score (LDSC) regression.
Snakefile:
workflow/rules/rg.smk: workflow for implementing MR anlaysis
Configuration files:
config_rg_covid.yaml: parameters for implementing rg analysis
Script files:
workflow/scripts/rg_*: script files for implementing spefific rules in the rg workflow
Mendelian randomization analysis was conducted using the TwoSampleMR package. Primary analysis was conducted using IVW to estimated causal relationships, while senstivity analysis were conducted using WME, WMBE, MR-Egger and MR-PRESSO.
Snakefile
workflow/rules/mr.smk: workflow for implementing MR anlaysis
Configuration files
config_covid_eur.yaml: analysis parameters for MR analysis COIVD-19 ouctomes using EUR only popultionsconfig_covid_eur_wo_ukbb.yaml: analysis parameters for MR analysis COIVD-19 ouctomes using EUR only popultions, without samples from UKBB
Script files
workflow/scripts/mr_*: script files for implementing spefific rules in MR workflow
Genetic correlations and Mendelian randomization causal estimates between 38 traits and COVID-19 Critical Illness, COVID-19 Hospitalization and SARS-CoV-2 reported infection. Blue, negative genetic correlation and protective Mendelian randomization (MR) causal estimates; red, positive genetic correlation and risk MR causal estimates. Larger squares correspond to more significant P values, with genetic correlations or MR causal estimates significantly different from zero at a P < 0.05 shown as a full-sized square. Genetic correlations or causal estimates that are significantly different from zero at a false discovery rate (FDR) of 5% are marked with an asterisk. Forest plots display the causal estimates for each of the sensitivity analyses used in the MR analysis for trait pairs that were significant at an FDR of 5%. Individual scatter and funnel plots for each pair of traits are available in docs/20210224/MRcovideur_MRScatterFunnelPlots.pdf.
IVW: Inverse variance weighted analysis; WME: Weighted median estimator; WMBE: weighted mode based estimator; MR-PRESSO: Mendelian Randomization Pleiotropy RESidual Sum and Outlier. RBC: Red blood cell count
Genetic correlation results:
data/RGcovidcontains intermediatry files generated during rg workflowresults/RGcovidcontains final results for rg analysis
MR results
data/MRcovideur, anddata/MRcovideurwoukbbcontain intermediatry files generated during MR workflowresults/MRcovideur, andresults/MRcovideurwoukbbcontain final results for MR analysis