Description
This track set shows the results of the
GWAS Data Release 4 (October 2020)
from the
COVID-19 Host Genetics Initiative (HGI):
a collaborative effort to facilitate
the generation of meta-analysis across multiple studies contributed by
partners world-wide
to identify the genetic determinants of SARS-CoV-2 infection susceptibility, disease severity
and outcomes. The COVID-19 HGI also aims to provide a platform for study partners to
share analytical results in the form of summary statistics and/or individual level data of COVID-19
host genetics research. At the time of this release, a total of 137 studies were registered with
this effort.
The specific phenotypes studied by the COVID-19 HGI are those that benefit from maximal sample
size: primary analysis on disease severity. For the Data Release 4 the number of cases have
increased by nearly ten-fold (more than 30,000 COVID-19 cases and 1.47 million controls) by combining
data from 34 studies across 16 countries.
The four tracks here are based on data from HGI meta-analyses A2, B2, C1, and C2, described here:
- Severe COVID vars (A2): Cases with very severe respiratory failure confirmed
for COVID-19 vs. population (i.e. everybody that is not a case).
The increased sample size resulted in strong evidence of
seven genomic regions associated with severe COVID-19 and one additional signal associated with
COVID-19 partial-susceptibility. Many of these regions were identified by the
Genetics of Mortality in Critical Care (GenOMICC)
study and are shown below (table adapted from
Pairo-Castineira et. al.).
- Hosp COVID vars (B2): Cases hospitalized and confirmed for COVID-19 vs.
population (i.e. everybody that is not a case)
- Tested COVID vars (C1): Cases with laboratory confirmed SARS-CoV-2 infection, or
health record/physician-confirmed COVID-19, or self-reported COVID-19 via questionare vs. laboratory
/self-reported negative cases
- All COVID vars (C2): Cases with laboratory confirmed SARS-CoV-2 infection, or
health record/physician-confirmed COVID-19, or self-reported COVID-19 vs. population (i.e. everybody
that is not a case)
Due to privacy concerns, these browser tracks exclude data provided by 23andMe contributed
studies in the full analysis results. The actual study and case
and control counts for the individual browser tracks are listed in the track labels. Details on
all studies can be found here.
Display Conventions
Displayed items are colored by GWAS effect: red for positive (harmful) effect,
blue for negative (protective) effect.
The height ('lollipop stem') of the item is based on statistical significance (p-value).
For better visualization of the data, only SNPs with p-values smaller than 1e-3 are
displayed by default.
The color saturation indicates effect size (beta coefficient): values over the median of effect
size are brightly colored (bright red
, bright blue
),
those below the median are paler (light red
, light blue
).
Each track has separate display controls and data can be filtered according to the
number of studies, minimum -log10 p-value, and the
effect size (beta coefficient), using the track Configure options.
Mouseover on items shows the rs ID (or chrom:pos if none assigned), both the non-effect
and effect alleles, the effect size (beta coefficient), the p-value, and the number of
studies.
Additional information on each variant can be found on the details page by clicking on
the item.
Methods
COVID-19 Host Genetics Initiative (HGI) GWAS meta-analysis round 4 (October 2020) results were
used in this study.
Each participating study partner submitted GWAS summary statistics for up to four
of the COVID-19 phenotype definitions.
Data were generated from genome-wide SNP array and whole exome and genome
sequencing, leveraging the impact of both common and rare variants. The statistical analysis
performed takes into account differences between sex, ancestry, and date of sample collection.
Alleles were harmonized across studies and reported allele frequencies are based on gnomAD
version 3.0 reference data. Most study partners used the SAIGE GWAS pipeline in order
to generate summary statistics used for the COVID-19 HGI meta-analysis. The summary statistics
of individual studies were manually examined for inflation,
deflation, and excessive number of false positives.
Qualifying summary statistics were filtered for
INFO > 0.6 and MAF > 0.0001 prior to meta-analyzing the entirety of the data.
The meta-analysis was performed using fixed effects inverse variance weighting.
The meta-analysis software and workflow are available here. More information about the
prospective studies, processing pipeline, results and data sharing can be found
here.
Data Access
The data underlying these tracks and summary statistics results are publicly available in COVID19-hg Release 4 (October 2020).
The raw data can be explored interactively with the
Table Browser, or the Data Integrator.
Please refer to
our mailing list archives for questions, or our Data Access FAQ for more information.
Credits
Thanks to the COVID-19 Host Genetics Initiative contributors and project leads for making these
data available, and in particular to Rachel Liao, Juha Karjalainen, and Kumar Veerapen at the
Broad Institute for their review and input during browser track development.
References
COVID-19 Host Genetics Initiative.
The COVID-19 Host Genetics Initiative, a global initiative to elucidate the role of host genetic
factors in susceptibility and severity of the SARS-CoV-2 virus pandemic.
Eur J Hum Genet. 2020 Jun;28(6):715-718.
PMID: 32404885; PMC: PMC7220587
Pairo-Castineira E, Clohisey S, Klaric L, Bretherick AD, Rawlik K, Pasko D, Walker S, Parkinson N,
Fourman MH, Russell CD et al.
Genetic mechanisms of critical illness in Covid-19.
Nature. 2020 Dec 11;.
PMID: 33307546
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