This track shows variants associated with monogenic congenital defects of immunity to SARS-CoV-2, with incomplete or complete penetrance from the COVID Human Genetic Effort. This international consortium aims to detect rare or common monogenic inborn immunity errors (IEI) underlying severe forms of COVID-19 in previously healthy individuals, as well as rare or common monogenic variations that make certain -individuals resistant to the infection by SARS-CoV2 itself despite repeated exposure. +individuals resistant to the infection by SARS-CoV2 virus despite repeated exposure.
The major feature of the small set of variants in this track is that they are functionally tested to be deleterious and genetically tested to be disease-causing. Specifically, rare variants were predicted to be loss-of-function (LOF) at 13 human loci known to govern TLR3- and IRF7-dependent type I interferon (IFN) immunity to influenza virus in patients with life-threatening COVID-19 pneumonia, relative to subjects with asymptomatic or benign infection. These genetic defects display incomplete penetrance for influenza respiratory distress and only manifested clinically upon infection with the more virulent SARS-CoV-2.
Variant calls in 12 autosomal IFN-related genes from whole exome or genome data with a MAF lower than 0.001 (gnomAD v2.1.1) and experimental demonstration of loss-of-function (LOF) were considered -for statistical analysis. Proportion of individuals carrying at least one pLOF variant was compared -between cases and controls by means of logistic regression with the likelihood ratio test. The first -three principal components of the PCA were included in the logistic regression model to account for -ethnic heterogeneity of the cohorts. Analysis of enrichment in rare (MAF < 0.001) synonymous -variants of the 12 genes was performed to check the calibration of the burden test. PCA war +for statistical analysis. The proportion of individuals carrying at least one pLOF variant was +compared between cases and controls by means of logistic regression with the likelihood ratio test. +The first three principal components of the PCA were included in the logistic regression model +to account for ethnic heterogeneity of the cohorts. +Analysis of enrichment in rare (MAF < 0.001) synonymous +variants of the 12 genes was performed to check the calibration of the burden test. PCA was conducted with Plink v1.9 software on whole exome and genome sequencing data and 1000 Genomes (1kG) Project phase 3 public database as reference, using 27,480 exonic variants with a minor allele frequency >0.01 and a call rate >0.99. The odds ratio was also estimated by logistic regression and adjusted for ethnic heterogeneity.
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