Rare predicted loss-of-function variants of type I IFN immunity genes are associated with critical COVID-19

BackgroundWe previously reported inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity in 1-5% of unvaccinated patients with life-threatening COVID-19, and auto-antibodies against type I IFN in another 15-20% of cases. MethodsWe report here a genome-wide rare variant burden association analysis in 3,269 unvaccinated patients with life-threatening COVID-19 (1,301 previously reported and 1,968 new patients), and 1,373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. A quarter of the patients tested had antibodies against type I IFN (234 of 928) and were excluded from the analysis. ResultsNo gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI:1.5-528.7, P=1.1x10-4), in analyses restricted to biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR=3.70 [95%CI:1.3-8.2], P=2.1x10-4). Adding the recently reported TYK2 COVID-19 locus strengthened this enrichment, particularly under a recessive model (OR=19.65 [95%CI:2.1-2635.4]; P=3.4x10-3). When these 14 loci and TLR7 were considered, all individuals hemizygous (n=20) or homozygous (n=5) for pLOF or bLOF variants were patients (OR=39.19 [95%CI:5.2-5037.0], P=4.7x10-7), who also showed an enrichment in heterozygous variants (OR=2.36 [95%CI:1.0-5.9], P=0.02). Finally, the patients with pLOF or bLOF variants at these 15 loci were significantly younger (mean age [SD]=43.3 [20.3] years) than the other patients (56.0 [17.3] years; P=1.68x10-5). ConclusionsRare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old.

The butterfly effect: mutational bias of SARS-CoV-2 affects its pattern of molecular evolution on synonymous and nonsynonymous levels

Evolution is a function of mutagenesis and selection. To analyse the role of mutagenesis on the structure of the SARS-CoV-2 genome, we reconstructed the mutational spectrum, which was highly C>U and G>U biased. This bias forces the SARS-CoV-2 genome to become increasingly U-rich unless selection cancels it. We analysed the consequences of this bias on the composition of the most neutral (four-fold degenerate synonymous substitutions) and the least neutral positions (nonsynonymous substitutions). The neutral nucleotide composition is already highly saturated by U and, according to our model, it is at equilibrium, suggesting that in the future, we dont expect any more increase in U. However, nonsynonymous changes continue slowly evolve towards equilibrium substituting CG-rich amino-acids ("losers") with U-rich ones ("gainers"). This process is universal for all genes of SARS-CoV-2 as well as for other coronaviridae species. In line with the direction mutation pressure hypothesis, we show that viral-specific amino acid content is associated with the viral-specific mutational spectrum due to the accumulation of effectively neutral slightly deleterious variants (losers to gainers) during the molecular evolution. The tuning of a protein space by the mutational process is expected to be typical for species with relaxed purifying selection, suggesting that the purging of slightly-deleterious variants in the SARS-CoV-2 population is not very effective, probably due to the fast expansion of the viral population during the pandemic. Understanding the mutational process can help to design more robust vaccines, based on gainer-rich motifs, close to the mutation-selection equilibrium.

Assessing the impact of non-pharmaceutical interventions on SARS-CoV-2 transmission in Switzerland

Following the rapid dissemination of COVID-19 cases in Switzerland, large-scale non-pharmaceutical interventions (NPIs) were implemented by the cantons and the federal government between February 28 and March 20. Estimates of the impact of these interventions on SARS-CoV-2 transmission are critical for decision making in this and future outbreaks. We here aim to assess the impact of these NPIs on disease transmission by estimating changes in the basic reproduction number (R0) at national and cantonal levels in relation to the timing of these NPIs. We estimate the time-varying R0 nationally and in twelve cantons by fitting a stochastic transmission model explicitly simulating within hospital dynamics. We use individual-level data of >1,000 hospitalized patients in Switzerland and public daily reports of hospitalizations and deaths. We estimate the national R0 was 3.15 (95% CI: 2.13-3.76) at the start of the epidemic. Starting from around March 6, we find a strong reduction in R0 with a 85% median decrease (95% quantile range, QR: 83%-90%) to a value of 0.44 (95% QR: 0.27-0.65) in the period of March 29-April 5. At the cantonal-level R0 decreased over the course of the epidemic between 71% and 94%. We found that reductions in R0 were synchronous with changes in mobility patterns as estimated through smartphone activity, which started before the official implementation of NPIs. We found that most of the reduction of transmission is due to behavioural changes as opposed to natural immunity, the latter accounting for only about 3% of the total reduction in effective transmission. As Switzerland considers relaxing some of the restrictions of social mixing, current estimates of R0 well below one are promising. However most of inferred transmission reduction was due to behaviour change (<3% due to natural immunity buildup), with an estimated 97% (95% QR: 96.6%-97.2%) of the Swiss population still susceptible to SARS-CoV-2 as of April 24. These results warrant a cautious relaxation of social distance practices and close monitoring of changes in both the basic and effective reproduction numbers.