New (not yet peer-reviewed) work by Katie Kistler and @huddlej in the lab assessing adaptive evolution in SARS-CoV-2 across the viral genome. 1/12 biorxiv.org/content/10.110…
We measure adaptive evolution by correlating mutations in different regions of the genome with growth of clade frequency. For this, we use a viral phylogeny of ~10k genomes sampled equitably through space and time across the pandemic (nextstrain.org/groups/blab/nc…). 2/12
If mutations to a region result in fitter viruses, clades bearing these mutations should expand more rapidly. We find that the S1 domain of spike accumulates protein-coding (nonsynonymous) changes rapidly and that clades with more S1 mutations tend to grow in frequency. 3/12
As a control we looked at non-protein coding (synonymous) mutations in S1 and nonsynonymous mutations in the RdRp polymerase. In both cases we fail to observe a significant correlation with clade growth. 4/12
Across the genome, we see the highest correlation in the S1 domain of spike, but find weaker (though statistically significant) evidence of adaptive evolution in Nsp6 and ORF7a. 5/12
Focusing on S1, we calculate a common metric called dN/dS that compares nonsynonymous mutations to synonymous mutations. We find that dN/dS in S1 increases through time during the pandemic with the most recent timepoint showing dN/dS of ~2.1. 6/12
This is a fast pace of adaptive evolution and it's rare to observe such a strong signal. HA1 in influenza H3N2 as the canonical example of an adaptively evolving viral protein shows dN/dS of ~0.4, or about 5 times lower than what's currently being observed in SARS-CoV-2. 7/12
Further observations show that nonsynonymous mutations in S1 cluster along the phylogeny quantifying the anecdotal observation that variant viruses often have multiple mutations occurring all together. 8/12
We also observe convergent evolution in individual mutations and identify a subset that occur repeatedly in parallel and when occurring are associated with clade growth. This highlights spike mutations 95I, 452R and 484K as well as a 3 amino acid deletion in Nsp6. 9/12
Most of this rapid pace of evolution is likely due to adaptation to a new host, but in general, this suggests to me that the S1 domain of spike in SARS-CoV-2 is a readily evolvable domain. 10/12
Circulating mutations like 484K partially escape from antibody responses and although I'd anticipate the pace of evolution to slow as the virus becomes endemic in the human population, I would also expect relatively rapid antigenic drift, just given this data. 11/12
We'll of course have to wait to see what unfolds, but I would, at this point, suspect an influenza H3N2-like process of antigenic drift and necessarily frequent vaccine updates in the upcoming years. 12/12
• • •
Missing some Tweet in this thread? You can try to
force a refresh
Currently, the US is reporting about 54k daily cases of COVID-19 (16 per 100k per capita) and the UK is reporting about 4k (6 per 100k). This seems comfortingly low compared to even this summer's BA.5 wave and let alone last winter's BA.1 wave. Figure from @OurWorldInData. 1/16
However, at this point, nearly all infections will be in individuals with prior immunity from vaccination or infection and this combined with a roll back in testing makes it unclear how to interpret current case counts compared to previous time periods. 2/16
We're interested in the case detection rate or the ratio of underlying new infections compared to reported cases. Throughout much of 2020 and 2021, I had a working estimate of 1 infection in ~3.5 getting reported as a case. 3/16
Largely through partial immune escape, lineage BA.5 viruses resulted in sizable epidemics throughout much of the world. However, in most countries these epidemics are now beginning to wind down. What do we expect after BA.5? 1/10
Lineage BA.2.75 (aka 'Centaurus') has been high on watch lists due to sustained increase in frequency in India combined with the presence of multiple mutations to spike protein. We now have enough sampled BA.2.75 viruses from outside India to make some initial conclusions. 2/10
If we look at frequency data we see sustained logistic growth of BA.2.75 in India, Japan, Singapore and the US. Critically, in India it is clearly displacing BA.5. 3/10
Based on the experience in winter 2020/2021, seasonal influence on SARS-CoV-2 transmission is quite clear, but much of the Northern Hemisphere is currently experiencing large summer epidemics driven the spread of evolved BA.5 viruses. 1/11
It's necessarily fraught to try to make predictions of seasonal circulation patterns going forwards, but we can gain some intuition from simple epidemiological models. 2/11
In particular, we can use an SIRS system in which individuals go from Susceptible to Infected to Recovered, and then return to the Susceptible class due to immune waning / antigenic drift of the virus. 3/11
There seems to be a worry that telling people we've exited the "pandemic phase" will lead to further reduced precautions. As always however, I think it's best not to conduct messaging for intended behavioral effect and just try to make scientifically accurate statements. 1/5
Given vaccination and infection, the US and global population now has widespread immunity to SARS-CoV-2 and deaths per-infection are about 10 times lower than they were pre-immunity in 2020 with a ballpark IFR of 0.05% (though this will vary by immunity and age demographics). 2/5
You can see this reduction in mortality rate in looking at projections of deaths from lagged-cases keyed to early case fatality rate. 3/5
The @US_FDA VRBPAC committee will be meeting tomorrow to discuss variant-specific COVID-19 vaccines (fda.gov/advisory-commi…). Based on present observations, I would argue that the most important metric to optimize are titers against BA.4/BA.5 viruses. 1/10
We've seen repeated replacement of SARS-CoV-2 variants during 2022, first of Delta by Omicron BA.1 and then by sub-lineages of Omicron, with BA.2 replacing BA.1 and now with BA.4/BA.5 replacing BA.2. 2/10
Viruses have been evolving to be higher fitness through both increases in intrinsic transmissibility (seen in BA.2 vs BA.1) as well as escape from existing population immunity (seen in Omicron vs Delta as well as BA.4/BA.5 vs BA.2). 3/10
Global monkeypox confirmed and suspected cases compiled by @globaldothealth show initial rapid increase as case-based surveillance comes online, followed by slower continued growth. 1/10
This is data from github.com/globaldothealt… and has had a 7-day smoothing applied and all y-axes are shown on a log scale. 2/10
If we focus on the last 11 days, we can see steady exponential growth in global cases with a ~7.7 day doubling. 3/10