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Quantifying the immunological distinctiveness of emerging SARS-CoV-2 variants in the context of prior regional herd exposure.

Michiel J M NiesenKarthik MurugadossPatrick J LenehanAron Marchler-BauerJiyao WangRyan ConnorJ Rodney BristerA J VenkatakrishnanVenky Soundararajan
Published in: PNAS nexus (2022)
The COVID-19 pandemic has seen the persistent emergence of immune-evasive SARS-CoV-2 variants under the selection pressure of natural and vaccination-acquired immunity. However, it is currently challenging to quantify how immunologically distinct a new variant is compared to all the prior variants to which a population has been exposed. Here, we define "Distinctiveness" of SARS-CoV-2 sequences based on a proteome-wide comparison with all prior sequences from the same geographical region. We observe a correlation between Distinctiveness relative to contemporary sequences and future change in prevalence of a newly circulating lineage (Pearson r  = 0.75), suggesting that the Distinctiveness of emergent SARS-CoV-2 lineages is associated with their epidemiological fitness. We further show that the average Distinctiveness of sequences belonging to a lineage, relative to the Distinctiveness of other sequences that occur at the same place and time ( n  = 944 location/time data points), is predictive of future increases in prevalence (Area Under the Curve, AUC = 0.88 [95% confidence interval 0.86 to 0.90]). By assessing the Delta variant in India versus Brazil, we show that the same lineage can have different Distinctiveness-contributing positions in different geographical regions depending on the other variants that previously circulated in those regions. Finally, we find that positions that constitute epitopes contribute disproportionately (20-fold higher than the average position) to Distinctiveness. Overall, this study suggests that real-time assessment of new SARS-CoV-2 variants in the context of prior regional herd exposure via Distinctiveness can augment genomic surveillance efforts.
Keyphrases
  • sars cov
  • copy number
  • respiratory syndrome coronavirus
  • risk factors
  • single cell
  • public health
  • physical activity
  • current status
  • body composition
  • genome wide
  • cell fate
  • artificial intelligence