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• W4283802009 abstract "Abstract 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." @default.
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• W4283802009 date "2022-07-01" @default.
• W4283802009 modified "2023-10-16" @default.
• W4283802009 title "Quantifying the immunological distinctiveness of emerging SARS-CoV-2 variants in the context of prior regional herd exposure" @default.
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• W4283802009 doi "https://doi.org/10.1093/pnasnexus/pgac105" @default.
• W4283802009 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35899067" @default.
• W4283802009 hasPublicationYear "2022" @default.
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