Forecasting framework for dominant SARS-CoV-2 strains before clade replacement using phylogeny-informed genetic distances - Lee, Kyuyoung; Demirev, Atanas V.; Lee, Sangyi; Cho, Seunghye; Kim, Hyunbeen; Cho, Junhyung; Yang, Jeong-Sun; Kim, Kyung-Chang; Lee, Joo-Yeon; Shin, Woojin; Lee, Soyoung; Park, Sejik; et al. (Frontiers in Microbiology, 2025)
IntroductionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the global coronavirus disease 2019 (COVID-19) pandemic and continues to drive successive waves of infection through the emergence of novel variants. Consequently, accurately predicting the next clade roots through global surveillance is crucial for effective prevention, control, and timely updates of vaccine antigen updates. This study evaluated the evolutionary dynamics of SARS-CoV-2 using phylogeny-informed genetic distances based on 394 complete genomes and spike (S) gene sequences. Furthermore, we introduced a forecasting framework to estimate the potential of emerging variants leading to clade replacement by analyzing non-synonymous and synonymous genetic distances from clade roots, which reflect global herd immune pressure.MethodsNon-synonymous and synonymous genetic distances from both Wuhan and clade root strains were assessed to predict whether a clade would become dominant or extinct within 3 months before the clade replacement.ResultsThrough five observed clade replacements up to January 2024, we captured the quantifiable heterogeneity in non-synonymous and synonymous genetic distances of the S gene from clade roots between dominant and extinct variants, as measured by the extent of novelty, whether through gradual or drastic change.DiscussionOur framework demonstrated high predictability for identifying the next clade root before replacement in both training and test datasets (area under the receiver operating characteristic curve [AUROC] > 0.90) by incorporating differential weighting of non-synonymous and synonymous genetic distances. Additionally, the framework solely using spike gene data demonstrated similar accuracy to those using the complete genome. Overall, our approach establishes quantifiable molecular criteria for identifying potential updates to the SARS-CoV-2 vaccine, contributing to proactive pandemic preparedness.