{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Zhang X"],"funding":["Beijing Municipal Natural Science Foundation","Guangdong-PHOENIX Center Joint Lab on Chinese Medicine","State Key Laboratory of Proteomics","Science and Technology Planning Project of Guangdong Province","National Key R&D Program of China","Capital Health Development Research Project","National Key Research and Development Program of China","Beijing Municipal International Cooperation and Exchange Project","Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine"],"pagination":["e2402639"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11516136"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["11(40)"],"pubmed_abstract":["Host immunity is central to the virus's spread dynamics, which is significantly influenced by vaccination and prior infection experiences. In this work, we analyzed the co-evolution of SARS-CoV-2 mutation, angiotensin-converting enzyme 2 (ACE2) receptor binding, and neutralizing antibody (NAb) responses across various variants in 822 human and mice vaccinated with different non-Omicron and Omicron vaccines is analyzed. The link between vaccine efficacy and vaccine type, dosing, and post-vaccination duration is revealed. The classification of immune protection against non-Omicron and Omicron variants is co-evolved with genetic mutations and vaccination. Additionally, a model, the Prevalence Score (P-Score) is introduced, which surpasses previous algorithm-based models in predicting the pote"],"journal":["Advanced science (Weinheim, Baden-Wurttemberg, Germany)"],"pubmed_title":["SARS-CoV-2 Evolution: Immune Dynamics, Omicron Specificity, and Predictive Modeling in Vaccinated Populations."],"pmcid":["PMC11516136"],"funding_grant_id":["ZYYCXTD-C-202204","2024-1-4093","2022YFE0210400","2023YFC0872400","2020B1111100006","Z231100002723004","L234034","SKLP-O202007","SKLP-O202205","2021YFA1301604","YN2021DB06","2024-1-1201","M23010","YN2021DB03"],"pubmed_authors":["Li H","Zhu Y","Wang B","Zhang N","Teng F","Guo S","Li M","Li Y","Zhang X","Jia Y","Xu X","Wang Y","Yu X","Qin C"],"additional_accession":[]},"is_claimable":false,"name":"SARS-CoV-2 Evolution: Immune Dynamics, Omicron Specificity, and Predictive Modeling in Vaccinated Populations.","description":"Host immunity is central to the virus's spread dynamics, which is significantly influenced by vaccination and prior infection experiences. In this work, we analyzed the co-evolution of SARS-CoV-2 mutation, angiotensin-converting enzyme 2 (ACE2) receptor binding, and neutralizing antibody (NAb) responses across various variants in 822 human and mice vaccinated with different non-Omicron and Omicron vaccines is analyzed. The link between vaccine efficacy and vaccine type, dosing, and post-vaccination duration is revealed. The classification of immune protection against non-Omicron and Omicron variants is co-evolved with genetic mutations and vaccination. Additionally, a model, the Prevalence Score (P-Score) is introduced, which surpasses previous algorithm-based models in predicting the pote","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Oct","modification":"2026-04-30T00:11:37.464Z","creation":"2025-04-04T00:30:02.57Z"},"accession":"S-EPMC11516136","cross_references":{"pubmed":["39206813"],"doi":["10.1002/advs.202402639"]}}