Evidence map›Paper›PMID 40620492›Full record

ArticleFrontiers in microbiology2025

Forecasting framework for dominant SARS-CoV-2 strains before clade replacement using phylogeny-informed genetic distances.

Kyuyoung Lee, Atanas V Demirev, Sangyi Lee, Seunghye Cho, Hyunbeen Kim, Junhyung Cho, Jeong-Sun Yang, Kyung-Chang Kim, Joo-Yeon Lee, Woojin Shin and 5 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Kyuyoung LeeDepartment of Microbiology, Institute for Viral Diseases, Korea University College of Medicine, Seoul, Republic of Korea.
Atanas V DemirevDepartment of Microbiology, Institute for Viral Diseases, Korea University College of Medicine, Seoul, Republic of Korea.
Sangyi LeeDepartment of Microbiology, Institute for Viral Diseases, Korea University College of Medicine, Seoul, Republic of Korea.
Seunghye ChoDepartment of Microbiology, Institute for Viral Diseases, Korea University College of Medicine, Seoul, Republic of Korea.
Hyunbeen KimDepartment of Microbiology, Institute for Viral Diseases, Korea University College of Medicine, Seoul, Republic of Korea.
Junhyung ChoDivision of Emerging Viral Diseases and Vector Research, Center for Infectious Diseases Research, National Institute of Infectious Diseases, Korea National Institute of Health, Osong, Republic of Korea.
Jeong-Sun YangDivision of Emerging Viral Diseases and Vector Research, Center for Infectious Diseases Research, National Institute of Infectious Diseases, Korea National Institute of Health, Osong, Republic of Korea.
Kyung-Chang KimDivision of Emerging Viral Diseases and Vector Research, Center for Infectious Diseases Research, National Institute of Infectious Diseases, Korea National Institute of Health, Osong, Republic of Korea.
Joo-Yeon LeeCenter for Infectious Diseases Research, National Institute of Infectious Diseases, Korea National Institute of Health, Osong, Republic of Korea.
Woojin ShinDepartment of Microbiology, Institute for Viral Diseases, Korea University College of Medicine, Seoul, Republic of Korea.
Soyoung LeeDepartment of Microbiology, Institute for Viral Diseases, Korea University College of Medicine, Seoul, Republic of Korea.
Sejik ParkDepartment of Microbiology, Institute for Viral Diseases, Korea University College of Medicine, Seoul, Republic of Korea.
Philippe LemeyDepartment of Microbiology, Immunology, and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium.
Man-Seong ParkDepartment of Microbiology, Institute for Viral Diseases, Korea University College of Medicine, Seoul, Republic of Korea.
Jin Il KimDepartment of Microbiology, Institute for Viral Diseases, Korea University College of Medicine, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Severe 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. Methods: Non-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. Results: Through 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. Discussion: Our 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.

Indexed as

clade replacementdominanceevolutionforecasting frameworkSARS-CoV-2spike gene

Identifiers

PMID40620492
PMCPMC12226564

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.