Evidence map›Paper›PMID 38736749›Full record

ArticleFrontiers in cellular and infection microbiology2024

Seasonal human coronavirus NL63 epidemics in children in Guilin, China, reveal the emergence of a new subgenotype of HCoV-NL63.

Renhe Zhu, Rundong Cao, Lulu Wang, Yue Gong, Qian Cheng, Hu Long, Dong Xia, Qinqin Song, Zhiqiang Xia, Mi Liu and 4 more

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

14 authors.

Renhe ZhuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Rundong CaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Lulu WangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yue GongNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Qian ChengNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Hu LongEpidemic Prevention and Control Department, Guilin Center for Disease Control and Prevention, Guilin, China.
Dong XiaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Qinqin SongNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Zhiqiang XiaNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Mi LiuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
HaiJun DuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Juan SongNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Jun HanNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Chen GaoNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Seasonal human coronavirus NL63 (HCoV-NL63) is a frequently encountered virus linked to mild upper respiratory infections. However, its potential to cause more severe or widespread disease remains an area of concern. This study aimed to investigate a rare localized epidemic of HCoV-NL63-induced respiratory infections among pediatric patients in Guilin, China, and to understand the viral subtype distribution and genetic characteristics. Methods: In this study, 83 pediatric patients hospitalized with acute respiratory infections and positive for HCoV-NL63 were enrolled. Molecular analysis was conducted to identify the viral subgenotypes and to assess genetic variations in the receptor-binding domain of the spiking protein. Results: Among the 83 HCoV-NL63-positive children, three subgenotypes were identified: C4, C3, and B. Notably, 21 cases exhibited a previously unreported subtype, C4. Analysis of the C4 subtype revealed a unique amino acid mutation (I507L) in the receptor-binding domain of the spiking protein, which was also observed in the previously reported C3 genotype. This mutation may suggest potential increases in viral transmissibility and pathogenicity. Discussion: The findings of this study highlight the rapid mutation dynamics of HCoV-NL63 and its potential for increased virulence and epidemic transmission. The presence of a unique mutation in the C4 subtype, shared with the C3 genotype, raises concerns about the virus's evolving nature and its potential public health implications. This research contributes valuable insights into the understanding of HCoV-NL63's epidemiology and pathogenesis, which is crucial for effective disease prevention and control strategies. Future studies are needed to further investigate the biological significance of the observed mutation and its potential impact on the virus's transmissibility and pathogenicity.

Indexed as

Coronavirus InfectionsCoronavirus NL63, HumanEpidemicsGenotypePhylogenyRespiratory Tract InfectionsAdolescentChildChild, PreschoolChinaFemaleHumansInfantMaleMutationSeasonsSpike Glycoprotein, Coronavirusclinical characteristicshuman coronavirus NL63molecular epidemiologynew subgenotypewhole-genome sequencing

Identifiers

PMID38736749
PMCPMC11082418

What OpenQuestion holds

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Registered trials

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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.