Evidence map›Paper›PMID 38483913›Full record

ArticlePloS one2024

Unravelling the link between SARS-CoV-2 mutation frequencies, patient comorbidities, and structural dynamics.

Amirah Azzeri, Nurul Azmawati Mohamed, Saarah Huurieyah Wan Rosli, Muttaqillah Najihan Abdul Samat, Zetti Zainol Rashid, Muhamad Arif Mohamad Jamali, Muhammad Zarul Hanifah Md Zoqratt, Muhammad Azamuddeen Mohammad Nasir, Harpreet Kaur Ranjit Singh, Liyana Azmi

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Amirah AzzeriFaculty of Medicine and Health Sciences, Universiti Sains Islam Malaysia, Nilai, Negeri Sembilan, Malaysia.
Nurul Azmawati MohamedFaculty of Medicine and Health Sciences, Universiti Sains Islam Malaysia, Nilai, Negeri Sembilan, Malaysia.
Saarah Huurieyah Wan RosliFaculty of Medicine and Health Sciences, Universiti Sains Islam Malaysia, Nilai, Negeri Sembilan, Malaysia.ORCID 0000-0002-7904-8984
Muttaqillah Najihan Abdul SamatDepartment of Medical Microbiology and Immunology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Cheras, Kuala Lumpur, Malaysia.
Zetti Zainol RashidDepartment of Medical Microbiology and Immunology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Cheras, Kuala Lumpur, Malaysia.
Muhamad Arif Mohamad JamaliFaculty of Science and Technology, Universiti Sains Islam Malaysia, Nilai, Negeri Sembilan, Malaysia.
Muhammad Zarul Hanifah Md ZoqrattFast Genomics Solutions, Subang Jaya, Selangor Darul Ehsan, Malaysia.ORCID 0000-0002-5075-1828
Muhammad Azamuddeen Mohammad NasirFast Genomics Solutions, Subang Jaya, Selangor Darul Ehsan, Malaysia.
Harpreet Kaur Ranjit SinghFast Genomics Solutions, Subang Jaya, Selangor Darul Ehsan, Malaysia.
Liyana AzmiFaculty of Medicine and Health Sciences, Universiti Sains Islam Malaysia, Nilai, Negeri Sembilan, Malaysia.ORCID 0000-0002-7149-8016

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomic surveillance is crucial for tracking emergence and spread of novel variants of pathogens, such as SARS-CoV-2, to inform public health interventions and to enforce control measures. However, in some settings especially in low- and middle- income counties, where sequencing platforms are limited, only certain patients get to be selected for sequencing surveillance. Here, we show that patients with multiple comorbidities potentially harbour SARS-CoV-2 with higher mutation rates and thus deserve more attention for genomic surveillance. The relationship between the patient comorbidities, and type of amino acid mutations was assessed. Correlation analysis showed that there was a significant tendency for mutations to occur within the ORF1a region for patients with higher number of comorbidities. Frequency analysis of the amino acid substitution within ORF1a showed that nsp3 P822L of the PLpro protease was one of the highest occurring mutations. Using molecular dynamics, we simulated that the P822L mutation in PLpro represents a system with lower Root Mean Square Deviation (RMSD) fluctuations, and consistent Radius of gyration (Rg), Solvent Accessible Surface Area (SASA) values-indicate a much stabler protein than the wildtype. The outcome of this study will help determine the relationship between the clinical status of a patient and the mutations of the infecting SARS-CoV-2 virus.

Indexed as

COVID-19Mutation RateAmino Acid SubstitutionHumansMolecular Dynamics SimulationMutationSARS-CoV-2

Identifiers

PMID38483913
PMCPMC10939192

What Socratic holds

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LicenceCC BY
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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 Socratic graph.