Evidence map›Paper›PMID 36215001›Full record

ArticleInflammation2023

SARS-CoV-2 Variants Show a Gradual Declining Pathogenicity and Pro-Inflammatory Cytokine Stimulation, an Increasing Antigenic and Anti-Inflammatory Cytokine Induction, and Rising Structural Protein Instability: A Minimal Number Genome-Based Approach.

Debmalya Barh, Sandeep Tiwari, Lucas Gabriel Rodrigues Gomes, Cecília Horta Ramalho Pinto, Bruno Silva Andrade, Shaban Ahmad, Alaa A A Aljabali, Khalid J Alzahrani, Hamsa Jameel Banjer, Sk Sarif Hassan and 8 more

Open access · bronzeAbstract read
In one paragraph

Article in Inflammation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
3.8field-weighted citation impact, top 5% of its field
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

32 citing papers in PubMed, 39 citations in OpenAlex.

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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

18 authors at 10 institutions in 6 countries.

Debmalya BarhCentre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology (IIOAB), Nonakuri, West Bengal, 721172, Purba Medinipur, India. dr.barh@gmail.com.
Sandeep TiwariLaboratory of Cellular and Molecular Genetics (LGCM) and PG Program in Bioinformatics, Department of Genetics, Ecology and Evolution, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, CEP, 31270-901, Brazil.
Lucas Gabriel Rodrigues GomesLaboratory of Cellular and Molecular Genetics (LGCM) and PG Program in Bioinformatics, Department of Genetics, Ecology and Evolution, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, CEP, 31270-901, Brazil.
Cecília Horta Ramalho PintoDepartment of Biochemistry and Immunology, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, 31270-901, Brazil.
Bruno Silva AndradeLaboratory of Bioinformatics and Computational Chemistry, Department of Biological Sciences, State University of Southwest Bahia (UESB), Jequié, 45206-190, Brazil.
Shaban AhmadDepartment of Computer Science, Jamia Millia Islamia, New Delhi, 110025, India.
Alaa A A AljabaliDepartment of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmacy, Yarmouk University, P O BOX 566, Irbid, 21163, Jordan.
Khalid J AlzahraniDepartment of Clinical Laboratories Sciences, College of Applied Medical Sciences, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia.
Hamsa Jameel BanjerDepartment of Clinical Laboratories Sciences, College of Applied Medical Sciences, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia.
Sk Sarif HassanDepartment of Mathematics, Pingla Thana Mahavidyalaya, Maligram, 721140, India.
Elrashdy M RedwanDepartment of Biological Science, Faculty of Science, King Abdulazizi University, Jeddah, 21589, Saudi Arabia.
Khalid RazaDepartment of Computer Science, Jamia Millia Islamia, New Delhi, 110025, India.
Aristóteles Góes-NetoLaboratory of Cellular and Molecular Genetics (LGCM) and PG Program in Bioinformatics, Department of Genetics, Ecology and Evolution, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, CEP, 31270-901, Brazil.
Robinson Sabino-SilvaDepartment of Physiology, Institute of Biomedical Sciences, Federal University of Uberlandia, Minas Gerais, Uberlandia, CEP, 38400-902, Brazil.
Kenneth LundstromPanTherapeutics, 1095, Lutry, Switzerland.
Vladimir N UverskyDepartment of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, 33612, USA.
Vasco AzevedoLaboratory of Cellular and Molecular Genetics (LGCM) and PG Program in Bioinformatics, Department of Genetics, Ecology and Evolution, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, CEP, 31270-901, Brazil.
Murtaza M TambuwalaLincoln Medical School, University of Lincoln, Brayford Pool Campus, Lincoln, LN6 7TS, UK.
Universidade Federal de Minas Gerais · BRJamia Millia Islamia · INTaif University · SAInstitute of Bioinformatics and Applied Biotechnology · INKing Abdulaziz University · SASouthwest Bahia State University · BRUniversidade Federal de Uberlândia · BRUniversity of Lincoln · GBUniversity of South Florida · USYarmouk University · JO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hyper-transmissibility with decreased disease severity is a typical characteristic of the SARS-CoV-2 Omicron variant. To understand this phenomenon, we used various bioinformatics approaches to analyze randomly selected genome sequences (one each) of the Gamma, Delta, and Omicron variants submitted to NCBI from December 15 to 31, 2021. We report that the pathogenicity of SARS-CoV-2 variants decreases in the order of Wuhan > Gamma > Delta > Omicron; however, the antigenic property follows the order of Omicron > Gamma > Wuhan > Delta. The Omicron spike RBD shows lower pathogenicity but higher antigenicity than other variants. The reported decreased disease severity by the Omicron variant may be due to its decreased pro-inflammatory and IL-6 stimulation and increased IFN-γ and IL-4 induction efficacy. The mutations in the N protein are probably associated with this decreased IL-6 induction and human DDX21-mediated increased IL-4 production for Omicron. Due to the mutations, the stability of S, M, N, and E proteins decreases in the order of Omicron > Gamma > Delta > Wuhan. Although a stronger spike RBD-hACE2 binding of Omicron increases its transmissibility, the lowest stability of its spike protein makes spike RBD-hACE2 interaction weak for systemic infection and for causing severe disease. Finally, the highest instability of the Omicron E protein may also be associated with decreased viral maturation and low viral load, leading to less severe disease and faster recovery. Our findings will contribute to the understanding of the dynamics of SARS-CoV-2 variants and the management of emerging variants. This minimal genome-based method may be used for other similar viruses avoiding robust analysis.

Indexed as

COVID-19CytokinesAnti-Inflammatory AgentsDEAD-box RNA HelicasesHumansInterleukin-4Interleukin-6SARS-CoV-2Transcription FactorsVirulenceAnti-Inflammatory AgentsCytokinesDDX21 protein, humanDEAD-box RNA HelicasesInterleukin-4Interleukin-6Transcription FactorsAntigenic propertyCytokine inductionOmicronPathogenicityProtein–protein interactionProtein stability.SARS-CoV-2Transmission

Identifiers

PMID36215001
PMCPMC9549046
OpenAlexW4303984078

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.