Evidence map›Paper›PMID 37590197›Full record

ArticlePloS one2023

Airway and Oral microbiome profiling of SARS-CoV-2 infected asthma and non-asthma cases revealing alterations-A pulmonary microbial investigation.

Karthik Sekaran, Rinku Polachirakkal Varghese, George Priya Doss C, Alsamman M Alsamman, Hatem Zayed, Achraf El Allali

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. 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
0.8field-weighted citation impact, top 27% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Trial
  2. Article
  3. Microbiota of Saliva: A Non-invasive Diagnostic Tool.Indian journal of microbiology · 2024
    Review
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

6 authors at 4 institutions in 4 countries.

Karthik SekaranVellore Institute of Technology, School of Biosciences and Technology, Vellore, India.
Rinku Polachirakkal VargheseVellore Institute of Technology, School of Biosciences and Technology, Vellore, India.
George Priya Doss CVellore Institute of Technology, School of Biosciences and Technology, Vellore, India.
Alsamman M AlsammanDepartment of Genome Mapping, Molecular Genetics and Genome Mapping Laboratory, Agricultural Genetic Engineering Research Institute, Giza, Egypt.
Hatem ZayedDepartment of Biomedical Sciences College of Health Sciences, QU Health, Qatar University, Doha, Qatar.
Achraf El AllaliAfrican Genome Center, Mohammed VI Polytechnic University, Ben Guerir, Morocco.ORCID 0000-0002-4561-2161
Vellore Institute of Technology University · INAgricultural Genetic Engineering Research Institute · EGQatar University · QAUniversité Mohammed VI Polytechnique · MA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

New evidence strongly discloses the pathogenesis of host-associated microbiomes in respiratory diseases. The microbiome dysbiosis modulates the lung's behavior and deteriorates the respiratory system's effective functioning. Several exogenous and environmental factors influence the development of asthma and chronic lung disease. The relationship between asthma and microbes is reasonably understood and yet to be investigated for more substantiation. The comorbidities such as SARS-CoV-2 further exacerbate the health condition of the asthma-affected individuals. This study examines the raw 16S rRNA sequencing data collected from the saliva and nasopharyngeal regions of pre-existing asthma (23) and non-asthma patients (82) infected by SARS-CoV-2 acquired from the public database. The experiment is designed in a two-fold pattern, analyzing the associativity between the samples collected from the saliva and nasopharyngeal regions. Later, investigates the microbial pathogenesis, its role in exacerbations of respiratory disease, and deciphering the diagnostic biomarkers of the target condition. LEfSE analysis identified that Actinobacteriota and Pseudomonadota are enriched in the SARS-CoV-2-non-asthma group and SARS-CoV-2 asthma group of the salivary microbiome, respectively. Random forest algorithm is trained with amplicon sequence variants (ASVs) attained better classification accuracy, ROC scores on nasal (84% and 87%) and saliva datasets (93% and 97.5%). Rothia mucilaginosa is less abundant, and Corynebacterium tuberculostearicum showed higher abundance in the SARS-CoV-2 asthma group. The increase in Streptococcus at the genus level in the SARS-CoV-2-asthma group is evidence of discriminating the subgroups.

Indexed as

AsthmaCOVID-19MicrobiotaHumansLungNoseRNA, Ribosomal, 16SSARS-CoV-2RNA, Ribosomal, 16S

Identifiers

PMID37590197
PMCPMC10434894
OpenAlexW4385938454

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.