Evidence map›Paper›PMID 36333579›Full record

ArticleScientific reports2022

Environmental pathways affecting gene expression (E.PAGE) as an R package to predict gene-environment associations.

Sachin Muralidharan, Sarah Ali, Lilin Yang, Joshua Badshah, Syeda Farah Zahir, Rubbiya A Ali, Janin Chandra, Ian H Frazer, Ranjeny Thomas, Ahmed M Mehdi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2022. 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

10 authors.

Sachin Muralidharan *The University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, 37 Kent St, Woolloongabba, QLD, 4102, Australia.
Sarah Ali *Centre for Microscopy and Microanalysis, University of Queensland, St. Lucia, QLD, 4072, Australia.
Lilin Yang *The University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, 37 Kent St, Woolloongabba, QLD, 4102, Australia.
Joshua BadshahThe University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, 37 Kent St, Woolloongabba, QLD, 4102, Australia.
Syeda Farah ZahirQCIF Facility for Advanced Bioinformatics, Queensland Cyber Infrastructure Foundation Ltd, Brisbane, QLD, Australia.
Rubbiya A AliCentre for Microscopy and Microanalysis, University of Queensland, St. Lucia, QLD, 4072, Australia.
Janin ChandraThe University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, 37 Kent St, Woolloongabba, QLD, 4102, Australia.
Ian H FrazerThe University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, 37 Kent St, Woolloongabba, QLD, 4102, Australia.
Ranjeny ThomasThe University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, 37 Kent St, Woolloongabba, QLD, 4102, Australia.
Ahmed M MehdiThe University of Queensland Diamantina Institute, Translational Research Institute, The University of Queensland, 37 Kent St, Woolloongabba, QLD, 4102, Australia. a.mehdi@uq.edu.au.

Funding

PA Research Foundation 2020002553
6 · The paper itself

Abstract

The purpose of this study is to manually and semi-automatically curate a database and develop an R package that will act as a comprehensive resource to understand how biological processes are dysregulated due to interactions with environmental factors. The initial database search run on the Gene Expression Omnibus and the Molecular Signature Database retrieved a total of 90,018 articles. After title and abstract screening against pre-set criteria, a total of 237 datasets were selected and 522 gene modules were manually annotated. We then curated a database containing four environmental factors, cigarette smoking, diet, infections and toxic chemicals, along with a total of 25,789 genes that had an association with one or more of gene modules. The database and statistical analysis package was then tested with the differentially expressed genes obtained from the published literature related to type 1 diabetes, rheumatoid arthritis, small cell lung cancer, COVID-19, cobalt exposure and smoking. On testing, we uncovered statistically enriched biological processes, which revealed pathways associated with environmental factors and the genes. The curated database and enrichment tool are available as R packages at https://github.com/AhmedMehdiLab/E.PATH and https://github.com/AhmedMehdiLab/E.PAGE respectively.

Indexed as

COVID-19Gene Expression ProfilingDatabases, FactualGene ExpressionGene Regulatory NetworksHumans

Identifiers

PMID36333579
PMCPMC9636158

What Socratic holds

Textmetadata
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.