Evidence map›Paper›PMID 25760038›Full record

ArticlePloS one2015

Prediction of chemical respiratory sensitizers using GARD, a novel in vitro assay based on a genomic biomarker signature.

Andy Forreryd, Henrik Johansson, Ann-Sofie Albrekt, Carl A K Borrebaeck, Malin Lindstedt

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Responses of anToxics · 2024
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Skin Sensitization Testing-What's Next?International journal of molecular sciences · 2019
    Review
  14. Review
  15. Testing Human Skin and Respiratory Sensitizers-What Is Good Enough?International journal of molecular sciences · 2017
    Review
  16. 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

5 authors.

Andy ForrerydDepartment of Immunotechnology, Lund University, Medicon Village, Lund, Sweden.
Henrik JohanssonDepartment of Immunotechnology, Lund University, Medicon Village, Lund, Sweden; SenzaGen AB, Medicon Village, Lund, Sweden.
Ann-Sofie AlbrektDepartment of Immunotechnology, Lund University, Medicon Village, Lund, Sweden.
Carl A K BorrebaeckDepartment of Immunotechnology, Lund University, Medicon Village, Lund, Sweden.
Malin LindstedtDepartment of Immunotechnology, Lund University, Medicon Village, Lund, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRepeated exposure to certain low molecular weight (LMW) chemical compounds may result in development of allergic reactions in the skin or in the respiratory tract. In most cases, a certain LMW compound selectively sensitize the skin, giving rise to allergic contact dermatitis (ACD), or the respiratory tract, giving rise to occupational asthma (OA). To limit occurrence of allergic diseases, efforts are currently being made to develop predictive assays that accurately identify chemicals capable of inducing such reactions. However, while a few promising methods for prediction of skin sensitization have been described, to date no validated method, in vitro or in vivo, exists that is able to accurately classify chemicals as respiratory sensitizers.

resultsRecently, we presented the in vitro based Genomic Allergen Rapid Detection (GARD) assay as a novel testing strategy for classification of skin sensitizing chemicals based on measurement of a genomic biomarker signature. We have expanded the applicability domain of the GARD assay to classify also respiratory sensitizers by identifying a separate biomarker signature containing 389 differentially regulated genes for respiratory sensitizers in comparison to non-respiratory sensitizers. By using an independent data set in combination with supervised machine learning, we validated the assay, showing that the identified genomic biomarker is able to accurately classify respiratory sensitizers.

conclusionsWe have identified a genomic biomarker signature for classification of respiratory sensitizers. Combining this newly identified biomarker signature with our previously identified biomarker signature for classification of skin sensitizers, we have developed a novel in vitro testing strategy with a potent ability to predict both skin and respiratory sensitization in the same sample.

Indexed as

Gene Expression ProfilingAsthma, OccupationalCell LineHazardous SubstancesHumansRisk AssessmentTranscriptomeHazardous Substances

Identifiers

PMID25760038
PMCPMC4356558

What OpenQuestion 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 OpenQuestion graph.