RNA-Seq Can Be Used to Quantify Gene Expression Levels for Use in the GARDskin Assay

Non-animal methods for identification and characterization of skin sensitizers are continuously evolving, advancing towards more effective, accurate, and informational assays. The GARDskin assay is a scientifically and regulatory recognized assay for the assessment of skin sensitizers. It currently relies on targeted gene expression measurement to derive hazard classifications. With the progression of next generation sequencing technologies, whole transcriptome analysis provides an interesting alternative to the currently implemented targeted gene expression approach. RNA-seq was evaluated for its use in the GARDskin assay as a gene expression quantification method. Based on 24 paired samples acquired on both RNA-seq and the NanoString nCounter platform (the currently standard GARDskin acquisition method), gene expression profiles were found to be highly similar. Comparisons of treatment effects yielded a Spearman's correlation coefficient of 0.95 and a Lin's concordance correlation coefficient of 0.87. RNA-seq data was also used to classify the sensitizing hazard of 24 treatments using the standard GARDskin analysis pipeline. The classifications corresponded completely with references, rendering correct classifications for all treatments. In conclusion, it was found that the RNA-seq data strongly resembled NanoString nCounter data, and that it could be used to derive reliable hazard classifications in the GARDskin assay.

Authors

Institutions

Publication Details

Journal
Toxics
Published
2025-12-20
DOI
https://doi.org/10.3390/toxics14010009
Primary Topic
Contact Dermatitis and Allergies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

RNA-Seq Can Be Used to Quantify Gene Expression Levels for Use in the GARDskin Assay

Robin Gradin, Andy Forreryd, Henrik J. Johansson, Johan Andersson
Toxics
Contact Dermatitis and Allergies
article

RNA-Seq Can Be Used to Quantify Gene Expression Levels for Use in the GARDskin Assay

Robin Gradin, Andy Forreryd, Henrik J. Johansson, Johan Andersson
article en

Abstract

Non-animal methods for identification and characterization of skin sensitizers are continuously evolving, advancing towards more effective, accurate, and informational assays. The GARDskin assay is a scientifically and regulatory recognized assay for the assessment of skin sensitizers. It currently relies on targeted gene expression measurement to derive hazard classifications. With the progression of next generation sequencing technologies, whole transcriptome analysis provides an interesting alternative to the currently implemented targeted gene expression approach. RNA-seq was evaluated for its use in the GARDskin assay as a gene expression quantification method. Based on 24 paired samples acquired on both RNA-seq and the NanoString nCounter platform (the currently standard GARDskin acquisition method), gene expression profiles were found to be highly similar. Comparisons of treatment effects yielded a Spearman's correlation coefficient of 0.95 and a Lin's concordance correlation coefficient of 0.87. RNA-seq data was also used to classify the sensitizing hazard of 24 treatments using the standard GARDskin analysis pipeline. The classifications corresponded completely with references, rendering correct classifications for all treatments. In conclusion, it was found that the RNA-seq data strongly resembled NanoString nCounter data, and that it could be used to derive reliable hazard classifications in the GARDskin assay.

ToxicsVol. 14(1)
Medicon Village (SE)
Openalex Percentile: Top 24%
Contact Dermatitis and Allergies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.