Evidence map›Paper›PMID 26979667›Full record

ArticleParticle and fibre toxicology2016

Nano-risk Science: application of toxicogenomics in an adverse outcome pathway framework for risk assessment of multi-walled carbon nanotubes.

Sarah Labib, Andrew Williams, Carole L Yauk, Jake K Nikota, Håkan Wallin, Ulla Vogel, Sabina Halappanavar

Open access · goldAbstract read
In one paragraph

Article in Particle and fibre toxicology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
7.5field-weighted citation impact, top 2% 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

44 citing papers in PubMed, 135 citations in OpenAlex.

  1. Article
  2. Environmental science. Nano · 2024
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  12. New "Omics" Approaches as Tools to Explore Mechanistic Nanotoxicology.Advances in experimental medicine and biology · 2022
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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

7 authors at 3 institutions in 2 countries.

Sarah LabibEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, ON, K1A 0K9, Canada.
Andrew WilliamsEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, ON, K1A 0K9, Canada.
Carole L YaukEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, ON, K1A 0K9, Canada.
Jake K NikotaEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, ON, K1A 0K9, Canada.
Håkan WallinNational Research Centre for the Working Environment, Lerso Parkallé 105, DK-2100, Copenhagen, Denmark.
Ulla VogelNational Research Centre for the Working Environment, Lerso Parkallé 105, DK-2100, Copenhagen, Denmark.
Sabina HalappanavarEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, ON, K1A 0K9, Canada. sabina.halappanavar@hc-sc.gc.ca.
Health Canada · CATechnical University of Denmark · DKUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA diverse class of engineered nanomaterials (ENMs) exhibiting a wide array of physical-chemical properties that are associated with toxicological effects in experimental animals is in commercial use. However, an integrated framework for human health risk assessment (HHRA) of ENMs has yet to be established. Rodent 2-year cancer bioassays, clinical chemistry, and histopathological endpoints are still considered the 'gold standard' for detecting substance-induced toxicity in animal models. However, the use of data derived from alternative toxicological tools, such as genome-wide expression profiling and in vitro high-throughput assays, are gaining acceptance by the regulatory community for hazard identification and for understanding the underlying mode-of-action. Here, we conducted a case study to evaluate the application of global gene expression data in deriving pathway-based points of departure (PODs) for multi-walled carbon nanotube (MWCNT)-induced lung fibrosis, a non-cancer endpoint of regulatory importance.

methodsGene expression profiles from the lungs of mice exposed to three individual MWCNTs with different physical-chemical properties were used within the framework of an adverse outcome pathway (AOP) for lung fibrosis to identify key biological events linking MWCNT exposure to lung fibrosis. Significantly perturbed pathways were categorized along the key events described in the AOP. Benchmark doses (BMDs) were calculated for each perturbed pathway and were used to derive transcriptional BMDs for each MWCNT.

resultsSimilar biological pathways were perturbed by the different MWCNT types across the doses and post-exposure time points studied. The pathway BMD values showed a time-dependent trend, with lower BMDs for pathways perturbed at the earlier post-exposure time points (24 h, 3d). The transcriptional BMDs were compared to the apical BMDs derived by the National Institute for Occupational Safety and Health (NIOSH) using alveolar septal thickness and fibrotic lesions endpoints. We found that regardless of the type of MWCNT, the BMD values for pathways associated with fibrosis were 14.0-30.4 μg/mouse, which are comparable to the BMDs derived by NIOSH for MWCNT-induced lung fibrotic lesions (21.0-27.1 μg/mouse).

conclusionsThe results demonstrate that transcriptomic data can be used to as an effective mechanism-based method to derive acceptable levels of exposure to nanomaterials in product development when epidemiological data are unavailable.

Indexed as

Gene Expression ProfilingNanotechnologyToxicogeneticsAnimalsBenchmarkingComputational BiologyDatabases, GeneticDose-Response Relationship, DrugGene Expression RegulationGene Regulatory NetworksHumansLungMaleMiceNanotubes, CarbonOligonucleotide Array Sequence AnalysisNanotubes, CarbonAdverse outcome pathwaysBenchmark doseCase studyLung fibrosisNanoRisk assessmentToxicogenomics

Identifiers

PMID26979667
PMCPMC4792104
OpenAlexW2297465774

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.