ArticleEnvironmental health : a global access science source2016
Gene expression network analyses in response to air pollution exposures in the trucking industry.
Article in Environmental health : a global access science source, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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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.
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Who cites it
16 citing papers in PubMed, 33 citations in OpenAlex.
- Conceptual frameworks for the integration of genetic and social epidemiology in complex diseases.Global epidemiology · 2024Article
- Particulate matter-induced gene expression patterns in human-derived cells based on 11 public gene expression datasets.Genes & genomics · 2024Article
- Gene Expression Profile of Uterine Leiomyoma from Women Exposed to Different Air Pollution Levels in Metropolitan Cities of Sao Paulo, Brazil.International journal of molecular sciences · 2023Article
- Article
- Integrated molecular response of exposure to traffic-related pollutants in the US trucking industry.Environment international · 2022Article
- The Influence of Air Pollution on the Development of Allergic Inflammation in the Airways in Krakow's Atopic and Non-Atopic Residents.Journal of clinical medicine · 2021Article
- Application of high-resolution metabolomics to identify biological pathways perturbed by traffic-related air pollution.Environmental research · 2021Article
- Bile Acids and GPBAR-1: Dynamic Interaction Involving Genes, Environment and Gut Microbiome.Nutrients · 2020Review
- Cardiovascular adaptations to particle inhalation exposure: molecular mechanisms of the toxicology.American journal of physiology. Heart and circulatory physiology · 2020Review
- Involvement of fine particulate matter exposure with gene expression pathways in breast tumor and adjacent-normal breast tissue.Environmental research · 2020Article
- Metabolomic assessment of exposure to near-highway ultrafine particles.Journal of exposure science & environmental epidemiology · 2019Article
- Ambient Pollution-related Reprogramming of the Human Small Airway Epithelial Transcriptome.American journal of respiratory and critical care medicine · 2018Article
- Mechanisms and Measurement of Changes in Gene Expression.Biological research for nursing · 2018Article
- Changes in gene expression in chronic allergy mouse model exposed to natural environmental PM2.5-rich ambient air pollution.Scientific reports · 2018Article
- Prediction of microRNA and gene target from an integrated network in chronic obstructive pulmonary disease based on canonical correlation analysis.Technology and health care : official journal of the European Society for Engineering and Medicine · 2018Article
- Predictive and Prognostic Biomarkers of Respiratory Diseases due to Particulate Matter Exposure.Journal of cancer prevention · 2017Review
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundExposure to air pollution, including traffic-related pollutants, has been associated with a variety of adverse health outcomes, including increased cardiopulmonary morbidity and mortality, and increased lung cancer risk.
methodsTo better understand the cellular responses induced by air pollution exposures, we performed genome-wide gene expression microarray analysis using whole blood RNA sampled at three time-points across the work weeks of 63 non-smoking employees at 10 trucking terminals in the northeastern US. We defined genes and gene networks that were differentially activated in response to PM
resultsMultiple transcripts were strongly associated (p
conclusionsThese data provide a molecular link between the associations of air pollution exposures with health effects.
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Registered trials
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.