ArticleGenome medicine2025
Airway transcriptome networks for ozone and PM
Article in Genome medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
The trial behind it
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Authors and funding
8 authors.
Funding
Abstract
backgroundAir pollution disproportionately affects individuals with asthma, triggering asthma exacerbations and morbidity. We hypothesized that children with and without asthma have distinct airway transcriptome networks associated with ozone and particulate matter ≤ 2.5 µm (PM
methodsWe recruited children from the New York metropolitan area, mapped their air pollutant exposures, and collected nasal and bronchial samples for transcriptome and cellular profiling. We used causal network construction and key driver analyses to build airway transcriptome networks for ozone and PM
resultsThe cohort included 307 children, including 167 (54.4%) with asthma and 140 (45.6%) without asthma. The mean age was 13.4 years (SD 4.4 years). Among children with asthma, the airway causal network and its key drivers represented pro-inflammatory adaptive immune processes. Six key driver transcripts for ozone (CLC, CPA3, FGL2, LGALS12, IL7R, HRH4) and three key driver transcripts for PM
conclusionChildren with and without asthma have very distinct causal networks and key drivers for ozone and PM
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