BackgroundChildhood asthma is a major public health concern, with its incidence continuing to rise in many industrialized countries. While genetic factors contribute to asthma development, environmental exposures, particularly volatile organic compounds (VOCs), have been increasingly recognized as key risk factors. This study investigates the association between blood VOC levels and childhood asthma risk in the U.S. adolescent population using a combination of epidemiological and computational modeling approaches.MethodsNHANES 2013-2016 data were analyzed to investigate associations between blood VOC levels and childhood asthma. Weighted Quantile Sum (WQS) regression was applied to assess VOC mixture effects, and weighted logistic regression models were used to evaluate individual VOC associations. Potential targets related to 1,4-Dichlorobenzene and childhood asthma were collected from ChEMBL, TargetNet, GeneCards, OMIM, and TTD. Overlapping targets were used to construct a protein-protein interaction (PPI) network via STRING, followed by GO and KEGG enrichment analyses using DAVID. Molecular docking and tissue-expression plausibility assessment of core targets were performed using AutoDock Vina 1.1.2, GEPIA, and the Human Protein Atlas (HPA).ResultsThe WQS regression model showed a significant positive association between the VOC mixture and childhood asthma, with 1,4-dichlorobenzene receiving the largest weight in the mixture. In single-pollutant models, 1,4-dichlorobenzene and o-xylene showed positive associations with childhood asthma after adjustment, although these findings should be interpreted cautiously. Integrative target-based analyses highlighted EGFR, PIK3CA, PIK3CD, SRC, and AKT1 as candidate genes potentially relevant to the observed association, and enrichment analyses suggested involvement of pathways such as MAPK, TNF, and PI3K-Akt signaling.ConclusionThis study suggests that higher exposure to multiple VOCs, particularly 1,4-dichlorobenzene, is associated with childhood asthma in U.S. adolescents. Integrative bioinformatics and docking analyses indicate biologically plausible pathways that may underlie this association. These findings are hypothesis-generating, and prospective and experimental studies are needed to further clarify temporality and mechanism.
Liang et al. (Tue,) studied this question.