Chemicals that induce asthma at the workplace are substances of concern. At present, there are no widely accepted methods to identify respiratory sensitizers, and classification of these substances is based on human occupational data. Several studies have contributed to understanding the mechanisms involved in respiratory sensitization, although uncertainties remain. One point of interest for respiratory sensitization is the reaction of the epithelial lung barrier to respiratory sensitizers. To elucidate potential molecular effects of exposure of the epithelial lung barrier, a gene expression profile was created based on a DNA microarray experiment using the bronchial epithelial cell line 16 HBE14o(-). The cells were exposed to 12 respiratory sensitizers and 10 non-sensitizers. For statistical analysis, we used a class prediction approach that combined three machine learning algorithms, leave-one-compound-out cross validation, and majority voting per tested compound. This approach allowed for a prediction accuracy of 95%. Identified predictive genes were mainly associated with the cytoskeleton and barrier function of the epithelial cell. Several of these genes were reported to be associated with asthma as well. Taken together, this indicates that pulmonary barrier function is an important target for respiratory sensitizers and associated genes can be used to predict the respiratory sensitization potential of chemicals.

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http://dx.doi.org/10.1016/j.tiv.2015.10.010DOI Listing

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