Identification of gene expression predictors of occupational benzene exposure

Abstract

BackgroundPreviously, using microarrays and mRNA-Sequencing (mRNA-Seq) we found that occupational exposure to a range of benzene levels perturbed gene expression in peripheral blood mononuclear cells.ObjectivesIn the current study, we sought to identify gene expression biomarkers predictive of benzene exposure below 1 part per million (ppm), the occupational standard in the U.S.MethodsFirst, we used the nCounter platform to validate altered expression of 30 genes in 33 unexposed controls and 57 subjects exposed to benzene (<1 to ≥5 ppm). Second, we used SuperLearner (SL) to identify a minimal number of genes for which altered expression could predict <1 ppm benzene exposure, in 44 subjects with a mean air benzene level of 0.55±0.248 ppm (minimum 0.203ppm).ResultsnCounter and microarray expression levels were highly correlated (coefficients >0.7, p<0.05) for 26 microarray-selected genes. nCounter and mRNA-Seq levels were poorly correlated for 4 mRNA-Seq-selected genes. Using negative binomial regression with adjustment for covariates and multiple testing, we confirmed differential expression of 23 microarray-selected genes in the entire benzene-exposed group, and 27 genes in the <1 ppm-exposed subgroup, compared with the control group. Using SL, we identified 3 pairs of genes that could predict <1 ppm benzene exposure with cross-validated AUC estimates >0.9 (p<0.0001) and were not predictive of other exposures (nickel, arsenic, smoking, stress). The predictive gene pairs are PRG2/CLEC5A, NFKBI/CLEC5A, and ACSL1/CLEC5A. They play roles in innate immunity and inflammatory responses.ConclusionsUsing nCounter and SL, we validated the altered expression of multiple mRNAs by benzene and identified gene pairs predictive of exposure to benzene at levels below the US occupational standard of 1ppm.

Gene Expression Response in Peripheral Blood Cells of Petroleum Workers Exposed to Sub-Ppm Benzene Levels

“…Illumina ID and gene name conversions for this study (IlluminaHumanRef8v3) and “the China benzene exposure study” [ 7 , 8 , 9 ] (IlluminaHumanRef8v2) were performed using reference lists for the arrays posted in GEO (GPL6883-11606 and GPL6104-11576) and using gConvert, a part of the gProfiler tool [ 24 ] in R (version 3.5.0).…”

“…Next, supervised multivariate analysis was performed using gene expression data as input and benzene exposure vs. referents as response (as a categorical variable). The first analysis was performed on the six genes Schiffmann and coworkers [ 9 ] selected from the “the China benzene exposure study” as the minimal number of genes for prediction of benzene exposure below 1 ppm. We also analysed all 30 of the genes tested by Schiffman and coworkers [ 9 ].…”

“…Gene expression studies of workers exposed to low levels of benzene (<1 ppm) with a dose-related decreased white blood cell counts, suggest that benzene also affects genes involved in AML and immune response pathways in a supra-linear manner [ 7 ], even at concentrations as low as 0.1 ppm benzene [ 8 ]. These observations were reported from a study of 125 Chinese subjects exposed to different levels of benzene, hereafter referred to as “the China benzene exposure study” [ 7 , 8 , 9 ]. An increased risk of haematopoietic malignancies and altered gene expression also at exposure below 1 ppm is compatible with a suggested non-linear metabolism of benzene, favouring production of a higher proportion of toxic metabolites in subjects exposed to benzene concentrations below 1 ppm than in heavily exposed workers [ 10 ].…”

“…An increased risk of haematopoietic malignancies and altered gene expression also at exposure below 1 ppm is compatible with a suggested non-linear metabolism of benzene, favouring production of a higher proportion of toxic metabolites in subjects exposed to benzene concentrations below 1 ppm than in heavily exposed workers [ 10 ]. Recently, six genes were selected from “the China benzene exposure study” as a minimal number of genes whose expression could predict low exposure to benzene (<1 ppm), including interferon beta 1 (IFNB1), acyl-CoA synthetase long chain family member 1 (ACSL1), nuclear factor kappa B subunit 1 (NFKB1), aquaporin 9 (AQP9), proteoglycan 2 (PRG2), and C-type lectin domain containing 5A (CLEC5A) [ 9 ].…”

“…In the present study, we aimed to investigate whether these workers deviated from the unexposed referents also in the gene expression in whole blood samples. In order to limit the number of tests in our small data set, we utilized our data to perform an independent validation of the findings reported from “the China benzene exposure study”, by testing the six genes that were proposed by Schiffmann and co-workers (2018) to predict low levels of benzene exposure [ 9 ]. The Schiffman study also highlights the importance of immune and inflammatory genes in the response to benzene.…”