Influence of Genetic Variance on Occupational Exposure to 1,6-Hexamethylene Diisocyanate (HDI) and Its Trimer HDI Isocyanurate

Polyurethane spray-painting can result in significant occupational exposure to 1,6-hexamethylene diisocyanate (HDI) monomer and its trimer, HDI isocyanurate. Inter-individual genetic differences have been linked with adverse health effects and asthma risk in isocyanate-exposed workers. However, little is known about inter-individual differences in response to HDI isocyanurate exposure compared to the HDI monomer. We are investigating the similarities and differences in exposure-dose responses and the genetic variants that modify or predict relationships between toxicokinetics and biomarker levels in exposed workers. Inhalation and skin exposure to HDI monomer and HDI isocyanurate were measured in 33 spray-painters along with the respective urine and blood biomarkers of 1,6-hexamethylene diamine (HDA) and trisaminohexyl isocyanurate (TAHI). Genome-wide microarrays (Affymetrix 6.0) were used to genotype the workers’ single nucleotide polymorphisms (SNPs) and to conduct a genome-wide association study (GWAS). Using exposure values as covariates and a false discovery rate <0.20 for significance, GWAS showed that one SNP was associated with TAHI levels in urine, six SNPs were associated with HDA in plasma, and twelve SNPs were associated with HDA levels in urine. No SNP associations reached significance for TAHI levels in plasma. The SNPs were tested in linear mixed models (LMM) and bioinformatics data of the genes proximal to the top ten most significant SNPs for each compound were assessed for biological plausibility. Bioinformatics for HDI monomer associated SNPs included predicted interactions involving signal transduction and the immune function. Bioinformatics for HDI isocyanurate predicted interactions for cell signaling, structure, and adhesion. We demonstrate that genetic variance impacts the biomarker levels in workers exposed to HDI monomer and HDI isocyanurate, and that HDA and TAHI levels can be used to refine exposure prediction models for both compounds.