Mixture design and multivariate analysis in mixture research.

Abstract

Mixture design has been used to identify possible interactions between mutagens in a mixture. In this paper the use of mixture design in multidimensional isobolographic studies is introduced. Mutagenicity of individual nitro-polycyclic aromatic hydrocarbons (PAH) was evaluated is an organic extract of diesel exhaust particles (DEPs). The particles were extracted with dichloromethane (DCM). After replacing DCM with dimethyl sulfoxide, the extract was spiked with three individual nitro-PAH: 1-nitropyrene, 2-nitrofluorene, and 1,8-dinitropyrene. The nitro-PAH were added separately and in various combinations to the extract to determine the effects of each variable and to identify possible interactions between the individual nitro-PAH and between the nitro-PAH and the extract. The composition of the mixtures was determined by mixture design (linear axial normal) with four variables (the DEP extract and the three nitro-PAH, giving 8 different mixtures plus a triplicate centerpoint, i.e., a total of 11. The design supports a model with linear and interaction (product) terms. Two different approaches were used: traditional mixture design within a well-defined range on the linear part of the dose-response curves and an isobolographic mixture design with equipotent doses of each variable. The mixtures were tested for mutagenicity in the Ames assay using the TA98 strain of Salmonella typhimurium. The data were analyzed with projections to latent structures (PLS). The three individual nitro-PAH and the DEP extract acted additively in the Ames test. The use of mixture design either within a well-defined range of the linear part on the dose-response curve or with equipotent doses saves experiments and reduces the possibility of false interaction terms in situations with dose additivity or response additivity.