Exposure to ambient particulate matter (PM) has been linked to several adverse health effects. Since vehicular traffic is a PM source of growing importance, we sampled total suspended particulate (TSP), PM(10), and PM(2.5) at six urban locations with pronounced differences in traffic intensity. The mutagenicity, DNA-adduct formation, and induction of oxidative DNA damage by the samples were studied as genotoxicological parameters, in relation to polycyclic aromatic hydrocarbon (PAH) levels, elemental composition, and radical-generating capacity (RGC) as chemical characteristics. We found pronounced differences in the genotoxicity and chemical characteristics of PM from the various locations, although we could not establish a correlation between traffic intensity and any of these characteristics for any of the PM size fractions. Therefore, the differences between locations may be due to local sources of PM, other than traffic. The concentration of total (carcinogenic) PAHs correlated positively with RGC, direct and S9-mediated mutagenicity, as well as the induction of DNA adducts and oxidative DNA damage. The interaction between total PAHs and transition metals correlated positively with DNA-adduct formation, particularly from the PM(2.5) fraction. RGC was not associated with one specific PM size fraction, but mutagenicity and DNA reactivity after metabolic activation were relatively high in PM(10) and PM(2.5), when compared with TSP. We conclude that the toxicological characteristics of urban PM samples show pronounced differences, even when PM concentrations at the sample sites are comparable. This implies that emission reduction strategies that take chemical and toxicological characteristics of PM into account may be useful for reducing the health risks associated with PM exposure.

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In current molecular epidemiology studies, a wide range of methods are used to monitor early biological effects after exposure to xenobiotic agents. Gene expression profiling is considered a promising tool that may provide more sensitive, mechanism-based biomarkers. As a first step toward obtaining information on the applicability of gene expression profiles as a biomarker for early biological effects of carcinogen exposure, we conducted in vitro studies on human peripheral blood mononuclear cells (PBMC). We used cigarette smoke condensate (CSC) and a selection of its genotoxic constituents as model agents, applying cDNA microarray technology to investigate modulated gene expression. In independent experiments using cells from several donors, quiescent PBMC were exposed for 18 h, followed by gene expression analyses on a microarray containing 600 toxicologically relevant genes. The search for candidate biomarker genes was binomial: first we looked for genes responding similarly to all agents; second, for agent-specific genes. Many genes were significantly deregulated by all compounds, but as the direction of deregulation frequently differed per agent, they are not useful as generic biomarkers. Cigarette smoke condensate modulated the expression of many more genes than any of its constituents, with the largest effect in SERPINB2. The affected genes are involved in immune or stress responses, but surprisingly no genes involved in DNA damage response were modulated, and only a few in DNA repair. In conclusion, several genes have been identified as potential biomarkers for population studies on early biological effects caused by cigarette smoke exposure, but no genes were identified that represent a generic biomarker.

The embryonic stem cell test (EST) has been designed to predict developmental toxicity based upon compound-induced inhibition of embryonic stem cell (ESC) differentiation. The end point scoring, the test duration, and the definition of the predictivity and the applicability domain require improvements to facilitate implementation of the EST into regulatory testing strategies. The use of transcriptomics to study compound-induced differentiation modulation may improve the EST in each of these aspects. ESC differentiation was induced, and cell samples were collected after 0, 24, and 48 h of differentiation. Additionally, samples were collected that were 24 h exposed to one of five developmentally toxic compounds or a nondevelopmentally toxic compound. All samples were hybridized to Affymetrix GeneChips, and analyses revealed that 26 genes were significantly regulated both during ESC differentiation and by exposure to each of the developmentally toxic compounds tested. Using principal component analysis, we defined a "differentiation track" on the basis of this gene list, which represents ESC differentiation. We showed that significant deviation from the differentiation track was in line with the developmental toxic properties of the compounds. The significance of deviation was analyzed using the leave-one-out cross-validation, which showed a favorable prediction of toxicity in the system. Our findings show that gene expression signatures can be used to identify developmental toxicant-induced differentiation modulation. In addition, studying compound-induced effects at an early stage of differentiation combined with transcriptomics leads to increased objectivity in determining differentiation inhibition and to a reduction of the test duration. Furthermore, this approach may improve the predictivity and applicability domain of the EST.

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