Predictive Analysis Using Chemical-Gene Interaction Networks Consistent with Observed Endocrine Activity and Mutagenicity of U.S. Streams

In a recent U.S. Geological Survey/U.S.
Environmental Protection
Agency study assessing more than 700 organic compounds in 38 streams, in vitro assays indicated generally low estrogen, androgen,
and glucocorticoid receptor activities, with 13 surface waters with
17β-estradiol-equivalent (E2Eq) activities greater than a 1-ng/L
estimated effects-based trigger value for estrogenic effects in male
fish. Among the 36 samples assayed for mutagenicity in the Salmonella bioassay (reported here), 25% had low mutagenic
activity and 75% were not mutagenic. Endocrine and mutagenic activities
of the water samples were well correlated with each other and with
the total number and cumulative concentrations of detected chemical
contaminants. To test the predictive utility of knowledge-base-leveraging
approaches, site-specific predicted chemical-gene (pCGA) and predicted
analogous pathway-linked (pPLA) association networks identified in
the Comparative Toxicogenomics Database were compared with observed
endocrine/mutagenic bioactivities. We evaluated pCGA/pPLA patterns
among sites by cluster analysis and principal component analysis and
grouped the pPLA into broad mode-of-action classes. Measured E2eq
and mutagenic activities correlated well with predicted pathways.
The pPLA analysis also revealed correlations with signaling, metabolic,
and regulatory groups, suggesting that other effects pathways may
be associated with chemical contaminants in these waters and indicating
the need for broader bioassay coverage to assess potential adverse
impacts.