Towards Whole Health Toxicology: In-Silico Prediction of Diseases Sensitive to Multi-Chemical Exposures

Chemical exposures from diverse sources merge on a limited number of molecular pathways described as toxicity pathways. Changes in the same set of molecular pathways in different cell and tissue types may generate seemingly unrelated health conditions. Today, no approaches are available to predict in an unbiased way sensitivities of different disease states and their combinations to multi-chemical exposures across the exposome. We propose an inductive in-silico workflow where sensitivities of genes to chemical exposures are identified based on the overlap of existing genomic datasets, and data on sensitivities of individual genes is further used to sequentially derive predictions on sensitivities of molecular pathways, disease states, and groups of disease states (syndromes). Our analysis predicts that conditions representing the most significant public health problems are among the most sensitive to cumulative chemical exposures. These conditions include six leading types of cancer in the world (prostatic, breast, stomach, lung, colorectal neoplasms, and hepatocellular carcinoma), obesity, type 2 diabetes, non-alcoholic fatty liver disease, autistic disorder, Alzheimer's disease, hypertension, heart failure, brain and myocardial ischemia, and myocardial infarction. Overall, our predictions suggest that environmental risk factors may be underestimated for the most significant public health problems.

Combined Effect of Lead Exposure and Allostatic Load on Cardiovascular Disease Mortality-A Preliminary Study

This study explores the combined effect of lead (Pb) exposure and an index of chronic physiological stress on cardiovascular disease mortality using data from the National Health and Nutrition Examination Survey (NHANES) 1999-2008 linked to 1999-2014 National Death Index data. Chronic physiological stress was measured using the allostatic load (AL) index, which was formed by analyzing markers from the cardiovascular, inflammatory, and metabolic systems, with Pb levels, assessed using blood lead levels (BLL). The dataset was analyzed with statistical techniques to explore (a) the relationship between Pb exposure and AL, and (b) the combined role of Pb and AL on cardiovascular disease mortality. Results indicated that AL was more elevated in those with BLLs above the 50th percentile in the US population and that those with elevated AL were more likely to have high BLL. Finally, the interaction of AL and BLL significantly increased the likelihood of cardiovascular disease mortality. These findings highlight the need for considering the totality of exposures experienced by populations to build holistic programs to prevent Pb exposure and reduce stressors to promote optimal health outcomes and reduce cardiovascular mortality risk.