A deeper understanding of the mechanisms through which environmental exposures affect biological processes leading to disease is critical to understanding susceptibility, as well as preventing and treating adverse health outcomes. NIEHS studies in cell-, tissue-, and organ-based systems, as well as in animal models and new approach methodologies (NAMs), will provide a roadmap for understanding environmental exposure effects.
NIEHS works to develop and apply improved test methods and models of genetic, epigenetic, and cellular effects that can be used to predict health outcomes resulting from environmental exposures. Challenges include developing approaches to assess the hazards of complex, real-world mixtures of chemicals, modeling nonchemical stressors that contribute to health disparities in under-resourced communities, creating approaches to better evaluate broad classes of environmental agents, identifying and evaluating environmental exposures related to climate change, and searching for early biomarkers of adverse health effects, especially in at-risk populations. Additionally, experimental approaches will need to be developed to accurately assess the molecular mechanisms associated with environmental exposures that promote health and that can potentially mitigate adverse environmental exposures.
Key approaches to mechanistic biology include research to identify the mechanisms by which environmental factors influence cells, tissues, organ systems, physiology, and behavior; increase understanding of how exposures impact vulnerability and disease risk over the life course; and integrate data from different domains to solve environmental health problems. Key approaches to mechanistic toxicology include research to understand how an agent provokes or prevents damage in the body, generation of mechanistic data that is highly translatable to human biology, integration of innovative approaches to studying environmental exposures, and emphasizing the predictive value of toxicology for promoting human health.
Along with dissemination among the scientific and biomedical communities, it is critical to translate the research insights to inform public health practices and policies, including risk assessment and regulatory decision-making. Research translation is done in partnership with regulatory scientists, federal and state agencies, advocacy organizations, and other public groups. Areas where innovation is needed to promote research translation include creating efficiencies in leveraging existing data and knowledge and taking advantage of AI/ML-based approaches to derive insights from mechanistic and toxicological studies that are targeted at novel questions or uses.
Translational Goal
Discover the mechanisms underlying the biological impacts of environmental exposures and use that knowledge to identify strategies to improve individual and population health.
Priority Approaches
- Elucidate the mechanisms and systems underlying tissue, cell, and genetic abnormalities that occur in the face of known and emerging environmental exposures, and develop approaches to better understand the fundamental mechanisms through which some environmental exposures can promote health and potentially mitigate adverse physical/chemical exposures.
- Develop data integration tools and approaches, such as systematic evidence mapping to collate and review the science on chemicals of concern to advance our understanding of human health impacts.
- Utilize single-cell technologies through -omics approaches, including epigenomics and transcriptomics, as well as proteomic and metabolomic technologies, to study complex biological processes.
- Develop and implement state-of-the-art, high-resolution imaging techniques to enhance mechanistic understanding.
- Conduct epidemiological, computational, and laboratory-based studies that are reciprocally informative, to uncover mechanistic insights and to identify strategies to improve human health.
- Improve capacity of computational models to include more complex data, including data on human biology and mechanisms of susceptibility, as well as AI/ML-based approaches, to ensure research findings are relevant and actionable.
- Develop and validate innovative research approaches that improve human relevance and increase efficiencies to better predict human responses to environmental exposures.
- Develop mechanistically driven approaches to understanding the toxicology of emerging contaminants to provide more timely knowledge that can help avoid adverse health impacts.
