Neurodevelopment and cognitive function are among the most important outcomes in public health, particularly with the rise of knowledge-based economies. While it is widely believed that the simultaneous presence of several toxic exposures can alter developmental trajectories of the central nervous system, studies designed to address mixed chemical exposures are rare, and represent a critical need in the field of public health. Multiple barriers are inherent to conducting mixtures research and must be overcome if this field is to progress. Obvious barriers include the need for large sample sizes and prospective data to assess exposure timing (i.e. critical developmental windows). Two additional barriers include exposure misclassification and lack of statistical approaches available for higher dimensional interactions. Our proposal addresses all of these barriers directly and will establish a framework for the study of chemical mixtures that can be applied broadly in environmental health. We have developed a novel biomarker that can objectively reconstruct the dose and timing of past chemical exposure using deciduous teeth. This biomarker differs from standard tooth biomarkers as it combines sophisticated histological and chemical analyses to precisely sample dentine layers corresponding to specific life stages, generating integrated, longitudinal weekly exposure estimates in the second and third trimesters and during early childhood. Our proposal will address mixed metal exposure, as a first step. We note, however, that our approach can and will be applied to organic chemicals in the future, and we are in parallel developing methods for their analysis in teeth. On another front, we will also apply cutting-edge statistical machine learning methods. In this study, we will focus on five metals/metalloids that are of public health significance, manganese (Mn), lead (Pb), arsenic (As), zinc (Zn) and cadmium (Cd). We will conduct this study in the Early Life Exposures in MExico and NeuroToxicology (ELEMENT), a prospective birth cohort using advanced methods in social science, genetics and toxicology to assess transdisciplinary risk factors impacting neurodevelopment.

Public Health Relevance

Neurodevelopment and cognitive function are among the most important outcomes in public health. While it is widely believed that the simultaneous presence of several toxic exposures can alter developmental trajectories of the central nervous system, studies designed to address mixed chemical exposures are rare, and represent a critical need in the field of public health. The proposed program will apply a novel dental biomarker of exposure to multiple chemicals and cutting-edge statistical methods to identify specific life stages including perinatal periods that correspond to increased susceptibility to neurodevelopmental effects of metal toxicant mixtures.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Research Project (R01)
Project #
1R01ES026033-01A1
Application #
9127482
Study Section
Neurological, Aging and Musculoskeletal Epidemiology (NAME)
Program Officer
Gray, Kimberly A
Project Start
2016-09-01
Project End
2021-08-31
Budget Start
2016-09-01
Budget End
2017-08-31
Support Year
1
Fiscal Year
2016
Total Cost
$708,300
Indirect Cost
$288,029
Name
Icahn School of Medicine at Mount Sinai
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029
Liu, Shelley H; Bobb, Jennifer F; Lee, Kyu Ha et al. (2018) Lagged kernel machine regression for identifying time windows of susceptibility to exposures of complex mixtures. Biostatistics 19:325-341
Claus Henn, Birgit; Austin, Christine; Coull, Brent A et al. (2018) Uncovering neurodevelopmental windows of susceptibility to manganese exposure using dentine microspatial analyses. Environ Res 161:588-598
Horton, Megan K; Hsu, Leon; Claus Henn, Birgit et al. (2018) Dentine biomarkers of prenatal and early childhood exposure to manganese, zinc and lead and childhood behavior. Environ Int 121:148-158
Curtin, Paul; Austin, Christine; Curtin, Austen et al. (2018) Dynamical features in fetal and postnatal zinc-copper metabolic cycles predict the emergence of autism spectrum disorder. Sci Adv 4:eaat1293
Bambino, Kathryn; Zhang, Chi; Austin, Christine et al. (2018) Inorganic arsenic causes fatty liver and interacts with ethanol to cause alcoholic liver disease in zebrafish. Dis Model Mech 11:
Bauer, Julia Anglen; Claus Henn, Birgit; Austin, Christine et al. (2017) Manganese in teeth and neurobehavior: Sex-specific windows of susceptibility. Environ Int 108:299-308
Bello, Ghalib A; Arora, Manish; Austin, Christine et al. (2017) Extending the Distributed Lag Model framework to handle chemical mixtures. Environ Res 156:253-264
Cassidy-Bushrow, Andrea E; Sitarik, Alexandra R; Havstad, Suzanne et al. (2017) Burden of higher lead exposure in African-Americans starts in utero and persists into childhood. Environ Int 108:221-227
Zheng, Laura Y; Sanders, Alison P; Saland, Jeffrey M et al. (2017) Environmental exposures and pediatric kidney function and disease: A systematic review. Environ Res 158:625-648
Chiu, Yueh-Hsiu Mathilda; Claus Henn, Birgit; Hsu, Hsiao-Hsien Leon et al. (2017) Sex differences in sensitivity to prenatal and early childhood manganese exposure on neuromotor function in adolescents. Environ Res 159:458-465

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