The objective of this training grant is to train biostatisticians to work in inter-disciplinary collaborative teams addressing the problems associated with evaluating the effects of relevant environmental chemical mixtures or in the area of toxicogenomics. A key to the success of this venture is the joining of the efforts of key scientists (genomic or mixtures toxicologists, environmental epidemiologists and biostatisticians) in the fields of chemical mixtures or toxicogenomics with trainees from a department of biostatistics. The goal is for trainees to gain an understanding of and experience working on statistical issues for these two important areas of toxicology. These trainees will be qualified to hold unique positions in governmental agencies, academia, and industry where properly evaluating risks associated with relevant chemical exposures is becoming increasingly important. The trainees will be Ph.D. students in the Department of Biostatistics at the Virginia Commonwealth University (VCU), where they will pursue pre-doctoral training in the discipline of biostatistics. Additional expertise will be achieved through work on dissertation/research topics that are pertinent to the field of mixtures or toxicogenomics and through collaborative work with toxicologists and/or environmental epidemiologists actively working in their area of interest. Through these research projects, students will gain experience collaborating with a team of experts working to understand the relationship between environmental exposures and human disease susceptibility. The trainees will assist in the design of studies, conduct appropriate power analyses, analyze resulting data, write reports with proper interpretation of the results, and participate in a collaborative team to produce one or more manuscripts for peer-review publication. In addition, the trainees will have dissertation topics developing statistical methodology for issues involved in the design and analysis of data resulting from chemical mixtures studies or high-throughput technologies.

Public Health Relevance

The discipline of biostatistics applies statistical theory and methodology to the biological sciences. A successful biostatistician must be proficient in statistical applications, mathematical statistics and statistical computing. The objective of the training program is to enhance this proficiency by training pre-doctoral biostatisticians so that they may become experts in the design and analysis of studies of mixtures of chemicals or toxicogenomics - two important and emerging areas of toxicology.

National Institute of Health (NIH)
National Institute of Environmental Health Sciences (NIEHS)
Institutional National Research Service Award (T32)
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Special Emphasis Panel (ZES1)
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Shreffler, Carol A
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Virginia Commonwealth University
Biostatistics & Other Math Sci
Schools of Medicine
United States
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Grant, Lauren P; Gennings, Chris; Wickham, Edmond P et al. (2018) Modeling Pediatric Body Mass Index and Neighborhood Environment at Different Spatial Scales. Int J Environ Res Public Health 15:
Zirkle, Keith W; Nolan, Bernard T; Jones, Rena R et al. (2016) Assessing the relationship between groundwater nitrate and animal feeding operations in Iowa (USA). Sci Total Environ 566-567:1062-1068
Shah, Keyur B; Flattery, Maureen P; Smallfield, Melissa C et al. (2015) Surveillance Endomyocardial Biopsy in the Modern Era Produces Low Diagnostic Yield for Cardiac Allograft Rejection. Transplantation 99:e75-80
Czarnota, Jenna; Gennings, Chris; Wheeler, David C (2015) Assessment of weighted quantile sum regression for modeling chemical mixtures and cancer risk. Cancer Inform 14:159-71
Grant, Lauren P; Gennings, Chris; Wheeler, David C (2015) Selecting spatial scale of covariates in regression models of environmental exposures. Cancer Inform 14:81-96
Franke, Laura M; Czarnota, Jenna N; Ketchum, Jessica M et al. (2015) Factor analysis of persistent postconcussive symptoms within a military sample with blast exposure. J Head Trauma Rehabil 30:E34-46
Czarnota, Jenna; Wheeler, David C; Gennings, Chris (2015) Evaluating geographically weighted regression models for environmental chemical risk analysis. Cancer Inform 14:117-27
Czarnota, Jenna; Gennings, Chris; Colt, Joanne S et al. (2015) Analysis of Environmental Chemical Mixtures and Non-Hodgkin Lymphoma Risk in the NCI-SEER NHL Study. Environ Health Perspect 123:965-70
Johnson, Ryan M; Vu, Ngoc T; Griffin, Brian P et al. (2015) The Alternative Splicing of Cytoplasmic Polyadenylation Element Binding Protein 2 Drives Anoikis Resistance and the Metastasis of Triple Negative Breast Cancer. J Biol Chem 290:25717-27
Carr, Caroline K; Watkins, Andrew M; Wolf, Cynthia J et al. (2013) Testing for departures from additivity in mixtures of perfluoroalkyl acids (PFAAs). Toxicology 306:169-75

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