The proposed research will develop novel methods to assess mediation and interaction between genetic and environmental exposures and different disease subtypes so as to better tailor treatments and prevention efforts to individuals' characteristics and so as to better understand the mechanisms governing disease. Methods will be developed for settings in which there are multiple disease subtypes and these disease subtypes may have different prognosis for survival and may be more amenable to different types of treatment and preventive efforts. Methodology for assessing the role of interaction in understanding mechanisms will also be developed. This will include elucidating the role of gene-environment interaction in the heritability of disease, understanding mediating pathways from exposure to disease in the presence of interaction, and identifying sufficient cause interaction for diseases or disease subtypes such that an outcome would occur if two (or more) exposures are present, but not if only one or the other were present. The methodology will be applied to understand prognosis, treatment decisions, preventive interventions, and mechanisms for colorectal cancer, and also for the development of skin lesions; the methodology will also be applied to understand the role of gene-environment interaction in the heritability of numerous traits.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA222147-02
Application #
9652827
Study Section
Cancer, Heart, and Sleep Epidemiology B Study Section (CHSB)
Program Officer
Divi, Rao L
Project Start
2018-02-19
Project End
2023-01-31
Budget Start
2019-02-01
Budget End
2020-01-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Harvard University
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
149617367
City
Boston
State
MA
Country
United States
Zip Code
02115
VanderWeele, Tyler J (2018) On Well-defined Hypothetical Interventions in the Potential Outcomes Framework. Epidemiology 29:e24-e25
Mathur, Maya B; Ding, Peng; Riddell, Corinne A et al. (2018) Web Site and R Package for Computing E-values. Epidemiology 29:e45-e47
Jackson, John W; VanderWeele, Tyler J (2018) Decomposition Analysis to Identify Intervention Targets for Reducing Disparities. Epidemiology 29:825-835
Mathur, Maya B; VanderWeele, Tyler J (2018) R Function for Additive Interaction Measures. Epidemiology 29:e5-e6