The proposed research will develop novel methods to assess interactions 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 Institute of Environmental Health Sciences (NIEHS)
Type
High Priority, Short Term Project Award (R56)
Project #
2R56ES017876-06A1
Application #
9319410
Study Section
Biostatistical Methods and Research Design Study Section (BMRD)
Program Officer
Mcallister, Kimberly A
Project Start
2010-04-01
Project End
2017-09-29
Budget Start
2016-09-30
Budget End
2017-09-29
Support Year
6
Fiscal Year
2016
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
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
Chen, Ying; VanderWeele, Tyler J (2018) Associations of Religious Upbringing With Subsequent Health and Well-Being From Adolescence to Young Adulthood: An Outcome-Wide Analysis. Am J Epidemiol 187:2355-2364
VanderWeele, Tyler J; Tchetgen Tchetgen, Eric J (2017) Mediation analysis with time varying exposures and mediators. J R Stat Soc Series B Stat Methodol 79:917-938
VanderWeele, Tyler J (2017) Religion and health in Europe: cultures, countries, context. Eur J Epidemiol 32:857-861
VanderWeele, Tyler J (2017) Invited Commentary: The Continuing Need for the Sufficient Cause Model Today. Am J Epidemiol 185:1041-1043
Spiegelman, Donna; VanderWeele, Tyler J (2017) Evaluating Public Health Interventions: 6. Modeling Ratios or Differences? Let the Data Tell Us. Am J Public Health 107:1087-1091
VanderWeele, Tyler J (2017) On a Square-Root Transformation of the Odds Ratio for a Common Outcome. Epidemiology 28:e58-e60
Sun, BaoLuo; VanderWeele, Tyler; Tchetgen Tchetgen, Eric J (2017) A Multinomial Regression Approach to Model Outcome Heterogeneity. Am J Epidemiol 186:1097-1103

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