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Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes$
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Michael Windle

Print publication date: 2016

Print ISBN-13: 9780262034685

Published to MIT Press Scholarship Online: May 2017

DOI: 10.7551/mitpress/9780262034685.001.0001

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Statistical Strategies for Modeling Gene × Environment Interactions in Longitudinal Cohort Studies

Statistical Strategies for Modeling Gene × Environment Interactions in Longitudinal Cohort Studies

Chapter:
(p.147) 8 Statistical Strategies for Modeling Gene × Environment Interactions in Longitudinal Cohort Studies
Source:
Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes
Author(s):

Bhramar Mukherjee

Yin-Hsiu Chen

Yi-An Ko

Zihuai He

Seunggeun Lee

Min Zhang

Sung Kyun Park

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262034685.003.0008

In this chapter, Mukherjee and colleagues highlight the importance of longitudinal research designs and statistical models to investigate G x E relationships. The chapter provides a history of a range of alternative statistical models that have been used to study G X E interactions with longitudinal data, as well as a critique of their relative strengths and weaknesses. Of importance, the models reviewed incorporate information on both time invariant and time varying exposures to characterize more dynamic patterns of change across time. The authors use longitudinal data from the Normative Aging Study to illustrate some of the longitudinal models by focusing on pulse pressure, which is a risk factor for arterial stiffness. A reduced set of SNPs that have been identified in this substantive area of research were identified and the outcome measure was level of lead in the tibia bone. The authors describe their approach as a pathway orientation toward identifying how environmental exposures across time may influence changes in bone lead levels. This illustration provides clarity on issues raised in modeling G X E longitudinal data that generalize to other areas of health and to other phenotypes. It also raises critical questions about where we have been and where we need to go in the modeling of G X E interactions with longitudinal data.

Keywords:   Longitudinal cohort designs, G X E longitudinal modelling, Normative Aging Study, Arterial stiffness

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