Understanding interactions between risk factors, and assessing the utility of the additive and multiplicative models through simulations.

ABSTRACT: Understanding the genetic background of complex diseases requires the expansion of studies beyond univariate associations. Therefore, it is important to use interaction assessments of risk factors in order to discover whether, and how genetic risk variants act together on disease development. The principle of interaction analysis is to explore the magnitude of the combined effect of risk factors on disease causation. In this study, we use simulations to investigate different scenarios of causation to show how the magnitude of the effect of two risk factors interact. We mainly focus on the two most commonly used interaction models, the additive and multiplicative risk scales, since there is often confusion regarding their use and interpretation. Our results show that the combined effect is

SUBMITTER: Diaz-Gallo LM 

PROVIDER: S-EPMC8075235 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature