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Title: A knowledge-based multivariate method for examining gene-brain-behavioural/cognitive relationships Authors:  Heungsun Hwang - McGill University (Canada) [presenting]
Abstract: With advances in neuroimaging and genetics, imaging genetics is a naturally emerging field that combines genetic and neuroimaging data with behavioural or cognitive outcomes to examine the genetic influence on altered brain functions associated with behavioural or cognitive variation. We propose a statistical approach, termed imaging genetics generalized structured component analysis (IG-GSCA), which allows researchers to investigate such gene-brain-behaviour/cognitive associations, taking into account well-documented biological characteristics (e.g., genetic pathways, gene-environment interactions, etc.) and methodological complexities (e.g., multicollinearity) in imaging genetic studies. We describe the conceptual and technical underpinnings of IG-GSCA and provide its application for investigating how several depression-related genes and their interactions with an environmental variable (experience of potentially traumatic events) might influence the thickness variations of 53 brain regions, which in turn tended to affect depression severity in a sample of Korean participants.