An ENIGMA voxel-based morphometry (VBM) meta-analysis of structural brain differences in generalized anxiety disorder (GAD)

Authors

  • E Giampetruzzi
  • A Zugman
  • K Kircanski
  • DS Pine

Abstract

The Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA) consortium is a collaborative framework that aggregates neuro-imaging data from different centers and analyzes it using a standardized processing pipeline. This study builds on a previous analysis by the ENIGMA-Anxiety working group in the generalized anxiety disorder (GAD) dataset by employing the ENIGMA voxel-based morphometry (VBM) tool to conduct a whole-brain VBM comparison between individuals with GAD and healthy controls (Harrewjin et al., 2021.) The ENIGMA VBM tool was developed to allow for a meta-analytical approach where each site can process their data independently and share the resulting voxel-based effect size T-maps prior to subsequent meta-analysis using Seed-based d-Mapping (SDM). This method of standardized processing across sites may enhance the reproducibility and robustness of findings.

The current proposal differs from previous methodology in that it employs VBM in a meta-analysis approach to analyze gray and white matter structure. The previous study of the ENIGMA-Anxiety GAD data showed no significant group differences between GAD and healthy controls using Freesurfer in a mega-analysis approach (Harrewjin et al., 2021). It is not uncommon that voxel-based and surface-based methods will yield different results in the same population, and the approaches can be viewed as complementary (Goto et al., 2022; Grimm et al., 2015.) The present study’s use of VBM may help clarify and further capture the complexity of neurostructural abnormalities associated with GAD.

Scientific Focus Area: Neuroscience

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