Focusing on Comorbidity—A Novel Meta-Analytic Approach and Protocol to Disentangle the Specific Neuroanatomy of Co-occurring Mental Disorders

Lydia Fortea, Anton Albajes-Eizagirre, Yuan Wei Yao, Edu Soler, Norma Verdolini, Alexander O. Hauson, Adriana Fortea, Santiago Madero, Aleix Solanes, Scott C. Wollman, Maria Serra-Blasco, Toby Wise, Steve Lukito, Maria Picó-Pérez, Christina Carlisi, Jin Tao Zhang, Ping Lei Pan, Álvar Farré-Colomés, Danilo Arnone, Matthew J. KemptonCarles Soriano-Mas, Katya Rubia, Luke Norman, Paolo Fusar-Poli, David Mataix-Cols, Marc Valentí, Esther Via, Narcis Cardoner, Marco Solmi, Jae I. Shin, Eduard Vieta, Joaquim Radua

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Background: In mental health, comorbidities are the norm rather than the exception. However, current meta-analytic methods for summarizing the neural correlates of mental disorders do not consider comorbidities, reducing them to a source of noise and bias rather than benefitting from their valuable information. Objectives: We describe and validate a novel neuroimaging meta-analytic approach that focuses on comorbidities. In addition, we present the protocol for a meta-analysis of all major mental disorders and their comorbidities. Methods: The novel approach consists of a modification of Seed-based d Mapping—with Permutation of Subject Images (SDM-PSI) in which the linear models have no intercept. As in previous SDM meta-analyses, the dependent variable is the brain anatomical difference between patients and controls in a voxel. However, there is no primary disorder, and the independent variables are the percentages of patients with each disorder and each pair of potentially comorbid disorders. We use simulations to validate and provide an example of this novel approach, which correctly disentangled the abnormalities associated with each disorder and comorbidity. We then describe a protocol for conducting the new meta-analysis of all major mental disorders and their comorbidities. Specifically, we will include all voxel-based morphometry (VBM) studies of mental disorders for which a meta-analysis has already been published, including at least 10 studies. We will use the novel approach to analyze all included studies in two separate single linear models, one for children/adolescents and one for adults. Discussion: The novel approach is a valid method to focus on comorbidities. The meta-analysis will yield a comprehensive atlas of the neuroanatomy of all major mental disorders and their comorbidities, which we hope might help develop potential diagnostic and therapeutic tools.

Original languageEnglish
Article number807839
JournalFrontiers in Psychiatry
Volume12
DOIs
Publication statusPublished - Jan 18 2022

Keywords

  • comorbidity
  • gray matter (GM)
  • magnetic resonance imaging (MRI)
  • medication
  • mental disorder
  • meta-analysis
  • seed-based d mapping (SDM)

ASJC Scopus subject areas

  • Psychiatry and Mental health

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