Atlas of gray matter volume differences across psychiatric conditions: A systematic review with a novel meta-analysis that considers co-occurring disorders

Lydia Fortea, Maria Ortuño, Michele De Prisco, Vincenzo Oliva, Anton Albajes-Eizagirre, Adriana Fortea, Santiago Madero, Aleix Solanes, Enric Vilajosana, Yuanwei Yao, Lorenzo Del Fabro, Eduard Solé Galindo, Norma Verdolini, Alvar Farré-Colomés, Maria Serra-Blasco, Maria Picó-Pérez, Steve Lukito, Toby Wise, Christina Carlisi, Danilo ArnoneMatthew Kempton, Alexander Omar Hauson, Scott Wollman, Carles Soriano-Mas, Katya Rubia, Luke Norman, Paolo Fusar-Poli, David Mataix-Cols, Marc Valentí, Esther Via, Narcis Cardoner, Marco Solmi, Jintao Zhang, Pinglei Pan, Jae Il Shin, Miquel Àngel Fullana, Eduard Vieta, Joaquim Radua

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Abstract

BACKGROUND: Regional gray matter volume (GMV) differences between individuals with mental disorders and comparison subjects may be confounded by co-occurring disorders. To disentangle the disorder-specific GMV correlates, we conducted a large-scale multi-disorder meta-analysis using a novel approach that explicitly models co-occurring disorders.

METHODS: We systematically reviewed voxel-based morphometry studies indexed in PubMed and Scopus up to January 2023 comparing adults with major mental disorders (anorexia nervosa, schizophrenia-spectrum, anxiety, bipolar, major depressive, obsessive-compulsive, and post-traumatic stress disorders, plus attention-deficit/hyperactivity, autism spectrum, and borderline personality disorders) to comparison subjects. Two authors independently extracted data and assessed quality using the Newcastle-Ottawa Scale. We derived GMV correlates for each disorder using: a) a multi-disorder meta-analysis accounting for all co-occurring mental disorders simultaneously; b) separate standard meta-analyses for each disorder ignoring co-occurring disorders. We assessed the alterations' extent, intensity (effect size), and specificity (inter-disorder correlations and transdiagnostic alterations) for both approaches.

RESULTS: We included 433 studies (499 datasets) involving 19,718 patients and 16,441 comparison subjects (51% females, aged 20-67 years). We provide GMV correlate maps for each disorder using both approaches. The novel approach, which accounted for co-occurring disorders, produced GMV correlates that were more focal and disorder-specific (less correlated across disorders and fewer transdiagnostic abnormalities).

CONCLUSIONS: This work offers the most comprehensive atlas of GMV correlates across major mental disorders. Modeling co-occurring disorders yielded more specific correlates, supporting this approach's validity. The atlas NIfTI maps are available online.

Original languageEnglish
JournalBiological psychiatry
Early online date2 Nov 2024
DOIs
Publication statusE-pub ahead of print - 2 Nov 2024

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