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

Publicat a:Biological Psychiatry. S0006-3223 (24): 01729-3 - 2024-11-02 S0006-3223(24), DOI: 10.1016/j.biopsych.2024.10.020

Autors: Fortea L; Ortuño M; De Prisco M; Oliva V; Albajes-Eizagirre A; Fortea A; Madero S; Solanes A; Vilajosana E; Yao Y; Del Fabro L; Solé E; Verdolini N; Farré-Colomés A; Serra-Blasco M; Picó-Pérez M; Lukito S; Wise T; Carlisi C; Arnone D; Kempton MJ; Hauson AO; Wollman S; Soriano-Mas C; Rubia K; Norman L; Fusar-Poli P; Mataix-Cols D; Valentí M; Via E; Cardoner N; Solmi M; Zhang J; Pan P; Shin JI; Fullana MA; Vieta E; Radua J

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Resum

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. 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. 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). 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.

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