TY - JOUR
T1 - Atlas of gray matter volume differences across psychiatric conditions
T2 - A systematic review with a novel meta-analysis that considers co-occurring disorders
AU - Fortea, Lydia
AU - Ortuño, Maria
AU - De Prisco, Michele
AU - Oliva, Vincenzo
AU - Albajes-Eizagirre, Anton
AU - Fortea, Adriana
AU - Madero, Santiago
AU - Solanes, Aleix
AU - Vilajosana, Enric
AU - Yao, Yuanwei
AU - Del Fabro, Lorenzo
AU - Galindo, Eduard Solé
AU - Verdolini, Norma
AU - Farré-Colomés, Alvar
AU - Serra-Blasco, Maria
AU - Picó-Pérez, Maria
AU - Lukito, Steve
AU - Wise, Toby
AU - Carlisi, Christina
AU - Arnone, Danilo
AU - Kempton, Matthew
AU - Hauson, Alexander Omar
AU - Wollman, Scott
AU - Soriano-Mas, Carles
AU - Rubia, Katya
AU - Norman, Luke
AU - Fusar-Poli, Paolo
AU - Mataix-Cols, David
AU - Valentí, Marc
AU - Via, Esther
AU - Cardoner, Narcis
AU - Solmi, Marco
AU - Zhang, Jintao
AU - Pan, Pinglei
AU - Shin, Jae Il
AU - Fullana, Miquel Àngel
AU - Vieta, Eduard
AU - Radua, Joaquim
N1 - Copyright © 2024. Published by Elsevier Inc.
PY - 2024/11/2
Y1 - 2024/11/2
N2 - 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.
AB - 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.
U2 - 10.1016/j.biopsych.2024.10.020
DO - 10.1016/j.biopsych.2024.10.020
M3 - Article
C2 - 39491638
SN - 0006-3223
JO - Biological psychiatry
JF - Biological psychiatry
ER -