Atlas of Gray Matter Volume Differences Across Psychiatric Conditions: A Systematic Review With a Novel Meta-Analysis That Considers Co-Occurring Disorders

地图集(解剖学) 荟萃分析 灰色(单位) 心理学 精神科 医学 病理 核医学 解剖
作者
Lydia Fortea,María Ortuño,Michele De Prisco,Vincenzo Oliva,Anton Albajes‐Eizagirre,Adriana Fortea,Santiago Madero,Aleix Solanes,Enric Vilajosana,Yuan‐Wei Yao,Lorenzo Del Fabro,Eduard Solé‐González,Norma Verdolini,Àlvar Farré‐Colomés,Maria Serra-Blasco,Maria Picó‐Pérez,Steve Lukito,Toby Wise,Christina Carlisi,Danilo Arnone
出处
期刊:Biological Psychiatry [Elsevier BV]
卷期号:98 (1): 76-90 被引量:13
标识
DOI:10.1016/j.biopsych.2024.10.020
摘要

BACKGROUND: Regional gray matter volume (GMV) differences between individuals with mental disorders and comparison participants may be confounded by co-occurring disorders. To disentangle disorder-specific GMV correlates, we conducted a large-scale multidisorder 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 that compared adults with major mental disorders (anorexia nervosa, schizophrenia spectrum, anxiety, bipolar, major depressive, obsessive-compulsive, and posttraumatic stress disorders plus attention-deficit/hyperactivity, autism spectrum, and borderline personality disorders) with comparison participants. Two authors independently extracted data and assessed quality using the Newcastle-Ottawa Scale. We derived GMV correlates for each disorder using: 1) a multidisorder meta-analysis that accounted for all co-occurring mental disorders simultaneously and 2) separate standard meta-analyses for each disorder in which co-occurring disorders were ignored. We assessed the alterations' extent, intensity (effect size), and specificity (interdisorder correlations and transdiagnostic alterations) for both approaches. RESULTS: We included 433 studies (499 datasets) involving 19,718 patients and 16,441 comparison participants (51% female, ages 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.
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