Authors
Trang Cao, James C Pang, Mehul Gajwani, Ashlea Segal, Alexander Holmes, Joshua F Wiley, Sidhant Chopra, Juan Helen Zhou, Christopher L H Chen, Fang Ji, Ben J Harrison, Christopher G Davey, Toby Constable, Jeggan Tiego, Bree Hartshorn, Jessica Kwee, Mark A Bellgrove, Alex Fornito
Published in
Nature neuroscience. Jul 30, 2026. Epub Jul 30, 2026.
Abstract
Decades of structural magnetic resonance imaging (MRI) studies have documented alterations of gray matter morphometry in psychiatric disorders, but the field has failed to identify any consensus disease phenotypes. Here we examine whether current approaches will ever converge on such phenotypes by evaluating the consistency of brain-wide maps of gray matter volume and cortical thickness differences obtained for each of 59 study sites of five psychiatric disorders (schizophrenia, schizoaffective disorder, autism spectrum disorder, major depressive disorder and bipolar disorder), totaling 2,437 patients and 2,065 controls. We find that cross-site consistency is low (median r ≤ 0.16); markedly reduced compared to Alzheimer's disease (r = 0.54); unexplained by demographic, clinical or scanner differences; and robust to analytic choices. Using bootstrapping, we observe that consistency may improve for sample sizes ≥200 per group for schizophrenia but that other disorders may require much larger samples. Our findings indicate that current widespread practices in structural MRI are unlikely to identify robust morphometric phenotypes for psychiatric disorders.
PMID:
42533130
Bibliographic data and abstract were imported from PubMed on 31 Jul 2026.
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