Evidence map›Paper›PMID 42533130›Full record

ArticleNature neuroscience2026

The cross-site reproducibility of MRI morphometric phenotypes in psychiatric disorders.

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 and 8 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Trang CaoTurner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia. trang.cao@monash.edu.ORCID http://orcid.org/0000-0003-4000-8931
James C PangTurner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.ORCID http://orcid.org/0000-0002-2461-2760
Mehul GajwaniTurner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
Ashlea SegalTurner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
Alexander HolmesCentre for Integrative Neuroimaging (OxCIN), FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Joshua F WileyTurner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
Sidhant ChopraOrygen, The National Centre of Excellence in Youth Mental Health, Parkville, Victoria, Australia.ORCID http://orcid.org/0000-0003-0866-3477
Juan Helen ZhouCentre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0002-0180-8648
Christopher L H ChenMemory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0002-1047-9225
Fang JiCentre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0002-7471-0115
Ben J HarrisonDepartment of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia.
Christopher G DaveyDepartment of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia.ORCID http://orcid.org/0000-0003-1431-3852
Toby ConstableTurner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.ORCID http://orcid.org/0000-0001-9904-6129
Jeggan TiegoTurner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.ORCID http://orcid.org/0000-0001-7835-6398
Bree HartshornTurner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
Jessica KweeTurner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.ORCID http://orcid.org/0009-0007-1094-3626
Mark A BellgroveTurner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.ORCID http://orcid.org/0000-0003-0186-8349
Alex FornitoTurner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia. alex.fornito@monash.edu.ORCID http://orcid.org/0000-0001-9134-480X

Funding

Department of Education and Training | Australian Research Council (ARC) DP200103509, FL220100184Department of Health | National Health and Medical Research Council (NHMRC) 1146292, 1197431Department of Health | National Health and Medical Research Council (NHMRC) 2033976Department of Health | National Health and Medical Research Council (NHMRC) 2034000
6 · The paper itself

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.

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.