Are neuroanatomical phenotypes for psychiatric disorders robust? An assessment of the reproducibility of grey matter differences in mental illness

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This study found low cross-site consistency in grey matter morphometry differences for five psychiatric disorders, suggesting current structural MRI practices are unlikely to yield robust phenotypes.

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This multicenter MRI study assessed how reproducible brain-wide grey matter volume and cortical thickness difference maps are across 59 sites for five psychiatric disorders (schizophrenia, schizoaffective disorder, autism spectrum disorder, major depressive disorder, and bipolar disorder), using 2437 patients and 2065 controls, and benchmarking against Alzheimer’s disease data from 7 sites. The authors found low cross-site consistency for psychiatric disorders (median pair-wise spatial correlation r ≤ 0.16) compared with Alzheimer’s disease (r = 0.54), and reported that consistency was not strongly driven by variations in demographic, clinical, or scanner characteristics and was robust to processing/analysis choices. Bootstrapping suggested schizophrenia could yield higher consistency (r > 0.5) when site-specific sample sizes exceed about 200 cases and controls, whereas other disorders likely require much larger samples and/or more phenotypically homogeneous recruitment. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Decades of structural magnetic resonance imaging (MRI) studies have documented alterations of grey 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 grey 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 2437 patients and 2065 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.
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Abstract

Background Despite thousands of magnetic resonance imaging (MRI) studies reporting grey matter alterations in psychiatric disorders, the field has failed to converge on robust neuroanatomical phenotypes for any specific diagnosis. Here, we examine whether current practices will ever converge on such a phenotype, which is essential for tracking illness risk, progression, and treatment.

Methods

We evaluated the consistency of brain-wide maps of grey matter volume and cortical thickness alterations obtained for each of 59 study sites of five psychiatric disorders (schizophrenia, schizoaffective disorder, autism spectrum disorder, major depressive disorder, and bipolar disorder), totalling 2437 patients and 2065 controls. We calculated cross-site consistency using spatial correlations between pairs of site-specific difference maps and benchmarked the findings against 7 study sites of Alzheimer’s disease (654 patients, 937 controls). Findings Disorder-specific volume and thickness alterations showed low consistency, with a median pair-wise cross-site correlation of 𝑟 ≤ 0.16 for psychiatric disorders compared to 𝑟 = 0.54 in Alzheimer’s disease. Consistency estimates were not strongly associated with site-specific variations in 19 different demographic, clinical, and scanner characteristics of the study participants and were robust to data processing and analysis. Bootstrapping analyses indicated that consistent results (𝑟 > 0.5) could be obtained for schizophrenia if study-specific sample sizes exceed approximately 200 (for cases and controls), but consistent findings for other disorders may require much larger samples. Interpretation Our findings indicate that current widespread practices, involving case-control comparisons of convenience samples numbering between 30 and 100 patients, will not converge on robust neuroanatomical phenotypes for psychiatric disorders. Increasing sample size will facilitate this goal in schizophrenia, but much larger samples, or refined ascertainment strategies aiming to recruit phenotypically homogeneous patient subgroups, may be required for other disorders. Competing Interest Statement The authors have declared no competing interest. Funding Statement This study was funded by National Health and Medical Research Council, Australian Research Council, Singapore National Medical Research Council, Yong Loo Lin School of Medicine Research Core Funding. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Human Ethics Team of Monash University gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes Funding: National Health and Medical Research Council and Australian Research Council. Singapore National Medical Research Council, Yong Loo Lin School of Medicine Research Core Funding. Data Availability All data produced in the present study are available upon reasonable request to the authors

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