Journal article
Regional, circuit and network heterogeneity of brain abnormalities in psychiatric disorders
- Abstract:
- The substantial individual heterogeneity that characterizes people with mental illness is often ignored by classical case–control research, which relies on group mean comparisons. Here we present a comprehensive, multiscale characterization of the heterogeneity of gray matter volume (GMV) differences in 1,294 cases diagnosed with one of six conditions (attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, obsessive–compulsive disorder and schizophrenia) and 1,465 matched controls. Normative models indicated that person-specific deviations from population expectations for regional GMV were highly heterogeneous, affecting the same area in <7% of people with the same diagnosis. However, these deviations were embedded within common functional circuits and networks in up to 56% of cases. The salience–ventral attention system was implicated transdiagnostically, with other systems selectively involved in depression, bipolar disorder, schizophrenia and attention-deficit/hyperactivity disorder. Phenotypic differences between cases assigned the same diagnosis may thus arise from the heterogeneous localization of specific regional deviations, whereas phenotypic similarities may be attributable to the dysfunction of common functional circuits and networks.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 9.9MB, Terms of use)
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- Publisher copy:
- 10.1038/s41593-023-01404-6
Authors
- Publisher:
- Nature Research
- Journal:
- Nature Neuroscience More from this journal
- Volume:
- 26
- Issue:
- 9
- Pages:
- 1613-1629
- Publication date:
- 2023-08-14
- Acceptance date:
- 2023-07-13
- DOI:
- EISSN:
-
1546-1726
- ISSN:
-
1097-6256
- Language:
-
English
- Keywords:
- Pubs id:
-
2374530
- UUID:
-
uuid_2383fef7-de81-43ef-b6e9-c6e88f72d5eb
- Local pid:
-
pubs:2374530
- Source identifiers:
-
3714336
- Deposit date:
-
2026-01-31
- ARK identifier:
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Terms of use
- Copyright date:
- 2023
- Licence:
- CC Attribution (CC BY)
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