{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T21:54:53Z","timestamp":1792446893152,"version":"4.5.0"},"reference-count":78,"publisher":"Cambridge University Press (CUP)","issue":"14","license":[{"start":{"date-parts":[[2023,3,6]],"date-time":"2023-03-06T00:00:00Z","timestamp":1678060800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Psychol. Med."],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec id=\"S0033291723000302_sec_a1\"><jats:title>Background<\/jats:title><jats:p>Mental disorders, including depression, obsessive compulsive disorder (OCD), and schizophrenia, share a common neuropathy of disturbed large-scale coordinated brain maturation. However, high-interindividual heterogeneity hinders the identification of shared and distinct patterns of brain network abnormalities across mental disorders. This study aimed to identify shared and distinct patterns of altered structural covariance across mental disorders.<\/jats:p><\/jats:sec><jats:sec id=\"S0033291723000302_sec_a2\" sec-type=\"methods\"><jats:title>Methods<\/jats:title><jats:p>Subject-level structural covariance aberrance in patients with mental disorders was investigated using individualized differential structural covariance network. This method inferred structural covariance aberrance at the individual level by measuring the degree of structural covariance in patients deviating from matched healthy controls (HCs). T1-weighted anatomical images of 513 participants (105, 98, 190 participants with depression, OCD and schizophrenia, respectively, and 130 age- and sex-matched HCs) were acquired and analyzed.<\/jats:p><\/jats:sec><jats:sec id=\"S0033291723000302_sec_a3\" sec-type=\"results\"><jats:title>Results<\/jats:title><jats:p>Patients with mental disorders exhibited notable heterogeneity in terms of altered edges, which were otherwise obscured by group-level analysis. The three disorders shared high difference variability in edges attached to the frontal network and the subcortical-cerebellum network, and they also exhibited disease-specific variability distributions. Despite notable variability, patients with the same disorder shared disease-specific groups of altered edges. Specifically, depression was characterized by altered edges attached to the subcortical-cerebellum network; OCD, by altered edges linking the subcortical-cerebellum and motor networks; and schizophrenia, by altered edges related to the frontal network.<\/jats:p><\/jats:sec><jats:sec id=\"S0033291723000302_sec_a4\" sec-type=\"conclusions\"><jats:title>Conclusions<\/jats:title><jats:p>These results have potential implications for understanding heterogeneity and facilitating personalized diagnosis and interventions for mental disorders.<\/jats:p><\/jats:sec>","DOI":"10.1017\/s0033291723000302","type":"journal-article","created":{"date-parts":[[2023,3,6]],"date-time":"2023-03-06T11:12:05Z","timestamp":1678101125000},"page":"6780-6791","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":13,"title":["Identification of shared and distinct patterns of brain network abnormality across mental disorders through individualized structural covariance 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