Linking language features to clinical symptoms and multimodal imaging in individuals at clinical high risk for psychosis.

Autor:	Haas SS; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA., Doucet GE; Boys Town National Research Hospital, Omaha, Nebraska, USA., Garg S; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA., Herrera SN; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA., Sarac C; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA., Bilgrami ZR; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA., Shaik RB; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA., Corcoran CM; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Jazyk:	angličtina
Zdroj:	European psychiatry : the journal of the Association of European Psychiatrists [Eur Psychiatry] 2020 Aug 11; Vol. 63 (1), pp. e72. Date of Electronic Publication: 2020 Aug 11.
DOI:	10.1192/j.eurpsy.2020.73
Abstrakt:	Background: Abnormalities in the semantic and syntactic organization of speech have been reported in individuals at clinical high-risk (CHR) for psychosis. The current study seeks to examine whether such abnormalities are associated with changes in brain structure and functional connectivity in CHR individuals. Methods: Automated natural language processing analysis was applied to speech samples obtained from 46 CHR and 22 healthy individuals. Brain structural and resting-state functional imaging data were also acquired from all participants. Sparse canonical correlation analysis (sCCA) was used to ascertain patterns of covariation between linguistic features, clinical symptoms, and measures of brain morphometry and functional connectivity related to the language network. Results: In CHR individuals, we found a significant mode of covariation between linguistic and clinical features (r = 0.73; p = 0.003), with negative symptoms and bizarre thinking covarying mostly with measures of syntactic complexity. In the entire sample, separate sCCAs identified a single mode of covariation linking linguistic features with brain morphometry (r = 0.65; p = 0.05) and resting-state network connectivity (r = 0.63; p = 0.01). In both models, semantic and syntactic features covaried with brain structural and functional connectivity measures of the language network. However, the contribution of diagnosis to both models was negligible. Conclusions: Syntactic complexity appeared sensitive to prodromal symptoms in CHR individuals while the patterns of brain-language covariation seemed preserved. Further studies in larger samples are required to establish the reproducibility of these findings.
Databáze:	MEDLINE
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