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Gargano G, Caletti E, Perlini C, Turtulici N, Bellani M, Bonivento C, Garzitto M, Siri FM, Longo C, Bonetto C, Cristofalo D, Scocco P, Semrov E, Preti A, Lazzarotto L, Gardellin F, Lasalvia A, Ruggeri M, Marini A, Brambilla P. Language production impairments in patients with a first episode of psychosis. PLoS One 2022; 17:e0272873. [PMID: 35951619 PMCID: PMC9371299 DOI: 10.1371/journal.pone.0272873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 07/27/2022] [Indexed: 11/18/2022] Open
Abstract
Language production has often been described as impaired in psychiatric diseases such as in psychosis. Nevertheless, little is known about the characteristics of linguistic difficulties and their relation with other cognitive domains in patients with a first episode of psychosis (FEP), either affective or non-affective. To deepen our comprehension of linguistic profile in FEP, 133 patients with FEP (95 non-affective, FEP-NA; 38 affective, FEP-A) and 133 healthy controls (HC) were assessed with a narrative discourse task. Speech samples were systematically analyzed with a well-established multilevel procedure investigating both micro- (lexicon, morphology, syntax) and macro-linguistic (discourse coherence, pragmatics) levels of linguistic processing. Executive functioning and IQ were also evaluated. Both linguistic and neuropsychological measures were secondarily implemented with a machine learning approach in order to explore their predictive accuracy in classifying participants as FEP or HC. Compared to HC, FEP patients showed language production difficulty at both micro- and macro-linguistic levels. As for the former, FEP produced shorter and simpler sentences and fewer words per minute, along with a reduced number of lexical fillers, compared to HC. At the macro-linguistic level, FEP performance was impaired in local coherence, which was paired with a higher percentage of utterances with semantic errors. Linguistic measures were not correlated with any neuropsychological variables. No significant differences emerged between FEP-NA and FEP-A (p≥0.02, after Bonferroni correction). Machine learning analysis showed an accuracy of group prediction of 76.36% using language features only, with semantic variables being the most impactful. Such a percentage was enhanced when paired with clinical and neuropsychological variables. Results confirm the presence of language production deficits already at the first episode of the illness, being such impairment not related to other cognitive domains. The high accuracy obtained by the linguistic set of features in classifying groups support the use of machine learning methods in neuroscience investigations.
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Affiliation(s)
- Giulia Gargano
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Elisabetta Caletti
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda-Ospedale Maggiore Policlinico, Milan, Italy
| | - Cinzia Perlini
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
- Verona Hospital Trust–Azienda Ospedaliera Universitaria Integrata Verona–AOUI, Verona, Italy
| | - Nunzio Turtulici
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Marcella Bellani
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
- Verona Hospital Trust–Azienda Ospedaliera Universitaria Integrata Verona–AOUI, Verona, Italy
| | - Carolina Bonivento
- IRCCS “E.Medea” Polo Friuli Venezia Giulia, San Vito al Tagliamento, PN, Italy
| | - Marco Garzitto
- Department of Languages and Literatures, Communication, Education and Society, University of Udine, Udine, Italy
| | - Francesca Marzia Siri
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda-Ospedale Maggiore Policlinico, Milan, Italy
| | - Chiara Longo
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda-Ospedale Maggiore Policlinico, Milan, Italy
| | - Chiara Bonetto
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Doriana Cristofalo
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Paolo Scocco
- Department of Mental Health, Azienda ULSS 16, Padua, Italy
| | | | - Antonio Preti
- Department of Mental Health, Niguarda Ca’ Granda Hospital, Milan, Italy
| | - Lorenza Lazzarotto
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | | | - Antonio Lasalvia
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
- Verona Hospital Trust–Azienda Ospedaliera Universitaria Integrata Verona–AOUI, Verona, Italy
| | - Mirella Ruggeri
- Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
- Verona Hospital Trust–Azienda Ospedaliera Universitaria Integrata Verona–AOUI, Verona, Italy
| | - Andrea Marini
- Department of Languages and Literatures, Communication, Education and Society, University of Udine, Udine, Italy
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda-Ospedale Maggiore Policlinico, Milan, Italy
- * E-mail:
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