Dataset Information

Investigating temporal and prosodic markers in clinical high-risk for psychosis participants using automated acoustic analysis.

ABSTRACT:

Aim

Language disturbances are a candidate biomarker for the early detection of psychosis. Temporal and prosodic abnormalities have been observed in schizophrenia patients, while there is conflicting evidence whether such deficits are present in participants meeting clinical high-risk for psychosis (CHR-P) criteria.

Methods

Clinical interviews from CHR-P participants (n = 50) were examined for temporal and prosodic metrics and compared against a group of healthy controls (n = 17) and participants with affective disorders and substance abuse (n = 23).

Results

There were no deficits in acoustic variables in the CHR-P group, while participants with affective disorders/substance abuse were characterized by slower speech rate, longer pauses and higher unvoiced frames percentage.

Conclusion

Our finding suggests that temporal and prosodic aspects of speech are not impaired in early-stage psychosis. Further studies are required to clarify whether such abnormalities are present in sub-groups of CHR-P participants with elevated psychosis-risk.

SUBMITTER: Bianciardi B

PROVIDER: S-EPMC10946925 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Publications

Investigating temporal and prosodic markers in clinical high-risk for psychosis participants using automated acoustic analysis.

Bianciardi Bianca B Gajwani Ruchika R Gross Joachim J Gumley Andrew I AI Lawrie Stephen M SM Moelling Melina M Schwannauer Matthias M Schultze-Lutter Frauke F Fracasso Alessio A Uhlhaas Peter J PJ

Early intervention in psychiatry 20221007 3

<h4>Aim</h4>Language disturbances are a candidate biomarker for the early detection of psychosis. Temporal and prosodic abnormalities have been observed in schizophrenia patients, while there is conflicting evidence whether such deficits are present in participants meeting clinical high-risk for psychosis (CHR-P) criteria.<h4>Methods</h4>Clinical interviews from CHR-P participants (n = 50) were examined for temporal and prosodic metrics and compared against a group of healthy controls (n = 17) a ...[more]

PMID: 36205386

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Project description:Neuroinflammatory events prior to the diagnosis of schizophrenia may play a role in transition to illness. To date only one in-vivo study has investigated this association between peripheral proinflammatory cytokines and brain markers of inflammation (e.g., mitochondrial 18 kDa translocator protein, TSPO) in schizophrenia, but none in its putative prodrome. In this study, we primarily aimed to (Barron et al., 2017) test study group (clinical high-risk (CHR) and healthy controls) differences in peripheral inflammatory markers and test for any associations with symptom measures, (Hafizi et al., 2017a) investigate the interaction between brain TSPO levels (dorsolateral prefrontal cortex (DLPFC) and hippocampus) and peripheral inflammatory clusters (entire cohort and (CHR) group independently) within a relatively large group of individuals at CHR for psychosis (N = 38) and healthy controls (N = 20). Participants underwent structural brain magnetic resonance imaging (MRI) and TSPO [18F]FEPPA positron emission tomography (PET) scans. Serum samples were assessed for peripheral inflammatory markers (i.e., CRP and interleukins). For exploratory analysis, we aimed to examine cluster differences for symptom measures and identify independent peripheral predictors of brain TSPO expression. Here, we report increased IL-8 levels that are positively correlated with prodromal general symptom severity and showed trend-level association with apathy in CHR. We identified distinct inflammatory clusters characterized by inflammatory markers (IL-1 β, IL-2, IFN-γ) that were comparable between entire cohort and CHR. TSPO levels did not differ between inflammatory clusters (entire cohort or CHR). Finally, we show that CRP, IL-1 β, TNF-α, and IFN-γ levels were the independent peripheral predictors of brain TSPO expression. Thus, alterations in brain TSPO expression in response to inflammatory processes are not evident in CHR. Taken together, clustering by inflammatory status is a promising strategy to characterize the interaction between brain TSPO and peripheral markers of inflammation.

Project description:IntroductionIdentification of participants at clinical high-risk (CHR) for the development of psychosis is an important objective of current preventive efforts in mental health research. However, the utility of using web-based screening approaches to detect CHR participants at the population level has not been investigated.MethodsWe tested a web-based screening approach to identify CHR individuals. Potential participants were invited to a website via e-mail invitations, flyers, and invitation letters involving both the general population and mental health services. Two thousand two hundred seventy-nine participants completed the 16-item version of the prodromal questionnaire (PQ-16) and a 9-item questionnaire of perceptual and cognitive aberrations (PCA) for the assessment of basic symptoms (BS) online. 52.3% of participants met a priori cut-off criteria for the PQ and 73.6% for PCA items online. One thousand seven hundred eighty-seven participants were invited for a clinical interview and n = 356 interviews were conducted (response rate: 19.9%) using the Comprehensive Assessment of At-Risk Mental State (CAARMS) and the Schizophrenia Proneness Interview, Adult Version (SPI-A). n = 101 CHR participants and n = 8 first-episode psychosis (FEP) were detected. ROC curve analysis revealed good to moderate sensitivity and specificity for predicting CHR status based on online results for both UHR and BS criteria (sensitivity/specificity: PQ-16 = 82%/46%; PCA = 94%/12%). Selection of a subset of 10 items from both PQ-16 and PCA lead to an improved of specificity of 57% while only marginally affecting sensitivity (81%). CHR participants were characterized by similar levels of functioning and neurocognitive deficits as clinically identified CHR groups.ConclusionThese data provide evidence for the possibility to identify CHR participants through population-based web screening. This could be an important strategy for early intervention and diagnosis of psychotic disorders.

Dataset Information

Investigating temporal and prosodic markers in clinical high-risk for psychosis participants using automated acoustic analysis.

Aim

Methods

Results

Conclusion

Publications

Investigating temporal and prosodic markers in clinical high-risk for psychosis participants using automated acoustic analysis.

Similar Datasets

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