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Multivariate patterns of gray matter volume in thalamic nuclei are associated with positive schizotypy in healthy individuals

Published online by Cambridge University Press:  30 July 2019

Pasquale Di Carlo Open the ORCID record for Pasquale Di Carlo [Opens in a new window] ,
Giulio Pergola Open the ORCID record for Giulio Pergola [Opens in a new window] ,
Linda A. Antonucci Open the ORCID record for Linda A. Antonucci [Opens in a new window] ,
Aurora Bonvino Open the ORCID record for Aurora Bonvino [Opens in a new window] ,
Marina Mancini Open the ORCID record for Marina Mancini [Opens in a new window] ,
Tiziana Quarto ,
Antonio Rampino Open the ORCID record for Antonio Rampino [Opens in a new window] ,
Teresa Popolizio Open the ORCID record for Teresa Popolizio [Opens in a new window] ,
Alessandro Bertolino  and
Giuseppe Blasi Open the ORCID record for Giuseppe Blasi [Opens in a new window]
Pasquale Di Carlo
Affiliation:
Group of Psychiatric Neuroscience, Department of Basic Medical Science, Neuroscience, and Sense Organs – University of Bari Aldo Moro, Bari, Italy Lieber Institute for Brain Development, Johns Hopkins Medical Campus – Baltimore, MD, USA
Giulio Pergola
Affiliation:
Group of Psychiatric Neuroscience, Department of Basic Medical Science, Neuroscience, and Sense Organs – University of Bari Aldo Moro, Bari, Italy Lieber Institute for Brain Development, Johns Hopkins Medical Campus – Baltimore, MD, USA
Linda A. Antonucci
Affiliation:
Group of Psychiatric Neuroscience, Department of Basic Medical Science, Neuroscience, and Sense Organs – University of Bari Aldo Moro, Bari, Italy Department of Psychiatry and Psychotherapy – Ludwig-Maximilians University, Munich, Germany
Aurora Bonvino
Affiliation:
Group of Psychiatric Neuroscience, Department of Basic Medical Science, Neuroscience, and Sense Organs – University of Bari Aldo Moro, Bari, Italy IRCCS ‘Casa Sollievo della Sofferenza’, San Giovanni Rotondo, Italy
Marina Mancini
Affiliation:
Group of Psychiatric Neuroscience, Department of Basic Medical Science, Neuroscience, and Sense Organs – University of Bari Aldo Moro, Bari, Italy
Tiziana Quarto
Affiliation:
Group of Psychiatric Neuroscience, Department of Basic Medical Science, Neuroscience, and Sense Organs – University of Bari Aldo Moro, Bari, Italy
Antonio Rampino
Affiliation:
Group of Psychiatric Neuroscience, Department of Basic Medical Science, Neuroscience, and Sense Organs – University of Bari Aldo Moro, Bari, Italy Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
Teresa Popolizio
Affiliation:
IRCCS ‘Casa Sollievo della Sofferenza’, San Giovanni Rotondo, Italy
Alessandro Bertolino
Affiliation:
Group of Psychiatric Neuroscience, Department of Basic Medical Science, Neuroscience, and Sense Organs – University of Bari Aldo Moro, Bari, Italy Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
Giuseppe Blasi*
Affiliation:
Group of Psychiatric Neuroscience, Department of Basic Medical Science, Neuroscience, and Sense Organs – University of Bari Aldo Moro, Bari, Italy Azienda Ospedaliero-Universitaria Consorziale Policlinico, Bari, Italy
*
Author for correspondence: Giuseppe Blasi, E-mail: giuseppe.blasi@uniba.it
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Abstract

Background

Previous models suggest biological and behavioral continua among healthy individuals (HC), at-risk condition, and full-blown schizophrenia (SCZ). Part of these continua may be captured by schizotypy, which shares subclinical traits and biological phenotypes with SCZ, including thalamic structural abnormalities. In this regard, previous findings have suggested that multivariate volumetric patterns of individual thalamic nuclei discriminate HC from SCZ. These results were obtained using machine learning, which allows case–control classification at the single-subject level. However, machine learning accuracy is usually unsatisfactory possibly due to phenotype heterogeneity. Indeed, a source of misclassification may be related to thalamic structural characteristics of those HC with high schizotypy, which may resemble structural abnormalities of SCZ. We hypothesized that thalamic structural heterogeneity is related to schizotypy, such that high schizotypal burden would implicate misclassification of those HC whose thalamic patterns resemble SCZ abnormalities.

Methods

Following a previous report, we used Random Forests to predict diagnosis in a case–control sample (SCZ = 131, HC = 255) based on thalamic nuclei gray matter volumes estimates. Then, we investigated whether the likelihood to be classified as SCZ (π-SCZ) was associated with schizotypy in 174 HC, evaluated with the Schizotypal Personality Questionnaire.

Results

Prediction accuracy was 72.5%. Misclassified HC had higher positive schizotypy scores, which were correlated with π-SCZ. Results were specific to thalamic rather than whole-brain structural features.

Conclusions

These findings strengthen the relevance of thalamic structural abnormalities to SCZ and suggest that multivariate thalamic patterns are correlates of the continuum between schizotypy in HC and the full-blown disease.

Keywords

Machine learningrandom forestsmagnetic resonance imagingschizophreniaSchizotypal Personality Questionnaire (SPQ)thalamus

Information

Type
Original Articles
Information
Psychological Medicine , Volume 50 , Issue 9 , July 2020 , pp. 1501 - 1509
Copyright
Copyright © Cambridge University Press 2019

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