Extending schizophrenia diagnostic model to predict schizotypy in first-degree relatives
description: Recently, we developed a machine-learning algorithm EMPaSchiz that learns, from a training set of schizophrenia patients and healthy individuals, a model that predicts if a novel individual has schizophrenia, based on features extracted from his/her resting-state functional magnetic resonance imaging. In this study, we apply this learned model to first-degree relatives of schizophrenia patients, who were found to not have active psychosis or schizophrenia. We observe that the participants that this model classified as schizophrenia patients had significantly higher schizotypal personality scores than those who were not. Further, the EMPaSchiz probability score for schizophrenia status was significantly correlated with schizotypal personality score. This demonstrates the potential of machine-learned diagnostic models to predict state-independent vulnerability, even when symptoms do not meet the full criteria for clinical diagnosis. 2020, The Author(s).
creator: Kalmady S.V.; Paul A.K.; Greiner R.; Agrawal R.; Amaresha A.C.; Shivakumar V.; Narayanaswamy J.C.; Greenshaw A.J.; Dursun S.M.; Venkatasubramanian G.
source: npj Schizophrenia, Vol-6, No. 1
publisher: Nature Research
date: 2020-01-01
rights: All Open Access; Gold Open Access; Green Open Access
relation: ISSN: 2334265X
format: Online
language: English
type: Article
coverage: Kalmady S.V., Alberta Machine Intelligence Institute, University of Alberta, Edmonton, AB, Canada, Canadian VIGOUR Centre, University of Alberta, Edmonton, AB, Canada; Paul A.K., Alberta Machine Intelligence Institute, University of Alberta, Edmonton, AB, Canada, Department of Computing Science, University of Alberta, Edmonton, AB, Canada; Greiner R., Alberta Machine Intelligence Institute, University of Alberta, Edmonton, AB, Canada, Department of Computing Science, University of Alberta, Edmonton, AB, Canada, Department of Psychiatry, University of Alberta, Edmonton, AB, Canada; Agrawal R., Translational Psychiatry Laboratory, Neurobiology Research Centre, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Amaresha A.C., Department of Sociology and Social Work, Christ- Deemed to be University Bangalore, Bangalore, India; Shivakumar V., Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India, Department of Integrative Medicine, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Narayanaswamy J.C., Translational Psychiatry Laboratory, Neurobiology Research Centre, National Institute of Mental Health and Neuro Sciences, Bangalore, India, Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Greenshaw A.J., Department of Psychiatry, University of Alberta, Edmonton, AB, Canada; Dursun S.M., Department of Psychiatry, University of Alberta, Edmonton, AB, Canada; Venkatasubramanian G., Translational Psychiatry Laboratory, Neurobiology Research Centre, National Institute of Mental Health and Neuro Sciences, Bangalore, India, Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India