Eye Movement Patterns Can Distinguish Schizophrenia From the Major Affective Disorders and Healthy Control Subjects

David St Clair* (Corresponding Author), Graeme MacLennan, Sara A Beedie, Eva Nouzová, Helen Lemmon, Dan Rujescu, Philip J Benson, Andrew McIntosh, Mintu Nath

*Corresponding author for this work

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Abstract

No objective tests are currently available to help diagnosis of major psychiatric disorders. This study evaluates the potential of eye movement behavior patterns to predict schizophrenia subjects compared to those with major affective disorders and control groups.Eye movements were recorded from a training set of UK subjects with schizophrenia (SCZ; n = 120), bipolar affective disorder (BPAD; n = 141), major depressive disorder (MDD; n = 136), and healthy controls (CON; n = 142), and from a hold-out set of 133 individuals with proportional group sizes. A German cohort of SCZ (n = 60) and a Scottish cohort of CON subjects (n = 184) acted as a second semi-independent test set. All patients met DSMIV and ICD10 criteria for SCZ, BPAD, and MDD. Data from 98 eye movement features were extracted. We employed a gradient boosted (GB) decision tree multiclass classifier to develop a predictive model. We calculated the area under the curve (AUC) as the primary performance metric.Estimates of AUC in one-versus-all comparisons were: SCZ (0.85), BPAD (0.78), MDD (0.76), and CON (0.85). Estimates on part-external validation were SCZ (0.89) and CON (0.65). In all cases, there was good specificity but only moderate sensitivity. The best individual discriminators included free viewing, fixation duration, and smooth pursuit tasks. The findings appear robust to potential confounders such as age, sex, medication, or mental state at the time of testing.Eye movement patterns can discriminate schizophrenia from major mood disorders and control subjects with around 80\% predictive accuracy.
Original languageEnglish
Article numbersgac032
Number of pages10
JournalSchizophrenia Bulletin Open
Volume3
Issue number1
Early online date20 May 2022
DOIs
Publication statusPublished - 2022

Bibliographical note

Open Access under the OUP Agreement
Funding
This project was supported by the following grants: The Royal Society of London, Chief Scientist Office Scotland (CZB/4/734), NHS Grampian Tenovus Scotland (G12/31), NHS Grampian Endowment Fund, Miller MacKenzie Trust, EU-FP6 (SGENE) and Health Innovation Challenge Fund, jointly from Wellcome Trust and Department of Health (WT-103911/Z/14/Z). The funders had no role in the original study design, the ongoing data collection and analysis, interpretation, or writing of the manuscript.
We thank all who helped with clinical aspects of the study including research assistants Barbara Duff, Kate Cotton, Foteini Okonomitsiou, Elizabeth Hannaford, Zsuszanna Nemeth and Joanna Rodzinko Paska as well as the patients and volunteers whose help was indispensable. P Benson and D St Clair are co-founders of SACCADE Diagnostics Ltd a spin out company tasked to develop eye movement technology to assist diagnosis of major mental health disorders. The University of Aberdeen has patents pending in Europe (PCT/GB2013/050016) and USA (14/370,611). The data reported in this paper arose solely from funding by the acknowledged UK research bodies and charities none of whom have vested interests in the company. David St Clair had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Design of study and development of protocols: D St Clair, P Benson and S Beedie. Recruitment of patients, case note review and clinical and eye movement data collection, quality control and feature extraction of eye movement variables: St Clair, Rujescu, MacIntosh, Beedie, Lemmon, Nouzova. Drafting of the manuscript: St Clair and Nath. Critical revision of manuscript for important intellectual content: all authors. Statistical analyses: Nath and Benson. Interpretation of results: Nath, Benson, MacLennan and St Clair. Obtained funding: St Clair, Benson, MacIntosh, Rujescu. Supervision: St Clair, Benson, MacIntosh, Nath, Rujescu.

Data Availability Statement

Requests for access to anonymized study data for replication or related studies should be directed to the corresponding author. All reasonable requests will be considered positively. There are plans for the datasets to be publically posted in due course.

Keywords

  • eye movement
  • schizophrenia
  • affective disorder
  • biomarker
  • predictive modelling

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