Frederick Shic1,2, Adam J Naples3, Erin C Barney4,3, Shou An Chang5, Beibin Li4,6, Takumi McAllister3, Minah Kim7, Kelsey J Dommer4, Simone Hasselmo3, Adham Atyabi4,8,9, Quan Wang3, Gerhard Helleman10, April R Levin11,12, Helen Seow3, Raphael Bernier13, Katarzyna Charwaska3, Geraldine Dawson14, James Dziura15, Susan Faja12,16, Shafali Spurling Jeste17, Scott P Johnson18, Michael Murias19, Charles A Nelson12,16,20, Maura Sabatos-DeVito14, Damla Senturk21, Catherine A Sugar21,17, Sara J Webb4,13, James C McPartland22. 1. Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, 1920 Terry Ave, Seattle, WA, 98101, USA. fshic@uw.edu. 2. Department of General Pediatrics, University of Washington School of Medicine, Seattle, WA, USA. fshic@uw.edu. 3. Yale Child Study Center, Yale University School of Medicine, 230 South Frontage Road, New Haven, CT, 06520, USA. 4. Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, 1920 Terry Ave, Seattle, WA, 98101, USA. 5. Department of Psychology, Yale University, 2 Hillhouse Ave, New Haven, CT, 06520, USA. 6. Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA. 7. Department of Psychology, University of Virginia, 102 Gilmer Hall, P.O. Box 400400, Charlottesville, VA, 22904, USA. 8. Department of General Pediatrics, University of Washington School of Medicine, Seattle, WA, USA. 9. Department of Computer Science, University of Colorado - Colorado Springs, Colorado Springs, CO, USA. 10. Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA. 11. Department of Neurology, Boston Children's Hospital, Boston, MA, USA. 12. Harvard Medical School, Boston, MA, USA. 13. Department of Psychiatry and Behavioral Science, University of Washington School of Medicine, Seattle, WA, USA. 14. Duke Center for Autism and Brain Development, Duke University, Durham, NC, USA. 15. Emergency Medicine, Yale University School of Medicine, New Haven, CT, USA. 16. Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA. 17. Division of Neurology, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA. 18. Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA. 19. Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL, USA. 20. Graduate School of Education, Harvard University, Boston, MA, USA. 21. Department of Biostatistics, University of California Los Angeles, Los Angeles, CA, USA. 22. Yale Child Study Center, Yale University School of Medicine, 230 South Frontage Road, New Haven, CT, 06520, USA. james.mcpartland@yale.edu.
Abstract
BACKGROUND: Eye tracking (ET) is a powerful methodology for studying attentional processes through quantification of eye movements. The precision, usability, and cost-effectiveness of ET render it a promising platform for developing biomarkers for use in clinical trials for autism spectrum disorder (ASD). METHODS: The autism biomarkers consortium for clinical trials conducted a multisite, observational study of 6-11-year-old children with ASD (n = 280) and typical development (TD, n = 119). The ET battery included: Activity Monitoring, Social Interactive, Static Social Scenes, Biological Motion Preference, and Pupillary Light Reflex tasks. A priori, gaze to faces in Activity Monitoring, Social Interactive, and Static Social Scenes tasks were aggregated into an Oculomotor Index of Gaze to Human Faces (OMI) as the primary outcome measure. This work reports on fundamental biomarker properties (data acquisition rates, construct validity, six-week stability, group discrimination, and clinical relationships) derived from these assays that serve as a base for subsequent development of clinical trial biomarker applications. RESULTS: All tasks exhibited excellent acquisition rates, met expectations for construct validity, had moderate or high six-week stabilities, and highlighted subsets of the ASD group with distinct biomarker performance. Within ASD, higher OMI was associated with increased memory for faces, decreased autism symptom severity, and higher verbal IQ and pragmatic communication skills. LIMITATIONS: No specific interventions were administered in this study, limiting information about how ET biomarkers track or predict outcomes in response to treatment. This study did not consider co-occurrence of psychiatric conditions nor specificity in comparison with non-ASD special populations, therefore limiting our understanding of the applicability of outcomes to specific clinical contexts-of-use. Research-grade protocols and equipment were used; further studies are needed to explore deployment in less standardized contexts. CONCLUSIONS: All ET tasks met expectations regarding biomarker properties, with strongest performance for tasks associated with attention to human faces and weakest performance associated with biological motion preference. Based on these data, the OMI has been accepted to the FDA's Biomarker Qualification program, providing a path for advancing efforts to develop biomarkers for use in clinical trials.
BACKGROUND: Eye tracking (ET) is a powerful methodology for studying attentional processes through quantification of eye movements. The precision, usability, and cost-effectiveness of ET render it a promising platform for developing biomarkers for use in clinical trials for autism spectrum disorder (ASD). METHODS: The autism biomarkers consortium for clinical trials conducted a multisite, observational study of 6-11-year-old children with ASD (n = 280) and typical development (TD, n = 119). The ET battery included: Activity Monitoring, Social Interactive, Static Social Scenes, Biological Motion Preference, and Pupillary Light Reflex tasks. A priori, gaze to faces in Activity Monitoring, Social Interactive, and Static Social Scenes tasks were aggregated into an Oculomotor Index of Gaze to Human Faces (OMI) as the primary outcome measure. This work reports on fundamental biomarker properties (data acquisition rates, construct validity, six-week stability, group discrimination, and clinical relationships) derived from these assays that serve as a base for subsequent development of clinical trial biomarker applications. RESULTS: All tasks exhibited excellent acquisition rates, met expectations for construct validity, had moderate or high six-week stabilities, and highlighted subsets of the ASD group with distinct biomarker performance. Within ASD, higher OMI was associated with increased memory for faces, decreased autism symptom severity, and higher verbal IQ and pragmatic communication skills. LIMITATIONS: No specific interventions were administered in this study, limiting information about how ET biomarkers track or predict outcomes in response to treatment. This study did not consider co-occurrence of psychiatric conditions nor specificity in comparison with non-ASD special populations, therefore limiting our understanding of the applicability of outcomes to specific clinical contexts-of-use. Research-grade protocols and equipment were used; further studies are needed to explore deployment in less standardized contexts. CONCLUSIONS: All ET tasks met expectations regarding biomarker properties, with strongest performance for tasks associated with attention to human faces and weakest performance associated with biological motion preference. Based on these data, the OMI has been accepted to the FDA's Biomarker Qualification program, providing a path for advancing efforts to develop biomarkers for use in clinical trials.
Authors: Thomas W Frazier; Mark Strauss; Eric W Klingemier; Emily E Zetzer; Antonio Y Hardan; Charis Eng; Eric A Youngstrom Journal: J Am Acad Child Adolesc Psychiatry Date: 2017-05-11 Impact factor: 8.829
Authors: Amanda R Jensen; Alison L Lane; Brianna A Werner; Sallie E McLees; Tessa S Fletcher; Richard E Frye Journal: Mol Diagn Ther Date: 2022-06-27 Impact factor: 4.476