Adi Maron-Katz1, Yu Zhang1, Manjari Narayan1, Wei Wu1, Russell T Toll1, Sharon Naparstek1, Carlo De Los Angeles1, Parker Longwell1, Emmanuel Shpigel1, Jennifer Newman1, Duna Abu-Amara1, Charles Marmar1, Amit Etkin1. 1. Department of Bioengineering (Toll) and Department of Psychiatry and Behavioral Sciences and Wu Tsai Neurosciences Institute (Maron-Katz, Zhang, Narayan, Wu, Toll, Naparstek, De Los Angeles, Longwell, Shpigel, Etkin), Stanford University, Stanford, Calif.; VA Palo Alto Health Care System and Sierra Pacific Mental Illness Research, Education, and Clinical Center, Palo Alto, Calif. (Maron-Katz, Zhang, Narayan, Wu, Toll, Naparstek, De Los Angeles, Longwell, Shpigel, Etkin); School of Automation Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China (Wu); Steven and Alexandra Cohen Veterans Center for the Study of Post-Traumatic Stress and Traumatic Brain Injury and Department of Psychiatry (Newman, Abu-Amara, Marmar), New York University Langone School of Medicine, New York.
Abstract
OBJECTIVE: A major challenge in understanding and treating posttraumatic stress disorder (PTSD) is its clinical heterogeneity, which is likely determined by various neurobiological perturbations. This heterogeneity likely also reduces the effectiveness of standard group comparison approaches. The authors tested whether a statistical approach aimed at identifying individual-level neuroimaging abnormalities that are more prevalent in case subjects than in control subjects could reveal new clinically meaningful insights into the heterogeneity of PTSD. METHODS: Resting-state functional MRI data were recorded from 87 unmedicated PTSD case subjects and 105 war zone-exposed healthy control subjects. Abnormalities were modeled using tolerance intervals, which referenced the distribution of healthy control subjects as the "normative population." Out-of-norm functional connectivity values were examined for enrichment in cases and then used in a clustering analysis to identify biologically defined PTSD subgroups based on their abnormality profiles. RESULTS: The authors identified two subgroups among PTSD cases, each with a distinct pattern of functional connectivity abnormalities with respect to healthy control subjects. Subgroups differed clinically on levels of reexperiencing symptoms and improved case-control discriminability and were detectable using independently recorded resting-state EEG data. CONCLUSIONS: The results provide proof of concept for the utility of abnormality-based approaches for studying heterogeneity within clinical populations. Such approaches, applied not only to neuroimaging data, may allow detection of subpopulations with distinct biological signatures so that further clinical and mechanistic investigations can be focused on more biologically homogeneous subgroups.
OBJECTIVE: A major challenge in understanding and treating posttraumatic stress disorder (PTSD) is its clinical heterogeneity, which is likely determined by various neurobiological perturbations. This heterogeneity likely also reduces the effectiveness of standard group comparison approaches. The authors tested whether a statistical approach aimed at identifying individual-level neuroimaging abnormalities that are more prevalent in case subjects than in control subjects could reveal new clinically meaningful insights into the heterogeneity of PTSD. METHODS: Resting-state functional MRI data were recorded from 87 unmedicated PTSD case subjects and 105 war zone-exposed healthy control subjects. Abnormalities were modeled using tolerance intervals, which referenced the distribution of healthy control subjects as the "normative population." Out-of-norm functional connectivity values were examined for enrichment in cases and then used in a clustering analysis to identify biologically defined PTSD subgroups based on their abnormality profiles. RESULTS: The authors identified two subgroups among PTSD cases, each with a distinct pattern of functional connectivity abnormalities with respect to healthy control subjects. Subgroups differed clinically on levels of reexperiencing symptoms and improved case-control discriminability and were detectable using independently recorded resting-state EEG data. CONCLUSIONS: The results provide proof of concept for the utility of abnormality-based approaches for studying heterogeneity within clinical populations. Such approaches, applied not only to neuroimaging data, may allow detection of subpopulations with distinct biological signatures so that further clinical and mechanistic investigations can be focused on more biologically homogeneous subgroups.
Entities:
Keywords:
Models/Theories Of Psychiatry; Posttraumatic Stress Disorder
Authors: Yu Zhang; Wei Wu; Russell T Toll; Sharon Naparstek; Adi Maron-Katz; Mallissa Watts; Joseph Gordon; Jisoo Jeong; Laura Astolfi; Emmanuel Shpigel; Parker Longwell; Kamron Sarhadi; Dawlat El-Said; Yuanqing Li; Crystal Cooper; Cherise Chin-Fatt; Martijn Arns; Madeleine S Goodkind; Madhukar H Trivedi; Charles R Marmar; Amit Etkin Journal: Nat Biomed Eng Date: 2020-10-19 Impact factor: 25.671