Individual Patterns of Abnormality in Resting-State Functional Connectivity Reveal Two Data-Driven PTSD Subgroups

Adi Maron-Katz, Yu Zhang, Manjari Narayan, Wei Wu, Russell T. Toll, Sharon Naparstek, Carlo De Los Angeles, Parker Longwell, Emmanuel Shpigel, Jennifer Newman, Duna Abu-Amara, Charles Marmar, Amit Etkin

Research output: Contribution to journalArticle

2 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)244-253
Number of pages10
JournalThe American journal of psychiatry
Volume177
Issue number3
DOIs
StatePublished - Mar 1 2020
Externally publishedYes

Keywords

  • Models/Theories Of Psychiatry
  • Posttraumatic Stress Disorder

ASJC Scopus subject areas

  • Psychiatry and Mental health

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    Maron-Katz, A., Zhang, Y., Narayan, M., Wu, W., Toll, R. T., Naparstek, S., De Los Angeles, C., Longwell, P., Shpigel, E., Newman, J., Abu-Amara, D., Marmar, C., & Etkin, A. (2020). Individual Patterns of Abnormality in Resting-State Functional Connectivity Reveal Two Data-Driven PTSD Subgroups. The American journal of psychiatry, 177(3), 244-253. https://doi.org/10.1176/appi.ajp.2019.19010060