# Defining biotypes of PTSD with resting-state connectivity

> **NIH VA I01** · VA BOSTON HEALTH CARE SYSTEM · 2020 · —

## Abstract

Posttraumatic stress disorder is not a unitary disorder, but rather a heterogeneous syndrome, both in its
symptomatology and response to treatment. Although there have been important breakthroughs in our
understanding of neurobiological pathways associated with PTSD, its neurobiological heterogeneity has
impeded the identification of consistent biomarkers, which remain elusive. A major limitation of previous work
is that clinical symptoms and behavioral subtypes of PTSD do not adequately capture variation in the
underlying neurobiology, as the same symptoms can stem from different underlying neurobiological
mechanisms. To address this critical gap, the proposed study will pioneer a new analytic methodology to
identify neurophysiological subtypes, or biotypes of PTSD, based on shared patterns of brain
dysfunction in resting fMRI connectivity. The following aims to discover and validate MRI-based
biotypes of PTSD in our Veterans have wide-ranging future applications such as improving objective diagnostic
tools, providing targets for interventions, and predicting who will response to a particular treatment.
DESIGN AND METHODS: The current proposal will use multi-site neural, clinical, and cognitive data to
discover resting fMRI-based biotypes of PTSD, determine their reliability and replicability, and relationship to
symptoms, comorbidities, and cognition. Veterans' imaging and clinical data will come primarily from the VA
Boston (n>500) as well as a replication site at the Houston VA (n>200). An additional 300 participants will be
recruited for a state-of-the-art cognitive battery, to determine if these biotypes have cognitive signatures that
can be inferred from sensitive cognitive tests. Analytically the research will use a general set of techniques at
the forefront of an exciting new era for brain imaging- MRI-based “fingerprinting”, or measuring and modeling
the reproducible and yet substantial individual variation in the fMRI-based connectome (functional
connectivity).
OBJECTIVES. Aim 1. Using existing data (n>500), we will A) Define distinct biotypes of PTSD using
patterns of fMRI connectivity. We will further test the reliability of these biotypes across two consecutive
resting scans, and the ability to predict PTSD biotype in individual Veterans. We will also explore if certain
symptoms and comorbidities differentially cluster with PTSD biotypes. Aim 2. We will determine the across-
time reliability of these biotypes by examining repeated assessments of the same participants 1-2 years later
(n>300). Aim 3. We will validate these biotypes in an independent replication data set, from the Houston VA
(n>200 Veterans). Aim 4. We will collect a comprehensive state-of-the-art cognitive battery (n=300)
measuring PTSD-specific mechanisms (e.g., fear learning, inhibitory control, attentional bias) to determine if
these biotypes can be inferred from cognitive performance profiles.

## Key facts

- **NIH application ID:** 9932306
- **Project number:** 5I01CX001653-03
- **Recipient organization:** VA BOSTON HEALTH CARE SYSTEM
- **Principal Investigator:** Michael Esterman
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2018-07-01 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9932306

## Citation

> US National Institutes of Health, RePORTER application 9932306, Defining biotypes of PTSD with resting-state connectivity (5I01CX001653-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9932306. Licensed CC0.

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