Email

cnievergelt@ucsd.edu

For a full PDF of the proposal, click here

Danielle R. Sullivan, Ph.D.1,2

Jasmeet P. Hayes, Ph.D. 1,2

Mieke Verfaellie, Ph.D. 2,3

 

1National Center for PTSD, VA Boston Healthcare System, Boston, MA

2Department of Psychiatry, Boston University School of Medicine, Boston, MA

3Memory Disorders Research Center, VA Boston Healthcare System, Boston, MA

Abstract

Posttraumatic stress disorder (PTSD) is a psychiatric disorder characterized by debilitating

re-experiencing, avoidance, and hyperarousal symptoms following trauma exposure. Recent

evidence suggests that individuals with PTSD show disrupted functional connectivity in the

default mode network, an intrinsic network that consists of a midline core, a medial temporal

lobe (MTL) subsystem, and a dorsomedial prefrontal cortex (dMPFC) subsystem. Although

there is a lot of work investigating the default mode network in PTSD, there is not much

research focused on the default mode network subsystems in PTSD. Therefore, a large study

investigating whether functional connectivity in these subsystems is differentially disrupted in

PTSD is needed to better understand the role of the default mode network in the disorder. Here,

we propose to use a seed-based approach in the ENIGMA-PGC PTSD sample of ~1500 PTSD

patients and ~1500 controls to examine resting state functional connectivity in the default mode

network subsystems in PTSD.

 

A. Research Question, Goal, or Specific Aims

Provide a brief description (e.g., 1 paragraph) describing the aims of the proposal and

the research questions to be addressed.

Posttraumatic stress disorder (PTSD) is a debilitating psychiatric disorder that develops

after exposure to highly distressing and life-threatening events. The most common features of

PTSD include re-experiencing of the trauma (e.g. flashbacks), avoidance (e.g., avoiding traumarelated

stimuli or trauma-evoking situations), and hyperarousal symptoms (e.g., hypervigilance).

Current neurocircuitry models of PTSD suggest that the medial prefrontal cortex and

hippocampus are critically involved in mediating the disorder (1-7). According to these models,

abnormal structure and function of the ventromedial prefrontal cortex (vMPFC) in PTSD results

in a failure to regulate activity in brain regions important for fear expression and appraisal,

leading to an exaggerated fear response (3, 4, 8-13). Further, alterations in hippocampal

function in PTSD may contribute to impaired contextual fear learning (3, 4, 9, 10) and impaired

contextual fear extinction recall (11, 14, 15), an adaptive process that relies on both the

hippocampus and vMPFC (16-19). Taken together, these studies suggest that PTSD is

associated with dysregulation of a frontal-medial temporal lobe (MTL) circuit that results in an

exaggerated fear response and an inability to extinguish this fear when the context no longer

predicts threat.

More recently, studies have used resting state functional MRI (rs-fMRI) to examine

connectivity among brain regions that form integrated networks in PTSD. One such network is

the default mode network, which includes the MTL, posterior cingulate cortex (PCC), medial

prefrontal cortex, inferior parietal lobule, and lateral temporal cortex (20). Several studies have

found PTSD-related alterations in the default mode network (21-26), and a recent meta-analysis

found that PTSD is consistently associated with reduced functional connectivity (27). Evidence

in healthy individuals suggests that the default mode network can be further fractionated into a

midline core consisting of the PCC and anterior medial prefrontal cortex (aMPFC) and two

functionally and anatomically distinct subsystems (28): a MTL system that includes the vMPFC,

posterior inferior parietal lobule, retrosplenial cortex, parahippocampal cortex, and hippocampal

formation; and a dorsomedial prefrontal cortex (dMPFC) system that includes the dMPFC,

temporoparietal junction, lateral temporal cortex, and temporal pole. These subsystems are

differentially affected by MTL lesions (29) and are thought to be involved in distinct cognitive

processes (28, 30). For example, the MTL subsystem includes regions that are important for

learning and memory (30), while the dMPFC subsystem includes regions that are critical for

mentalizing and social processing of the self and others (30-32). Although there is evidence that

connectivity within the default mode network is compromised in PTSD (21-25, 27, 33), it is

unclear whether the subsystems of the default mode network are differentially disrupted. As

memory alterations appear to be a core feature of the disorder (34, 35), we predict that the MTL

subsystem might be particularly affected in PTSD.

In addition to disruptions to the default mode network, other networks are also altered in

PTSD (23, 25, 27, 36). Networks such as the salience network and central executive network

are engaged during externally-directed and attention-demanding tasks and are anticorrelated

with the default mode network. Daniels et al. (36) found that individuals with PTSD may have

difficulty disengaging the default mode network and engaging salience and central executive

networks during attention-demanding tasks. Further, there appears to be increased crossnetwork

connectivity between the default mode network and salience network in PTSD at rest

(23, 27), which suggests that neural networks may be less differentiated in PTSD.

In our previous work (37), we examined whether functional connectivity in the default

mode network subsystems was differentially disrupted in a cohort of 69 veterans with PTSD

compared to 44 trauma-exposed veterans without PTSD. We found selective alterations in

functional connectivity in the MTL subsystem of the default mode network in PTSD, with

reduced correlation between the PCC and the hippocampus and reduced anticorrelation

between the vMPFC and the dorsal anterior cingulate cortex. Further, we found that functional

connectivity between the PCC and hippocampus was associated with avoidance/numbing

symptoms (i.e., avoidance of thoughts and feelings associated with the trauma, avoidance of

reminders of the trauma, or inability to recall an important aspect of the trauma), such that

PTSD individuals with reduced PCC-hippocampal functional connectivity exhibited more

symptoms. In contrast, no alterations were observed in the dMPFC subsystem of the default

mode network. Although this work is a good first step in further understanding the role of the

default mode network in PTSD, more research is needed to confirm these initial findings. The

ENIGMA PGC-PTSD neuroimaging group offers an unprecedented opportunity to do so in a

large sample. Moreover, PTSD and depression were highly comorbid in our original sample,

raising a question concerning the specificity of our findings. Complicating this question, PTSD

encompasses an array of symptoms, some shared with depression and some unique. Thus, the

ENIGMA PGC-PTSD neuroimaging group also offers an opportunity to investigate the specificity

of these initial findings by including depression as a variable of interest.

The objective of this study is to use seed based resting state functional magnetic

resonance imaging (rs-fMRI) in a large cohort to examine how PTSD affects the default mode

network subsystems. Given the critical role of the vMPFC and hippocampus in PTSD, two areas

associated with the MTL subsystem of the default mode network, as well as our initial findings,

we hypothesize that PTSD will be associated with decreased default mode network functional

connectivity specific to the MTL subsystem. Additionally, in light of evidence for diminished

network segregation in PTSD (23, 27, 37), we hypothesize that PTSD will be associated with

increased connectivity (i.e., reduced anticorrelation) between the default mode network and

regions outside of the default mode network, such as those in the salience and central executive

networks. Lastly, we hypothesize that MTL subsystem disruptions will be specific to PTSD when

accounting for depression.

B. Analyses Plan

Primary Aim

To use seed based resting state functional magnetic resonance imaging (rs-fMRI) in a

large cohort to examine how PTSD affects the default mode network subsystems.

Primary Hypotheses

1. We hypothesize that PTSD will be associated with decreased default mode network

functional connectivity specific to the MTL subsystem.

2. We hypothesize that PTSD will be associated with increased connectivity (i.e., reduced

anticorrelation) between the default mode network and regions outside of the default

mode network, such as those in the salience and central executive networks.

3. We hypothesize that MTL subsystem disruptions will be specific to PTSD when

accounting for depression.

Variables to be used in the analysis (the main predictor and outcome variables, and

potential covariates must be identified)

Main predictor

• Diagnosis (PTSD vs healthy controls)

• PTSD symptom severity (including symptom subscores)

• For depression sub analysis- depression diagnosis (comorbid depression PTSD, PTSD

only, depression only, controls)

Outcome variables

• DMN subsystem functional connectivity

o Hubs of core network (PCC and aMPFC)

o Hub of dorsal medial prefrontal cortex subsystem (dMPFC)

o Hub of medial temporal lob sybsystem (vMPFC)

Covariates

• Age

• Gender

• Depression (yes/no)

• mTBI (yes/no)

• Scanner

Age2

PTSD x Age

Childhood Trauma (number of categories from CTQ)

PTSD x Childhood Trauma

Gender

ICV

Comorbidity (depression and alcohol use disorder)

Some of the thalamic nuclei defined by Iglesias and colleagues are very small. To minimize

floor effects and segmentation failures, we recombine these subnuclei to five larger groups

of thalamic subnuclei per hemisphere (see table below).

Participants

Eligible participants will be accessed through the ENIGMA-PGC PTSD consortium.

Resting state scans are estimated to include ~1500 PTSD patients and ~1500 controls. PTSD

diagnosis will be obtained from individual studies and was assessed with the Clinician-

Administered PTSD Scale (CAPS), the PTSD Symptom Scale (PSS), or equivalent.

Exclusionary criteria will include (a) past or current Axis I disorders other than PTSD or MDD,

(b) current substance disorder, (c) history of moderate or severe TBI, and/or (d) history of a

significant neurological condition (e.g., stroke).

Resting State fMRI Analyses

Preprocessing. Resting state data will be analyzed centrally and preprocessed using

the ENIGMA resting-state pipeline (38). First, we will use Marchenko-Pastur principal

components analysis for denoising to improve the signal-to-noise ratio of the data. Next, we will

correct for spatial distortion associated with long-TE gradient echo imaging (i.e., using gradientecho

fieldmap or reversed-gradient approach). Third, we will compute a transformation by

registering the base volume to the ENIGMA EPI template to develop a spatial template and

spatial atlas, which will be used for regression of the global signal and an anatomical spatial

reference frame. Correction for head motion will then be performed by registering each volume

to the volume with the minimum outlier fraction. Nuisance variables including linear trend, the 6

motion parameters and their derivatives, and the time courses of white matter and cerebrospinal

fluid (CSF) from the lateral ventricles will be modelled in multiple linear regression analyses.

Time points of excessive motion (>0.2mm) will be further censored from the analyses. Images

will be spatially normalized to the ENIGMA EPI template in MNI standard space and smoothed

for group-level analyses.

First-level processing. Whole-brain resting-state fMRI analyses will be performed using

a seed based approach. Seeds will consist of four 8-mm spherical regions of interest (ROIS)

obtained from Andrews-Hanna et al. (28): PCC (MNI coordinates = -8, -56, 26), aMPFC (MNI

coordinates = -6, 52, -2), dMPFC (MNI coordinates = 0, 52, 26), and vMPFC (MNI coordinates =

0, 26, -18). The PCC and aMPFC seeds were chosen because they represent the two core

hubs of the default mode network; the dMPFC and vMPFC seeds were selected because they

represent the core hubs of the dMPFC and MTL subsystems, respectively. All seeds and ROIs

of CSF, white matter, and whole brain will be first transformed to each individual’s native space

and then the mean time series (based on all of the voxels within the region) will be computed.

Next, we will complete a whole-brain voxel-wise analysis assessing the correlation between the

seed region and the rest of the brain, with nuisance regressors (CSF, white matter, and whole

brain time-series along with the motion parameters) included in the model.

Group-level processing. To determine connectivity differences across groups (PTSD v.

controls), group level connectivity maps will be generated for each seed. Age, sex, depression

(yes/no), mTBI (yes/no), and scanner site will be entered into the model as covariates. Statistic

images will be thresholded using clusters determined by p<0.001 with a corrected cluster

significance threshold of p=0.05.

To examine associations between functional connectivity and PTSD symptom subscores,

Z-values of significant functional connectivity clusters in the group contrast will be

extracted from connectivity maps and entered into SPSS. For the subset of participants that

have more detailed information regarding PTSD including PTSD symptom sub-scores, Pearson

correlations will be calculated between functional connectivity Z-values and CAPS reexperiencing,

avoidance/numbing, and hyperarousal scores. Bonferroni correction will be used

to correct for multiple comparisons.

To determine whether the observed PTSD alterations could be linked specifically to

PTSD rather than depression, additional analyses will be limited to participants with depression

information and groups will be further divided into comorbid depression and PTSD, PTSD only,

depression only, and controls. Group level connectivity maps will be generated for each seed.

Age, sex, mTBI (yes/no), and scanner site will be entered into the model as covariates. Statistic

images will be thresholded using clusters determined by p<0.001 with a corrected cluster

significance threshold of p=0.05.

C. Investigative Team

1. Danielle Sullivan

2. Jasmeet Hayes

3. Mieke Verfaellie

4. Mark Miller

5. Erika Wolf

6. Mark Logue

7. David Salat

D. Resources Needed

Describe the resources needed to achieve the aims of the analysis, including variables

needed, analysis support, and any other issues that may affect the feasibility of the plan.

Resting state data will be analyzed centrally and preprocessed using the ENIGMA

resting-state pipeline using FSL’s FEAT program. Whole-brain resting-state fMRI analyses will be

performed using a seed based approach. Seeds will consist of four 8-mm spherical regions of

interest (ROIS) obtained from Andrews-Hanna et al. (28): PCC (MNI coordinates = -8, -56, 26),

aMPFC (MNI coordinates = -6, 52, -2), dMPFC (MNI coordinates = 0, 52, 26), and vMPFC (MNI

coordinates = 0, 26, -18). All seeds and ROIs of CSF, white matter, and whole brain will be first

transformed to each individual’s native space and then the mean time series (based on all of the

voxels within the region) will be computed. Next, we will complete a whole-brain voxel-wise

analysis assessing the correlation between the seed region and the rest of the brain, with

nuisance regressors (CSF, white matter, and whole brain time-series along with the motion

parameters) included in the model. Then, group level connectivity maps will be generated

examining our variable of interest along with covariates.

E. Timeline

6 months

F. Collaboration

The following is the standard PGC policy about secondary analyses. Any deviation from this

policy needs to be described and justified, and could negatively impact the proposal.

PGC investigators who are not named on this proposal but who wish to substantively contribute

to the analysis and manuscript may contact the proposing group to discuss joining the proposal.

G. Authorship

We will follow the authorship policy of the PGC-PTSD which can be found at https://pgcptsd.

com/wp-content/uploads/2017/06/Authorship-Guidelines-PGC-PTSD.pdf

(a) are you following the authorship policies of the groups involved? YES see https://pgcptsd.

com/wp-content/uploads/2017/06/Authorship-Guidelines-PGC-PTSD.pdf

(b) will there be a writing group and if so, who will be included? The writing group will be

comprised of the investigative team (#1 – #5) listed above.

(c) what groups or individuals will be listed as authors? Authors will include the writing group

plus individual and group contributors of data and analysis from each site (generally 2-3

co-authors from each site).

(d) will PGC members not listed as named authors be listed at the end of the manuscript?

All individuals who meet the criteria established in the PGC-PTSD authorship policy will

be co-authors. Other PGC members will not be listed at the end of the manuscript.

(e) will PGC members or groups be listed as “collaborators” on the PubMed abstract page?

All individuals and groups who meet the authorship criteria of the PGC-PTSD authorship

policy will be listed as collaborators on the PubMed abstract page. No other individuals

or groups will be listed.

(f) how will funding sources be handled or acknowledged? All funding sources that

supported data collection and analysis will be listed in the manuscript.

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