Neurobehavioral Mechanisms of Emotion Regulation in Depression Across the Adult Lifespan

NCT ID: NCT03207503

Last Updated: 2023-12-20

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

296 participants

Study Classification

OBSERVATIONAL

Study Start Date

2017-10-10

Study Completion Date

2023-11-20

Brief Summary

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The aim of this study is to test a model of demographic (age, sex), clinical, cognitive, and neurocircuitry predictors of emotion regulation ability and long-term depressive symptoms.

Detailed Description

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Emotion regulation capacities are crucial for sustaining mental health in the face of cumulative stressors over one's lifetime. Although it is well documented that some emotion regulation abilities are preserved or even improved in healthy aging, little is known about why regulatory deficits persist in older adults who suffer from depression. Treatments for major depressive disorder (MDD) focus on remediating affective dysregulation processes that confer risks for disability, poor quality of life, and morbidity into late life. Theoretical perspectives on emotional aging propose myriad lifespan changes that potentially impact regulatory capacities, including structural and functional integrity of dorsal attentional and ventral affective processing pathways, cognitive status, and use of specific regulatory strategies, among others. However, there is a dearth of empirical evidence to indicate which combination of these factors critically interacts with depressive symptoms to impact emotional dysregulation in older adults, when these factors become important across the course of the adult lifespan, which strategies they apply to, and whether they can predict future depression status. Thus, the goal of this specific application is to test a comprehensive model of age-related changes to brain circuitry, neurocognitive performance, and social support as predictors of emotion regulation abilities and depressive symptoms in individuals with and without MDD. Reappraisal and distraction are the emotion regulation strategies of primary interest.

Models will be evaluated using primarily a series of linear (multiple) regression models focusing on between-subject effects/comparisons (age, MDD status, etc.) and the emotion regulation outcomes separately for reappraisal and distraction processes. As an extension of these models we will perform Structural Equation Modeling (SEM) type modeling to summarize the liability dimensions underlying the specific domains of depression \[BDI scores measuring depression severity; lifetime duration of depressive episode(s)\], and neural measures of dorsal attention network functioning \[gPPI connectivity between dlPFC and amygdala; task-based activation during distraction in dACC, dlPFC, and inferior parietal lobe; DTI FA measure in SLF II\] and affective network functioning \[gPPI connectivity between vlPFC and amygdala; task-based activation during reappraisal in vmPFC, vlPFC, and amygdala; DTI FA measure of UF\]. The SEM will be especially useful in predicting the future depression that will be assessed at one-year follow up, where the predicted (best linear unbiased predictors-BLUPS) values of lower-dimensional latent traits, along with emotion regulation outcomes, can be used as predictors for future depression. Moreover, hierarchical modeling structures can be imposed on latent traits conditionally on a shared latent trait describing associations among several latent traits thus further reducing underlying dimensionality and simplifying computations. This single trait can be thought as a cumulative effect of all latent traits and can be used a single index of uncertainty in predicting future depression symptom severity.

Conditions

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Depressive Disorder, Major

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

PROSPECTIVE

Study Groups

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MDD patients

Participants ages 35-75 determined to be clinically depressed via structured clinical interview. No interventions will be administered as part of this study.

fMRI

Intervention Type PROCEDURE

Patients will undergo fMRI imaging to assess areas of the brain that are active during emotion regulation. No clinical benefit of MRI imaging is anticipated.

non-MDD patients

Participants ages 35-75 determined to be lifetime free of psychiatric conditions as assessed by structured clinical interview. No interventions will be administered as part of this study.

fMRI

Intervention Type PROCEDURE

Patients will undergo fMRI imaging to assess areas of the brain that are active during emotion regulation. No clinical benefit of MRI imaging is anticipated.

Interventions

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fMRI

Patients will undergo fMRI imaging to assess areas of the brain that are active during emotion regulation. No clinical benefit of MRI imaging is anticipated.

Intervention Type PROCEDURE

Eligibility Criteria

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Inclusion Criteria

* age 35-75
* No MRI contra-indications (e.g., metal in body)
* Not currently pregnant
* Ambulatory
* No known uncorrected sensory deficits
* Estimated verbal IQ of 85+ as indicated by the North American Adult Reading test MDD group: Current MDD assessed by history of MDD as assessed by standardized SCID interview
* Control Group: no lifetime of history of MDD as assessed by standardized SCID interview

Exclusion Criteria

* History of moderate or severe substance dependence, as assessed by standardized SCID interview
* History of psychosis, mania, or eating disorders, as assessed by standardized SCID interview
* Disorders with impact on brain characteristics (e.g., epilepsy, Parkinson's Disease) or history of stroke
* Contraindications to MRI scanning, as indicated on the MRI safety screening questionnaire
* Use of antidepressants or other psychotropics other than sleep aids in the past 4 weeks (8 weeks for fluoxetine)
* Indication of mild cognitive impairment or dementia. To meet screening criteria, participants must meet all of the following:

* Scoring of 24 or higher on the Montreal Cognitive Assessment;
* perform above 1.5 standard deviations on the following measures: HVLT delayed recall, Trail Making B, and Animal Naming based normative values
Minimum Eligible Age

35 Years

Maximum Eligible Age

75 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Duke University

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Moria Smoski, PhD

Role: PRINCIPAL_INVESTIGATOR

Duke Department of Psychiatry

Locations

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Civitan Building, Duke Psychiatry and Behavioral Sciences

Durham, North Carolina, United States

Site Status

Psychiatry and Behavioral Services

Durham, North Carolina, United States

Site Status

Countries

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United States

References

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Nienhuis FJ, van de Willige G, Rijnders CA, de Jonge P, Wiersma D. Validity of a short clinical interview for psychiatric diagnosis: the mini-SCAN. Br J Psychiatry. 2010 Jan;196(1):64-8. doi: 10.1192/bjp.bp.109.066563.

Reference Type BACKGROUND
PMID: 20044664 (View on PubMed)

Winecoff A, Labar KS, Madden DJ, Cabeza R, Huettel SA. Cognitive and neural contributors to emotion regulation in aging. Soc Cogn Affect Neurosci. 2011 Apr;6(2):165-76. doi: 10.1093/scan/nsq030. Epub 2010 Apr 12.

Reference Type BACKGROUND
PMID: 20385663 (View on PubMed)

Levenson RW, Carstensen LL, Friesen WV, Ekman P. Emotion, physiology, and expression in old age. Psychol Aging. 1991 Mar;6(1):28-35. doi: 10.1037//0882-7974.6.1.28.

Reference Type BACKGROUND
PMID: 2029364 (View on PubMed)

Knight BG, Maines ML, Robinson GS. The effects of sad mood on memory in older adults: a test of the mood congruence effect. Psychol Aging. 2002 Dec;17(4):653-61. doi: 10.1037//0882-7974.17.4.653.

Reference Type BACKGROUND
PMID: 12507361 (View on PubMed)

Other Identifiers

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R01MH113238-1

Identifier Type: OTHER_GRANT

Identifier Source: secondary_id

R01MH113238

Identifier Type: NIH

Identifier Source: secondary_id

View Link

Pro00082070

Identifier Type: -

Identifier Source: org_study_id