Neurobehavioral Mechanisms of Emotion Regulation in Depression Across the Adult Lifespan
Condition: Depressive Disorder, Major
MeSH terms: Depressive Disorder; Depressive Disorder, Major
Study type: Observational

Summary: 
      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: 
      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.
    

Intervention name(s): fMRI
Intervention type(s): Procedure
Intervention description(s): 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.
Observational model: Case-Control
Time perspective: Prospective
Sampling method: Non-Probability Sample
Study population: 
        100 MDD and 100 non-depressed (ND) adult qualifying participants ranging in age from 35-75