Studying the Health of Asians to Advance Knowledge, Treatments, and Interventions for Depression

SHAKTI is a non-randomized, natural history, non-treatment, longitudinal cohort study. Participants who are receiving standard of care treatment for depression and other comorbidities from their treating clinician will be allowed to continue such treatments in this study. There are no experimental study procedures, other than methods used for data capture (questionnaires, biospecimen collection, EEG, and MRI). Participants will be expected to visit study site(s) for repeated collection of data (assessments, biospecimens, and imaging procedures), up to 4 times a year for up to 5 years. A reduced battery of tests is allowable if subject is not able or willing to complete the full battery after the baseline visit.

The primary objective of this initiative is to implement a prospective study that will allow us to identify and validate biosignatures of 1) response to treatments for depression and depression outcome and 2) resilience and protective factors that reduce the risk of developing mood and anxiety disorders (using an integrated array of participant specific data: socio-demographic, lifestyle, clinical and behavioral assessments, fluid-based biomarkers, genomics, neuroimaging, EEG, and cell-based assays) in a longitudinal cohort of Asian and Pacific Islander (API) participants with elevated symptoms of a depressive disorder and participants at risk for these illnesses.

Symptom presence, severity, and remission across various treatment options will be assessed using questionnaires for symptom changes, antidepressant treatment tolerability and overall quality of life. Other outcomes generated from this study will include rate of change in quantitative measures of brain function, of depression relevant brain regions correlated with systems-levels behavior and other functional neuro-circuitry MRI measures. Rate of change of specified biochemical biomarkers will also be assessed. Integration of these measures will provide an unmatched understanding into the mechanisms of depression and hold tremendous promise for better disease treatment and associated outcomes.

Integration of these measures will provide an unmatched understanding into the mechanisms of depression and hold tremendous promise for better disease treatment and associated outcomes.

Data will be collected from 3 participant groups:

1. Individuals with a lifetime or a current diagnosis of a mood disorder (based upon a semi-structured diagnostic interview)
2. Individuals at risk for developing mood disorders (has history of anxiety disorder, substance use disorder, trauma, or mood disorder that does not meet criteria for major depressive disorder (MDD) or Bipolar Disorder or a first-degree relative with a history of mood disorders)
3. Healthy individuals who do not have a psychiatric diagnosis (including no history of mood disorders and no relative with a history)

We also plan to enroll families within and across all three groups. For the purposes of this study, we are defining family as a group of two or more people related by either birth, marriage, or adoption, and residing together. Participants may enroll in this study as an individual or with their family member(s). If participants and their family member(s) are enrolled together, their study identifiers (IDs) will be linked so that we may group family data. Participants will NOT be able to see or learn about their family members' data.

Specific Aims of this Study:

Aim 1. Create the longitudinal SHAKTI research cohort to support a natural history study of depression, an important source of knowledge to advance depression understanding and management among API individuals.

Aim 2. Establish a SHAKTI biospecimen resource consisting of blood, plasma, serum, peripheral blood mononuclear cells (PBMCs), DNA, RNA, saliva, and urine samples collected from participants at study visits as a platform for translational research into biochemical and molecular characterization of depression.

Aim 3. Identify neuroimaging and neuropsychiatric parameters that serve as biomarkers or may be associated with response to specific antidepressant treatment modalities.

Aim 4. Annually examine biosignatures and independent factors (demographic, social, environmental, genetic, EEG, fMRI) associated with resilience in at-risk participants to determine changes and plasticity of biomarkers.

Aim 5. Examine the interaction between psychiatric symptoms and changes in the biopsychosocial signature.

Aim 6. Identify gut microbiome biomarkers that are linked to psychiatric status in participants with mood disorders.

Aim 7. Identify the association between participants who are family members to compare biosignatures of depression and resilience.

Aim 8. Sub-Study: Evaluate psychological, social, and physiological correlates, from mobile device-based data, of depression severity and construct a model to estimate mood based on these measures.