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This study will examine if brain insulin resistance is a feature of depression in humans using magnetic resonance imaging (MRI) measures sensitive to brain insulin action. This study will examine adolescents, as depression onset commonly occurs during this age, and the impacts of cumulative medication exposure and other lifestyle-related confounds are also lower in this age group, improving our ability to understand the underlying biology.
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BACKGROUND: Major depressive disorder (MDD) is associated with metabolic dysfunction, including higher body mass index and increased risk for type 2 diabetes (T2D). This relationship is bidirectional as insulin resistance is associated with greater depressive symptom severity and worse cognition. These nested relationships between metabolic and mental health have encouraged a reconceptualization of MDD as a metabolic disorder. In this context, insulin in the brain has been implicated as a potential mediator unifying the mechanisms underlying metabolic and mental health. There is early evidence supporting this hypothesis; mice with brain-specific knockout of insulin receptor exhibited depression-like behavior that was reversed by treatment with monoamine oxidase inhibitors, while anti-diabetic agents that can potentially cross the blood-brain barrier have shown initial promise in reducing depressive symptoms.
HYPOTHESES: 1) Adolescents diagnosed with MDD will have greater brain insulin resistance in comparison to matched healthy controls. 2) Greater brain insulin resistance will be associated with increased illness severity, worse cognitive performance, and worse short-term outcomes (i.e., at 6 months) in the depression group. 3) Greater peripheral insulin resistance (measured using fasting blood work) and hepatic and visceral adiposity (measured using MRI) will be associated with greater brain insulin resistance.
APPROACH AND METHODOLOGY: Twelve adolescents with depression (14 to 18 years old) and 12 age-, sex-, and BMI-matched healthy controls will be recruited for the study. In a single-blinded crossover design, all 24 participants will undergo fasting blood work (glucose, insulin, and c-peptide) followed by an MRI-based protocol of brain insulin action. This includes two MRI scans; one with intranasal insulin challenge (80 IU) and one with intranasal placebo. This protocol leverages the property of intranasal insulin to induce resting state connectivity and blood flow changes in the brain. This will be achieved using a 3 Tesla (3T) MRI scanner, where participants will undergo a high-resolution T1-weighted structural scan, a resting state functional MRI scan, and an arterial spin labeling scan. Single voxel 1H-magnetic resonance spectroscopy will also be employed to examine changes in glutamate levels in the frontal and temporal cortex. The difference in change induced by intranasal insulin compared to that with intranasal placebo will be utilized as an index of insulin activity since any difference observed between placebo and insulin during this controlled manipulation is likely to be due to the intranasal insulin. THINC-it, a brief cognitive assessment, will also be performed to measure cognitive function in relation to insulin induced brain changes. An abdominal surface coil scan will also be used to measure visceral and hepatic adiposity. Participants with depression will be invited for a six-month follow-up visit to repeat fasting blood work, along with clinical and cognitive assessments. Age, sex, and BMI will be used as covariates in all analyses.
SIGNIFICANCE: Demonstrating disrupted brain insulin action can provide novel insights into poorly understood mechanisms underlying the relationship between MDD and T2D. Evidence of brain insulin resistance early in the course of illness may also identify a modifiable risk factor that can be targeted using brain insulin sensitizers at the earliest stages of the illness. Thus, this work that lies at the intersection of psychiatry, physiology, and psychopharmacology has the potential to generate new knowledge and improve outcomes in an area of significant unmet need.
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24 participants in 1 patient group
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Mahavir Agarwal, MD, PhD; Maria Papoulias
Data sourced from clinicaltrials.gov
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