The proposed K23 Patient-Oriented Research Career Development Award is designed to provide the candidate with the conceptual knowledge and technical skills needed for a career of an independent investigator focused on the engagement of behavioral and neural network targets during personalized psychotherapies for mid- and late depression. The candidate will conduct her training and research activities at the ALACRITY Center of the Weill Cornell Institute of Geriatric Psychiatry. The proposal is based on the premise that identifying specific behavioral and neural network targets can guide development of streamlined interventions with potential for broad scalability and reach. ?Engage?, a streamlined therapy for late-life depression, whose principal intervention is ?reward exposure?, may change Positive Valence Systems (PVS) functions. Preliminary studies by the candidate show that early increase in resting state functional connectivity (rsFC) of PVS structures during ?Engage? predicts increased behavioral activation. Additionally, compared to solitary pleasant activities, exposure to rewarding social interactions during ?Engage? leads to greater increase in behavioral activation and reduction of depression severity. Finally, a machine learning analysis conducted by the candidate showed that low perceived social support is the strongest predictor of poor response early in psychotherapy. These findings are in line with animal and human studies demonstrating the protective role of social rewards. Based on these observations, the candidate developed ?Engage-S?, a social-reward based version of ?Engage?, aimed to increase exposure to meaningful social interactions with others. The training study proposes to examine whether social reward exposure in ?Engage-S? enhances PVS abnormalities and improves mid- and late-life depression. The participants will be 60 middle-aged and older adults (age ? 50) with major depression who will be randomized to 9-weeks of ?Engage-S? or to a Symptom Review and Psychoeducation (SRP) comparison condition. During treatment, we will examine target engagement of the PVS with rsFC, a behavioral activation scale (BADS), and performance on a novel social reward paradigm at baseline, 5 weeks, and 9 weeks. We will use computational methods to identify neuroimaging and behavioral profiles associated with treatment response. The training plan consists of formal courses, structured tutorials, and hands-on methodological training that will offer the candidate knowledge and skills in: 1) Functional neuroanatomy of depression and aging; 2) Use of fMRI to assess target engagement during psychotherapies for mid- and late-life depression; 3) Computational modeling for the identification of clinical and neuroimaging predictors of treatment response that can be used to personalize psychotherapy; and 4) Generate preliminary data for an R-series experimental therapeutics target engagement application.

Public Health Relevance

Abnormalities in the Positive Valence System (PVS) are associated with depressive symptoms and reduced behavioral activation in mid- and late-life. This study will investigate the engagement of the PVS during exposure to social rewards, part of a novel streamlined psychotherapy for mid- and late-life depression. Use of computational modeling will enable identification of neuroimaging and behavioral profiles associated with greater treatment response, and may guide future personalization of psychotherapy.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Mentored Patient-Oriented Research Career Development Award (K23)
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Special Emphasis Panel (ZRG1)
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Chavez, Mark
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Weill Medical College of Cornell University
Schools of Medicine
New York
United States
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