Frontline treatments for major depressive disorder (MDD), including psycho- and pharmacotherapy, have limited effectiveness, with usual care treatment success at just 29% after 1 year. Remission rates for depression would be enhanced if treatments could be optimized and prescribed to those most likely to benefit. There is a critical need to develop and test novel, efficacious treatments for MDD and simultaneously work to optimize their benefits. Resistance exercise training (RET) is a promising but understudied treatment approach. Our recent meta-analysis found a large antidepressant effect of RET in the few very small trials with clinically depressed samples (d=0.90), highlighting the potential of RET for treating MDD. These trials, while underpowered to determine clinically meaningful effects, showed positive results and provide the foundation for larger mechanistically-informed trials to confirm their promising early effects. Importantly, cerebral blood flow is lower in adults with MDD, linked with a poor treatment response, and RET can improve cerebral blood flow in adults. As such, RET may treat MDD via improving cerebral blood flow. However, the mechanistic pathway linking RET’s antidepressant effects to improved cerebral blood flow in MDD is as-of-yet untested. Further, with advances in machine learning, the identification of modifiable and stable predictors of clinical and mechanistic change as well as adherence can inform future precision medicine initiatives for treating MDD. Thus, a trial to confirm the efficacy of RET for MDD, understand its potential cerebrovascular mechanisms, and uncover the modifiable predictors of its effects is urgently needed. Toward this end, we propose a confirmatory efficacy 1:1 randomized controlled trial (n=200) of 16 weeks of progressive RET or low dose RET (SHAM) in adults with DSM-5 diagnosed MDD. Aim 1 will confirm the efficacy of RET vs SHAM on depressive symptoms at 16 weeks, and evaluate both potentially quicker and enduring effects of RET at 8, 26 and 52 weeks. Aim 2 will determine the effect of RET vs. SHAM on the mechanistic target of cerebral blood velocity and pulsatility and their potential mediation of antidepressant efficacy. Aim 3 will use supervised machine learning tools to predict depression changes, cerebrovascular changes, and participant adherence. Upon completion, this study will build towards our long-term goal of identifying and translating mechanistically-driven behavioral treatments to reduce the global burden of mental illness by determining the extent to which a promising, accessible, translatable RET approach can treat MDD by improving cerebrovascular function. Simultaneously, this project will inform future precision medicine approaches that will target modifiable predictors of treatment response and adherence to behavioral interventions to optimize MDD treatments and individually prescribe them to those most likely to benefit. If RET effectively treats MDD, this trial would lay the foundation to apply RET as a standalone treatment for MDD, and potentially as a standalone or augmentation treatment to reduce the widespread burden of mood disorders and serious mental illnesses.

PROJECT NARRATIVE Depression is a leading cause of disability worldwide and current treatments, such as psychotherapy and medication, are ineffective for many people, leading to a high global burden of depression. This project will investigate the efficacy of a 16-week Resistance Exercise Training (RET) program for treatment of Major Depressive Disorder via improving cerebrovascular mechanisms and using machine learning to inform future precision medicine approaches by modeling changes in depression outcomes, cerebrovascular function, and variation in adherence. If efficacy is confirmed, this highly translatable, accessible, low-cost treatment would add a novel behavioral treatment option for MDD while the machine learning modeling will independently help to improve treatment prescription and optimization for people with depression and other serious mental illnesses.