We are in critical need of targeted and individualized treatments for mental health disorders, which affect nearly 50% of Americans during our lifetimes. Brain stimulation treatments, including repetitive transcranial magnetic stimulation (rTMS), represent the front-line of innovative approaches to correct dysfunctional brain networks for patients suffering from mental illness. rTMS is FDA-approved for depression and obsessive- compulsive disorder (OCD) with clinical trials underway for post-traumatic stress disorder (PTSD) and substance use, among others. However, as currently administered, rTMS lacks a biomarker to individually optimize treatment and thus suffers from a poor clinical response rate (<50%). Without personalization of rTMS, we risk a one-size-fits-all treatment for all psychiatric disorders, not dissimilar to how antidepressants are administered. Using simultaneous TMS and electroencephalography (TMS-EEG), I identified a depression severity biomarker from a double-blind randomized clinical trial treating depressed patients with one month of active or placebo rTMS. The degree of this biomarker change significantly predicted clinical improvement after rTMS treatment. Direct brain recordings further suggest that a single stimulation session is sufficient to modulate this biomarker, indicating that this brain-based biomarker can be monitored daily to support empiric treatment optimization. With this in mind, I propose to develop the first broadly generalizable platform for real-time biomarker monitoring (Aim #1) and personalized rTMS treatment (Aims #2 & 3). I will enroll 54 depressed patients to participate in a cross-over, placebo-controlled study directly comparing personalized, adaptive rTMS to standard rTMS. Primary outcome will be target engagement and dose-response of the depression severity biomarker. Successful implementation of this work includes the early stratification of treatment responders and personalized and more effective treatments for non-responders. This approach is broadly applicable to other depression biomarkers, all psychiatric populations treated with rTMS, and other brain stimulation modalities. More generally, my goals are to establish the fundamental principles of human brain plasticity and to construct platforms for rapid biomarker development, engagement, and integration into personalized brain stimulation treatments.

Public Health Relevance

We need targeted, individualized treatments for mental health disorders, which affects nearly 50% of Americans. Brain stimulation treatments target dysfunctional brain networks with minimal side effects but are currently applied in a one-size-fits-all manner, thus limiting its efficacy. I aim to develop a non-invasive personalized brain stimulation platform for neuropsychiatric disorders; here I will create a real-time monitoring system for brain changes, evaluate the mechanism underlying these brain changes, and develop and test an adaptive stimulation paradigm to maximally drive individual brain changes and improve clinical outcome.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
8R01MH126639-02
Application #
10020446
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Mcmullen, David
Project Start
2019-09-18
Project End
2024-11-30
Budget Start
2020-12-01
Budget End
2021-11-30
Support Year
2
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Stanford University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305