# Cortical Inhibition as a Biomarker of Response in a Comparison of Bilateral versus Unilateral Accelerated Theta Burst Stimulation for Suicidal Ideation in Treatment-Resistant Depression -COMBAT-SI

> **NIH NIH K23** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2024 · $197,576

## Abstract

PROJECT SUMMARY / ABSTRACT
Over 700,000 individuals across the world die by suicide annually. Most individuals who complete suicide suffer
from psychiatric illness, of which major depressive disorder (MDD) is most common. Suicidal ideation (SI) is
more prevalent in individuals with treatment-resistant depression (TRD) compared to those who respond to
treatment. Given treatment limitations of SI in TRD, novel interventions paired with an improved understanding
of the neurobiology of SI are needed. Repetitive transcranial magnetic stimulation (rTMS) is efficacious for TRD.
Evidence suggests that bilateral rTMS (i.e., targeting both the right and left prefrontal cortex) may be more
efficacious for SI in TRD compared to unilateral rTMS, and bilateral brain disturbances are evident from
neuroimaging studies in individuals with SI. Recent advances in rTMS delivery have greatly decreased treatment
duration: accelerated intermittent theta burst stimulation (aiTBS) condenses 6-weeks of standard rTMS into 1-
week. In fact, a unilateral form of aiTBS, the Stanford Accelerated Intelligent Neuromodulation Therapy (SAINT)
System, was recently approved by the FDA for the treatment of TRD. Given the efficacy of bilateral rTMS for SI,
and recent advances in accelerated treatment paradigms, investigation of bilateral accelerated TBS (aTBS) for
the treatment of SI in TRD is warranted. Compelling evidence suggests that SI in TRD is related to aberrant
cortical inhibition bilaterally in the dorsolateral prefrontal cortex (DLPFC) and that rTMS may modulate inhibitory
neurotransmission. Mechanistically, cortical inhibition is closely associated with γ-aminobutyric acid (GABA)
signaling. Therefore, investigating cortical inhibition in the bilateral DLPFC in conjunction with bilateral aTBS
treatment may be key to understanding treatment response. We propose to use transcranial magnetic stimulation
combined with simultaneous electroencephalography (TMS-EEG) to investigate cortical inhibition as a biological
target of treatment in this study (Aim 1). A randomized double-blind clinical trial will be conducted to test the
hypothesis of superiority of bilateral aTBS to unilateral aiTBS on SI in TRD (Aim 2). Seventy-six participants will
be recruited over 5 years. The applicant serves as Medical Director of the Interventional Psychiatry Program at
UC San Diego Health, and he will facilitate appropriate recruitment of participants into this study. The career
development objectives for the applicant are: 1) develop independence as a clinical trialist with relevant statistical
approaches; 2) gain expertise in the conduct and analysis of TMS-EEG; and 3) establish working knowledge in
MRI functional connectivity analysis to guide future rTMS protocols. The applicant’s primary mentor is the Chair
of the Department of Psychiatry at UCSD, neurophysiology and clinical trial expert, Dr. Jeff Daskalakis. Dr. Greg
Appelbaum, Research Director of the Interventional Psychiatry Program will ...

## Key facts

- **NIH application ID:** 11033877
- **Project number:** 1K23MH138746-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Cory R Weissman
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $197,576
- **Award type:** 1
- **Project period:** 2024-09-01 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11033877

## Citation

> US National Institutes of Health, RePORTER application 11033877, Cortical Inhibition as a Biomarker of Response in a Comparison of Bilateral versus Unilateral Accelerated Theta Burst Stimulation for Suicidal Ideation in Treatment-Resistant Depression -COMBAT-SI (1K23MH138746-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/11033877. Licensed CC0.

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