¹University of Toronto, Psychiatry, Toronto, Canada, ²University of Toronto, Biostatistics, Toronto, Canada

Background: Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression. However, individual responses vary, highlighting the need to identify reliable predictors of treatment outcome. Irritability is a common, understudied symptom that may help predict rTMS outcomes, and examining it by sex may reveal patterns. However, no study has investigated whether early changes in irritability predict rTMS response by sex.

Aims & Objectives: This study aimed to determine how early irritability change predicts treatment outcomes in males and females and whether baseline resting-state functional connectivity predicts irritability improvements.

Method: Participants included 157 adults with treatment-resistant depression (TRD) (age 19-60, 92 female), from the CARTBIND trial, who received 30 days of rTMS. Early irritability change was defined as the baseline-to-week 2 difference in the restlessness and irritability items of the General Anxiety Disorder Assessment (GAD-7) scale. Linear regressions were conducted separately in males and females to assess the relationship between early irritability change and final depression severity. Additionally, a whole-brain seed-to-voxel resting state functional magnetic resonance imaging (rs-fMRI) general linear model using the dorsolateral prefrontal cortex (DLPFC) seed was performed to identify neural correlates of early irritability improvement.

Results: Early irritability change was significantly correlated to final depression severity in males (p=0.011), but not in females (p=0.980). Increased baseline DLPFC-posterior cingulate cortex (PCC) connectivity was associated with greater irritability improvement at week 2 of rTMS.

Discussion & Conclusions: Early change in irritability predicts rTMS outcomes in males and baseline DLPFC-PCC connectivity predicts week 2 irritability improvement. Evaluating sex differences can reveal biological and clinical factors, supporting personalized and effective treatment.