Presented During:
Wednesday, June 25, 2025: 5:45 PM - 5:57 PM
Brisbane Convention & Exhibition Centre
Room:
Great Hall
Poster No:
75
Submission Type:
Abstract Submission
Authors:
Nga Yan Tse1, Aswin Ratheesh2, Luke Hearne3, Conor Robinson4, Bjorn Burgher5, Luca Cocchi6, Robin Cash7, Andrew Zalesky8
Institutions:
1Systems Lab, Department of Psychiatry, The University of Melbourne, Carlton, VIC, 2Discipline of Psychiatry and Mental Health, University of New South Wales, Randwick, New South Wales, 3QIMR Berghofer Medical Research Institute, Herston, Queensland, 4QIMR Berghofer Medical Research Institute, Brisbane, QLD, 5Queensland Institute for Medical Research, Brisbane, Queensland, 6Queensland Institute for Medical Research, Brisbane, QLD, 7University of Melbourne, Torquay, VIC, 8Systems Lab, Department of Psychiatry, The University of Melbourne, Melbourne, Australia
First Author:
Nga Yan Tse
Systems Lab, Department of Psychiatry, The University of Melbourne
Carlton, VIC
Co-Author(s):
Aswin Ratheesh, A/Prof
Discipline of Psychiatry and Mental Health, University of New South Wales
Randwick, New South Wales
Luke Hearne
QIMR Berghofer Medical Research Institute
Herston, Queensland
Conor Robinson
QIMR Berghofer Medical Research Institute
Brisbane, QLD
Bjorn Burgher
Queensland Institute for Medical Research
Brisbane, Queensland
Luca Cocchi
Queensland Institute for Medical Research
Brisbane, QLD
Andrew Zalesky
Systems Lab, Department of Psychiatry, The University of Melbourne
Melbourne, Australia
Introduction:
Growing knowledge of the link between brain connectivity and transcranial magnetic stimulation (TMS) treatment response has driven recent advances in target refinement and, in turn, treatment efficacy in major depressive disorder (MDD). Notably, mounting evidence suggests that prospectively targeting TMS to dorsolateral prefrontal cortex (DLPFC) sites according to connectivity with the subgenual anterior cingulate cortex (sgACC) might improve therapeutic outcomes in adult MDD.1–6 However, outcome variability remains, with sex differences widely implicated as a contributor7, yet the potential mechanism underlying this difference has remained unexplored.
Here, we explored whether sex differences may exist in DLPFC-sgACC functional connectivity. We also assessed the potential contribution of sex to variability in clinical outcomes in 51 adult patients who received personalized connectivity-guided TMS for treatment of refractory MDD.
Methods:
Our sample consisted of 51 (24 F, 27 M) adult MDD patients. T1 and resting-state-fMRI brain scans were acquired in each individual prior to 20-30 sessions of DLPFC-sgACC-connectivity-targeted TMS treatment. To increase the signal-to-noise ratio given the small volume of the sgACC, each patient's DLPFC-sgACC was weighted by the group-average DLPFC-sgACC connectivity map derived from the high-resolution 7T Human Connectome Project (HCP) dataset8. Next, we examined whether individual differences in DLPFC-SGC connectivity were correlated with post-treatment depressive symptoms scores (as measured by the The Montgomery–Åsberg Depression Rating Scale [MADRS]) within each sex group. The partial correlation was used, with baseline MADRS scores, age, total treatment sessions, framewise displacement values, as well as the presence of comorbid anxiety, post-traumatic stress disorder (PTSD) and/or obsessive-compulsive disorder (OCD) diagnoses included as covariates.
Results:
Female patients had a significantly higher baseline MADRS score compared to male participants (p = .002), and a significantly higher proportion of responders was found in the male than female group (p = .037). There were however no significant differences across all other demographic, clinical and neuroimaging characteristics, including age, illness duration, total treatment sessions, post-treatment MADRS severity, distribution of comorbid anxiety, PTSD and OCD diagnosis, DLPFC-sgACC connectivity strength, and framewise displacement values.
Sex differences emerged in the correlation between DLPFC-sgACC connectivity and depressive symptom improvement. In female patients, higher anti-correlation between the DLPFC and sgACC at baseline was significantly associated with greater MADRS reduction (n = 24; r = .57; p = .011; Figure 1i and 1iii). An effect that was not observed in the male patients (n = 27; r = -.08; p = .733; Figure 1ii and 1iv).
Conclusions:
Our work suggests sex differences in the connectivity signatures underpinning TMS treatment outcomes in depression. Greater anti-correlation between the DLPFC and sgACC was associated with depression symptom improvement in female but not male patients. This finding underscores a potential role of sgACC connectivity alterations for females in influencing TMS outcomes, while exploration of refined or alternative TMS targets may be warranted in male MDD patients in future work. Together, our findings have direct therapeutic relevance in TMS treatment refinement.
Brain Stimulation:
TMS 1
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling
Task-Independent and Resting-State Analysis
Keywords:
Psychiatric
Psychiatric Disorders
Transcranial Magnetic Stimulation (TMS)
Other - Major depression
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Resting state
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Patients
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
NOTE: Any animal studies without IACUC approval will be automatically rejected.
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Please indicate which methods were used in your research:
Functional MRI
TMS
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
FSL
Provide references using APA citation style.
1. Weigand A, Horn A, Caballero R, et al. Prospective Validation That Subgenual Connectivity Predicts Antidepressant Efficacy of Transcranial Magnetic Stimulation Sites. Biol Psychiatry. 2018;84(1):28-37. doi:10.1016/j.biopsych.2017.10.028
2. Cash RFH, Cocchi L, Anderson R, et al. A multivariate neuroimaging biomarker of individual outcome to transcranial magnetic stimulation in depression. Hum Brain Mapp. 2019;40(16):4618-4629. doi:10.1002/hbm.24725
3. Cash RFH, Cocchi L, Lv J, Fitzgerald PB, Zalesky A. Functional Magnetic Resonance Imaging-Guided Personalization of Transcranial Magnetic Stimulation Treatment for Depression. JAMA Psychiatry. 2021;78(3):337-339. doi:10.1001/jamapsychiatry.2020.3794
4. Siddiqi SH, Weigand A, Pascual-Leone A, Fox MD. Identification of Personalized Transcranial Magnetic Stimulation Targets Based on Subgenual Cingulate Connectivity: An Independent Replication. Biol Psychiatry. 2021;90(10):e55-e56. doi:10.1016/j.biopsych.2021.02.015
5. Cole EJ, Phillips AL, Bentzley BS, et al. Stanford Neuromodulation Therapy (SNT): A Double-Blind Randomized Controlled Trial. Am J Psychiatry. 2022;179(2):132-141. doi:10.1176/appi.ajp.2021.20101429
6. Moreno-Ortega M, Kangarlu A, Lee S, et al. Parcel-guided rTMS for depression. Transl Psychiatry. 2020;10(1). doi:10.1038/s41398-020-00970-8
7. Slan AR, Citrenbaum C, Corlier J, et al. The role of sex and age in the differential efficacy of 10 Hz and intermittent theta-burst (iTBS) repetitive transcranial magnetic stimulation (rTMS) treatment of major depressive disorder (MDD). J Affect Disord. 2024;366:106-112. doi:10.1016/j.jad.2024.08.129
8. Cash RFH, Cocchi L, Lv J, Wu Y, Fitzgerald PB, Zalesky A. Personalized connectivity-guided DLPFC-TMS for depression: Advancing computational feasibility, precision and reproducibility. Hum Brain Mapp. 2021;(December 2020):1-18. doi:10.1002/hbm.25330
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