Structural and functional connectivity in patients with major depressive disorder undergoing accelerated intermittent theta burst stimulation
by Asude Tura
Date of Examination:2024-05-23
Date of issue:2024-06-05
Advisor:PD Dr. Roberto Goya-Maldonado
Referee:PD Dr. Roberto Goya-Maldonado
Referee:Prof. Dr. Susann Boretius
Persistent Address:
http://dx.doi.org/10.53846/goediss-10519
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Abstract
English
Major depressive disorder (MDD) is one of the most prevalent mental health conditions, primarily characterized by depressed mood and loss of interest or pleasure. Cognitive impairments, including psychomotor agitation or retardation, and decreased concentration, are also frequently seen in MDD. The pathophysiology of MDD is highly complex, involving alterations in neurotransmitter systems, disrupted neurogenesis, inflammation, and hormonal changes. From a systems neuroscience perspective, MDD is conceptualized by aberrant structural connectivity (SC) and functional connectivity (FC) patterns of the brain. The limited clinical efficacy of the first-line treatments like pharmacotherapy and psychotherapy necessitates the investigation of newer treatment methods for this complex disorder. Repetitive transcranial magnetic stimulation (rTMS) targeting the left dorsolateral prefrontal cortex (dlPFC) has been recognized as an effective treatment option, inducing changes in SC and FC patterns. Notably, intermittent theta burst simulation (iTBS), a variant of rTMS, has the advantage of shorter session of treatment delivery. iTBS can also be implemented in an accelerated iTBS (aiTBS) protocol, extensively reducing the treatment duration and improving patient convenience. Despite the demonstrated clinical benefits of rTMS and aiTBS in randomized controlled trials (RCT), the exact mechanism of action and their effect on brain connectivity are not fully understood. Enhancing our understanding of the neurobiological effects of aiTBS could help the optimization of the treatment method. Moreover, clinicians are challenged in selecting the most appropriate treatment option for individual patients before commencing their therapeutic regimen. Therefore, identifying baseline demographic and neurobiological predictors that inform the choice of treatment for each patient would be paramount in enhancing clinical decision-making. This work presents a detailed investigation of how aiTBS affects brain activity and connectivity in MDD, employing a RCT design that uses multimodal connectivity data and functional assessments during various experimental tasks. The research aims to uncover the changes in brain activity and connectivity following aiTBS, and to identify baseline neurobiological biomarkers of treatment response. Firstly, since affective symptoms lie on the core of MDD symptomatology, I examined amygdala activity and FC using an emotional face matching task via functional magnetic resonance imaging (fMRI). Secondly, given the cognitive impairments associated with MDD, I assessed frontoparietal network (FPN) activity and FC during the Nback working memory task. Complementary to these functional investigations, I explored the SC of these regions using diffusion tensor imaging (DTI). Finally, I investigated the relationship between SC and resting-state FC in a joint analysis with SC-FC coupling, the correlation between SC and FC patterns. Given the previously reported amygdala hyperactivity, and its decreased FC and SC with the prefrontal cortices seen during the emotional faces task in MDD patients compared to healthy controls (HC), I hypothesized a decrease in amygdala activity, and an increase in FC and SC with the prefrontal regions following aiTBS treatment. Although I did not observe the hypothesized changes in SC or FC of the amygdala, there was a trend towards decrease in right amygdala activity following active aiTBS. Regarding the association vii between baseline amygdala connectivity and clinical improvement, I observed a significant positive correlation between fractional anisotropy (FA) in the anterior commissure, the white matter tract connecting the left and right amygdalae, and clinical improvement following aiTBS treatment. Considering the earlier findings of hyperactivity of the prefrontal cortices, and increased FC within the FPN during the N-back task in MDD patients compared to HC, I hypothesized a decrease in dlPFC activity and FPN FC following aiTBS. My analyses confirmed the decrease in right dlPFC activity and FPN FC, accompanying a significant increase in working memory performance following active aiTBS. As patients with MDD also have widespread decreases in FA within the white matter tracts, I hypothesized an increase in FA within the tracts connecting the FPN correlating with clinical improvement following treatment. In line with this, I observed a significant negative correlation between change in FA within the right FPN and change in severity of depression following treatment. This suggests that patients experiencing a more pronounced decrease in depression severity following treatment exhibited a greater increase in FA in the right FPN. Additionally, regarding the association between baseline activity and FC during the N-back task and clinical improvement, I observed a significant negative association between baseline activity of the precuneus and cuneus during the N-back task, and clinical improvement following aiTBS treatment. Finally, in a joint analysis approach, I investigated if aiTBS could enhance SCFC coupling, a measure significantly reduced in MDD. Confirming this, I found that aiTBS induced a significant increase in whole-brain SC-FC coupling, primarily stemming from increased SC-FC coupling within the default mode network (DMN). This was accompanied by a decrease in FC between the hubs of the DMN and limbic regions including right amygdala and hippocampus. Additionally, I found that SC-FC coupling of the left dlPFC was a significant predictor of aiTBS treatment response, surpassing the predictive value of SC and FC measures alone. This comprehensive study, employing multimodal imaging data and diverse fMRI tasks, represents one of the most extensive investigation of aiTBS treatment for MDD to date. It unveils valuable insights into baseline predictors of treatment response and post-aiTBS changes in brain connectivity in MDD. These findings also highlight the importance of concurrently analyzing both SC and FC data, as this joint analysis enhances our understanding of disorders that involve both connectivity types, while focusing solely on one type of connectivity limits our ability to comprehend the broader clinical picture.
Keywords: major depressive disorder; repetitive transcranial magnetic stimulation; accelerated intermittent theta burst stimulation; fMRI; DTI; connectivity; neuroscience; connectomics
