Intrinsic Brain Network Biomarkers of Antidepressant Response: a Review

Abstract

Purpose of Review Poor treatment response is a hallmark of major depressive disorder. To tackle this problem, recent neuroimaging studies have sought to characterize antidepressant response in terms of pretreatment differences in intrinsic functional brain networks. Our aim is to review recent studies that predict antidepressant response using intrinsic network connectivity. We discuss current methodological limitations and directions for future antidepressant biomarker studies. Recent Findings Functional connectivity stemming from the subgenual and rostral anterior cingulate has shown particular consistency in predicting antidepressant response. Differences in this connectivity may prove fruitful in differentiating treatment responders to many antidepressant interventions. Future biomarker studies should integrate biological MDD subtypes to address the disorder’s inherent clinical heterogeneity. Summary These clinical and scientific advancements have the potential to address this population marked by limited treatment response. Methodological considerations, including patient selection, response criteria, and model overfitting, will require future investigation to ensure that biomarkers generalize for prospective prediction of treatment response.

Resting State Functional Connectivity of Brain With Electroconvulsive Therapy in Depression: Meta-Analysis to Understand Its Mechanisms

“…There was a reduction in rsFC of the L. dACC after the course of ECT. Neuroimaging studies suggest increased activity in the ACC as an important biomarker for depression (Helm et al, 2018 ; Lai, 2019 ), which normalizes after treatment with antidepressants and serves as a predictor for the response (Arnone, 2019 ; Dunlop et al, 2019 ; Tian et al, 2020 ). However, sgACC/rACC are implicated here more often than dACC.…”

“…PCC is considered to be an important part of pDMN and is found to have increased FC with dmPFC in people having depression compared with controls (Mulders et al, 2015 ; Helm et al, 2018 ). Increased rsFC of PCC has been shown to be a predictor for response to antidepressants (Goldstein-Piekarski et al, 2018 ; Dunlop et al, 2019 ), psychotherapy (Dunlop et al, 2019 ), and ECT (van Waarde et al, 2015 ). Although there is evidence of reduction in FC of PCC with antidepressants in response to a negative emotional task in some studies, the evidence is limited in rsFC studies to overall increased activity in pDMN rather than in PCC specifically (Arnone, 2019 ; Ichikawa et al, 2020 ).…”

“…The link of global atrophy of HC to the pathology of depression is reasonably recognized, and so is the improvement in its size and associated neurogenesis with antidepressants and other treatment for depression (Helm et al, 2018 ; Santos et al, 2018 ; Lai, 2019 ; Price and Duman, 2020 ). However, the knowledge about FC of HC during the depressive episode and post response to antidepressants or ECT is ambiguous (Fonseka et al, 2018 ; Dunlop et al, 2019 ). Hence, our result of increased FC between R. HC and R. PHG after a course of ECT is valuable.…”

Neuroimaging as a Tool for Individualized Treatment Choice in Depression: the Past, the Present and the Future

“…Brain regions most consistently identified as abnormal prior to treatment, in either function or structure, included the amygdala, ventral striatum, thalamus, hippocampus, anterior cingulate cortex (ACC), ventromedial PFC (vmPFC), orbitofrontal cortex (OFC), and dorsolateral prefrontal cortex (dlPFC). More recent studies have emphasized the role of brain networks of which these structures are a part, rather than that of single structures [12]. Importantly, AD treatment effects have been mapped onto the widely accepted models of biological mechanisms of depression [13].…”

“…PgACC plays a crucial role in the development of depressive symptoms and antidepressant response due to its central position between the circuits responsible for a quick automatic response to emotionally salient stimuli and prefrontal regions exerting cognitive control over them. A recent review [12] emphasized its role at the network level and suggested that functional connectivity from pgACC showed a particular consistency in predicting antidepressant response.…”