Prospective Validation That Subgenual Connectivity Predicts Antidepressant Efficacy of Transcranial Magnetic Stimulation Sites

Weigand, Anne; Horn, Andreas; Caballero, Ruth; Cooke, Danielle; Stern, Adam P.; Taylor, Stephan F.; Press, Daniel Z.; Pascual‐Leone, Álvaro; Fox, Michael

doi:10.1016/j.biopsych.2017.10.028

Cited by 380 publications

(347 citation statements)

References 79 publications

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“…Of note, although the sgACC was not implicated in our findings, the structural and functional connections between the striatum (caudate) and the (sg)ACC are well known (Gabbay et al, 2013). In treatment-resistant depression, the sgACC has been proposed as biomarker for response for a variety of interventions, including rTMS treatment (Fox et al, 2012;Fox et al, 2013;Weigand et al, 2017).…”

Section: Graph Measures As Biomarkermentioning

confidence: 75%

Focal application of accelerated iTBS results in global changes in graph measures

Klooster

Franklin

Besseling

et al. 2018

Human Brain Mapping

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Graph analysis was used to study the effects of accelerated intermittent theta burst stimulation (aiTBS) on the brain's network topology in medication‐resistant depressed patients. Anatomical and resting‐state functional MRI (rs‐fMRI) was recorded at baseline and after sham and verum stimulation. Depression severity was assessed using the Hamilton Depression Rating Scale (HDRS). Using various graph measures, the different effects of sham and verum aiTBS were calculated. It was also investigated whether changes in graph measures were correlated to clinical responses. Furthermore, by correlating baseline graph measures with the changes in HDRS in terms of percentage, the potential of graph measures as biomarker was studied. Although no differences were observed between the effects of verum and sham stimulation on whole‐brain graph measures and changes in graph measures did not correlate with clinical response, the baseline values of clustering coefficient and global efficiency showed to be predictive of the clinical response to verum aiTBS. Nodal effects were found throughout the whole brain. The distribution of these effects could not be linked to the strength of the functional connectivity between the stimulation site and the node. This study showed that the effects of aiTBS on graph measures distribute beyond the actual stimulation site. However, additional research into the complex interactions between different areas in the brain is necessary to understand the effects of aiTBS in more detail.

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Section: Graph Measures As Biomarkermentioning

confidence: 75%

Focal application of accelerated iTBS results in global changes in graph measures

Klooster

Franklin

Besseling

et al. 2018

Human Brain Mapping

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“…Fourth, lesion network mapping uses connectome data from a large normative cohort to approximate connectivity in an individual patient at the time of the lesion, and thus ignores individual differences in brain connectivity. This appears to be a reasonable approximation given the success of lesion network mapping across many different symptoms, and prior work using an age‐matched or disease‐matched connectome has had little impact on results …”

Section: Discussionmentioning

confidence: 99%

“…This appears to be a reasonable approximation given the success of lesion network mapping across many different symptoms, 7 and prior work using an age-matched or disease-matched connectome has had little impact on results. 9,37,38 It is important to highlight that most of the above limitations, including inaccuracy of lesion tracing, clinical heterogeneity, and individual differences in brain connectivity, should all bias us against the present findings. As such, our finding that heterogeneous lesion locations causing Holmes tremor map to a common brain circuit is present despite these limitations, not because of them.…”

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confidence: 88%

Mapping holmes tremor circuit using the human brain connectome

Joutsa

Shih

Fox

2019

Annals of Neurology

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Objective Holmes tremor is a debilitating movement disorder with limited treatment options. Lesions causing Holmes tremor can occur in multiple different brain locations, leaving the neuroanatomical substrate unclear. Here, we test whether lesion locations that cause Holmes tremor map to a connected brain circuit and whether this circuit might serve as a useful therapeutic target. Methods Case reports of Holmes tremor caused by focal brain lesions were identified through a systematic literature search. Connectivity between each lesion location and the rest of the brain was computed using resting state functional connectivity magnetic resonance imaging data from 1,000 healthy volunteers. Commonalities across lesion locations were identified. This Holmes tremor circuit was then compared to neurosurgical treatment targets and clinical efficacy. Results We identified 36 lesions causing Holmes tremor, which were scattered across multiple different brain regions. However, all lesion locations were connected to a common brain circuit with nodes in the red nucleus, thalamus, globus pallidus, and cerebellum. In cases with effective neurosurgical treatment, the treatment target was connected with the lesion location, indicating that a second hit to the same circuit might be beneficial. Commonly used deep brain stimulation targets such as the ventral intermediate nucleus and subthalamic nucleus fell outside our Holmes tremor circuit, whereas the globus pallidus target was close, consistent with published clinical response rates for these targets. Interpretation Lesions causing Holmes tremor are part of a single connected brain circuit that may serve as an improved therapeutic target. ANN NEUROL 2019;86:812–820

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“…Fox, Buckner, White, Greicius, and Pascualleone () applied rTMS to depressed patients and found that a more anticorrelated FC of ACC predicted better treatment response. Weigand et al () also applied rTMS to predict antidepressant efficacy but targeted the subgenual ACC. In addition, CBT trials found that ACC hypoactivation was linked to better treatment outcomes (Ball, Stein, & Paulus, ).…”

Section: Discussionmentioning

confidence: 99%

Predicting escitalopram monotherapy response in depression: The role of anterior cingulate cortex

Tian

Sun

Shao

et al. 2019

Human Brain Mapping

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Neuroimaging biomarkers of treatment efficacy can be used to guide personalized treatment in major depressive disorder (MDD). Escitalopram is recommended as first‐line therapy for MDD and severe depression. An interesting hypothesis suggests that the reconfiguration of dynamic brain networks might provide important insights into antidepressant mechanisms. The present study assesses whether the spatiotemporal modulation across functional brain networks could serve as a predictor of effective antidepressant treatment with escitalopram. A total of 106 first‐episode, drug‐naïve patients and 109 healthy controls from three different multicenters underwent resting‐state functional magnetic resonance imaging. Patients were considered as responders if they had a reduction of at least 50% in Hamilton Rating Scale for Depression scores at endpoint (>2 weeks). Multilayer modularity framework was applied on the whole brain to construct features in relation to network dynamic characters that were used for multivariate pattern analysis. Linear soft‐threshold support vector machine models were used to separate responders from nonresponders. The permutation tests demonstrated the robustness of discrimination performances. The discriminative regions formed a spatially distributed pattern with anterior cingulate cortex (ACC) as the hub in the default mode subnetwork. Interestingly, a significantly larger module allegiance of ACC was also found in treatment responders compared to nonresponders, suggesting high interactivities of ACC to other regions may be beneficial for the recovery after treatment. Consistent results across multicenters confirmed that ACC could serve as a predictor of escitalopram monotherapy treatment outcome, implying strong likelihood of replication in the future.

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Prospective Validation That Subgenual Connectivity Predicts Antidepressant Efficacy of Transcranial Magnetic Stimulation Sites

Abstract: This study provides prospective validation that functional connectivity between an individual's rTMS cortical target and the subgenual cingulate predicts antidepressant response. Implications for improving the cortical rTMS target for depression are discussed.

Cited by 380 publications

References 79 publications

Focal application of accelerated iTBS results in global changes in graph measures

Focal application of accelerated iTBS results in global changes in graph measures

Mapping holmes tremor circuit using the human brain connectome

Predicting escitalopram monotherapy response in depression: The role of anterior cingulate cortex

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