Importance
Magnetic seizure therapy (MST) is a novel therapeutic option for treatment-resistant depression (TRD). Suicidal ideation is often associated with TRD and contributes to the increased mortality and morbidity of the disorder.
Objective
To identify a biomarker that may serve as an indicator of remission of suicidal ideation following a course of MST by using cortical inhibition measures from interleaved transcranial magnetic stimulation and electroencephalography (TMS-EEG).
Design, Setting, and Participants
Thirty-three patients with TRD were part of an open-label clinical trial of MST treatment. Data from 27 patients (82%) were available for analysis in this study. Baseline TMS-EEG measures were assessed within 1 week before the initiation of MST treatment using the TMS-EEG measures of cortical inhibition (ie, N100 and long-interval cortical inhibition [LICI]) from the left dorsolateral prefrontal cortex and the left motor cortex, with the latter acting as a control site.
Interventions
The MST treatments were administered under general anesthesia, and a stimulator coil consisting of 2 individual cone-shaped coils was used.
Main Outcomes and Measures
Suicidal ideation was evaluated before initiation and after completion of MST using the Scale for Suicide Ideation (SSI). Measures of cortical inhibition (ie, N100 and LICI) from the left dorsolateral prefrontal cortex were selected. N100 was quantified as the amplitude of the negative peak around 100 milliseconds in the TMS-evoked potential (TEP) after a single TMS pulse. LICI was quantified as the amount of suppression in the double-pulse TEP relative to the single-pulse TEP.
Results
Of the 27 patients included in the analyses, 15 (56%) were women; mean (SD) age of the sample was 46.0 (15.3) years. At baseline, patients had a mean SSI score of 9.0 (6.8), with 8 of 27 patients (30%) having a score of 0. After completion of MST, patients had a mean SSI score of 4.2 (6.3) (pre-post treatment mean difference, 4.8 [6.7]; paired t26 = 3.72; P = .001), and 18 of 27 individuals (67%) had a score of 0 for a remission rate of 53%. The N100 and LICI in the frontal cortex—but not in the motor cortex—were indicators of remission of suicidal ideation with 89% accuracy, 90% sensitivity, and 89% specificity (area under the curve, 0.90; P = .003).
Conclusions and Relevance
These results suggest that cortical inhibition may be used to identify patients with TRD who are most likely to experience remission of suicidal ideation following a course of MST. Stronger inhibitory neurotransmission at baseline may reflect the integrity of transsynaptic networks that are targeted by MST for optimal therapeutic response.
Major depressive disorder (MDD) is a debilitating mood disorder characterized by persistent sadness, negative thoughts, anhedonia, irregular sleep and eating patterns, and, in severe cases, suicidal ideation.1 Up to 40% of patients with MDD are diagnosed as having treatment-resistant depression (TRD), defined as an inability to respond to 2 or more separate trials of antidepressants.2,3 The most effective treatment for patients with TRD is electroconvulsive therapy (ECT), which has also been shown4 to be particularly effective for reducing suicidal ideation in patients with TRD. However, the adverse effects on memory and stigma associated with ECT have impeded its widespread use.5 Magnetic seizure therapy (MST) represents a potential alternative to ECT since MST demonstrates clinical efficacy in patients with TRD6 and has a more benign cognitive adverse effect profile.7-9Quiz Ref ID With MST, electrical current is induced directly in brain tissue through fluctuating magnetic fields that, unlike the electric currents of ECT, are not shunted by the skull. Thus, compared with ECT, MST stimulates a much smaller region of the cortex and elicits seizures with a weaker induced electric field,10 which may explain why MST produces fewer cognitive adverse effects.
Repetitive transcranial magnetic stimulation (TMS) can modulate both cortical and subcortical networks via transsynaptic interneuron activation,11,12 and MST can target these same transsynaptic mechanisms to produce its therapeutic effects. Moreover, since seizures are initiated focally by MST, the pattern of transsynaptic propagation is greatly dependent on interneuron connectivity of endogenous brain networks.13 Previous studies14-16 have shown that treatment response for depression is associated with changes in γ-aminobutyric acid (GABA)ergic interneurons, particularly in the dorsolateral prefrontal cortex (DLPFC). Likewise, improvement in suicidal ideation has been linked17-19 to GABAergic interneuron transmission. Therefore, we hypothesized that the integrity of the GABAergic interneuron network in the frontal cortex may predict MST treatment outcome.
Suicidal ideation was chosen as the clinical outcome of interest in the present study for 2 key reasons. The first reason is the enormous personal and societal costs that are associated with this devastating symptom. The second reason is that suicidal ideation follows the National Institute of Mental Health research domain criteria, which attempt to restructure the depression phenotype by focusing on specific symptom constructs.20 Major depressive disorder is heterogeneous, with many different symptoms contributing to the diagnosis. Certain treatments and biological indices may target specific symptoms (eg, suicidal ideation) more effectively than the heterogeneous clinical picture that constitutes MDD.
To test our hypothesis, we selected 2 cortical inhibition measures assessed by combined TMS and electroencephalography (TMS-EEG)21 in the left DLPFC. These 2 measures include the N10022 and long-interval cortical inhibition (LICI).23 The N100 measure was quantified as the amplitude of the negative peak of approximately 100 milliseconds in the TMS-evoked potential (TEP) after a single TMS pulse. LICI was quantified as the amount of suppression in the double-pulse TEP relative to the single-pulse TEP.23 These measures have been shown23-25 to be reliable indices of GABAergic interneuron function. For example, Premoli et al24,25 reported that both the amplitude of the N100 and level of LICI were increased in healthy volunteers following a single oral dose of baclofen, a GABAB agonist. Both the N100 and LICI can be reliably recorded from the DLPFC23 and the 2 are highly correlated,26,27 suggesting that similar GABAergic inhibitory mechanisms underlie these 2 paradigms. Further support that these 2 paradigms are related to GABAB receptor–mediated inhibitory neurotransmission includes the fact that their time course of inhibition is consistent with that of GABAB-mediated inhibitory postsynaptic potentials that peak at approximately 135 milliseconds28 and that suprathreshold stimulation is required to generate both the N100 response and LICI level, which is consistent with greater activation thresholds that are needed to stimulate GABAB-mediated inhibitory postsynaptic potentials.29 Because both higher N100 (ie, more negative) amplitude and LICI levels are associated with greater integrity of an individual’s GABAergic interneuron network,24,25 we hypothesized that higher N100 amplitude and LICI over the frontal cortex would be associated with greater reduction in suicidal ideation.
Thirty-three patients with TRD were included in this study. The level of treatment resistance was quantified with the antidepressant treatment history form.30 All patients were part of an open-label clinical trial of MST in several severe psychiatric disorders (NCT01596608),31 and our sample was limited to those with a diagnosis of MDD based on the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders.32 All patients provided written informed consent, and the protocol was approved by the ethics committee at the University of Toronto Centre for Addiction and Mental Health. Participants did not receive financial compensation. Fourteen patients with MDD had comorbid psychiatric disorders, which included panic disorder, general anxiety disorder, eating disorders, posttraumatic stress disorder, attention deficit disorder, and a history of alcohol dependence and other substance dependence. Information on demographics and other clinical characteristics of the patient sample is found in the Table.
Baseline TMS-EEG testing was done within 1 week before the initiation of MST treatment. Patients were tested using the LICI experimental paradigm in the left DLPFC as well as the left motor cortex as a control site based on previously published methods.23 In brief, patients were tested in 4 different conditions, with 2 for each site of stimulation, which included 1 condition with 100 single TMS pulses (test pulse only) and the other with 100 double TMS pulses separated by 100 milliseconds (conditioning plus test pulse). The TMS pulses were administered using a 70-mm figure-of-8 coil and 2 stimulators (Magstim 200; Magstim Company Ltd) linked with a connection module (BiStim; Magstim). When stimulating the motor cortex, the TMS coil was placed at the optimal position for eliciting motor-evoked potentials from the right abductor pollicis brevis muscle. The intensity of stimulation was then adjusted to produce a mean peak-to-peak, motor-evoked potential amplitude of 1 mV in the motor cortex, which was also the intensity subsequently used to index cortical inhibition in the motor cortex and DLPFC.23,26,33 For DLPFC stimulation, the TMS coil was placed over electrode F5 and oriented along the line connecting F5 and AF3. Although magnetic resonance imaging (MRI)–guided TMS-EEG is more accurate than non–MRI-guided methods, the added step of obtaining an MRI for every participant would have significantly slowed recruitment for this study owing to the pressing need to begin treatment in acutely ill patients, many of whom were experiencing suicidal ideation. As such, we proceeded with non–MRI-guided TMS-EEG using EEG-guided methods according to a previously published study.34
The EEG (Synamps RT; Compumedics Neuroscan) was acquired using a 64-channel EEG cap. All electrodes were referenced to an electrode positioned posterior to the Cz. The EEG signals were recorded in DC mode with a 100-Hz low-pass filter (48 dB/octave) and a sampling rate of 20 kHz. The recording measures were chosen to avoid saturation of the amplifier and to minimize the TMS-related artifact.23
Assessment of Suicidal Ideation
Suicidal ideation was evaluated before initiation and after completion of MST using the Scale for Suicide Ideation (SSI). The SSI is a dedicated clinical scale for assessing suicidal intent and has been shown to be sensitive to changes in suicidal symptoms over time.35 The SSI scale has 19 items and a maximum possible score of 38. A higher SSI score indicates greater suicidal intent, and a score of zero indicates no suicidal symptoms.
The MST treatments were administered under general anesthesia using a stimulator machine (MagPro MST; MagVenture) with a twin coil. Methohexital sodium (n = 14), methohexital with remifentanil hydrochloride (n = 18), and ketamine hydrochloride (n = 1) were used as the anesthetic agents. Succinylcholine chloride was used as the neuromuscular blocker. Patients had a mean (SD) seizure duration of 45.1 (21.4) seconds. The twin coil consists of 2 individual cone-shaped coils. Stimulation was delivered over the frontal cortex at the midline position directly over the electrode Fz according to the international 10-20 system.36 Placing the twin coil symmetrically over electrode Fz results in the centers of the 2 coils being over F3 and F4. Based on finite element modeling, this configuration produces a maximum induced electric field between the 2 coils, which is over electrode Fz in this case.37 Patients were treated for 24 sessions or until remission of depressive symptoms based on the 24-item Hamilton Rating Scale for Depression (HRSD) (defined as an HRSD-24 score ≤10 and 60% reduction in symptoms for at least 2 days after the last treatment).38 These remission criteria were standardized from previous ECT depression trials.39,40 Further details of the treatment protocol are available,30 and comprehensive clinical and neurophysiologic trial results will be reported separately.
To study the underlying neurophysiologic signal, the recorded EEG was preprocessed (MATLAB; MathWorks) using the EEGLAB toolbox41 and custom scripts that were developed based on previous work.42,43 The recorded EEG signal was resampled from 20 kHz to 1000 Hz and epoched into trials with data from 1000 milliseconds before to 1000 milliseconds after the onset of each test pulse. Each data trial was baseline corrected with the mean of the TMS artifact-free time period (−1000 to −110 milliseconds) before the test stimulus onset. To remove the TMS stimulation artifact, EEG data from 5 milliseconds before the onset of each TMS pulse until 10 milliseconds after the onset was removed from further analysis. Channels and trials that were gross outliers in terms of amplitude and high-frequency power were labeled and removed semiautomatically.42 Independent component analysis was applied to the data, and components that captured TMS decay artifacts were removed based on previously identified features.44 The signal was band-pass filtered to the typical range of physiologically meaningful EEG (1-80 Hz) along with a notch filter set at 60 Hz to remove any line noise. Any remaining outlier trials and channels were removed, and independent component analysis was conducted a second time to remove other nonneurogenic components, including those caused by eye blinks, other eye movements, muscle artifacts, and electrode movements.45 Any missing channels were interpolated from the available channels using linear surface interpolation, and all channels were then average referenced.
To calculate the N100 response, the mean of single-pulse data across all trials was calculated for each electrode to obtain the TEP. The peak value of the N100 was then extracted from each electrode by finding the negative peak closest to 100 milliseconds, which was calculated by finding the minimum value across the interval from 90 to 130 milliseconds (Figure 1).
The LICI was calculated using the TEP from both the single-pulse and paired-pulse stimulation conditions. For paired-pulse stimulation, the response from the second pulse (test stimulus) was superimposed with the response from the first pulse (conditioning stimulus). Therefore, to isolate the response from the second pulse, the TEP from the corresponding single-pulse condition (TEP1) was aligned with the conditioning pulse and subtracted from the raw paired pulse-evoked potential (TEP2), resulting in an adjusted waveform (TEP2A). This approach resulted in a more accurate measure of LICI based on previous works.26 The value of the LICI was calculated based on equation 2 (Figure 1), which uses the area under the curve of the rectified waveform of TEP1 and TEP2A. The integration ranged from 50 to 275 milliseconds in accordance with methods from previously published work.46
The Pearson correlation coefficient was used to evaluate the association between baseline TMS-EEG measures (N100 and LICI) and clinical outcome (SSI score change). To control for possible confounding effects, the use of concurrent benzodiazepine medication (present, 1; not present, 0) was used as a covariate. False detection rate correction was applied to the per-electrode significance values.47
Classification and Model Prediction
In addition, we used logistic regression models to assess the ability of the TMS-EEG measures to correctly indicate remission of suicidal ideation, defined as having a pre-MST SSI score of 1 or higher and a post-MST SSI score of 0. Based on this definition, suicidal ideation resolved in 10 (53%) of the 19 patients with suicidal ideation at baseline. Three different logistic regression models were used: 1 with N100 values as the indicator, 1 with LICI values as the indicator, and 1 with both N100 and LICI values as indicators. We used a receiver operating characteristic curve to plot the sensitivity and specificity values for the indicator across all possible thresholds in patients with suicidal ideation (ie, nonzero baseline SSI values). A larger area under the curve (AUC) for the receiver operating characteristic that is significantly different from that of a random guess signifies a better indicator.
Of the 33 patients with TRD who participated, 4 (12%) patients had no post-SSI evaluation and 2 (6%) had EEG recordings that were unusable. These data were excluded from further analysis. Quiz Ref IDAt baseline, patients had a mean (SD) SSI score of 9.0 (6.8), with 8 of 27 patients (30%) having a score of 0. After completion of MST (participants underwent a mean of 16.9 [7.0] sessions), the SSI score was 4.2 [6.3] (pre-post treatment difference, 4.8 [6.7]; paired t26 = 3.72; P = .001), and Quiz Ref ID18 of 27 individuals (67%) had a score of 0 for a remission rate of 53%.
Calculating the mean of the trial responses from single-pulse TMS stimulations resulted in a characteristic TEP waveform for the DLPFC and motor cortex, with peaks including the N100 at expected latencies (Figure 1A).44 The topography of N100 values across electrodes is shown in Figure 1B. Compared with the single-pulse response, the double-pulse response demonstrated a clear effect of inhibition in the dampening of the TEP, which is measured by LICI (Figure 1C). The topography of LICI values across electrodes is shown in Figure 1D.
Quiz Ref IDFor DLPFC stimulation, SSI score changes were strongly correlated with N100 values for frontal electrodes (maximum at FC4; R = −0.64; P < .001) (Figure 2A and C). The SSI score changes were also significantly correlated with LICI values for frontal electrodes (maximum at FC6; R = 0.58; P = .002) (Figure 2B and D). These correlations maintained significance after false detection rate correction was applied across all frontal electrodes.47 Although all patients were included in this correlation analysis, similar correlations across frontal electrodes were found when analysis was limited to 19 patients who had nonzero baseline SSI values. That is, SSI score changes correlated with both frontal N100 values (maximum at FC4; R = −0.65; P = .004) and LICI values (maximum at FC6; R = 0.64; P = .005). No significant correlations were found for values from the corresponding motor cortex stimulation.
Quiz Ref IDThe N100 values of the frontal electrodes resulting from DLPFC stimulation predicted resolution of suicidal ideation with high sensitivity and specificity. As expected, N100 values from the electrode with the strongest correlation with SSI score change (ie, FC4) demonstrated the best indication, resulting in classification accuracy of 84%, sensitivity of 80%, and specificity of 89% (AUC, 0.88; P = .006) (Figure 3A). In contrast, when motor cortex N100 values were used, no electrode had an AUC that differed significantly from a random guess. Although frontal LICI correlated with SSI score change, it did not indicate resolution of suicidal ideation (ie, no electrode generated an AUC significantly different from a random guess). However, when using both frontal N100 and LICI, the accuracy was 89%, with a sensitivity of 90% and specificity of 89% (AUC, 0.90; P = .003) (Figure 3B and C).
We found that TMS-EEG measures of cortical inhibition (ie, the N100 and LICI) in the frontal cortex, but not in the motor cortex, were strongly correlated with changes in suicidal ideation in patients with TRD who were treated with MST. These findings suggest that patients who benefitted the most from MST demonstrated the greatest cortical inhibition at baseline. More important, when patients were divided into remitters and nonremitters based on their SSI score, our results show that these measures can indicate remission of suicidal ideation from a course of MST with 90% sensitivity and 89% specificity.
The high indicator value derived by combining the N100 and LICI supports our hypothesis that the therapeutic effects of MST depend on the integrity of an individual’s frontal interneuronal network. This result is congruent with evidence48 suggesting that magnetic stimulation produces its treatment effects through transsynaptic interneuron mechanisms. We contend that a more robust interneuronal network, as indexed by a higher N100 (ie, more negative) amplitude and a greater LICI level, can allow for better transsynaptic activation of neuronal circuits during a seizure and that this process may be integral to the observed effectiveness of MST. This hypothesis is supported by in vitro studies49,50 showing that seizures induced focally by electrical currents may be initiated or controlled by GABAergic interneurons through transsynaptic modulation of neuronal networks. The fact that these interneuronal elements are both the putative site of MST action and are neurophysiologically evaluated through TMS-EEG may explain why our ability to predict suicidal ideation treatment response was so high.
Modulation of GABA-mediated neurotransmission has been proposed as a possible mechanism of action for both ECT51 and repetitive TMS52-54 in depression. However, treatment studies in depression that examined GABAergic neurotransmission have found mixed results. Although some studies14,55 showed an increase in GABAergic interneuron function with successful treatment, other investigations56,57 found that a blockade of GABAergic receptor function can lead to antidepressant effects. Nevertheless, these studies suggest that GABAergic inhibition is important for healthy brain function and is associated with antidepressant treatment response. This finding is consistent with our results suggesting that the therapeutic effect of MST depends on the modulation of GABAergic interneuron circuitry in the frontal cortex.
Our results also support the research domain criteria approach, that is, that suicidal ideation represents a homogeneous symptom construct in TRD that is targeted by MST. Suicidal ideation has been shown to be linked to hopelessness,58,59 negative affect, and attentional biases.60 These maladaptive behaviors all fall under the domain of negative valence systems and are associated with the specific constructs of loss, sustained threat, and frustrative nonreward.20 Suicidal ideation may represent a better phenotype through which to understand the neurobiologic features of mental illnesses.61 In this case, variations in GABAergic-mediated inhibition before MST treatment explained much of the variance for improvements in suicidal ideation across individuals with TRD.
There is also robust literature linking cortical inhibition to suicidal ideation. For example, previous studies have found abnormal GABAergic neurotransmission in suicidal patients, particularly in those with depression.62,63 Based on genetic and epigenetic studies, suicidal patients were shown to have decreased messenger RNA expression64 and increased DNA methylation65 of genes encoding the GABAA receptor in the frontal cortex. Moreover, messenger RNA expression of several genes related to the GABAA receptor is increased in depressed suicidal patients compared with nondepressed suicidal patients.66 It stands to reason that physiological measures that assess GABAergic neurotransmission can represent an important biological target through which treatment response can be predicted.
The limitations of this study include a relatively small sample size and lack of a placebo treatment group, with the latter being difficult to justify ethically given that an effective treatment for patients with TRD exists (ie, ECT). In addition, these findings will need replication in a larger sample of patients with TRD.
Transcranial magnetic stimulation and EEG measures of cortical inhibition (ie, the N100 and LICI) recorded over the frontal cortex represent promising indicators for resolution of suicidal ideation with MST in patients with TRD. These measures may be used to identify patients who are most likely to respond to MST.
Corresponding Author: Zafiris J. Daskalakis, MD, PhD, FRCPC, Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, University of Toronto, 1001 Queen St W, Unit 4-1, Toronto, ON M6J 1H4, Canada (jeff.daskalakis@camh.ca).
Submitted for Publication: September 21, 2015; final revision received November 23, 2015; accepted November 27, 2015.
Published Online: March 16, 2016. doi:10.1001/jamapsychiatry.2015.3097.
Author Contributions: Mr Sun and Dr Daskalakis had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Sun, Farzan, Rajji, Fitzgerald, Blumberger, Daskalakis.
Acquisition, analysis, or interpretation of data: Sun, Farzan, Mulsant, Rajji, Barr, Downar, Wong, Blumberger, Daskalakis.
Drafting of the manuscript: Sun, Wong, Daskalakis.
Critical revision of the manuscript for important intellectual content: Sun, Farzan Mulsant, Rajji, Fitzgerald, Barr, Downar, Blumberger, Daskalakis.
Statistical analysis: Sun, Farzan, Daskalakis.
Obtained funding: Mulsant, Rajji, Downar, Blumberger, Daskalakis.
Administrative, technical, or material support: Farzan, Mulsant, Barr, Downar, Daskalakis.
Study supervision: Farzan, Rajji, Fitzgerald, Wong, Blumberger, Daskalakis.
Conflict of Interest Disclosures: Dr Farzan reported receiving research support from the Brain and Behaviour Research Foundation and Natural Sciences and Engineering Research Council of Canada. Dr Mulsant reported receiving research support from the Canadian Institutes of Health Research (CIHR), National Institutes of Health (NIH), Bristol-Myers Squibb (medications for an NIH-funded clinical trial), and Pfizer (medications for an NIH-funded clinical trial). He directly owns stocks of General Electric. Within the past 5 years, he has received grant support from Eli Lilly (medications for an NIH-funded clinical trial) and Janssen and travel support from Roche. Dr Rajji reported receiving research support from the Brain and Behaviour Research Foundation, Canadian Foundation for Innovation, the CIHR, Ontario Ministry of Health and Long-term Care, Ontario Ministry of Research and Innovation, and the W. Garfield Weston Foundation. Dr Fitzgerald reported receiving equipment for research from Brainsway, Medtronic, and MagVenture A/S and funding for research from Cervel Neurotech. Dr Barr reported receiving research support from the Brain and Behaviour Research Foundation. Dr Downar reported receiving research support from the CIHR, Brain Canada, the NIH, the Klarman Family Foundation, the Edgestone Foundation, and the Toronto General and Western Hospital Foundation as well as travel stipends from Lundbeck and ANT Neuro and in-kind equipment support for an investigator-initiated study from MagVenture. Dr Blumberger reported receiving research support from the CIHR, the NIH, Brain Canada, the Temerty Family through the Temerty Centre for Addiction and Mental Health (CAMH) Foundation, and the Campbell Family Research Institute. He receives nonsalary operating funds and in-kind equipment support from Brain Research and Development Services Ltd for an investigator-initiated study. He is the site principal investigator for several sponsor-initiated clinical trials from Brain Research and Development Services Ltd. He receives in-kind equipment support from Tonika/MagVenture for an investigator-initiated study. Dr Daskalakis reported receiving research and in-kind equipment support for an investigator-initiated study through Brainsway Inc. He has also received speaker fees from Eli Lilly and has served on the advisory board for Hoffmann-La Roche Ltd, Merck, and Sunovion. No other disclosures were reported.
Funding/Support: This work was supported by the Canadian Institutes of Health Research, Brain and Behaviour Research Foundation, Temerty Family, Grant Family, Centre for Addiction and Mental Health Foundation, and Campbell Institute.
Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
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