Can psychological features predict antidepressant response to rTMS? A Discovery-Replication approach

Dimensional and Categorical Solutions to Parsing Depression Heterogeneity in a Large Single-Site Sample

BACKGROUND

Recent studies have reported significant advances in modeling the biological basis of heterogeneity in major depressive disorder, but investigators have also identified important technical challenges, including scanner-related artifacts, a propensity for multivariate models to overfit, and a need for larger samples with more extensive clinical phenotyping. The goals of the current study were to evaluate dimensional and categorical solutions to parsing heterogeneity in depression that are stable and generalizable in a large, single-site sample.

METHODS

We used regularized canonical correlation analysis to identify data-driven brain-behavior dimensions that explain individual differences in depression symptom domains in a large, single-site dataset comprising clinical assessments and resting-state functional magnetic resonance imaging data for 328 patients with major depressive disorder and 461 healthy control participants. We examined the stability of clinical loadings and model performance in held-out data. Finally, hierarchical clustering on these dimensions was used to identify categorical depression subtypes.

RESULTS

The optimal regularized canonical correlation analysis model yielded 3 robust and generalizable brain-behavior dimensions that explained individual differences in depressed mood and anxiety, anhedonia, and insomnia. Hierarchical clustering identified 4 depression subtypes, each with distinct clinical symptom profiles, abnormal resting-state functional connectivity patterns, and antidepressant responsiveness to repetitive transcranial magnetic stimulation.

CONCLUSIONS

Our results define dimensional and categorical solutions to parsing neurobiological heterogeneity in major depressive disorder that are stable, generalizable, and capable of predicting treatment outcomes, each with distinct advantages in different contexts. They also provide additional evidence that regularized canonical correlation analysis and hierarchical clustering are effective tools for investigating associations between functional connectivity and clinical symptoms.

Predicting treatment outcomes in major depressive disorder using brain magnetic resonance imaging: a meta-analysis

Recent studies have provided promising evidence that neuroimaging data can predict treatment outcomes for patients with major depressive disorder (MDD). As most of these studies had small sample sizes, a meta-analysis is warranted to identify the most robust findings and imaging modalities, and to compare predictive outcomes obtained in magnetic resonance imaging (MRI) and studies using clinical and demographic features. We conducted a literature search from database inception to July 22, 2023, to identify studies using pretreatment clinical or brain MRI features to predict treatment outcomes in patients with MDD. Two meta-analyses were conducted on clinical and MRI studies, respectively. The meta-regression was employed to explore the effects of covariates and compare the predictive performance between clinical and MRI groups, as well as across MRI modalities and intervention subgroups. Meta-analysis of 13 clinical studies yielded an area under the curve (AUC) of 0.73, while in 44 MRI studies, the AUC was 0.89. MRI studies showed a higher sensitivity than clinical studies (0.78 vs. 0.62, Z = 3.42, P = 0.001). In MRI studies, resting-state functional MRI (rsfMRI) exhibited a higher specificity than task-based fMRI (tbfMRI) (0.79 vs. 0.69, Z = -2.86, P = 0.004). No significant differences in predictive performance were found between structural and functional MRI, nor between different interventions. Of note, predictive MRI features for treatment outcomes in studies using antidepressants were predominantly located in the limbic and default mode networks, while studies of electroconvulsive therapy (ECT) were restricted mainly to the limbic network. Our findings suggest a promise for pretreatment brain MRI features to predict MDD treatment outcomes, outperforming clinical features. While tasks in tbfMRI studies differed, those studies overall had less predictive utility than rsfMRI data. Overlapping but distinct network-level measures predicted antidepressants and ECT outcomes. Future studies are needed to predict outcomes using multiple MRI features, and to clarify whether imaging features predict outcomes generally or differ depending on treatments.

A Deep Learning-Derived Transdiagnostic Signature Indexing Hypoarousal and Impulse Control: Implications for Treatment Prediction in Psychiatric Disorders

BACKGROUND

Psychiatric disorders are traditionally classified within diagnostic categories, but this approach has limitations. Research Domain Criteria (RDoC) constitute a research classification system for psychiatric disorders based on dimensions within domains that cut across these psychiatric diagnoses. The overall aim of RDoC is to better understand mental illness in terms of dysfunction in fundamental neurobiological and behavioral systems, leading to better diagnosis, prevention and treatment.

METHODS

A unique electroencephalographic (EEG) feature, referred to as spindling excessive beta (SEB), has been studied in relation to impulse control and sleep, as part of the arousal/regulatory systems RDoC domain. Here, we study EEG frontal beta activity as a potential transdiagnostic biomarker capable of diagnosing and predicting impulse control and sleep problems.

RESULTS

We show in the first dataset (n=3279) that the probability of having SEB, classified by a deep learning algorithm, is associated with poor sleep maintenance and low daytime impulse control. Furthermore, in two additional, independent datasets (iSPOT-A, n=336; iSPOT-D, n=1008), we revealed that conventional frontocentral beta power and/or SEB probability, referred to as Brainmarker-III, is associated with a diagnosis of attention deficit hyperactivity disorder (ADHD), with remission to methylphenidate in children with ADHD in a sex-specific manner, and with remission to antidepressant medication in adults with a major depressive disorder in a drug-specific manner.

CONCLUSION

Our results demonstrate the value of the RDoC approach in psychiatry research for the discovery of biomarkers with diagnostic and treatment prediction capacities.

The effect of noninvasive brain stimulation on anhedonia in patients with schizophrenia and depression: A systematic review and meta-analysis

Anhedonia is a transdiagnostic symptom found in patients with schizophrenia and depression. Current pharmacological interventions for anhedonia are unsatisfactory in a considerable proportion of patients. There has been growing interest in applying noninvasive brain stimulation (NIBS) to patients with anhedonia. However, evidence for the efficacy of NIBS for anhedonia remain inconsistent. This study systematically identified all studies that measured anhedonia and applied NIBS in patients with schizophrenia or depression. We conducted a search using the various databases in English (PubMed, EBSCOHost (PsycInfo/PsycArticles), Web of Science) and Chinese (China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform) languages, and reviewed original research articles on NIBS published from January 1989 to July 2023. Our search had identified 15 articles for quantitative synthesis, with three concerning schizophrenia samples, 11 concerning samples with depression, and one concerning both clinical samples. We conducted a meta-analysis based on the 15 included studies, and the results suggested that NIBS could improve anhedonia symptoms in schizophrenia patients and patients with depression, with a medium-to-large effect size. Our findings are preliminary, given the limited number of included studies. Future NIBS research should measure anhedonia as a primary outcome and should recruit transdiagnostic samples.

Clinical effects of anodal tDCS and identifying response markers in post-traumatic stress disorder (PTSD): An open-label study

Transcranial direct current stimulation (tDCS) is a promising treatment for post-traumatic stress disorder (PTSD). However, not all patients respond to this type of treatment. The first aim of present study was to examine efficacy of tDCS for PTSD, depression, anxiety, and anhedonia in patients with PTSD. The second aim of this study was to examine the demographic, clinical, and psychological factors that may predict response to tDCS. In this open-label study, 103 PTSD patients underwent 10 sessions of tDCS (2 mA, 20 min). The anodal and cathodal electrodes were placed over the left dorsolateral prefrontal cortex (DLPFC; F3) and right supra-orbital (FP2) Respectively. Clinical outcome measures included Posttraumatic the Stress Disorder Checklist for DSM-5 (PCL-5), the Beck Depression Inventory (BDI-II), the Beck Anxiety Inventory (BAI), and the Snaith-Hamilton Pleasure Scale (SHAPS). There was an overall significant improvement in symptoms of PTSD, depression, anxiety, and anhedonia from pre- to post-treatment. Results also revealed that non-responders had higher severity at baseline for depression, anxiety, and anhedonia. However, higher severity of depression and anhedonia at baseline predicted response status, with higher severity associated with greater likelihood of non-response. tDCS of the left dLPFC and right supra-orbital appears to have a positive effect in reducing PTSD and related symptoms. These initial results could have an important influence on the adoption of anodal tDCS over the left DLPFC for PTSD, by enabling the early identification of patients who respond to tDCS.

A posterior-alpha ageing network is differentially associated with antidepressant effects of venlafaxine and rTMS

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder, but chances for remission largely decrease with each failed treatment attempt. It is therefore desirable to assign a given patient to the most promising individual treatment option as early as possible. We used a polygenic score (PGS) informed electroencephalography (EEG) data-driven approach to identify potential predictors for MDD treatment outcome. Post-hoc we conducted exploratory analyses in order to understand the results in depth. First, an EEG independent component analysis produced 54 functional brain networks in a large heterogeneous cohort of psychiatric patients (n = 4,045; 5-84 yrs.). Next, the network that was associated to PGS for antidepressant-response (PRS-AR) in an independent sample (n = 722) was selected: an age-related posterior alpha network that explained >60 % of EEG variance, and was highly stable over recording time. Translational analyses were performed in two other independent datasets to examine if the network was predictive of psychopharmacotherapy (n = 535) and/or repetitive transcranial magnetic stimulation (rTMS) and concomitant psychotherapy (PT; n = 186) outcome. The network predicted remission to venlafaxine (p = 0.015), resulting in a normalized positive predicted value (nPPV) of 138 %, and rTMS + PT - but in opposite direction for women (p = 0.002) relative to men (p = 0.018) - yielding a nPPV of 131 %. Blinded out-of-sample validations for venlafaxine (n = 29) and rTMS + PT (n = 36) confirmed the findings for venlafaxine, while results for rTMS + PT could not be replicated. These data suggest the existence of a relatively stable EEG posterior alpha aging network related to PGS-AR that has potential as MDD treatment predictor.

Predicting response to repetitive transcranial magnetic stimulation in patients with chronic insomnia disorder using electroencephalography: A pilot study

Predicting responsvienss to repetitive transcranial magnetic stimulation (rTMS) can facilitate personalized treatments with improved efficacy; however, predictive features related to this response are still lacking. We explored whether resting-state electroencephalography (rsEEG) functional connectivity measured at baseline or during treatment could predict the response to 10-day rTMS targeted to the right dorsolateral prefrontal cortex (DLPFC) in 36 patients with chronic insomnia disorder (CID). Pre- and post-treatment rsEEG scans and the Pittsburgh Sleep Quality Index (PSQI) were evaluated, with an additional rsEEG scan conducted after four rTMS sessions. Machine-learning approaches were employed to assess the ability of each connectivity measure to distinguish between responders (PSQI improvement > 25%) and non-responders (PSQI improvement ≤ 25%). Furthermore, we analyzed the connectivity trends of the two subgroups throughout the treatment. Our results revealed that the machine learning model based on baseline theta connectivity achieved the highest accuracy (AUC = 0.843) in predicting treatment response. Decreased baseline connectivity at the stimulated site was associated with higher responsiveness to TMS, emphasizing the significance of functional connectivity characteristics in rTMS treatment. These findings enhance the clinical application of EEG functional connectivity markers in predicting treatment outcomes.

tDCS efficacy and utility of anhedonia and rumination as clinical predictors of response to tDCS in major depressive disorder (MDD)

BACKGROUND

Anhedonia and rumination are mental disorders' transdiagnostic features but remain difficult to treat. Transcranial direct current stimulation (tDCS) is a proven treatment for depression, but its effects on anhedonia and rumination and whether anhedonia and rumination can be used as a predictive biomarker of treatment response is not well known. This study aimed to investigate the tDCS efficacy and identify the predictive role of anhedonia and rumination in response to tDCS in patients with MDD.

METHODS

182 patients received 10 tDCS sessions delivered at 2 mA to left (anode) dorsolateral prefrontal cortex (DLPFC). Hamilton Rating Scale for Depression (HRSD-17), Snaith-Hamilton Pleasure Scale (SHAPS), and the 10-item Ruminative Response Scale (RRS-10) was administered to patients with MDD before treatment, following it, and after two weeks of tDCS.

RESULTS

There was an overall significant improvement in anhedonia from pre- to post-treatment. Regression analyses revealed that responders had higher baseline anhedonia and rumination (reflective pondering) scores. We found that the reduction in HRSD scores after tDCS was significantly associated with anhedonia's baseline values while no relation was found between baseline rumination and tDCS treatment response.

CONCLUSION

These results provide new evidence that pronounced anhedonia may be a significant clinical predictor of response to tDCS. Patients with severe or low baseline rumination had an equal chance of achieving clinical response. Prospective tDCS studies are necessary to validate the predictive value of the derived model.

Macroscopic resting state model predicts theta burst stimulation response: A randomized trial

Repetitive transcranial magnetic stimulation (rTMS) is a promising alternative therapy for treatment-resistant depression, although its limited remission rate indicates room for improvement. As depression is a phenomenological construction, the biological heterogeneity within this syndrome needs to be considered to improve the existing therapies. Whole-brain modeling provides an integrative multi-modal framework for capturing disease heterogeneity in a holistic manner. Computational modelling combined with probabilistic nonparametric fitting was applied to the resting-state fMRI data from 42 patients (21 women), to parametrize baseline brain dynamics in depression. All patients were randomly assigned to two treatment groups, namely active (i.e., rTMS, n = 22) or sham (n = 20). The active treatment group received rTMS treatment with an accelerated intermittent theta burst protocol over the dorsomedial prefrontal cortex. The sham treatment group underwent the identical procedure but with the magnetically shielded side of the coil. We stratified the depression sample into distinct covert subtypes based on their baseline attractor dynamics captured by different model parameters. Notably, the two detected depression subtypes exhibited different phenotypic behaviors at baseline. Our stratification could predict the diverse response to the active treatment that could not be explained by the sham treatment. Critically, we further found that one group exhibited more distinct improvement in certain affective and negative symptoms. The subgroup of patients with higher responsiveness to treatment exhibited blunted frequency dynamics for intrinsic activity at baseline, as indexed by lower global metastability and synchrony. Our findings suggested that whole-brain modeling of intrinsic dynamics may constitute a determinant for stratifying patients into treatment groups and bringing us closer towards precision medicine.

Repetitive transcranial magnetic stimulation treatment of major depressive disorder and comorbid chronic pain: response rates and neurophysiologic biomarkers

BACKGROUND

Major depressive disorder (MDD) and chronic pain are highly comorbid, and pain symptoms are associated with a poorer response to antidepressant medication treatment. It is unclear whether comorbid pain also is associated with a poorer response to treatment with repetitive transcranial magnetic stimulation (rTMS).

METHODS

162 MDD subjects received 30 sessions of 10 Hz rTMS treatment administered to the left dorsolateral prefrontal cortex (DLPFC) with depression and pain symptoms measured before and after treatment. For a subset of 96 patients, a resting-state electroencephalogram (EEG) was recorded at baseline. Clinical outcome was compared between subjects with and without comorbid pain, and the relationships among outcome, pain severity, individual peak alpha frequency (PAF), and PAF phase-coherence in the EEG were examined.

RESULTS

64.8% of all subjects reported pain, and both depressive and pain symptoms were significantly reduced after rTMS treatment, irrespective of age or gender. Patients with severe pain were 27% less likely to respond to MDD treatment than pain-free individuals. PAF was positively associated with pain severity. PAF phase-coherence in the somatosensory and default mode networks was significantly lower for MDD subjects with pain who failed to respond to MDD treatment.

CONCLUSIONS

Pain symptoms improved after rTMS to left DLPFC in MDD irrespective of age or gender, although the presence of chronic pain symptoms reduced the likelihood of treatment response. Individual PAF and baseline phase-coherence in the sensorimotor and midline regions may represent predictors of rTMS treatment outcome in comorbid pain and MDD.

Cognitive functioning as predictor and marker of response to repetitive transcranial magnetic stimulation in depressive disorders: A systematic review

OBJECTIVE

Cognitive performance in Major Depressive Disorder (MDD) is frequently impaired and related to functional outcomes. Repetitive Transcranial Magnetic Stimulation (rTMS) may exert its effects on MDD acting both on depressive symptoms and neurocognition. Furthermore, cognitive status could predict the therapeutic response of depressive symptoms to rTMS. However, cognitive performances as a predictor of rTMS response in MDD has not been thoroughly investigated. This review aims to evaluate the role of pre-treatment cognitive performance as a predictor of clinical response to rTMS, and the effects of rTMS on neurocognition in MDD.

METHOD

A systematic review of studies evaluating neurocognition in MDD as an outcome and/or predictor of response to rTMS was conducted using PubMed/Medline and Embase.

RESULTS

Fifty-eight articles were identified: 25 studies included neurocognition as a predictor of response to rTMS; 56 used cognitive evaluation as an outcome of rTMS. Baseline cognitive performance and cognitive improvements after rTMS predicted clinical response to rTMS. Moreover, rTMS improved cognition in MDD.

CONCLUSIONS

Cognitive assessment could predict improvement of depression in MDD patients undergoing rTMS and help selecting patients that could have beneficial effects from rTMS. A routine cognitive assessment might stratify MDD patients and track rTMS related cognitive improvement.

A polygenic-informed approach to a predictive EEG signature empowers antidepressant treatment prediction: A proof-of-concept study

The treatment of major depressive disorder (MDD) is hampered by low chances of treatment response in each treatment step, which is partly due to a lack of firmly established outcome-predictive biomarkers. Here, we hypothesize that polygenic-informed EEG signatures may help predict antidepressant treatment response. Using a polygenic-informed electroencephalography (EEG) data-driven, data-reduction approach, we identify a brain network in a large cohort (N=1,123), and discover it is sex-specifically (male patients, N=617) associated with polygenic risk score (PRS) of antidepressant response. Subsequently, we demonstrate in three independent datasets the utility of the network in predicting response to antidepressant medication (male, N=232) as well as repetitive transcranial magnetic stimulation (rTMS) and concurrent psychotherapy (male, N=95). This network significantly improves a treatment response prediction model with age and baseline severity data (area under the curve, AUC=0.623 for medicaton; AUC=0.719 for rTMS). A predictive model for MDD patients, aimed at increasing the likelihood of being a responder to antidepressants or rTMS and concurrent psychotherapy based on only this network, yields a positive predictive value (PPV) of 69% for medication and 77% for rTMS. Finally, blinded out-of-sample validation of the network as predictor for psychotherapy response in another independent dataset (male, N=50) results in a within-subsample response rate of 50% (improvement of 56%). Overall, the findings provide a first proof-of-concept of a combined genetic and neurophysiological approach in the search for clinically-relevant biomarkers in psychiatric disorders, and should encourage researchers to incorporate genetic information, such as PRS, in their search for clinically relevant neuroimaging biomarkers.

Response to TMS treatment for depression associated with higher levels of psychological well-being

Treatment resistant depression (TRD) is a complex condition associated with a great deal of disability and suffering. The relationship between TRD and psychological well-being (PWB) appears to be more complex than a simple antithesis. Transcranial magnetic stimulation (TMS) is a well-tolerated treatment for TRD. However successful, a drawback for TMS is that it has a lack of predictive biomarkers for treatment response. Our study focuses on the relationship between PWB and treatment resistant depression, and how PWB relates to TMS treatment response. We hypothesized that TMS treatment responders would have higher levels of PWB at baseline. In this study of 21 patients with TRD, we used the Ryff Scales of Psychological Well-Being and Patient Health Questionnaire-9 (PHQ-9). We found a significant relationship between environmental mastery, purpose in life, self-acceptance, and total PWB with baseline depression but no significant correlation between autonomy, personal growth, and positive relations with others and baseline PHQ-9 scores. No Ryff domain of PWB significantly predicted change in PHQ-9 score. Interestingly, however, we found that TMS responders had higher levels of autonomy (M(SD) = 62.10(10.46), p = 0.022) and personal growth (M(SD) = 65.00(11.04), p = 0.007) than non-responders at baseline. These specific aspects of well-being appear to be distinct from depression and particularly important in treatment response. This discovery suggests that assessing PWB might prove clinically useful when assessing future candidates for TMS treatment of TRD. Further research is necessary to evaluate the effects of TMS on PWB since these may be distinct from its effect on depression symptomology.

Therapeutic efficacy of connectivity-directed transcranial magnetic stimulation on anticipatory anhedonia

BACKGROUND

There are currently no effective treatments specifically targeting anticipatory anhedonia, a major symptom of severe depression which is associated with poor outcomes. The present study investigated the efficacy of individualized repetitive transcranial magnetic stimulation (rTMS) targeting the left dorsolateral prefrontal cortex (lDLPFC)-nucleus accumbens (NAcc) network on anticipatory anhedonia in depression.

METHODS

This randomized, double-blind, sham-controlled clinical trial (NCT03991572) enrolled 56 depression patients with anhedonia symptoms. Each participant received 15 once-daily sessions of rTMS at 10 Hz and 100% motor threshold. Stimulation was localized to the site of strongest IDLPFC-NAcc connectivity by functional magnetic resonance imaging. The Hamilton depression rating scale (HAMD) was used to measure depression severity, the temporal experience pleasure scale (TEPS) to measure anticipatory and consummatory anhedonia to specifically measure anticipatory/motivational anhedonia. Event-related potentials during the monetary incentive delay (MID) task were recorded to evaluate the electrophysiological correlates of reward anticipation and response.

RESULTS

Patients in the Real group showed significant improvements in anticipatory anhedonia and general depression symptoms posttreatment compared to the Sham group. The Real group also demonstrated more positive going cue-N2 and cue-P3 amplitude during MID reward trials after treatment. The change in cue-P3 posttreatment was positive correlated with improved TEPS-anti score.

CONCLUSION

Individualized rTMS of the lDLPFC-NAcc network can effectively alleviate anticipatory anhedonia and improved the reward seeking as evidenced by enhanced MID behavioral performance and more positive going cue-N2 and cue-P3. The lDLPFC-NAcc network plays a critical role in anticipatory reward and motivation processing.

Effects of transcranial magnetic stimulation on anhedonia in treatment resistant major depressive disorder

BACKGROUND

Anhedonia is one of the defining features of depression but it remains difficult to target and treat. Transcranial magnetic stimulation (TMS) is a proven treatment for depression, but its effects on anhedonia and whether anhedonia can be used as a predictive biomarker of response is not well known.

METHODS

Snaith-Hamilton Pleasure Scale was administered to patients with depression before and after a standard course of TMS in a naturalistic outpatient setting.

RESULTS

144 patients were analyzed. There was an overall significant improvement in anhedonia from pre- to post-treatment (7.69 ± 3.88 vs. 2.96 ± 3.45; p < .001). Significant correlations between improvements in anhedonia and other depressive symptoms were present (r = 0.55, p < .001). Logistic regression revealed that baseline anhedonia severity was not a significant predictor of clinical outcome.

CONCLUSION

This is the first large, naturalistic study examining the effects of standard, non-research TMS on anhedonia. Among depressed patients, TMS resulted in significant improvements in anhedonia. Patients with severe baseline anhedonia had an equal chance of achieving clinical response/remission. Patients with anhedonia should not be excluded from treatment if they are safe for outpatient care and otherwise appropriate candidates for treatment.

Dorsomedial prefrontal theta burst stimulation to treat anhedonia, avolition, and blunted affect in schizophrenia or depression - a randomized controlled trial

BACKGROUND

Intermittent theta burst stimulation (iTBS) over the dorsomedial prefrontal cortex (DMPFC) has shown promise in open-label trials of depression.

METHODS

In this randomized, double-blind, sham controlled trial we evaluate iTBS over the DMPFC for anhedonia, avolition, and blunted affect in patients with schizophrenia or depression. Active iTBS was delivered over the DMPFC with 1200 pulses per session, twice daily over ten weekdays at target intensity with an angled figure-of eight coil. Sham condition comprised the magnetically shielded side of the coil and simultaneous transcutaneous electrical nerve stimulation. Primary outcome was change on the Clinical Assessment Interview for Negative Symptoms (CAINS).

RESULTS

Twenty-eight patients were randomized to active iTBS and 28 to sham. Mean (standard deviation) change in CAINS score from baseline to the day after last treatment was -5.3 (8.1) in active iTBS and -2.1 (7.1) in sham. A linear model showed no significant effect of treatment, accounting for baseline scores p=.088. Sub analyses per diagnostic group showed a significant effect in patients with depression, p=.038, but not in the schizophrenia group, p=.850. However, overall depressive symptoms did not change significantly in patients with depression. There were three serious adverse events, all in the sham group.

LIMITATIONS

Possibly too short treatment course and few patients with schizophrenia.

CONCLUSION

In this first transdiagnostic randomized controlled trial of iTBS over DMPFC for anhedonia, avolition, and blunted affect it can be concluded that it was generally tolerable and safe but only more effective than sham in the subgroup of patients with depression.

Left handedness and response to repetitive transcranial magnetic stimulation in major depressive disorder

OBJECTIVES

Considerable research has demonstrated the efficacy of repetitive transcranial magnetic stimulation treatment (rTMS) in patients with major depressive disorder (MDD) with differences in effects related to laterality of stimulation. However, no systematic research has explored whether left-handed subjects respond in the same way as right-handed subjects.

METHODS

Data from 6 clinical trials (n = 310) were pooled and we explored whether left-handed patients with MDD responded in a similar manner to rTMS, including how they responded to both high-frequency left and low-frequency right-sided forms of treatment.

RESULTS

Overall, patients with MDD who were left-handed responded to a greater degree than right-handed patients to rTMS therapy. On subgroup analysis, notably limited by small numbers in the left handed groups, this effect was seen with high-frequency left-sided treatment but not with low-frequency right-sided treatment. The overall effect of a greater response in left-handed patients was not attributable to other clinical or study variables.

CONCLUSIONS

Standard forms of rTMS treatment appear to be effective in patients with MDD who are left-handed and there seems no justification for modifying the laterality of treatment application in these patients.

Repetitive transcranial magnetic stimulation treatment for peripartum depression: systematic review & meta-analysis

Background

Peripartum depression is a common disorder with very high potential hazards for both the patients and their babies. The typical treatment options include antidepressants and electroconvulsive therapy. However, these treatments do not ensure the safety of the fetus. Recently, repetitive transcranial magnetic stimulation has emerged as a promising treatment for neuropathies as well as depression. Nevertheless, many studies excluded pregnant women. This systematic review was conducted to confirm whether repetitive transcranial magnetic stimulation was a suitable treatment option for peripartum depression.

Methods

We performed a systematic review that followed the PRISMA guidelines. We searched for studies in the MEDLINE, PsycINFO, EMBASE, and Cochrane library databases published until the end of September 2020. Eleven studies were selected for the systematic review, and five studies were selected for quantitative synthesis. Data analysis was conducted using Comprehensive Meta-Analysis 3 software. The effect size was analyzed using the standardized mean difference, and the 95% confidence interval (CI) was determined by the generic inverse variance estimation method.

Results

The therapeutic effect size of repetitive transcranial magnetic stimulation for peripartum depression was 1.394 (95% CI: 0.944–1.843), and the sensitivity analysis effect size was 1.074 (95% CI: 0.689–1.459), indicating a significant effect. The side effect size of repetitive transcranial magnetic stimulation for peripartum depression was 0.346 (95% CI: 0.214–0.506), a meaningful result. There were no severe side effects to the mothers or fetuses.

Conclusions

From various perspectives, repetitive transcranial magnetic stimulation can be considered an alternative treatment to treat peripartum depression to avoid exposure of fetuses to drugs and the severe side effects of electroconvulsive therapy. Further research is required to increase confidence in the results.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-021-03600-3.

Unchanged Cognitive Performance and Concurrent Prefrontal Blood Oxygenation After Accelerated Intermittent Theta-Burst Stimulation in Depression: A Sham-Controlled Study

Aim: Intermittent theta-burst stimulation (iTBS) delivered over the dorsomedial prefrontal cortex (DMPFC) has shown promise as a treatment for anhedonia and amotivation in patients with depression. Here, we investigated whether this protocol modulates cognitive performance and concurrent prefrontal blood oxygenation. We also examined whether depressed patients exhibit cognitive dysfunction and prefrontal hypoactivity at baseline compared to healthy controls. Methods: This sham-controlled study comprises 52 patients randomized to either active or sham accelerated iTBS over the DMPFC (applied twice daily) for 10 consecutive treatment days, and 55 healthy controls. Cognitive performance was assessed at baseline and once again 4 weeks later using a cognitive test battery targeting attention, inhibitory control, and numerical, verbal, and visual working memory. Concurrent prefrontal oxygenated hemoglobin (oxy-Hb) was captured with functional near-infrared spectroscopy. Results: Active iTBS over DMPFC did not affect cognitive performance or concurrent oxy-Hb change compared to sham iTBS in patients with depression. Compared to controls, patients at baseline showed impaired performance in the Trail Making Test, the Rey Auditory Verbal Learning Test, the Animal Naming Test, and the Digit Symbol Substitution Test, however no difference in prefrontal oxy-Hb was observed. Conclusion: Patients with treatment-resistant depression displayed cognitive deficits, however without prefrontal hypoactivity, compared to healthy controls at baseline. iTBS treatment did not alter cognitive performance, nor concurrent prefrontal blood oxygenation, in patients. Taken together, iTBS can likely be considered a cognitively safe treatment option in this sample of patients.

Impact of personality on acoustic tinnitus suppression and emotional reaction to stimuli sounds

BACKGROUND

Acoustic stimulation was shown to be effective in short-term suppression of tinnitus. However, tinnitus cannot be suppressed in all patients. Recent insights from mental health research suggests that personality traits may be important factors in prediction of treatment outcomes or improvement of tinnitus over time. No previous acoustic stimulation study investigated the effects of personality traits on tinnitus suppression and rating of sound stimuli.

OBJECTIVES

The aim of this study was therefore to examine whether personality is capable to predict tinnitus suppression in chronic tinnitus patients as well as related emotional stimulus evaluation.

METHODS

Personality data (Big Five Index 2; BFI-2) of two acoustic stimulation experiments were pooled for this analysis. Both experiments were conducted at the University of Regensburg, Germany in the time period between April 2018 and October 2019 and consisted of individual designed noise and amplitude modulated tones matched to the participants' tinnitus pitch. Logistic regressions or linear mixed effect models were performed with tinnitus suppression as well as valence and arousal data as dependent variables and BFI-2 personality dimensions as predictors.

RESULTS

28% of the participants showed pronounced short-term tinnitus suppression after acoustic stimulation (50% reduction in subjective tinnitus loudness). Analyzing BFI-2 data, no significant impact of the big five personality traits (neuroticism, agreeableness, extraversion, conscientiousness, openness) were found, neither on acoustic tinnitus suppression, nor on emotional stimulus evaluation, namely arousal.

CONCLUSION

Personality was not shown to be a predictive factor, neither for acoustic stimulation, nor for emotional reaction to stimuli sounds in our studies. However, since tinnitus cannot be suppressed by acoustic stimulation in all patients, future studies should investigate other explaining factors such as patient-related or (neuro)physiological characteristics.

Predictors of remission after repetitive transcranial magnetic stimulation for the treatment of major depressive disorder: An analysis from the randomised non-inferiority THREE-D trial

BACKGROUND

Although repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for major depressive disorder (MDD), treatment selection is still mainly a process of trial-and-error. The present study aimed to identify clinical predictors of remission after a course of rTMS delivered to the left DLPFC to improve patient selection.

METHODS

Data from a large randomised non-inferiority trial comparing standard 10 Hz and intermittent theta burst stimulation (iTBS) for the treatment of MDD were used for the exploratory analyses. Individual variables were assessed for their association with remission and then included in a logistic regression model to determine odds ratios (OR) and corresponding 95% confidence intervals. Model discrimination (internal validation) was carried out to assess model optimism using the c-index. ClinicalTrials.gov identifier: NCT01887782.

FINDINGS

388 subjects were included in the analysis (199-iTBS and 189-10 Hz, respectively). Higher baseline severity of both depressive and anxiety symptoms were associated with a lower chance of achieving remission (OR=0.64, 95% CI 0.46-0.88; and 0.78, 95% CI 0·60-0.98, respectively). Current employment was a positive predictor for remission (OR=1.69, 95% CI 1.06-2.7), while greater number of treatment failures was associated with lower odds of achieving remission (OR=0.51, 95% CI 0.27-0.98). A non-linear effect of age and remission was observed. An analysis to allow an estimate of the probability of remission using all variables was assessed. The c-index for the fitted model was 0.687.

INTERPRETATION

Our results suggest that measuring depression symptom severity, employment status, and refractoriness are important in prognosticating outcome to a course of rTMS in MDD.

FUNDING

Canadian Institutes of Health Research MOP-136801.