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Using functional MRI in a large multisite sample of more that 1,000 patients, four distinct neurophysiological biotypes of depression are defined. These biotypes are used to develop diagnostic classifiers that distinguish patients with depression from controls in separate multisite validation and replication cohorts, and can predict patient responsiveness to therapy. Biomarkers have transformed modern medicine but remain largely elusive in psychiatry, partly because there is a weak correspondence between diagnostic labels and their neurobiological substrates. Like other neuropsychiatric disorders, depression is not a unitary disease, but rather a heterogeneous syndrome that encompasses varied, co-occurring symptoms and divergent responses to treatment. By using functional magnetic resonance imaging (fMRI) in a large multisite sample ( n = 1,188), we show here that patients with depression can be subdivided into four neurophysiological subtypes ('biotypes') defined by distinct patterns of dysfunctional connectivity in limbic and frontostriatal networks. Clustering patients on this basis enabled the development of diagnostic classifiers (biomarkers) with high (82–93%) sensitivity and specificity for depression subtypes in multisite validation ( n = 711) and out-of-sample replication ( n = 477) data sets. These biotypes cannot be differentiated solely on the basis of clinical features, but they are associated with differing clinical-symptom profiles. They also predict responsiveness to transcranial magnetic stimulation therapy ( n = 154). Our results define novel subtypes of depression that transcend current diagnostic boundaries and may be useful for identifying the individuals who are most likely to benefit from targeted neurostimulation therapies.

Despite its high toll on society, there has been little recent improvement in treatment efficacy for major depressive disorder (MDD). The identification of biological markers of successful treatment response may allow for more personalized and effective treatment. Here we investigate whether resting-state functional connectivity predicted response to treatment with repetitive transcranial magnetic stimulation (rTMS) to dorsomedial prefrontal cortex (dmPFC). Twenty-five individuals with treatment-refractory MDD underwent a 4-week course of dmPFC-rTMS. Before and after treatment, subjects received resting-state functional MRI scans and assessments of depressive symptoms using the Hamilton Depresssion Rating Scale (HAMD17). We found that higher baseline cortico-cortical connectivity (dmPFC-subgenual cingulate and subgenual cingulate to dorsolateral PFC) and lower cortico-thalamic, cortico-striatal, and cortico-limbic connectivity were associated with better treatment outcomes. We also investigated how changes in connectivity over the course of treatment related to improvements in HAMD17 scores. We found that successful treatment was associated with increased dmPFC-thalamic connectivity and decreased subgenual cingulate cortex-caudate connectivity, Our findings provide insight into which individuals might respond to rTMS treatment and the mechanisms through which these treatments work.

Multiple structural and functional neuroimaging measures vary over the course of the lifespan and can be used to predict chronological age. Accelerated brain aging, as quantified by deviations in the MRI-based predicted age with respect to chronological age, is associated with risk for neurodegenerative conditions, bipolar disorder, and mortality. Whether age-related changes in resting-state functional connectivity are accelerated in major depressive disorder (MDD) is unknown, and, if so, it is unclear if these changes contribute to specific cognitive weaknesses that often occur in MDD. Here, we delineated age-related functional connectivity changes in a large sample of normal control subjects and tested whether brain aging is accelerated in MDD. Furthermore, we tested whether accelerated brain aging predicts individual differences in cognitive function. We trained a support vector regression model predicting age using resting-state functional connectivity in 710 healthy adults aged 18–89. We applied this model trained on normal aging subjects to a sample of actively depressed MDD participants (n = 109). The difference between predicted brain age and chronological age was 2.11 years greater (p = 0.015) in MDD patients compared to control participants. An older MDD brain age was significantly associated with increased impulsivity and, in males, increased depressive severity. Unexpectedly, accelerated brain aging was also associated with increased placebo response in a sham-controlled trial of high-frequency repetitive transcranial magnetic stimulation targeting the dorsomedial prefrontal cortex. Our results indicate that MDD is associated with accelerated brain aging, and that accelerated aging is selectively associated with greater impulsivity and depression severity.

Late-life depression (LLD) is a growing worldwide problem due to demographic changes, with limited treatment options due to high rates of pharmacotherapy adverse effects, accessibility of psychotherapy, and tolerability of electroconvulsive therapy. Novel neuromodulation techniques, such as repetitive transcranial magnetic stimulation (rTMS), may overcome these limitations. The objective of this study is to determine the efficacy, tolerability, and cognitive effects of high-dose deep rTMS in LLD. In this study we randomized older adults between 60 and 85 years old with major depressive disorder (MDD) to sham or active deep rTMS (H1 coil, 6012 pulses, 18 Hz, 120% of resting motor threshold) delivered over the dorsolateral and ventrolateral prefrontal cortex 5 days per week over 4 weeks. Our primary outcome was remission of depression in an intention-to-treat analysis. We also assessed change in cognitive functioning with rTMS treatment and tolerability based on adverse effects. Fifty-two participants were randomized to active (n = 25) or sham H1 coil (n = 27). Remission rate was significantly higher with active than sham rTMS (40.0% vs 14.8%) with a number needed to treat of 4.0 (95% CI: 2.1–56.5). There was no change on any measure of executive function and no serious adverse events. Adverse effect profiles were similar between active and sham rTMS, except for reports of pain being significantly more common in the active condition (16.0% vs 0%). High-dose deep rTMS appears to be safe, well tolerated, and efficacious in the treatment of LLD.

The neural substrates of depression may differ in men and women, but the underlying mechanisms are incompletely understood. Here, we show that depression is associated with sex-specific patterns of abnormal functional connectivity in the default mode network and in five regions of interest with sexually dimorphic transcriptional effects. Regional differences in gene expression in two independent datasets explained the neuroanatomical distribution of abnormal connectivity. These gene sets varied by sex and were strongly enriched for genes implicated in depression, synapse function, immune signaling, and neurodevelopment. In an independent sample, we confirmed the prediction that individual differences in default mode network connectivity are explained by inferred brain expression levels for six depression-related genes, including PCDH8 , a brain-specific protocadherin integral membrane protein implicated in activity-related synaptic reorganization. Together, our results delineate both shared and sex-specific changes in the organization of depression-related functional networks, with implications for biomarker development and fMRI-guided therapeutic neuromodulation. The neural substrates of depression may differ by sex. Here the authors show that depression is associated with distinct brain connectivity changes in men and in women that are explained by sex-specific transcriptomic signatures involving genes previously implicated in synapse function, immune signalling, and depression risk.

Repetitive transcranial magnetic stimulation (rTMS) is an evidence-based treatment for depression that is increasingly implemented in healthcare systems across the world. A new form of rTMS called intermittent theta burst stimulation (iTBS) can be delivered in 3 min and has demonstrated comparable effectiveness to the conventional 37.5 min 10Hz rTMS protocol in patients with depression. To compare the direct treatment costs per course and per remission for iTBS compared to 10Hz rTMS treatment in depression. We conducted a cost analysis from a healthcare system perspective using patient-level data from a large randomized non-inferiority trial (THREE-D). Depressed adults 18 to 65 received either 10Hz rTMS or iTBS treatment. Treatment costs were calculated using direct healthcare costs associated with equipment, coils, physician assessments and technician time over the course of treatment. Cost per remission was estimated using the proportion of patients achieving remission following treatment. Deterministic sensitivity analyses and non-parametric bootstrapping was used to estimate uncertainty. From a healthcare system perspective, the average cost per patient was USD$1,108 (SD 166) for a course of iTBS and $1,844 (SD 304) for 10Hz rTMS, with an incremental net savings of $735 (95% CI 688 to 783). The average cost per remission was $3,695 (SD 552) for iTBS and $6,146 (SD 1,015) for 10Hz rTMS, with an average incremental net savings of $2,451 (95% CI 2,293 to 2,610). The shorter session durations and treatment capacity increase associated with 3 min iTBS translate into significant cost-savings per patient and per remission when compared to 10Hz rTMS.

Electroconvulsive therapy (ECT) is effective for major depressive disorder (MDD) but its effects on memory limit its widespread use. Magnetic seizure therapy (MST) is a potential alternative to ECT that may not adversely affect memory. In the current trial, consecutive patients with MDD consented to receive MST applied over the prefrontal cortex according to an open-label protocol. Depressive symptoms and cognition were assessed prior to, during and at the end of treatment. Patients were treated two to three times per week with high-frequency MST (i.e., 100 Hz) (N = 24), medium frequency MST (i.e., 60 or 50 Hz) (N = 26), or low-frequency MST (i.e., 25 Hz MST) (N = 36) using 100% stimulator output. One hundred and forty patients were screened; 86 patients with MDD received a minimum of eight treatments and were deemed to have an adequate course of MST; and 47 completed the trial per protocol, either achieving remission (i.e., 24-item Hamilton Rating Scale for Depression score <10 and a relative reduction of >60% at two consecutive assessments; n = 17) or received a maximum of 24 sessions (n = 30). High-frequency (100 Hz) MST produced the highest remission rate (33.3%). Performance on most cognitive measures remained stable, with the exception of significantly worsened recall consistency of autobiographical information and significantly improved brief visuospatial memory task performance. Under open conditions, MST led to clinically meaningful reduction in depressive symptoms in patients with MDD and produced minimal cognitive impairment. Future studies should compare MST and ECT under double-blind randomized condition.

A growing body of research suggests that non-invasive electrical brain stimulation can more effectively modulate neural activity when phase-locked to the underlying brain rhythms. Transcranial alternating current stimulation (tACS) can potentially stimulate the brain in-phase to its natural oscillations as recorded by electroencephalography (EEG), but matching these oscillations is a challenging problem due to the complex and time-varying nature of the EEG signals. Here we address this challenge by developing and testing a novel approach intended to deliver tACS phase-locked to the activity of the underlying brain region in real-time. This novel approach extracts phase and frequency from a segment of EEG, then forecasts the signal to control the stimulation. A careful tuning of the EEG segment length and prediction horizon is required and has been investigated here for different EEG frequency bands. The algorithm was tested on EEG data from 5 healthy volunteers. Algorithm performance was quantified in terms of phase-locking values across a variety of EEG frequency bands. Phase-locking performance was found to be consistent across individuals and recording locations. With current parameters, the algorithm performs best when tracking oscillations in the alpha band (8-13 Hz), with a phase-locking value of 0.77 ± 0.08. Performance was maximized when the frequency band of interest had a dominant frequency that was stable over time. The algorithm performs faster, and provides better phase-locked stimulation, compared to other recently published algorithms devised for this purpose. The algorithm is suitable for use in future studies of phase-locked tACS in preclinical and clinical applications.

Non-invasive brain stimulation techniques are entering widespread use for the investigation and treatment of a range of neurological and neuropsychiatric disorders. However, most current techniques are 'open-loop', without feedback from target brain region activity; this limitation could contribute to heterogeneous effects seen for nominally 'inhibitory' and 'excitatory' protocols across individuals. More potent and consistent effects may ensue from closed-loop and, in particular, phase-locked brain stimulation. In this work, a closed-loop brain stimulation system is introduced that can analyze EEG data in real-time, provide a forecast of the phase of an underlying brain rhythm of interest, and control pulsed transcranial electromagnetic stimulation to deliver pulses at a specific phase of the target frequency band. The technique was implemented using readily available equipment such as a basic EEG system, a low-cost Arduino board and MATLAB scripts. The phase-locked brain stimulation method was tested in 5 healthy volunteers and its phase-locking performance evaluated at 0, 90, 180, and 270 degree phases in theta and alpha frequency bands. On average phase locking values of 0.55° ± 0.11° and 0.52° ± 0.14° and error angles of 11° ± 11° and 3.3° ± 18° were achieved for theta and alpha stimulation, respectively. Despite the low-cost hardware implementation, signal processing time generated a phase delay of only 3.8° for theta and 57° for alpha stimulation, both readily accommodated in the pulse trigger algorithm. This work lays the methodological steps for achieving phase-locked brain stimulation for brief-pulse transcranial electrical stimulation (tES) and repetitive transcranial magnetic stimulation (rTMS), facilitating further research on the effect of stimulation phase for these techniques.

ABSTRACTBackgroundRepetitive transcranial magnetic stimulation (rTMS) is an effective treatment for major depressive disorder (MDD), but substantial heterogeneity in outcomes remains. We examined a potential mechanism of action of rTMS to normalize individual variability in resting-state functional connectivity (rs-fc) before and after a course of treatment. MethodsVariability in rs-fc was examined in healthy controls (baseline) and individuals with MDD (baseline and after 4–6 weeks of rTMS). Seed-based connectivity was calculated to 4 regions associated with MDD: left dorsolateral prefrontal cortex (DLPFC), right subgenual anterior cingulate cortex (sgACC), bilateral insula, and bilateral precuneus. Individual variability was quantified for each region by calculating the mean correlational distance of connectivity maps relative to the healthy controls; a higher variability score indicated a more atypical/idiosyncratic connectivity pattern. ResultsWe included data from 66 healthy controls and 252 individuals with MDD in our analyses. Patients with MDD did not show significant differences in baseline variability of rs-fc compared with controls. Treatment with rTMS increased rs-fc variability from the right sgACC and precuneus, but the increased variability was not associated with clinical outcomes. Interestingly, higher baseline variability of the right sgACC was significantly associated with less clinical improvement ( p = 0.037, uncorrected; did not survive false discovery rate correction). Limitations: The linear model was constructed separately for each region of interest. ConclusionThis was, to our knowledge, the first study to examine individual variability of rs-fc related to rTMS in individuals with MDD. In contrast to our hypotheses, we found that rTMS increased the individual variability of rs-fc. Our results suggest that individual variability of the right sgACC and bilateral precuneus connectivity may be a potential mechanism of rTMS.