The prefrontal cortex influence over subcortical and limbic regions governs antidepressant response by N=H/(M+R)

Assessing the Dose-Dependent Effects of tDCS on Neurometabolites using Magnetic Resonance Spectroscopy

Concurrent transcranial direct current stimulation (tDCS) and proton Magnetic Resonance Spectroscopy ( ¹ H MRS) experiments have shown up- or downregulation of neurotransmitter concentration. However, effects have been modest applying mostly lower current doses and not all studies found significant effects. Dose of stimulation might be an important variable in eliciting a consistent response. To investigate dose effects of tDCS on neurometabolites, we placed an electrode over the left supraorbital region (with a return electrode over the right mastoid bone) and utilized an MRS voxel (3x3x3cm) that was centered over the anterior cingulate/inferior mesial prefrontal region which is in the path of the current distribution. We conducted 5 epochs of acquisition, each one with a 9:18min acquisition time, and applied tDCS in the third epoch. We observed significant dose and polarity dependent modulation of GABA and to a lesser degree of Glutamine/Glutamate (GLX) with the highest and reliable changes seen with the highest current dose, 5mA (current density 0.39 mA/cm ² ), during and after the stimulation epoch compared with pre-stimulation baselines. The strong effect on GABA concentration (achieving a mean change of 63% from baseline, more than twice as much as reported with lower doses of stimulation) establishes tDCS-dose as an important parameter in eliciting a regional brain engagement and response. Furthermore, our experimental design in examining tDCS parameters and effects using shorter epochs of acquisitions might constitute a framework to explore the tDCS parameter space further and establish measures of regional engagement by non-invasive brain-stimulation.

Is the Antidepressant Activity of Selective Serotonin Reuptake Inhibitors Mediated by Nicotinic Acetylcholine Receptors?

It is generally assumed that selective serotonin reuptake inhibitors (SSRIs) induce antidepressant activity by inhibiting serotonin (5-HT) reuptake transporters, thus elevating synaptic 5-HT levels and, finally, ameliorates depression symptoms. New evidence indicates that SSRIs may also modulate other neurotransmitter systems by inhibiting neuronal nicotinic acetylcholine receptors (nAChRs), which are recognized as important in mood regulation. There is a clear and strong association between major depression and smoking, where depressed patients smoke twice as much as the normal population. However, SSRIs are not efficient for smoking cessation therapy. In patients with major depressive disorder, there is a lower availability of functional nAChRs, although their amount is not altered, which is possibly caused by higher endogenous ACh levels, which consequently induce nAChR desensitization. Other neurotransmitter systems have also emerged as possible targets for SSRIs. Studies on dorsal raphe nucleus serotoninergic neurons support the concept that SSRI-induced nAChR inhibition decreases the glutamatergic hyperstimulation observed in stress conditions, which compensates the excessive 5-HT overflow in these neurons and, consequently, ameliorates depression symptoms. At the molecular level, SSRIs inhibit different nAChR subtypes by noncompetitive mechanisms, including ion channel blockade and induction of receptor desensitization, whereas α9α10 nAChRs, which are peripherally expressed and not directly involved in depression, are inhibited by competitive mechanisms. According to the functional and structural results, SSRIs bind within the nAChR ion channel at high-affinity sites that are spread out between serine and valine rings. In conclusion, SSRI-induced inhibition of a variety of nAChRs expressed in different neurotransmitter systems widens the complexity by which these antidepressants may act clinically.

Experimental Therapeutics in Treatment-Resistant Major Depressive Disorder

Treatment-Resistant Depression (TRD) patients remain a challenging sub-division of patients with Major Depressive Disorder (MDD) in day to day clinical practice. As with any diagnostic condition, comprehensive evaluation, exclusion of other psychiatric conditions, assessment of co-morbid medical and psychiatric illnesses and psychosocial stressors are the keys to appropriate diagnosis and subsequent management. There are various management options available for the treatment of MDD, however, about 30% of the patients fail to achieve full remission of symptoms despite multiple trials and belong to this sub-category of MDD. This article brings forth discussion of other non-conventional medication and non-medication treatment alternatives that merit exploration of their efficacy in TRD. Many of the proposed novel medications and other treatment modalities such as Deep Brain Stimulation, exercise, yoga are already used for other medical and psychiatric disorders and have some evidence suggesting their potential benefits in TRD in conjunction with conventional medications or even as monotherapy. Nevertheless, more research is needed in this direction to establish effectiveness.

Connectome-based models can predict early symptom improvement in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a debilitating mental illness with more than 50% of patients not achieving an adequate response using first-line treatments. Reliable models that predict antidepressant treatment outcome are needed to guide clinical decision making. We aimed to build predictive models of treatment improvement for MDD patients using machine learning approaches based on fMRI resting-state functional connectivity patterns.

METHODS

Resting-state fMRI data were acquired from 192 untreated MDD patients at recruitment, and their severity of depression was assessed by Hamilton Rating Scale for Depression (HAMD) at baseline. Patients were given medication after the initial MR scan and their symptoms were monitored through HAMD for a period of six months. Connectome-based predictive modeling (CPM) algorithms were implemented to predict the improvement in HAMD score at one month from resting-state connectivity at baseline. Additionally, by selectively combining the features from all leave-one-out iterations in the model building stage, we created a consensus model that could be generalized to predict improvement in HAMD score in samples of non-overlapping subjects at different time points.

RESULTS

Using baseline functional connectivity, CPM successfully predicted symptom improvement of depression at one month. In addition, a consensus 'MDD improvement model' could predict symptom improvement for novel individuals at the two-week, one-month, two-month and three-month time points after antidepressant treatment.

CONCLUSIONS

Individual pre-treatment functional brain networks contain meaningful information that can be gleaned to build predictors of treatment outcome. The identified MDD improvement networks could be an appropriate biomarker for predicting individual therapeutic response of antidepressant treatment. Replication and validation using other large datasets will be a key next step before these models can be used in clinical practice.

Dorsolateral Prefrontal Cortex and Subcallosal Cingulate Connectivity Show Preferential Antidepressant Response in Major Depressive Disorder

BACKGROUND

Major depressive disorder is associated with abnormal connectivity across emotion and reward circuits as well as other established circuits that may negatively impact treatment response. The goal of this study was to perform an exploratory reanalysis of archival data from a clinical trial to identify moderators of treatment outcome of sertraline over placebo.

METHODS

EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study participants completed magnetic resonance imaging before randomization to either sertraline or placebo for 8 weeks (n = 279). Seed-based functional connectivity was computed using 4 bilateral seeds (2 spheres defined bilaterally): amygdala, dorsolateral prefrontal cortex (DLPFC), subcallosal cingulate cortex, and ventral striatum. Functional connectivity maps were generated, principal component analysis was performed, linear mixed effects models were used to determine moderators of treatment outcome, and post hoc analyses were used to determine level of connectivity (low and high, -1 and +1 SD from the mean) that was most sensitive to improved depression severity (baseline to week 8) based on treatment.

RESULTS

Greater mean reduction in the 17-item Hamilton Rating Scale for Depression score by 8 weeks occurred with sertraline relative to placebo when connectivity in the DLPFC was low (3-way interaction test, p = .05). Conditional on low connectivity in the DLPFC and subcallosal cingulate cortex and high connectivity in the ventral striatum and amygdala, there was on average a 4.8-point greater reduction in the 17-item Hamilton Rating Scale for Depression score with sertraline relative to placebo (p = .003).

CONCLUSIONS

The level of functional connectivity seeded in both the DLPFC and the subcallosal cingulate cortex networks may play an important role in identifying a favorable response to sertraline over placebo.

Activity in the Ventral Medial Prefrontal Cortex Is Necessary for the Therapeutic Effects of Extinction in Rats

Poor response and high relapse rates remain problematic in the treatment of stress-related psychiatric disorders such as depression and post-traumatic stress disorder. Although mechanisms of pharmacotherapies are intensely studied, little is known about mechanisms of behavioral therapy that could inform improved treatments. We have previously demonstrated the therapeutic effects of extinction learning as a behavioral intervention modeling exposure therapy in rats. In the present study, we tested the hypothesis that activity in the ventral medial prefrontal cortex (vmPFC) during extinction is necessary for its therapeutic effects. The inhibitory Gi-coupled designer receptor exclusively activated by designer drug CaMKIIα-hM4Di was expressed in vmPFC before administering chronic unpredictable stress (CUS). vmPFC projection neurons were then inhibited during extinction treatment by administering clozapine-N-oxide. Coping behavior and cognitive flexibility were assessed 24 h later on the shock-probe defensive burying test and attentional set-shifting test, respectively. Replicating previous results, extinction reversed the CUS-induced deficits in coping behavior and cognitive flexibility. Inhibiting vmPFC during extinction blocked these therapeutic effects. Further, increasing vmPFC activity with the excitatory Gq-coupled designer receptor exclusively activated by designer drug hM3Dq 24 h before testing was sufficient to reverse the CUS-induced deficits. CUS reduced mPFC responsivity, assessed by measuring afferent-evoked field potentials in the mPFC, and this reduction was reversed by extinction treatment 24 h before testing. These results demonstrate the necessity of vmPFC activity in the therapeutic effects of extinction as a model of exposure therapy, and suggest that increased vmPFC activity induced by extinction is sufficient to produce lasting plastic changes that underlie its beneficial effects.SIGNIFICANCE STATEMENT Stress-related psychiatric disorders remain poorly treated. Psychotherapies can be effective, but their mechanisms remain unknown, hindering progress toward improved treatment. We used a rat model of behavioral therapy to identify potential targets for enhancing treatment. Fear extinction as a therapeutic behavioral intervention reversed stress-induced cognitive dysfunction and passive coping in rats, modeling components of stress-related psychiatric disease. Extinction also reversed stress-induced attenuation of mPFC responsivity. The therapeutic effects were prevented by blocking activity of glutamatergic neurons in the mPFC during extinction, and were mimicked by inducing activity in lieu of extinction. Thus, activity and plasticity in the mPFC underlie the beneficial effects of extinction on cognitive flexibility and coping behavior compromised by stress, and could be targets to enhance behavioral therapy.

Functional Connectivity of the Subcallosal Cingulate Cortex And Differential Outcomes to Treatment With Cognitive-Behavioral Therapy or Antidepressant Medication for Major Depressive Disorder

OBJECTIVE

The purpose of this article was to inform the first-line treatment choice between cognitive-behavioral therapy (CBT) or an antidepressant medication for treatment-naive adults with major depressive disorder by defining a neuroimaging biomarker that differentially identifies the outcomes of remission and treatment failure to these interventions.

METHOD

Functional MRI resting-state functional connectivity analyses using a bilateral subcallosal cingulate cortex (SCC) seed was applied to 122 patients from the Prediction of Remission to Individual and Combined Treatments (PReDICT) study who completed 12 weeks of randomized treatment with CBT or antidepressant medication. Of the 122 participants, 58 achieved remission (Hamilton Depression Rating Scale [HAM-D] score ≤7 at weeks 10 and 12), and 24 had treatment failure (<30% decrease from baseline in HAM-D score). A 2×2 analysis of variance using voxel-wise subsampling permutation tests compared the interaction of treatment and outcome. Receiver operating characteristic curves constructed using brain connectivity measures were used to determine possible classification rates for differential treatment outcomes.

RESULTS

The resting-state functional connectivity of the following three regions with the SCC was differentially associated with outcomes of remission and treatment failure to CBT and antidepressant medication and survived application of the subsample permutation tests: the left anterior ventrolateral prefrontal cortex/insula, the dorsal midbrain, and the left ventromedial prefrontal cortex. Using the summed SCC functional connectivity scores for these three regions, overall classification rates of 72%-78% for remission and 75%-89% for treatment failure was demonstrated. Positive summed functional connectivity was associated with remission with CBT and treatment failure with medication, whereas negative summed functional connectivity scores were associated with remission to medication and treatment failure with CBT.

CONCLUSIONS

Imaging-based depression subtypes defined using resting-state functional connectivity differentially identified an individual's probability of remission or treatment failure with first-line treatment options for major depression. This biomarker should be explored in future research through prospective testing and as a component of multivariate treatment prediction models.

Posttraumatic stress disorder increases sensitivity to long term losses among patients with major depressive disorder

BACKGROUND

Decisions under risk and with outcomes that are delayed in time are ubiquitous in real life and can have a significant impact on the health and wealth of the decision-maker. Despite its potential relevance for real-world choices, the degree of aberrant risky and intertemporal decision-making in patients suffering from major depressive disorder (MDD) and posttraumatic stress disorder (PTSD) has received little attention to date.

METHOD

We used a case-control design to compare decision-making in healthy control subjects (N=16) versus untreated depressed subjects in a current major depressive episode (N=20). In order to examine how major depressive disorder (MDD) may impact decision-making, subjects made decisions over (1) risky outcomes and (2) delayed outcomes in the domain of gains and losses using choice paradigms from neuroeconomics. In a pre-planned analysis, depressed subjects were subdivided into those with primary PTSD along with comorbid MDD (MDD+PTSD) versus those with primary MDD without PTSD (MDD-only). Choice behavior was modeled via a standard econometric model of intertemporal choice, a quasi-hyperbolic temporal discounting function, which was estimated for each subject group separately.

RESULTS

Under conditions of potential gain, depressed subjects demonstrated greater discounting for gains across all time frames compared to controls. In the realm of losses, both subgroups of depressed subjects discounted more steeply than controls for short time frames. However, for delayed losses ranging from >1-10 years, MDD+PTSD subjects showed shallower discounting rates relative to MDD-only subjects, who continued to discount future losses steeply. Risk attitudes did not contribute to differences in intertemporal choice.

CONCLUSIONS

Depressed patients make choices that minimize current pain and maximize current reward, despite severe later consequences or lost opportunities. Anxiety associated with PTSD may serve as a partially protective factor in decision-making about long-term potential losses compared to MDD patients without PTSD.

Vestibular insights into cognition and psychiatry

The vestibular system has traditionally been thought of as a balance apparatus; however, accumulating research suggests an association between vestibular function and psychiatric and cognitive symptoms, even when balance is measurably unaffected. There are several brain regions that are implicated in both vestibular pathways and psychiatric disorders. The present review examines the anatomical associations between the vestibular system and various psychiatric disorders. Despite the lack of direct evidence for vestibular pathology in the key psychiatric disorders selected for this review, there is a substantial body of literature implicating the vestibular system in each of the selected psychiatric disorders. The second part of this review provides complimentary evidence showing the link between vestibular dysfunction and vestibular stimulation upon cognitive and psychiatric symptoms. In summary, emerging research suggests the vestibular system can be considered a potential window for exploring brain function beyond that of maintenance of balance, and into areas of cognitive, affective and psychiatric symptomology. Given the paucity of biological and diagnostic markers in psychiatry, novel avenues to explore brain function in psychiatric disorders are of particular interest and warrant further exploration.