Neural and neuroendocrine predictors of pharmacological treatment response in adolescents with depression: A preliminary study

Seeing adolescents grow from many angles using a multilevel approach: A tribute to the contributions of Dante Cicchetti to the field of developmental psychopathology

Dante Cicchetti propelled forward the field of developmental psychopathology by advancing this framework and championing new methods, including emphasizing the central role that multilevel analysis holds for explicating pathways of risk and resilience. His work continues to change the face of existing science. It has also paved the way for the formation of new projects, like the Research Domain Criteria initiative. This paper uses our laboratory's work on multilevel approaches to studying adolescent depression, non-suicidal self-injury, and suicidal thoughts and behaviors to shine a spotlight on Dr Cicchetti's contributions. In addition, we review recent developments, ongoing challenges, and promising future directions within developmental psychopathology as we endeavor to carry on the tradition of growth in the field.

Neuroimaging for precision medicine in psychiatry

Although the lifetime burden due to mental disorders is increasing, we lack tools for more precise diagnosing and treating prevalent and disabling disorders such as major depressive disorder. We lack strategies for selecting among available treatments or expediting access to new treatment options. This critical review concentrates on functional neuroimaging as a modality of measurement for precision psychiatry, focusing on major depressive and anxiety disorders. We begin by outlining evidence for the use of functional neuroimaging to stratify the heterogeneity of these disorders, based on underlying circuit dysfunction. We then review the current landscape of how functional neuroimaging-derived circuit predictors can predict treatment outcomes and clinical trajectories in depression and anxiety. Future directions for advancing clinically appliable neuroimaging measures are considered. We conclude by considering the opportunities and challenges of translating neuroimaging measures into practice. As an illustration, we highlight one approach for quantifying brain circuit function at an individual level, which could serve as a model for clinical translation.

Effects of electroconvulsive therapy on cortical thickness in depression: a systematic review

OBJECTIVE

Electroconvulsive therapy (ECT) is one of the most studied and validated available treatments for severe or treatment-resistant depression. However, little is known about the neural mechanisms underlying ECT. This systematic review aims to critically review all structural magnetic resonance imaging studies investigating longitudinal cortical thickness (CT) changes after ECT in patients with unipolar or bipolar depression.

METHODS

We performed a search on PubMed, Medline, and Embase to identify all available studies published before April 20, 2023. A total of 10 studies were included.

RESULTS

The investigations showed widespread increases in CT after ECT in depressed patients, involving mainly the temporal, insular, and frontal regions. In five studies, CT increases in a non-overlapping set of brain areas correlated with the clinical efficacy of ECT. The small sample size, heterogeneity in terms of populations, comorbidities, and ECT protocols, and the lack of a control group in some investigations limit the generalisability of the results.

CONCLUSIONS

Our findings support the idea that ECT can increase CT in patients with unipolar and bipolar depression. It remains unclear whether these changes are related to the clinical response. Future larger studies with longer follow-up are warranted to thoroughly address the potential role of CT as a biomarker of clinical response after ECT.

Hippocampal and parahippocampal volume and function predict antidepressant response in patients with major depression: A multimodal neuroimaging study

BACKGROUND

For many patients with major depressive disorder (MDD) adequate treatment remains elusive. Neuroimaging techniques received attention for their potential use in guiding and predicting response, but were rarely investigated in real-world psychiatric settings.

AIMS

To identify structural and functional Magnetic Resonance Imaging (MRI) biomarkers associated with antidepressant response in a real-world clinical sample.

METHODS

We studied 100 MDD inpatients admitted to our psychiatric ward, treated with various antidepressants upon clinical need. Hamilton Depression Rating Scale percentage decrease from admission to discharge was used as a measure of response. All patients underwent 3.0 T MRI scanning. Grey matter (GM) volumes were investigated both in a voxel-based morphometry (VBM), and in a regions of interest (ROI) analysis. In a subsample of patients, functional resting-state connectivity patterns were also explored.

RESULTS

In the VBM analysis, worse response was associated to lower GM volumes in two clusters, encompassing the left hippocampus and parahippocampal gyrus, and the right superior and middle temporal gyrus. Investigating ROIs, lower bilateral hippocampi and amygdalae volumes predicted worse treatment outcomes. Functional connectivity in the right temporal and parahippocampal gyrus was also associated to response.

CONCLUSION

Our results expand existing literature on the relationship between the structure and function of several brain regions and treatment response in MDD. While we are still far from routine use of MRI biomarkers in clinical practice, we confirm a possible role of these techniques in guiding treatment choices and predicting their efficacy.

Influences of resting-state intrinsic functional brain connectivity on the antidepressant treatment response in late-life depression

BACKGROUND

Late-life depression (LLD) is characterized by differences in resting state functional connectivity within and between intrinsic functional networks. This study examined whether clinical improvement to antidepressant medications is associated with pre-randomization functional connectivity in intrinsic brain networks.

METHODS

Participants were 95 elders aged 60 years or older with major depressive disorder. After clinical assessments and baseline MRI, participants were randomized to escitalopram or placebo with a two-to-one allocation for 8 weeks. Non-remitting participants subsequently entered an 8-week trial of open-label bupropion. The main clinical outcome was depression severity measured by MADRS. Resting state functional connectivity was measured between a priori key seeds in the default mode (DMN), cognitive control, and limbic networks.

RESULTS

In primary analyses of blinded data, lower post-treatment MADRS score was associated with higher resting connectivity between: (a) posterior cingulate cortex (PCC) and left medial prefrontal cortex; (b) PCC and subgenual anterior cingulate cortex (ACC); (c) right medial PFC and subgenual ACC; (d) right orbitofrontal cortex and left hippocampus. Lower post-treatment MADRS was further associated with lower connectivity between: (e) the right orbitofrontal cortex and left amygdala; and (f) left dorsolateral PFC and left dorsal ACC. Secondary analyses associated mood improvement on escitalopram with anterior DMN hub connectivity. Exploratory analyses of the bupropion open-label trial associated improvement with subgenual ACC, frontal, and amygdala connectivity.

CONCLUSIONS

Response to antidepressants in LLD is related to connectivity in the DMN, cognitive control and limbic networks. Future work should focus on clinical markers of network connectivity informing prognosis.

REGISTRATION

ClinicalTrials.gov NCT02332291.

Changes of insular function in lifelong premature ejaculation patients before and after SSRI administration

OBJECTIVE

Lifelong premature ejaculation (PE) is regarded as one of the most common male sexual dysfunction. We aimed to detect whether insula-related brain functional networks are altered in lifelong PE patients and whether such alterations are "normalised" after selective serotonin reuptake inhibitors (SSRI) administration.

METHODS

Twenty-three drug-naive lifelong PE patients and 30 healthy controls (HC) were recruited in current study. All subjects underwent resting-state functional magnetic resonance imaging (fMRI) scan at first. One hour after dapoxetine administration, all patients underwent fMRI scanning again. The degree centrality (DC), amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) analysis, and ROI-based functional connectivity (FC) analysis were applied to calculate the abnormalities in insula-related functions among three groups.

RESULTS

Compared to HC group, PE patients at baseline showed significantly altered DC, ALFF, and ReHo value of the bilateral insula, which subsequently showed a "normalised" trend after dapoxetine administration. Additionally, compared to HC group, PE patients at baseline showed significantly decreased FC between insula and precentral gyrus, inferior frontal gyrus, middle/inferior temporal gyrus, and caudate, while patients after dapoxetine administration showed increased insula-related FC in anterior cingulate cortex and decreased FC in thalamus and middle/inferior temporal gyrus. The main effects of dapoxetine were located in precentral gyrus, inferior frontal gyrus, caudate, and limbic system.

CONCLUSIONS

Our findings report altered brain mechanism of insula in lifelong PE patients and also indicate that dapoxetine can "normalise" the abnormal function of the insula to certain extent in lifelong PE patients.

Structural and Functional Neural Correlates of Treatment Response for Interpersonal Psychotherapy for Depressed Adolescents

Precision medicine approaches hold tremendous promise to advance current clinical practice by providing information about which individuals will benefit from which treatments. This pilot study evaluated if baseline structure and function of the salience and emotion brain regions implicated in adolescent depression, specifically the amygdala and anterior cingulate cortex (ACC), predict response to Interpersonal Psychotherapy for Depressed Adolescents (IPT-A). Adolescents (n = 15; mean age = 14.5 (1.6); 80.0% female) diagnosed with a depressive disorder completed brain scans before the start of a 16 week trial of IPT-A. Clinical measures assessing depressive symptoms were completed before, during, and after a trial of therapy. Results show that at baseline, greater ACC activation in the context of an emotion-matching task and greater amygdala-ACC resting-state functional connectivity was related to greater improvement in depression symptoms. There was minimal evidence that brain structure predicted changes in depressive symptoms. The present study is the first to evaluate neural predictors of IPT-A response. While the results are preliminary, these findings suggest some avenues for future research to pursue in the hopes that more will benefit from treatment.

Intrinsic Connectivity Networks of Glutamate-Mediated Antidepressant Response: A Neuroimaging Review

Conventional monoamine-based pharmacotherapy, considered the first-line treatment for major depressive disorder (MDD), has several challenges, including high rates of non-response. To address these challenges, preclinical and clinical studies have sought to characterize antidepressant response through monoamine-independent mechanisms. One striking example is glutamate, the brain's foremost excitatory neurotransmitter: since the 1990s, studies have consistently reported altered levels of glutamate in MDD, as well as antidepressant effects following molecular targeting of glutamatergic receptors. Therapeutically, this has led to advances in the discovery, testing, and clinical application of a wide array of glutamatergic agents, particularly ketamine. Notably, ketamine has been demonstrated to rapidly improve mood symptoms, unlike monoamine-based interventions, and the neurobiological basis behind this rapid antidepressant response is under active investigation. Advances in brain imaging techniques, including functional magnetic resonance imaging, magnetic resonance spectroscopy, and positron emission tomography, enable the identification of the brain network-based characteristics distinguishing rapid glutamatergic modulation from the effect of slow-acting conventional monoamine-based pharmacology. Here, we review brain imaging studies that examine brain connectivity features associated with rapid antidepressant response in MDD patients treated with glutamatergic pharmacotherapies in contrast with patients treated with slow-acting monoamine-based treatments. Trends in recent brain imaging literature suggest that the activity of brain regions is organized into coherent functionally distinct networks, termed intrinsic connectivity networks (ICNs). We provide an overview of major ICNs implicated in depression and explore how treatment response following glutamatergic modulation alters functional connectivity of limbic, cognitive, and executive nodes within ICNs, with well-characterized anti-anhedonic effects and the enhancement of "top-down" executive control. Alterations within and between the core ICNs could potentially exert downstream effects on the nodes within other brain networks of relevance to MDD that are structurally and functionally interconnected through glutamatergic synapses. Understanding similarities and differences in brain ICNs features underlying treatment response will positively impact the trajectory and outcomes for adults suffering from MDD and will facilitate the development of biomarkers to enable glutamate-based precision therapeutics.

Effect of SSRIs on Resting-State Functional Brain Networks in Adolescents with Major Depressive Disorder

Investigation of brain changes in functional connectivity and functional network topology from receiving 8-week selective serotonin reuptake inhibitor (SSRI) treatments is conducted in 12 unmedicated adolescents with major depressive disorder (MDD) by using wavelet-filtered resting-state functional magnetic resonance imaging (fMRI). Changes are observed in frontal-limbic, temporal, and default mode networks. In particular, topological analysis shows, at the global scale and in the 0.12–0.25 Hz band, that the normalized clustering coefficient and smallworldness of brain networks decreased after treatment. Regional changes in clustering coefficient and efficiency were observed in the bilateral caudal middle frontal gyrus, rostral middle frontal gyrus, superior temporal gyrus, left pars triangularis, putamen, and right superior frontal gyrus. Furthermore, changes of nodal centrality and changes of connectivity associated with these frontal and temporal regions confirm the global topological alternations. Moreover, frequency dependence is observed from FDR-controlled subnetworks for the limbic-cortical connectivity change. In the high-frequency band, the altered connections involve mostly frontal regions, while the altered connections in the low-frequency bands spread to parietal and temporal areas. Due to the limitation of small sample sizes and lack of placebo control, these preliminary findings require confirmation with future work using larger samples. Confirmation of biomarkers associated with treatment could suggest potential avenues for clinical applications such as tracking treatment response and neurobiologically informed treatment optimization.

The knowns and unknowns of SSRI treatment in young people with depression and anxiety: efficacy, predictors, and mechanisms of action

The use of SSRIs for the treatment of depression and anxiety in young people is increasing. However, the effects of SSRIs in adolescence, a time when there are substantial changes in neural, cognitive, and social functioning, are not well understood. Here, we review evidence from clinical trials about the benefits and risks of SSRIs in young people and consider their mechanisms of action, as shown through human experimental work and animal models. We emphasise key outstanding questions about the effects of SSRIs in youth, identified through gaps in the literature and in consultation with young people with lived experience. It is crucial to characterise the mechanisms underpinning risks and benefits of SSRIs in this age group to progress the field, and to narrow the chasm between the widespread use of SSRIs in youth and the science on which this use is based.

Acute Diallyl Disulfide Administration Prevents and Reveres Lipopolysaccharide-Induced Depression-Like Behaviors in Mice via Regulating Neuroinflammation and Oxido-Nitrosative Stress

Neuroinflammation and oxidative stress play critical roles in pathogenesis of depression. Diallyl disulfide (DADS), an active compound in garlic oil, has been shown to exhibit obvious anti-inflammatory and anti-oxidative activities. Preliminary evidence indicates that depression is associated with high levels of pro-inflammatory cytokines and oxidative markers, suggesting that inhibition of neuroinflammatory response and oxidative stress may be beneficial for depression interruption. Here, we investigated the antidepressant effect of DADS as well as it mechanisms in a depression-like model induced by lipopolysaccharide (LPS). Similarly to imipramine (10 mg/kg), a clinical antidepressant, DADS (40 or 80 mg/kg), which was administered 1 h before LPS treatment (pre-LPS) or 1.5 h and 23.5 h after LPS treatment (post-LPS), prevented and reversed LPS (100 μg/kg)-induced increase in immobility time in the tail suspension test (TST) and forced swim test (FST) in mice. Mechanistic studies revealed that DADS pre-treatment or post-treatment at the dose of 40 and 80 mg/kg prevented and reversed (i) LPS-induced increases in interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and nitric oxide (NO) levels in the hippocampus and prefrontal cortex, (ii) LPS-induced increases in contents of malondialdehyde (MDA), a parameter reflecting high levels of oxidative stress, and (iii) LPS-induced decreases in contents of GSH, a marker reflecting weakened anti-oxidative ability, in the hippocampus and prefrontal cortex in mice. These results indicate that DADS is comparable to imipramine in effectively ameliorating LPS-induced depression-like behaviors in mice, providing a potential value for DADS in prevention and/or therapy of depression.

The Role of Growth Hormone in Depression: A Human Model

Background

Although the relationship between acromegaly and depression has been ascribed to the effects of chronic disease, the role of growth hormone (GH), and insulin like growth factor-1 (IGF-1) is not clear.

Objective

To determine whether related hormones levels in acromegalics are correlated with depressive symptoms and whether these symptoms are ameliorated following surgery.

Materials and Methods

A prospective cohort study was conducted on patients diagnosed with acromegaly (n = 15) or non-functioning pituitary adenomas (NFPA; n = 20, as controls) and undergoing first-time surgery, who completed the Center for Epidemiological Studies Depression (CES-D) questionnaire both pre-surgery and post-surgery. The primary outcome was the patient's severity of depression symptomatology using the CES-D score; GH, IGF-1 levels, and tumor characteristics were also measured.

Results

Hormone levels (GH and IGF-1) and depression scores in acromegaly patients showed significant reductions following surgery (p < 0.05). The average change in CES-D score was 5.73 ± 2.58 (mean ± SE). A moderate correlation was found between GH levels and CES-D scores (r = 0.52, p < 0.01). The depressed affect subscale accounted for the most improvement in CES-D scores postoperatively and correlated most highly with GH levels. We did not find similar declines in the matched cohort of NFPA patients.

Conclusion and Relevance

Surgical resection of the pituitary tumor in acromegaly patients leads to reduction in GH levels that is correlated with reduction in CES-D scores. The results suggest a role for GH in depression and provide a stronger foundation on which to build the hypothesis that GH impacts affect. The study also suggests that hormones should be factored into the matrix that entails the neuro-biological underpinnings of depressive disorders. Future work could explore the mechanisms involved, further brain and neuropeptide interactions, and, novel potential therapeutic targets in depressive and other mental health disorders.

Repetitive Transcranial Magnetic Stimulation for Adolescent Major Depressive Disorder: A Focus on Neurodevelopment

Adolescent depression is a potentially lethal condition and a leading cause of disability for this age group. There is an urgent need for novel efficacious treatments since half of adolescents with depression fail to respond to current therapies and up to 70% of those who respond will relapse within 5 years. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising treatment for major depressive disorder (MDD) in adults who do not respond to pharmacological or behavioral interventions. In contrast, rTMS has not demonstrated the same degree of efficacy in adolescent MDD. We argue that this is due, in part, to conceptual and methodological shortcomings in the existing literature. In our review, we first provide a neurodevelopmentally focused overview of adolescent depression. We then summarize the rTMS literature in adult and adolescent MDD focusing on both the putative mechanisms of action and neurodevelopmental factors that may influence efficacy in adolescents. We then identify limitations in the existing adolescent MDD rTMS literature and propose specific parameters and approaches that may be used to optimize efficacy in this uniquely vulnerable age group. Specifically, we suggest ways in which future studies reduce clinical and neural heterogeneity, optimize neuronavigation by drawing from functional brain imaging, apply current knowledge of rTMS parameters and neurodevelopment, and employ an experimental therapeutics platform to identify neural targets and biomarkers for response. We conclude that rTMS is worthy of further investigation. Furthermore, we suggest that following these recommendations in future studies will offer a more rigorous test of rTMS as an effective treatment for adolescent depression.

Objective Assessments in Diagnoses and Treatment: A Proposed Change in Paradigm

For patients with psychiatric disorders, current diagnostic and treatment approaches are far from optimal. The clinical interview drives the standard approach-matching symptoms to diagnostic criteria-and results in standardized pharmacological and behavioral treatments, often, with inadequate outcome; but now, recent imaging advances can correlate behavioral assessments with brain function and measure them against normative databases to provide data critical for the reevaluation of patient diagnosis and treatment. This article addresses the data that support a redefinition of our current paradigm. We believe a neurobehavioral approach provides for more personalized treatment approaches unbound from classically defined diagnostic biases.

Coordination between frontolimbic resting state connectivity and hypothalamic-pituitary-adrenal axis functioning in adolescents with and without depression

Depression is associated with abnormalities in Hypothalamic-Pituitary-Adrenal (HPA) axis functioning and neural circuitry that underlie the stress response. Resting-state functional connectivity (RSFC) between frontolimbic brain regions captures intrinsic connections that may set the stage for the rallying and regulating of the HPA axis system. This study examined the association between cortisol stress response and frontolimbic (amygdala and ventral and dorsal medial prefrontal cortex [vmPFC and dmPFC respectively]) RSFC in 88 (Age: M = 15.95, SD = 2.04; 71.60% female) adolescents with (N = 55) and without (N = 33) major depressive disorder (MDD). We collected salivary cortisol in the context of a modified Trier Social Stress Test (TSST) paradigm. Key findings were that adolescents with depression and healthy controls showed different patterns of association between amygdala and vmPFC RSFC and HPA functioning: while healthy controls showed a positive relationship between frontolimbic connectivity and cortisol levels that may indicate coordination across neural and neuroendocrine systems, adolescents with depression showed a minimal or inverse relationship, suggesting poor coordination of these systems. Results were similar when examining non-suicidal self-injury subgroups within the MDD sample. These findings suggest that the intrinsic quality of this frontolimbic connection may be related to HPA axis functioning. In MDD, inverse associations may represent a compensatory response in one system in response to dysfunction in the other. Longitudinal multilevel research, however, is needed to disentangle how stress system coordination develops in normal and pathological contexts and how these systems recover with treatment.

Resting State Functional Connectivity Biomarkers of Treatment Response in Mood Disorders: A Review

There are currently no validated treatment biomarkers in psychiatry. Resting State Functional Connectivity (RSFC) is a popular method for investigating the neural correlates of mood disorders, but the breadth of the field makes it difficult to assess progress toward treatment response biomarkers. In this review, we followed general PRISMA guidelines to evaluate the evidence base for mood disorder treatment biomarkers across diagnoses, brain network models, and treatment modalities. We hypothesized that no treatment biomarker would be validated across these domains or with independent datasets. Results are organized, interpreted, and discussed in the context of four popular analytic techniques: (1) reference region (seed-based) analysis, (2) independent component analysis, (3) graph theory analysis, and (4) other methods. Cortico-limbic connectivity is implicated across studies, but there is no single biomarker that spans analyses or that has been replicated in multiple independent datasets. We discuss RSFC limitations and future directions in biomarker development.

Research Review: Brain network connectivity and the heterogeneity of depression in adolescence - a precision mental health perspective

BACKGROUND

Adolescence is a period of high risk for the onset of depression, characterized by variability in symptoms, severity, and course. During adolescence, the neurocircuitry implicated in depression continues to mature, suggesting that it is an important period for intervention. Reflecting the recent emergence of 'precision mental health' - a person-centered approach to identifying, preventing, and treating psychopathology - researchers have begun to document associations between heterogeneity in features of depression and individual differences in brain circuitry, most frequently in resting-state functional connectivity (RSFC).

METHODS

In this review, we present emerging work examining pre- and post-treatment measures of network connectivity in depressed adolescents; these studies reveal potential intervention-specific neural markers of treatment efficacy. We also review findings from studies examining associations between network connectivity and both types of depressive symptoms and response to treatment in adults, and indicate how this work can be extended to depressed adolescents. Finally, we offer recommendations for research that we believe will advance the science of precision mental health of adolescence.

RESULTS

Nascent studies suggest that linking RSFC-based pathophysiological variation with effects of different types of treatment and changes in mood following specific interventions will strengthen predictions of prognosis and treatment response. Studies with larger sample sizes and direct comparisons of treatments are required to determine whether RSFC patterns are reliable neuromarkers of treatment response for depressed adolescents. Although we are not yet at the point of using RSFC to guide clinical decision-making, findings from research examining the stability and reliability of RSFC point to a favorable future for network-based clinical phenotyping.

CONCLUSIONS

Delineating the correspondence between specific clinical characteristics of depression (e.g., symptoms, severity, and treatment response) and patterns of network-based connectivity will facilitate the development of more tailored and effective approaches to the assessment, prevention, and treatment of depression in adolescents.

Prediction on treatment improvement in depression with resting state connectivity: A coordinate-based meta-analysis

BACKGROUND

Previous neuroimaging studies revealed abnormal resting-state functional connectivity between distributed brain areas in patients with major depressive disorder. Those abnormalities were normalized after treatment. Moreover, the functional connectivity could predict clinical response to those treatments. However, there has currently been no meta-analysis to verify these findings.

METHODS

The current study aimed to investigate how the resting-state connectivity patterns predict antidepressant response to various treatments across depressive studies by using coordinate-based meta-analysis named activation likelihood estimation. The relevant articles were obtained by searching on PubMed and Web of Science.

RESULTS

Following exclusion criteria of inappropriate studies, seventeen papers with 392 individual depressive patients were included. Those articles contained repetitive transcranial magnetic stimulation (rTMS) treatment, pharmacotherapy, cognitive behavioral therapy (CBT), electroconvulsive therapy (ECT) and transcutaneous vagus nerve stimulation in patients with depression. Meta-analysis revealed that clinical response to all treatments could be predicted by baseline default mode network connectivity in patients with depression. The rTMS treatment had larger effect size compared to other treatment strategies. Furthermore, subgroup meta-analysis showed that the baseline connectivity of perigenual anterior cingulate cortex (pgACC) and ventral medial prefrontal cortex could predict symptoms improvement of rTMS treatment.

LIMITATIONS

More resting-state connectivity studies of CBT and ECT treatment are needed.

CONCLUSIONS

This study highlighted crucial role of DMN, especially the pgACC, in understanding the underlying treatment mechanism of depression.

Predicting Antidepressant Citalopram Treatment Response via Changes in Brain Functional Connectivity After Acute Intravenous Challenge

Introduction: The early and therapy-specific prediction of treatment success in major depressive disorder is of paramount importance due to high lifetime prevalence, and heterogeneity of response to standard medication and symptom expression. Hence, this study assessed the predictability of long-term antidepressant effects of escitalopram based on the short-term influence of citalopram on functional connectivity. Methods: Twenty nine subjects suffering from major depression were scanned twice with resting-state functional magnetic resonance imaging under the influence of intravenous citalopram and placebo in a randomized, double-blinded cross-over fashion. Symptom factors were identified for the Hamilton depression rating scale (HAM-D) and Beck's depression inventory (BDI) taken before and after a median of seven weeks of escitalopram therapy. Predictors were calculated from whole-brain functional connectivity, fed into robust regression models, and cross-validated. Results: Significant predictive power could be demonstrated for one HAM-D factor describing insomnia and the total score (r = 0.45-0.55). Remission and response could furthermore be predicted with an area under the receiver operating characteristic curve of 0.73 and 0.68, respectively. Functional regions with high influence on the predictor were located especially in the ventral attention, fronto-parietal, and default mode networks. Conclusion: It was shown that medication-specific antidepressant symptom improvements can be predicted using functional connectivity measured during acute pharmacological challenge as an easily assessable imaging marker. The regions with high influence have previously been related to major depression as well as the response to selective serotonin reuptake inhibitors, corroborating the advantages of the current approach of focusing on treatment-specific symptom improvements.

Developing a data-driven algorithm for guiding selection between cognitive behavioral therapy, fluoxetine, and combination treatment for adolescent depression

Treating adolescent depression effectively requires providing interventions that are optimally suited to patients' individual characteristics and needs. Therefore, we aim to develop an algorithm that matches patients with optimal treatment among cognitive-behavioral therapy (CBT), fluoxetine (FLX), and combination treatment (COMB). We leveraged data from a completed clinical trial, the Treatment for adolescents with depression study, where a wide range of demographic, clinical, and psychosocial measures were collected from adolescents diagnosed with major depressive disorder prior to treatment. Machine-learning techniques were employed to derive a model that predicts treatment response (week 12 children's depression rating scale-revised [CDRS-R]) to CBT, FLX, and COMB. The resulting model successfully identified subgroups of patients that respond preferentially to specific types of treatment. Specifically, our model identified a subgroup of patients (25%) that achieved on average a 16.9 point benefit on the CDRS-R from FLX compared to CBT. The model also identified a subgroup of patients (50%) that achieved an average benefit up to 19.0 points from COMB compared to CBT. Physical illness and disability were identified as overall predictors of response to treatment, regardless of treatment type, whereas baseline CDRS-R, psychosomatic symptoms, school missed, view of self, treatment expectations, and attention problems determined the patients' response to specific treatments. The model developed in this study provides a critical starting point for personalized treatment planning for adolescent depression.

MRI Insights Into Adolescent Neurocircuitry-A Vision for the Future

Adolescence is the time of onset of many psychiatric disorders. Half of pediatric patients present with comorbid psychiatric disorders that complicate both their medical and psychiatric care. Currently, diagnosis and treatment decisions are based on symptoms. The field urgently needs brain-based diagnosis and personalized care. Neuroimaging can shed light on how aberrations in brain circuits might underlie psychiatric disorders and their development in adolescents. In this perspective article, we summarize recent MRI literature that provides insights into development of psychiatric disorders in adolescents. We specifically focus on studies of brain structural and functional connectivity. Ninety-six included studies demonstrate the potential of MRI to assess psychiatrically relevant constructs, diagnose psychiatric disorders, predict their development or predict response to treatment. Limitations of the included studies are discussed, and recommendations for future research are offered. We also present a vision for the role that neuroimaging may play in pediatrics and primary care in the future: a routine neuropsychological and neuropsychiatric imaging (NPPI) protocol for adolescent patients, which would include a 30-min brain scan, a quality control and safety read of the scan, followed by computer-based calculation of the structural and functional brain network metrics that can be compared to the normative data by the pediatrician. We also perform a cost-benefit analysis to support this vision and provide a roadmap of the steps required for this vision to be implemented.

Differences in cytokines between patients with generalised anxiety disorder and panic disorder

OBJECTIVE

The purpose of this study was to evaluate the differences among panic disorder (PD), generalised anxiety disorder (GAD) and controls in inflammatory cytokines. We also analysed the correlation between inflammatory cytokines and response to escitalopram in PD and GAD patients.

METHODS

Eighty-six patients with PD, 86 patients with GAD and 86 healthy controls were recruited for this study. All participants were, respectively, assessed for severity of anxiety and panic symptoms using the Hamilton Anxiety Rating Scale (HAMA) and the Panic Disorder Severity Scale (PDSS); all patients in the study were also assessed after 4 weeks of treatment. The serum levels of cytokines were measured using a flow fluorescence microsphere assay.

RESULTS

Both PD and GAD patients had higher serum levels of interleukin 6 (IL-6) than controls, and patients with PD showed significantly higher IL-6 than GAD patients. Significant positive correlations were found between the IFN-γ levels and the severity of anxiety in GAD patients. Higher level of IL-6 was associated with better response to escitalopram treatment in PD patients. However, the baseline levels of cytokines were not associated with treatment responses in GAD patients.

CONCLUSION

The present findings suggest that patients with PD may have higher levels of IL-6 than GAD, and higher baseline levels of IL-6 may be a better response to escitalopram in the treatment of PD.

New Somatic Treatments for Child and Adolescent Depression

PURPOSE OF REVIEW

Depression is a common clinical problem in youth, with prevalence increasing significantly during the adolescent period. Although several evidence-based treatments are currently available for treating depression in adults, only a subset of these have been investigated in a pediatric sample. Unfortunately, even well-established, first-line interventions do not lead to sufficient treatment response for many children and adolescents suffering from depression. However, recent research has been conducted in the area of somatic treatments for youth with depression. This review focuses on current (past three years, including published results and ongoing studies) research on somatic treatments for adolescent depression in the following categories: psychopharmacology, nutraceuticals, interventions implicating motor and sensory systems, and neuromodulation.

FINDINGS

Results from recent randomized, controlled trials testing psychopharmacological options suggest that while antidepressants that have been recently approved for adult patients are safe and tolerable in children and adolescents, none have yet outperformed performed placebo in efficacy. Nutraceuticals, motor-sensory interventions, and neuromodulation techniques, present safe and promising results, but few have been tested against controls to support effectiveness over current treatment options.

SUMMARY

This review of research on pediatric depression treatment from the past 3 years highlights some disappointments (negative results following some of the well-designed clinical trials) and gaps (preliminary studies in need of follow up with robust methodology) but also some promising directions in research of the efficacyof these treatments in a pediatric sample. We offer suggestions for future research including consideration of treatment timing, sequencing, the role of symptom severity in directing treatment selection, the potential value of combined treatments, consideration of how to best account for high placebo response rates, and the incorporation of neurobiological assessments to examine mechanisms and biomarker predictors of treatment response.

Neural correlates of emotion processing comparing antidepressants and exogenous oxytocin in postpartum depressed women: An exploratory study

Despite common use of antidepressants to treat postpartum depression, little is known about the impact of antidepressant use on postpartum brain activity. Additionally, although oxytocin has been investigated as a potential treatment for postpartum depression, the interaction between antidepressants and exogenous oxytocin on brain activity is unknown. We explored postpartum depressed women's neural activation in areas identified as important to emotion and reward processing and potentially, antidepressant response: the amygdala, nucleus accumbens and ventral tegmental area. We conducted a secondary analysis of a functional imaging study of response to sexual, crying infant and smiling infant images in 23 postpartum depressed women with infants under six months (11 women taking antidepressants, 12 unmedicated). Participants were randomized to receive a single dose of oxytocin or placebo nasal spray. There was significantly higher amygdala activation to sexual stimuli than either neutral or infant-related stimuli among women taking antidepressants or receiving oxytocin nasal spray. Among unmedicated women receiving placebo, amygdala activation was similar across stimuli types. There were no significant effects of antidepressants nor oxytocin nasal spray on reward area processing (i.e., in the nucleus accumbens or ventral tegmental area). Among postpartum women who remain depressed, there may be significant interactions between the effects of antidepressant use and exogenous oxytocin on neural activity associated with processing emotional information. Observed effect sizes were moderate to large, strongly suggesting the need for further replication with a larger sample.

Hypothalamic-pituitary-adrenal axis dysregulation in depressed adolescents with non-suicidal self-injury

Non-suicidal self-injury (NSSI) is characterized by causing harm to one's own body without the intent of suicide. While major depressive disorder (MDD) has been associated with elevated cortisol (at least in some subgroups), prior studies in NSSI have suggested that NSSI is associated with blunted reactivity to stress of the hypothalamic-pituitary-adrenal (HPA) axis, possibly consistent with an allostatic load model. The present study used a multi-level approach to examine salivary cortisol in the context of a social stressor in 162 adolescents (ages 12 to 19 years old) with MDD with a history of repeated engagement in NSSI (MDD/NSSI) versus MDD without repeated NSSI (MDD), and healthy controls (HC). Observed (expressed) and self-reported (experienced) ratings of stress were also obtained during the social stress paradigm. The results showed that MDD/NSSI exhibited lower salivary cortisol levels and differed in cortisol trajectories in the context of a social stressor compared to HC and MDD. Observed stress, but not self-reported stress, during the social stress paradigm was greater for the MDD/NSSI than HC. Follow-up analyses suggested the possibility that this pattern of lower cortisol for those who engage in NSSI was present in females and males, and was more pronounced in those with repeated NSSI (but not subthreshold NSSI) and those with a history of NSSI and suicide attempts. Overall, these findings add to the prior literature and begin to show a consistent pattern for how stress is processed in atypical ways for those who engage in repeated NSSI. Importantly, these results suggest that some of the heterogeneity across adolescent depression may be better represented by these underlying biological processes, perhaps even representing subgroups that will benefit from different types of intervention. Hypothalamic-Pituitary-Adrenal Axis Dysregulation in Depressed Adolescents with Non-Suicidal Self-Injury.

Intrinsic Brain Network Biomarkers of Antidepressant Response: a Review

PURPOSE OF REVIEW

Poor treatment response is a hallmark of major depressive disorder. To tackle this problem, recent neuroimaging studies have sought to characterize antidepressant response in terms of pretreatment differences in intrinsic functional brain networks. Our aim is to review recent studies that predict antidepressant response using intrinsic network connectivity. We discuss current methodological limitations and directions for future antidepressant biomarker studies.

RECENT FINDINGS

Functional connectivity stemming from the subgenual and rostral anterior cingulate has shown particular consistency in predicting antidepressant response. Differences in this connectivity may prove fruitful in differentiating treatment responders to many antidepressant interventions. Future biomarker studies should integrate biological MDD subtypes to address the disorder's inherent clinical heterogeneity. These clinical and scientific advancements have the potential to address this population marked by limited treatment response. Methodological considerations, including patient selection, response criteria, and model overfitting, will require future investigation to ensure that biomarkers generalize for prospective prediction of treatment response.

Increases in orbitofrontal cortex thickness following antidepressant treatment are associated with changes in resting state autonomic function in adolescents with major depression - Preliminary findings from a pilot study

In adults with major depressive disorder (MDD), effective treatment has been associated with increases in both heart rate variability (HRV) and cortical thickness. However, the impact of treatment on these indices has not yet been examined in adolescents. Cortical thickness and HRV were measured in twelve adolescents with MDD before and after 8 weeks of treatment with a selective serotonin reuptake inhibitor (SSRI). We examined treatment-related changes in depression symptoms, HRV, heart rate (HR), and cortical thickness, and analyzed correlations among these change indices. At follow-up, patients showed significantly decreased depression severity, increased HRV and increased thickness of the left medial orbitofrontal cortex (OFC). Clinical improvement was associated with increased HRV and decreased HR. Increased HRV was associated with increased cortical thickness of left lateral OFC and superior frontal cortex. Due to the small sample size, results represent preliminary findings that need replication. Further, in the absence of a placebo arm, we cannot confirm that the observed effects are due solely to medication. These preliminary findings suggest that SSRI treatment in adolescents impacts both cortical thickness and autonomic functioning. Confirmation of these findings would support OFC thickness and HRV as neurobiological mediators of treatment outcome.

Classifying Treated vs. Untreated MDD Adolescents from Anatomical Connectivity using Nonlinear SVM

Identification of the treatment-related responders for adolescent Major Depressive Disorder (MDD) is urgently needed to develop effective treatments. In this paper, machine learning based classifiers are used to reveal anatomical features as responders for distinguishing MDD patients who have received treatment from those who never received any treatment. The features are drawn from two sets of measurements: 1) anatomical connectivity defined by diffusion tensor imaging measurements between a pair of brain regions, and 2) topological measurements from anatomical networks. Feature selection was performed based on p-value and minimum redundancy maximum relevance (mRMR) method to achieve improved classification accuracy. The classification performance is evaluated with a leave-one-out cross-validation method using 37 treated and 15 untreated subjects. The proposed methodology achieves 73% accuracy, 100% specificity, and 100% precision for 52 subjects. The most distinguishing features are the strength of the right hippocampus of the mean diffusivity (MD) network at 18% density and of the track-count (TR) network, the participation coefficient of the left middle temporal gyrus of the radial diffusivity (RD) network at 20% density, the axial diffusivity (AD) connectivity between right middle temporal gyrus and right supramarginal gyrus, the betweenness centrality of the right hippocampus of the TR network at 11% density, the apparent diffusion coefficient (ADC) connectivity between the left pars opercularis and the left rostral anterior cingulate cortex, the clustering coefficient of the middle anterior corpus callosum of the TR network at 11% density, and the AD connectivity between the left pars opercularis and the left rostral anterior cingulate cortex.

A Pilot Study of Stress System Activation in Children Enrolled in a Targeted Prevention Program: Implications for Personalization

Empirically validated interventions addressing childhood psychological problems are now readily available, but success likely depends in part on accurately identifying which children will benefit from which intervention. This pilot study examined the stress activation and response system, first as a way to differentiate high versus low-risk children, and second to explore indicators of the stress system associated with favorable intervention response. Method. Participants (N = 43, 58% male) were school-aged children who qualified for inclusion in the Early Risers “Skills for Success” Prevention Program based on their elevated levels of aggressive and/or socially withdrawn behavior and a normally developing comparison group. Compared to the normally developing group, children who were participants in the intervention exhibited a more blunted cortisol response to the stress paradigm. However, for the children in the intervention group, elevated cortisol levels at the start of the stress paradigm were concurrently associated with internalizing problems and predictive of improvement in internalizing problems over time. These findings provide preliminary evidence that hypothalamic pituitary adrenal (HPA) axis biological variables may be helpful tools for identifying children who would benefit from intervention and personalizing interventions.