Neural Correlates of Antidepressant Treatment Response in Adolescents with Major Depressive Disorder

Bright light therapy-induced improvements of mood, cognitive functions and cerebellar functional connectivity in subthreshold depression: A randomized controlled trial

Background

The efficacy of bright light therapy (BLT) in ameliorating depression has been validated. The present study is to investigate the changes of depressive symptoms, cognitive function and cerebellar functional connectivity (FC) following BLT in individuals with subthreshold depression (StD).

Method

Participants were randomly assigned to BLT group (N = 47) or placebo (N = 41) in this randomized controlled trial between March 2020 and June 2022. Depression severity and cognitive function were assessed, as well as resting-state functional MRI scan was conducted before and after 8-weeks treatment. Seed-based whole-brain static FC (sFC) and dynamic FC (dFC) analyses of the bilateral cerebellar subfields were conducted. Besides, a multivariate regression model examined whether baseline brain FC was associated with changes of depression severity and cognitive function during BLT treatment.

Results

After 8-week BLT treatment, individuals with StD showed improved depressive symptoms and attention/vigilance cognitive function. BLT also increased sFC between the right cerebellar lobule IX and left temporal pole, and decreased sFC within the cerebellum, and dFC between the right cerebellar lobule IX and left medial prefrontal cortex. Moreover, the fusion of sFC and dFC at baseline could predict the improvement of attention/vigilance in response to BLT.

Conclusions

The current study identified that BLT improved depressive symptoms and attention/vigilance, as well as changed cerebellum-DMN connectivity, especially in the cerebellar-frontotemporal and cerebellar internal FC. In addition, the fusion features of sFC and dFC at pre-treatment could serve as an imaging biomarker for the improvement of attention/vigilance cognitive function after BLT in StD.

Functional connectivity of the amygdala subregions and the antidepressant effects of repeated ketamine infusions in major depressive disorder

BACKGROUND

Amygdala subregion-based network dysfunction has been determined to be centrally implicated in major depressive disorder (MDD). Little is known about whether ketamine modulates amygdala subarea-related networks. We aimed to investigate the relationships between changes in the resting-state functional connectivity (RSFC) of amygdala subregions and ketamine treatment and to identify important neuroimaging predictors of treatment outcomes.

METHODS

Thirty-nine MDD patients received six doses of ketamine (0.5 mg/kg). Depressive symptoms were assessed, and magnetic resonance imaging (MRI) scans were performed before and after treatment. Forty-five healthy controls underwent one MRI scan. Seed-to-voxel RSFC analyses were performed on the amygdala subregions, including the centromedial amygdala (CMA), laterobasal amygdala (LBA), and superficial amygdala subregions.

RESULTS

Abnormal RSFC between the left LBA and the left precuneus in MDD patients is related to the therapeutic efficacy of ketamine. There were significant differences in changes in bilateral CMA RSFC with the left orbital part superior frontal gyrus and in changes in the left LBA with the right middle frontal gyrus between responders and nonresponders following ketamine treatment. Moreover, there was a difference in the RSFC of left LBA and the right superior temporal gyrus/middle temporal gyrus (STG/MTG) between responders and nonresponders at baseline, which could predict the antidepressant effect of ketamine on Day 13.

CONCLUSIONS

The mechanism by which ketamine improves depressive symptoms may be related to its regulation of RSFC in the amygdala subregion. The RSFC between the left LBA and right STG/MTG may predict the response to the antidepressant effect of ketamine.

Personality traits predict treatment outcome of an antidepressant in untreated adolescents with depression: An 8-week, open-label, flexible-dose study

BACKGROUND

Antidepressant response in adults with major depressive disorder (MDD) is probably influenced by personality dimensions. However, personality dimensions in depression and their association with antidepressant treatment in adolescents are relatively unknown. We sought to investigate whether personality traits (PTs) can influence antidepressant treatment response in adolescents with depression.

METHODS

Eighty-two adolescents with MDD who had completed the 8 weeks of treatment with selective serotonin reuptake inhibitors (SSRI) were enrolled. The Revised NEO Five-Factor Inventory (NEO-FFI-R) was used to measure their personality at baseline, and the 17-item Hamilton Depression Rating Scale (HAMD-17) and Children's Depression Rating Scale-Revised (CDRS-R) were used to evaluate depressive symptoms at baseline and 8 weeks. Moreover, logistic regression was performed to investigate the relationship between personality dimensions and antidepressant response. Receiver operating characteristic analyses were employed to determine the accuracy of a PT-based model in predicting the antidepressant response rate.

RESULTS

Adolescents with MDD had significantly different PTs at baseline. Multivariable logistic regression analysis showed that extroversion scores were associated with response to antidepressant treatment, the lower the extroversion score, the better the response to antidepressant treatment, after correcting for variables with significant differences and trends or all potential confounding variables. It was also found that the combination of disease duration, extraversion-gregariousness, and agreeableness-trust effectively predicted antidepressant response in adolescents with MDD, with a sensitivity of 79.4 % and specificity of 68.7 %.

CONCLUSION

Personality dysfunction in adolescents is associated with MDD. The antidepressant treatment response is influenced by the degree of extroversion in adolescents with MDD.

Vulnerable brain regions in adolescent major depressive disorder: A resting-state functional magnetic resonance imaging activation likelihood estimation meta-analysis

BACKGROUND

Adolescent major depressive disorder (MDD) is a significant mental health concern that often leads to recurrent depression in adulthood. Resting-state functional magnetic resonance imaging (rs-fMRI) offers unique insights into the neural mechanisms underlying this condition. However, despite previous research, the specific vulnerable brain regions affected in adolescent MDD patients have not been fully elucidated.

AIM

To identify consistent vulnerable brain regions in adolescent MDD patients using rs-fMRI and activation likelihood estimation (ALE) meta-analysis.

METHODS

We performed a comprehensive literature search through July 12, 2023, for studies investigating brain functional changes in adolescent MDD patients. We utilized regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) analyses. We compared the regions of aberrant spontaneous neural activity in adolescents with MDD vs healthy controls (HCs) using ALE.

RESULTS

Ten studies (369 adolescent MDD patients and 313 HCs) were included. Combining the ReHo and ALFF/fALFF data, the results revealed that the activity in the right cuneus and left precuneus was lower in the adolescent MDD patients than in the HCs (voxel size: 648 mm3, P < 0.05), and no brain region exhibited increased activity. Based on the ALFF data, we found decreased activity in the right cuneus and left precuneus in adolescent MDD patients (voxel size: 736 mm3, P < 0.05), with no regions exhibiting increased activity.

CONCLUSION

Through ALE meta-analysis, we consistently identified the right cuneus and left precuneus as vulnerable brain regions in adolescent MDD patients, increasing our understanding of the neuropathology of affected adolescents.

Trying to name what doesn't change: Neural nonresponse to Cognitive Therapy for depression

BACKGROUND

Theoretical models of neural mechanisms underlying Cognitive Behavior Therapy (CBT) for major depressive disorder (MDD) propose that psychotherapy changes neural functioning of prefrontal cortical structures associated with cognitive-control processes (DeRubeis, Siegle, & Hollon, ); however, MDD is persistent and characterized by long-lasting vulnerabilities to recurrence after intervention, suggesting that underlying neural mechanisms of MDD remain despite treatment. It follows that identification of treatment-resistant aberrant neural processes in MDD may inform clinical and research efforts targeting sustained remission. Thus, we sought to identify brain regions showing aberrant neural functioning in MDD that either (1) fail to exhibit substantive change (nonresponse) or (2) exhibit functional changes (response) following CBT.

METHODS

To identify treatment-resistant neural processes (as well as neural processes exhibiting change after treatment), we collected functional magnetic resonance imaging (fMRI) data of MDD patients (n = 58) before and after CBT as well as never-depressed controls (n = 35) before and after a similar amount of time. We evaluated fMRI data using conjunction analyses, which utilized several contrast-based criteria to characterize brain regions showing both differences between patients and controls at baseline and nonresponse or response to CBT.

RESULTS

Findings revealed nonresponse in a cerebellar region and response in prefrontal and parietal regions.

CONCLUSIONS

Results are consistent with prior theoretical models of CBT's direct effect on cortical regulatory processes but expand on them with identification of additional regions (and associated neural systems) of response and nonresponse to CBT.

Frontoamygdalar Effective Connectivity in Youth Depression and Treatment Response

BACKGROUND

Emotion regulation deficits are characteristic of youth depression and are underpinned by altered frontoamygdalar function. However, the causal dynamics of frontoamygdalar pathways in depression and how these dynamics relate to treatment prognosis remain unexplored. This study aimed to assess frontoamygdalar effective connectivity during cognitive reappraisal in youths with depression and to test whether pathway dynamics are predictive of individual response to combined cognitive behavioral therapy plus treatment with fluoxetine or placebo.

METHODS

One hundred seven young people with moderate to severe depression and 94 healthy control participants completed a functional magnetic resonance imaging cognitive reappraisal task. After the task, 87 participants with depression were randomized and received 12 weeks of cognitive behavioral therapy plus either fluoxetine or placebo. Dynamic causal modeling was used to map frontoamygdalar effective connectivity during reappraisal and to assess the predictive capacity of baseline frontoamygdalar effective connectivity on depression diagnosis and posttreatment depression remission.

RESULTS

Young people with depression showed weaker inhibitory modulation of ventrolateral prefrontal cortex to amygdala connectivity during reappraisal (0.29 Hz, posterior probability = 1.00). Leave-one-out cross-validation demonstrated that this effect was sufficiently large to predict individual diagnostic status (r = 0.20, p = .003). Posttreatment depression remission was associated with weaker excitatory ventromedial prefrontal cortex to amygdala connectivity (-0.56 Hz, posterior probability = 1.00) during reappraisal at baseline, though this effect did not predict individual remission status (r = -0.02, p = .561).

CONCLUSIONS

Frontoamygdalar effective connectivity shows promise in identifying youth depression diagnosis, and circuits responsible for negative affect regulation are implicated in responsiveness to first-line depression treatments.

Loss of PV interneurons in the BLA contributes to altered network and behavioral states in chronically epileptic mice

Psychiatric disorders, including anxiety and depression, are highly comorbid in people with epilepsy. However, the mechanisms mediating the shared pathophysiology are currently unknown. There is considerable evidence implicating the basolateral amygdala (BLA) in the network communication of anxiety and fear, a process demonstrated to involve parvalbumin-positive (PV) interneurons. The loss of PV interneurons has been well described in the hippocampus of chronically epileptic mice and in postmortem human tissue of patients with temporal lobe epilepsy (TLE). We hypothesize that a loss of PV interneurons in the BLA may contribute to comorbid mood disorders in epilepsy. To test this hypothesis, we employed a ventral intrahippocampal kainic acid (vIHKA) model of chronic epilepsy in mice, which exhibits profound behavioral deficits associated with chronic epilepsy. We demonstrate a loss of PV interneurons and dysfunction of remaining PV interneurons in the BLA of chronically epileptic mice. Further, we demonstrate altered principal neuron function and impaired coordination of BLA network and behavioral states in chronically epileptic mice. To determine whether these altered network and behavioral states were due to the loss of PV interneurons, we ablated a similar percentage of PV interneurons observed in chronically epileptic mice by stereotaxically injecting AAV-Flex-DTA into the BLA of PV-Cre mice. Loss of PV interneurons in the BLA is sufficient to alter behavioral states, inducing deficits in fear learning and recall of fear memories. These data suggest that compromised inhibition in the BLA in chronically epileptic mice contributes to behavioral deficits, suggesting a novel mechanism contributing to comorbid anxiety and epilepsy.

Significance Statement

Psychiatric illnesses and epilepsy are highly comorbid and negatively impact the quality of life of people with epilepsy. The pathophysiological mechanisms mediating the bidirectional relationship between mood disorders and epilepsy remain unknown and, therefore, treatment options remain inadequate. Here we demonstrate a novel mechanism, involving the loss of PV interneurons in the BLA, leading to a corruption of network and behavioral states in mice. These findings pinpoint a critical node and demonstrate a novel cellular and circuit mechanism involved in the comorbidity of psychiatric illnesses and epilepsy.

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.

Measures of Connectivity and Dorsolateral Prefrontal Cortex Volumes and Depressive Symptoms Following Treatment With Selective Serotonin Reuptake Inhibitors in Adolescents

Importance

Selective serotonin reuptake inhibitors (SSRIs) are considered a first-line pharmacological treatment for adolescent depression with moderate or higher levels of symptom severity. Thus, it is important to understand neurobiological changes related to SSRIs during the course of treatment for adolescents with depression.

Objective

To examine neurobiological changes associated with SSRI treatment in adolescents with major depressive disorder (MDD) by measuring longitudinal changes in volume and resting-state functional connectivity (rsFC) in the dorsolateral prefrontal cortex (DLPFC), a core region of cognitive control.

Design, Setting, and Participants

This cohort study was conducted with an open-label design. Adolescents with MDD and healthy controls were recruited at the Seoul National University Hospital (Seoul, South Korea). Adolescents with MDD were treated with escitalopram for 8 weeks. Data analysis was conducted between April 2021 and February 2022.

Main Outcomes and Measures

Depressive symptoms were assessed using the Children's Depression Rating Scale-Revised. The outcome measure was defined as the change in Children's Depression Rating Scale-Revised scores from week 0 (before treatment) to week 8 (after treatment) or upon termination. Participants completed structural and resting-state functional magnetic resonance imaging (rsfMRI) assessments before (week 0) and after (week 8) SSRI treatment. Repeated measures analysis of variance and liner mixed model analyses were used to examine the longitudinal associations of SSRI treatment with DLPFC volume and rsFC between responders who showed at least a 40% decrease in depressive symptoms and nonresponders who did not.

Results

Ninety-five adolescents with MDD and 57 healthy controls were initially recruited. The final analyses of volume included 36 responders (mean [SD] age, 15.0 [1.6] years; 25 girls [69.4%]) and 26 nonresponders (mean [SD] age, 15.3 [1.5] years; 19 girls [73.1%]). Analyses of rsFC included 33 responders (mean [SD] age, 15.2 [1.5] years; 21 girls [63.6%]) and 26 nonresponders (mean [SD] age, 15.3 [1.5] years; 19 girls [73.1%]). The longitudinal associations of SSRI treatment were more evident in responders than in nonresponders. Responders showed significantly increased right DLPFC volume, decreased bilateral DLPFC rsFC with the superior frontal gyri, and decreased left DLPFC rsFC with the ventromedial PFC after treatment compared with before treatment. Furthermore, increased right DLPFC volume was correlated with decreased rsFC between the right DLPFC and superior frontal gyri after SSRI treatment.

Conclusions and Relevance

The preliminary results of this cohort study suggest that the DLPFC volumetric and rsFC changes may serve as potential neurobiological treatment markers that are associated with symptom improvement in adolescents with MDD.

Resting-state functional connectivity predicting clinical improvement following treatment in female adolescents with non-suicidal self-injury

BACKGROUND

Non-suicidal self-injury (NSSI) is highly prevalent among adolescents and predicts future psychopathology including suicide. To improve therapeutic decisions and clinical outcome of patients engaging in NSSI, it seems beneficial to determine neurobiological markers associated with treatment response. The present study investigated whether resting-state functional brain connectivity (RSFC) served to predict clinical improvements following treatment in adolescents engaging in NSSI.

METHODS

N = 27 female adolescents with NSSI took part in a baseline MRI exam and clinical outcome was assessed at follow-ups one, two and three years after baseline. During the follow-up period, patients received in- and/or outpatient treatment. Mixed-effects linear regression models were calculated to examine whether RSFC was associated with clinical improvement.

RESULTS

Patients' clinical outcome improved across time. Lower baseline RSFC between left paracentral gyrus and right anterior cingulate gyrus was associated with clinical improvement from baseline to one-year and from two-year to three-year follow-up. Lower and higher baseline RSFC in several inter- and intrahemispheric cortico-cortical and cortico-subcortical connections of interest were associated with clinical symptomatology and its severity, independent from time.

LIMITATIONS

A relatively small sample size constrains the generalizability of our findings. Further, no control group not receiving treatment was recruited, therefore clinical changes across time cannot solely be attributed to treatment.

CONCLUSIONS

While there was some evidence that RSFC was associated with clinical improvement following treatment, our findings suggest that functional connectivity is more predictive of severity of psychopathology and global functioning independent of time and treatment. We thereby add to the limited research on neurobiological markers as predictors of clinical outcome after treatment.

Depressive symptoms following traumatic brain injury are associated with resting-state functional connectivity

BACKGROUND

To determine whether depressive symptoms in traumatic brain injury (TBI) patients were associated with altered resting-state functional connectivity (rs-fc) or voxel-based morphology in brain regions involved in emotional regulation and associated with depression.

METHODS

In the present study, we examined 79 patients (57 males; age range = 17-70 years, M ± s.d. = 38 ± 16.13; BDI-II, M ± s.d. = 9.84 ± 8.67) with TBI. We used structural MRI and resting-state fMRI to examine whether there was a relationship between depression, as measured with the Beck Depression Inventory (BDI-II), and the voxel-based morphology or functional connectivity in regions previously identified as involved in emotional regulation in patients following TBI. Patients were at least 4 months post-TBI (M ± s.d. = 15.13 ± 11.67 months) and the severity of the injury included mild to severe cases [Glasgow Coma Scale (GCS), M ± s.d. = 6.87 ± 3.31].

RESULTS

Our results showed that BDI-II scores were unrelated to voxel-based morphology in the examined regions. We found a positive association between depression scores and rs-fc between limbic regions and cognitive control regions. Conversely, there was a negative association between depression scores and rs-fc between limbic and frontal regions involved in emotion regulation.

CONCLUSION

These findings lead to a better understanding of the exact mechanisms that contribute to depression following TBI and better inform treatment decisions.

Functional Activity in the Effect of Transcranial Magnetic Stimulation Therapy for Patients with Depression: A Meta-Analysis

Depression is a long-lasting mental disorder that affects more than 264 million people worldwide. Transcranial magnetic stimulation (TMS) can be a safe and effective choice for the treatment of depression. Functional neuroimaging provides unique insights into the neuropsychiatric effects of antidepressant TMS. In this meta-analysis, we aimed to assess the functional activity of brain regions caused by TMS for depression. A literature search was conducted from inception to 5 January 2022. Studies were then selected according to predetermined inclusion and exclusion criteria. Activation likelihood estimation was applied to analyze functional activation. Five articles were ultimately included after selection. The main analysis results indicated that TMS treatment for depression can alter the activity in the right precentral gyrus, right posterior cingulate, left inferior frontal gyrus and left middle frontal gyrus. In resting-state studies, increased activation was shown in the right precentral gyrus, right posterior cingulate, left inferior frontal gyrus and left superior frontal gyrus associated with TMS treatment. In task-related studies, clusters in the right middle frontal gyrus, left sub-gyrus, left middle frontal gyrus and left posterior cingulate were hyperactivated post-treatment. Our study offers an overview of brain activity changes in patients with depression after TMS treatment.

Functional connectivity differences in the amygdala are related to the antidepressant efficacy of ketamine in patients with anxious depression

BACKGROUND

The antidepressant effects of ketamine in patients with anxious depression (AD) remain unclear. Functional connectivity (FC) differences in the amygdala have been linked to depression improvement after ketamine treatment in depressed patients, but their role in AD patients is uncertain. We investigated the correlation between depression improvement after ketamine treatment and amygdala FC in AD patients.

METHODS

Thirty-one AD patients and 18 non-anxious depression (NAD) patients received six intravenous ketamine infusions (0.5 mg/kg) over two weeks. AD patients were further divided into responders (defined as a ≥50% MADRS total score reduction on day 13) and non-responders. The FC of the amygdala subregions, including the laterobasal amygdala (LBA), centromedial amygdala (CMA), and superficial amygdala, were compared between the groups. Receiver operating characteristic curves were used to predict treatment response after ketamine infusions.

RESULTS

The baseline FC difference in the left LBA and the left precuneus between responders and non-responders among AD patients was found to be associated with depression improvement and was a significant predictor of treatment response to ketamine. A marked reduction in baseline LBA-precuneus FC after ketamine infusion was observed in responders. Unlike in patients with NAD, a lower right CMA-right middle temporal gyrus FC was found in AD patients.

LIMITATIONS

The sample size is rather small.

CONCLUSIONS

Our findings may suggest that amygdala FC is a significant predictor of treatment response to ketamine infusions in patients with AD. Further studies exploring the potential antidepressant mechanisms of ketamine may aid in the treatment of AD patients.

Exploring the course of adolescent anxiety and depression: associations with white matter tract microstructure

Cross-sectional Diffusion Tensor Imaging (DTI) studies have reported alterations in white matter (WM) microstructure in adolescents with internalizing psychopathology. Yet, longitudinal studies investigating the course of WM microstructure are lacking. This study explored WM alterations and its relation to clinical symptoms over time in adolescents with internalizing disorders. DTI scans were acquired at baseline and after three months in 22 adolescents with clinical depression and comorbid anxiety (INT), and 21 healthy peers (HC) (age: 12-18). Tract-based spatial statistics was used for three voxelwise analyses: i) changes in WM microstructure between and within the INT and HC group; ii) associations between changes in symptom severity and changes in WM microstructure within youths with INT; and iii) associations between baseline WM parameters with changes in symptom severity within youths with INT. Data did not reveal changes in WM microstructure between or within groups over three months' time nor associations between changes in WM microstructure and changes in self-reported symptoms (analyses corrected for age, gender and puberty stage). Lower baseline levels of fractional anisotropy (FA) in the right posterior corona radiata (PCR) and right cingulum were associated with a higher decrease of depressive symptoms within the INT group. Post hoc analysis of additional WM parameters in the significant FA clusters showed that higher levels of baseline mean diffusivity and radial diffusivity in the PCR were associated with a lower decrease in depressive symptoms. Baseline WM microstructure characteristics were associated with a higher decrease in depressive symptoms over time. These findings increase our understanding of neurobiological mechanisms underlying the course of internalizing disorders in adolescents.

Adolescent depression and resting-state fMRI brain networks: a scoping review of longitudinal studies

The neurobiological factors associated with the emergence of major depressive disorder (MDD) in adolescence are still unclear. Previous cross-sectional studies have documented aberrant connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) networks. However, whether these findings precede MDD onset has not been established. This scoping review mapped key methodological aspects and main findings of longitudinal rs-fMRI studies of MDD in adolescence. Three sets of neuroimaging methods to analyze rs-fMRI data were identified: seed-based analysis, independent component analysis, and network-based approaches. Main findings involved aberrant connectivity within and between the default mode network (DMN), the cognitive control network (CCN), and the salience network (SN). Accordingly, we utilized Menon's (2011) triple-network model for neuropsychiatric disorders to summarize key results. Adolescent MDD was associated with hyperconnectivity within the SN and between DMN and SN, as well as hypoconectivity within the CCN. These findings suggested that dysfunctional connectivity among the three main large-scale brain networks preceded MDD onset. However, there was high heterogeneity in neuroimaging methods and sampling procedures, which may limit comparisons between studies. Future studies should consider some level of harmonization for clinical instruments and neuroimaging methods.

A Double-Blind Randomized Trial to Investigate Mechanisms of Antidepressant-Related Dysfunctional Arousal in Depressed or Anxious Youth at Familial Risk for Bipolar Disorder

Antidepressants are standardly used to treat moderate to severe symptoms of depression and/or anxiety in youth but may also be associated with rare but serious psychiatric adverse events such as irritability, agitation, aggression, or suicidal ideation. Adverse events are especially common in youth with a family history of bipolar disorder (BD) who are at heightened risk for dysfunction in neurobiological systems that regulate emotion and arousal. To further understand this phenomenon, this study will examine (a) baseline risk factors associated with dysfunctional arousal in a sample of youth at high-risk for BD treated with or without an antidepressant, (b) whether antidepressant-related changes in arousal are mediated by changes in prefrontal-limbic circuitry, and (c) whether pharmacogenetic factors influence antidepressant-related changes in arousal. High-risk youth (aged 12-17 years with moderate to severe depressive and/or anxiety symptoms and at least one first-degree relative with bipolar I disorder) will be randomized to receive psychotherapy plus escitalopram or psychotherapy plus placebo. Neuroimaging and behavioral measures of arousal will be collected prior to randomization and at 4 weeks. Samples for pharmacogenetic analysis (serum escitalopram concentration, CYP2C19 metabolizer phenotype, and HTR2A and SLC6A4 genotypes) will be collected at 8 weeks. Youth will be followed for up to 16 weeks to assess change in arousal measures.

Neural correlates of affective control regions induced by common therapeutic strategies in major depressive disorders: An activation likelihood estimation meta-analysis study

In major depressive disorder (MDD), not only the pathophysiology of this disease is unknown but also the mechanisms of clinical efficacy across its therapeutic strategies are unclear. Although neuroimaging studies adopted activation likelihood estimation (ALE) approach to identify the convergent abnormalities of human brain in the MDD patients, the common alterations after antidepressant therapies were not summarized. Thus, we extracted the coordinates of brain regions in the MDD patients that showed differences in resting-state function, gray matter morphometry, and task-evoked neuronal responses after therapies. The ALE algorithm (GingerALE2.0.3) was employed in all 53 studies (64 experiments with 1406 MDD patients). Consistent results across treatment therapies were reported in the affective control network, including the bilateral thalamus, bilateral amygdala/parahippocampal gyrus, right anterior cingulate cortex/middle frontal gyrus, and right insular cortex/claustrum. Only electroconvulsive therapy partially replicated above findings. Our results indicate the antidepressant therapies efficiently influence core structures of the affective control network, which might be the underlying mechanism of remission in depression and provides potential targets for further treatment strategies.

Altered Resting-State Networks in Adolescent Non-Suicidal Self-Injury - A Graph Theory Analysis

Non-suicidal self-injury (NSSI) is a highly prevalent transdiagnostic symptom and risk marker for mental health problems among adolescents. Research on the neurobiological mechanisms underlying NSSI is needed to clarify the neural correlates associated with the behavior. We examined resting-state functional connectivity in n = 33 female adolescents aged 12–17 years engaging in NSSI, and in n = 29 age-matched healthy controls using graph theory. Mixed linear models were evaluated with the Bayes Factor to determine group differences on global and regional network measures and associations between network measures and clinical characteristics in patients. Adolescents engaging in NSSI demonstrated longer average characteristic path lengths and a smaller number of weighted hubs globally. Regional measures indicated lower efficiency and worse integration in (orbito)frontal regions and higher weighted coreness in the pericalcarine gyrus. In patients, higher orbitofrontal weighted local efficiency was associated with NSSI during the past month while lower pericalcarine nodal efficiency was associated with suicidal thoughts in the past year. Higher right but lower left pericalcarine weighted hubness was associated with more suicide attempts during the past year. Using a graph-based technique to identify functional connectivity networks, this study adds to the growing understanding of the neurobiology of NSSI.

Mapping the structure of depression biomarker research: A bibliometric analysis

BACKGROUND

Depression is a common mental disorder and the diagnosis is still based on the descriptions of symptoms. Biomarkers can reveal disease characteristics for diagnosis, prognosis, and treatment. In recent years, many biomarkers relevant to the mechanisms of depression have been identified. This study uses bibliometric methods and visualization tools to analyse the literature on depression biomarkers and its hot topics, and research frontiers to provide references for future research.

METHODS

Scientific publications related to depression biomarkers published between 2009 and 2022 were obtained from the Web of Science database. The BICOMB software was used to extract high-frequency keywords and to construct binary word-document and co-word matrices. gCLUTO was used for bicluster and visual analyses of high-frequency keywords. Further graphical visualizations were generated using R, CiteSpace and VOSviewer software.

RESULTS

A total of 14,403 articles related to depression biomarkers were identified. The United States (34.81%) and China (15.68%), which together account for more than half of all publications, can be considered the research base for the field. Among institutions, the University of California, University of London, and Harvard University are among the top in terms of publication number. Three authors (Maes M, Penninx B.W.J.H., and Berk M) emerged as eminent researchers in the field. Finally, eight research hotspots for depression biomarkers were identified using reference co-citation analysis.

CONCLUSION

This study used bibliometric methods to characterize the body of literature and subject knowledge in the field of depression biomarker research. Among the core biomarkers of depression, functional magnetic resonance imaging (fMRI), cytokines, and oxidative stress are relatively well established; however, research on machine learning, metabolomics, and microRNAs holds potential for future development. We found "microRNAs" and "gut microbiota" to be the most recent burst terms in the study of depression biomarkers and the likely frontiers of future research.

Effects of escitalopram therapy on resting-state functional connectivity of subsystems of the default mode network in unmedicated patients with major depressive disorder

Antidepressants are often the first-line medications prescribed for patients with major depressive disorder (MDD). Given the critical role of the default mode network (DMN) in the physiopathology of MDD, the current study aimed to investigate the effects of antidepressants on the resting-state functional connectivity (rsFC) within and between the DMN subsystems. We collected resting-state functional magnetic resonance imaging (rs-fMRI) data from 36 unmedicated MDD patients at baseline and after escitalopram treatment for 12 weeks. The rs-fMRI data were also collected from 61 matched healthy controls at the time point with the same interval. Then, we decomposed the DMN into three subsystems based on a template from previous studies and computed the rsFC within and between the three subsystems. Finally, repeated measures analysis of covariance was conducted to identify the main effect of group and time and their interaction effect. We found that the significantly reduced within-subsystem rsFC in the DMN core subsystem in patients with MDD at baseline was increased after escitalopram treatment and became comparable with that in the healthy controls, whereas the reduced within-subsystem rsFC persisted in the DMN dorsal medial prefrontal cortex (dMPFC) and medial temporal subsystems in patients with MDD following escitalopram treatment. In addition, the reduced between-subsystem rsFC between the core and dMPFC subsystem showed a similar trend of change after treatment in patients with MDD. Moreover, our main results were confirmed using the DMN regions from another brain atlas. In the current study, we found different effects of escitalopram on the rsFC of the DMN subsystems. These findings deepened our understanding of the neuronal basis of antidepressants' effect on brain function in patients with MDD. The trial name: appropriate technology study of MDD diagnosis and treatment based on objective indicators and measurement. URL: http://www.chictr.org.cn/showproj.aspx?proj=21377 . Registration number: ChiCTR-OOC-17012566.

Effective Connectivity of Right Amygdala Subregions Predicts Symptom Improvement Following 12-Week Pharmacological Therapy in Major Depressive Disorder

The low rates of treatment response still exist in the pharmacological therapy of major depressive disorder (MDD). Exploring an optimal neurological predictor of symptom improvement caused by pharmacotherapy is urgently needed for improving response to treatment. The amygdala is closely related to the pathological mechanism of MDD and is expected to be a predictor of the treatment. However, previous studies ignored the heterogeneousness and lateralization of amygdala. Therefore, this study mainly aimed to explore whether the right amygdala subregion function at baseline can predict symptom improvement after 12-week pharmacotherapy in MDD patients. We performed granger causality analysis (GCA) to identify abnormal effective connectivity (EC) of right amygdala subregions in MDD and compared the EC strength before and after 12-week pharmacological therapy. The results show that the abnormal EC mainly concentrated on the frontolimbic circuitry and default mode network (DMN). With relief of the clinical symptom, these abnormal ECs also change toward normalization. In addition, the EC strength of right amygdala subregions at baseline showed significant predictive ability for symptom improvement using a regularized least-squares regression predict model. These findings indicated that the EC of right amygdala subregions may be functionally related in symptom improvement of MDD. It may aid us to understand the neurological mechanism of pharmacotherapy and can be used as a promising predictor for symptom improvement in MDD.

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.

Functional impairment-based segmentation of anterior cingulate cortex in depression and its relationship with treatment effects

In major depressive disorder (MDD), the anterior cingulate cortex (ACC) is widely related to depression impairment and antidepressant treatment response. The multiplicity of ACC subdivisions calls for a fine‐grained investigation of their functional impairment and recovery profiles. We recorded resting state fMRI signals from 59 MDD patients twice before and after 12‐week antidepressant treatment, as well as 59 healthy controls (HCs). With functional connectivity (FC) between each ACC voxel and four regions of interests (bilateral dorsolateral prefrontal cortex [DLPFC] and amygdalae), subdivisions with variable impairment were identified based on groups' dissimilarity values between MDD patients before treatment and HC. The ACC was subdivided into three impairment subdivisions named as MedialACC, DistalACC, and LateralACC according to their dominant locations. Furthermore, the impairment pattern and the recovery pattern were measured based on group statistical analyses. DistalACC impaired more on its FC with left DLPFC, whereas LateralACC showed more serious impairment on its FC with bilateral amygdalae. After treatment, FCs between DistalACC and left DLPFC, and between LateralACC and right amygdala were normalized while impaired FC between LateralACC and left amygdala kept dysfunctional. Subsequently, FC between DistalACC and left DLPFC might contribute to clinical outcome prediction. Our approach could provide an insight into how the ACC was impaired in depression and partly restored after antidepressant treatment, from the perspective of the interaction between ACC subregions and critical frontal and subcortical regions.

Task MRI-Based Functional Brain Network of Major Depression

This chapter will focus on task magnetic resonance imaging (MRI) to understand the biological mechanisms and pathophysiology of brain in major depressive disorder (MDD), which would have minor alterations in the brain function. Therefore, the functional study, such as task MRI functional connectivity, would play a crucial role to explore the brain function in MDD. Different kinds of tasks would determine the alterations in functional connectivity in task MRI studies of MDD. The emotion-related tasks are linked with alterations in anterior cingulate cortex, insula, and default mode network. The emotional memory task is linked with amygdala-hippocampus alterations. The reward-related task would be related to the reward circuit alterations, such as fronto-straital. The cognitive-related tasks would be associated with frontal-related functional connectivity alterations, such as the dorsolateral prefrontal cortex, anterior cingulate cortex, and other frontal regions. The visuo-sensory characteristics of tasks might be associated with the parieto-occipital alterations. The frontolimbic regions might be major components of task MRI-based functional connectivity in MDD. However, different scenarios and tasks would influence the representations of results.

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.

The relationship between resting-state functional connectivity, antidepressant discontinuation and depression relapse

The risk of relapsing into depression after stopping antidepressants is high, but no established predictors exist. Resting-state functional magnetic resonance imaging (rsfMRI) measures may help predict relapse and identify the mechanisms by which relapses occur. rsfMRI data were acquired from healthy controls and from patients with remitted major depressive disorder on antidepressants. Patients were assessed a second time either before or after discontinuation of the antidepressant, and followed up for six months to assess relapse. A seed-based functional connectivity analysis was conducted focusing on the left subgenual anterior cingulate cortex and left posterior cingulate cortex. Seeds in the amygdala and dorsolateral prefrontal cortex were explored. 44 healthy controls (age: 33.8 (10.5), 73% female) and 84 patients (age: 34.23 (10.8), 80% female) were included in the analysis. 29 patients went on to relapse and 38 remained well. The seed-based analysis showed that discontinuation resulted in an increased functional connectivity between the right dorsolateral prefrontal cortex and the parietal cortex in non-relapsers. In an exploratory analysis, this functional connectivity predicted relapse risk with a balanced accuracy of 0.86. Further seed-based analyses, however, failed to reveal differences in functional connectivity between patients and controls, between relapsers and non-relapsers before discontinuation and changes due to discontinuation independent of relapse. In conclusion, changes in the connectivity between the dorsolateral prefrontal cortex and the posterior default mode network were associated with and predictive of relapse after open-label antidepressant discontinuation. This finding requires replication in a larger dataset.

Identification of common neural substrates with connectomic abnormalities in four major psychiatric disorders: A connectome-wide association study

Background

Recent imaging studies of large datasets suggested that psychiatric disorders have common biological substrates. This study aimed to identify all the common neural substrates with connectomic abnormalities across four major psychiatric disorders by using the data-driven connectome-wide association method of multivariate distance matrix regression (MDMR).

Methods

This study analyzed a resting functional magnetic resonance imaging dataset of 100 patients with schizophrenia, 100 patients with bipolar I disorder, 100 patients with bipolar II disorder, 100 patients with major depressive disorder, and 100 healthy controls (HCs). We calculated a voxel-wise 4,330 × 4,330 matrix of whole-brain functional connectivity (FC) with 8-mm isotropic resolution for each participant and then performed MDMR to identify structures where the overall multivariate pattern of FC was significantly different between each patient group and the HC group. A conjunction analysis was performed to identify common neural regions with FC abnormalities across these four psychiatric disorders.

Results

The conjunction of the MDMR maps revealed that the four groups of patients shared connectomic abnormalities in distributed cortical and subcortical structures, which included bilateral thalamus, cerebellum, frontal pole, supramarginal gyrus, postcentral gyrus, lingual gyrus, lateral occipital cortex, and parahippocampus. The follow-up analysis based on pair-wise FC of these regions demonstrated that these psychiatric disorders also shared similar patterns of FC abnormalities characterized by sensory/subcortical hyperconnectivity, association/subcortical hypoconnectivity, and sensory/association hyperconnectivity.

Conclusions

These findings suggest that major psychiatric disorders share common connectomic abnormalities in distributed cortical and subcortical regions and provide crucial support for the common network hypothesis of major psychiatric disorders.

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.

Neural effects of a single dose of fluoxetine on resting-state functional connectivity in adolescent depression

Fluoxetine is commonly prescribed in adolescent depression, but the neural mechanisms underlying its action remain poorly understood. Here, we used resting-state functional magnetic resonance imaging to investigate the effects of a single dose of fluoxetine vs. placebo in adolescents with major depressive disorder. In contrast with previous studies in adults that have demonstrated an acute effect of antidepressants on activity within the default mode network, a single dose of fluoxetine did not alter activity in this network in adolescent depression. There were unexpected group activity differences in the motor network, which should be clarified in future research.

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.

Resting-state functional connectivity of neural circuits associated with primary and secondary rewards in patients with bipolar disorder

Objective

We used resting-state functional connectivity (rsFC) to evaluate the integrity of the neural circuits associated with primary and secondary rewards in bipolar disorder (BD) with different mood phases.

Methods

Sixty patients with BD [21 patients with depressive episode of BD (BDD) and 41 patients with maniac episode of BD (BDM)] and 42 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. rsFC was assessed using region of interest-wise analyses.

Results

Attenuation of rsFC at the orbitofrontal cortex (OFC) and the left ventral striatum (LVS) was observed in the secondary reward circuit of patients with BD compared to that of HCs. Among BDD, BDM and HCs, the rsFC between OFC and LVS in BDM was intermediate, while the rsFC between OFC and right ventral striatum/right amygdala in BDM was the highest; the corresponding rsFC values in BDD were the lowest. Furthermore, a positive correlation was found between rsFC and Young Mania Rating Scale scores in BDM.

Conclusions

This study suggests that there may be an abnormal rsFC between OFC and LVS in the second reward of patients with BD and the discrepant patterns of rsFC may exist between different mood states in patients with BD.

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.

Neuroimaging Biomarkers for Predicting Treatment Response and Recurrence of Major Depressive Disorder

The acute treatment duration for major depressive disorder (MDD) is 8 weeks or more. Treatment of patients with MDD without predictors of treatment response and future recurrence presents challenges and clinical problems to patients and physicians. Recently, many neuroimaging studies have been published on biomarkers for treatment response and recurrence of MDD using various methods such as brain volumetric magnetic resonance imaging (MRI), functional MRI (resting-state and affective tasks), diffusion tensor imaging, magnetic resonance spectroscopy, near-infrared spectroscopy, and molecular imaging (i.e., positron emission tomography and single photon emission computed tomography). The results have been inconsistent, and we hypothesize that this could be due to small sample size; different study design, including eligibility criteria; and differences in the imaging and analysis techniques. In the future, we suggest a more sophisticated research design, larger sample size, and a more comprehensive integration including genetics to establish biomarkers for the prediction of treatment response and recurrence of MDD.

Disrupted intrinsic functional connectivity of the cognitive control network underlies disease severity and executive dysfunction in first-episode, treatment-naive adolescent depression

BACKGROUND

Previous neuroimaging studies have showed that imbalanced functional integration of distributed large-scale brain networks is associated with pathophysiological characteristics of major depressive disorder (MDD). However, the association between network integrative disturbances and clinical features and cognitive functions remains largely unclear in adolescent MDD. This study investigated the neural correlates of abnormal functional connectivity networks with clinical and cognitive characteristics in adolescent MDD.

METHODS

Twenty-eight first-episode, treatment-naive adolescents with MDD and 24 well-matched healthy controls (HCs) underwent functional magnetic resonance imaging (fMRI) and a battery of cognitive tests. A seed-based functional connectivity (FC) approach was used to depict connectivity patterns of the cognitive control network (CCN), affective network (AN) and default mode network (DMN), whose between-group differences were correlated with clinical variables and cognitive functions in the patients.

RESULTS

Compared with the HCs, the MDD patients exhibited impaired executive functions. The FC analysis revealed lower CCN FC with the temporal, parietal and frontal regions and the limbic system, higher AN FC with the temporal and occipital regions and the cerebellum, and lower DMN FC with the cerebellum and insula. Interestingly, the decreased CCN FC was related to disease severity (with the inferior frontal gyrus) and executive dysfunctions (with the middle cingulate gyrus and supramarginal gyrus) in the patients.

LIMITATIONS

The main limitations were the relatively small sample size and suboptimal imaging parameters.

CONCLUSION

Functional alteration of CCN during the developmentally sensitive period may be important in the neurobiology of adolescent MDD.

Individual-specific functional connectivity of the amygdala: A substrate for precision psychiatry

The amygdala is central to the pathophysiology of many psychiatric illnesses. An imprecise understanding of how the amygdala fits into the larger network organization of the human brain, however, limits our ability to create models of dysfunction in individual patients to guide personalized treatment. Therefore, we investigated the position of the amygdala and its functional subdivisions within the network organization of the brain in 10 highly sampled individuals (5 h of fMRI data per person). We characterized three functional subdivisions within the amygdala of each individual. We discovered that one subdivision is preferentially correlated with the default mode network; a second is preferentially correlated with the dorsal attention and fronto-parietal networks; and third subdivision does not have any networks to which it is preferentially correlated relative to the other two subdivisions. All three subdivisions are positively correlated with ventral attention and somatomotor networks and negatively correlated with salience and cingulo-opercular networks. These observations were replicated in an independent group dataset of 120 individuals. We also found substantial across-subject variation in the distribution and magnitude of amygdala functional connectivity with the cerebral cortex that related to individual differences in the stereotactic locations both of amygdala subdivisions and of cortical functional brain networks. Finally, using lag analyses, we found consistent temporal ordering of fMRI signals in the cortex relative to amygdala subdivisions. Altogether, this work provides a detailed framework of amygdala-cortical interactions that can be used as a foundation for models relating aberrations in amygdala connectivity to psychiatric symptoms in individual patients.

SSRI Treatment Response Prediction in Depression Based on Brain Activation by Emotional Stimuli

Introduction: The prediction of antidepressant treatment response may improve outcome. Functional magnetic resonance imaging (fMRI) of emotion processing in major depressive disorder (MDD) may reveal regional brain function serving as predictors of response to treatment with selective serotonin reuptake inhibitor (SSRI). Methods: We examined the association between pre-treatment neural activity by means of fMRI during the perception of emotional stimuli in 22 patients with MDD and the treatment outcome after 6 weeks' medication with an SSRI. A whole brain correlation analysis with Beck Depression Inventory (BDI) change between pre- to post-treatment was conducted to identify neural regions associated with treatment response. Results: During the perception of positive stimuli, responders were characterized by more activation in posterior cingulate cortex (PCC), medial prefrontal cortex, and thalamus as well as middle temporal gyrus. During perception of negative stimuli, PCC, and pregenual anterior cingulate cortex showed the highest correlation with treatment response. Furthermore, responders exhibited higher activation to emotional stimuli than to neutral stimuli in all the above-mentioned regions, while non-responders demonstrated an attenuated neural response to emotional compared to neutral stimuli. Conclusion: Our data suggest that the activity of distinct brain regions is correlated with SSRI treatment outcome and may serve as treatment response predictor. While some regions, in which activity was correlated with treatment response, can be assigned to networks that have been implied in the pathophysiology of depression, most of our regions of interest could also be matched to the default mode network (DMN). Higher DMN activity has been associated with increased rumination as well as negative self-referential processing in previous studies. This may suggest our responders to SSRI to be characterized by such dysregulations and that SSRIs might modify the function associated with this network.

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.

Psychoradiological Biomarkers for Psychopharmaceutical Effects

The application of personalized medicine to psychiatry is challenging. Psychoradiology could provide biomarkers based on objective tests in support of the diagnostic classifications and treatment planning. We review potential psychoradiological biomarkers for psychopharmaceutical effects. Although none of the biomarkers reviewed are yet of sufficient clinical utility to inform the selection of a specific pharmacologic compound for an individual patient, there is strong consensus that advanced multimodal approaches will contribute to discovery of novel treatment predictors in psychiatric disorders. Progress has been sufficient to warrant enthusiasm, in which application of neuroimaging-based biomarkers would represent a paradigm shift and modernization of psychiatric practice.

Identification of Common Thalamocortical Dysconnectivity in Four Major Psychiatric Disorders

BACKGROUND

Recent genetic and imaging analyses of large datasets suggested that common biological substrates exist across psychiatric diagnoses. Functional connectivity (FC) abnormalities of thalamocortical circuits were consistently found in patients with schizophrenia but have been less studied in other major psychiatric disorders. This study aimed to examine thalamocortical FC in 4 major psychiatric disorders to identify the common connectivity abnormalities across major psychiatric disorders.

METHODS

This study recruited 100 patients with schizophrenia, 100 patients with bipolar I disorder, 88 patients with bipolar II disorder, 100 patients with major depressive disorder, and 160 healthy controls (HCs). Each participant underwent resting functional magnetic resonance imaging. The thalamus was used to derive FC maps, and group comparisons were made between each patient group and HCs using an independent-sample t test. Conjunction analysis was used to identify the common thalamocortical abnormalities among these 4 psychiatric disorders.

RESULTS

The 4 groups of patients shared a similar pattern of thalamocortical dysconnectivity characterized by a decrease in thalamocortical FC with the dorsal anterior cingulate, anterior prefrontal cortex and inferior parietal cortex. The groups also showed an increase in FC with the postcentral gyrus, precentral gyrus, superior temporal cortex, and lateral occipital areas. Further network analysis demonstrated that the frontoparietal regions showing hypoconnectivity belonged to the salience network.

CONCLUSION

Our findings provide FC evidence that supports the common network hypothesis by identifying common thalamocortical dysconnectivities across 4 major psychiatric disorders. The network analysis also supports the cardinal role of salience network abnormalities in major psychiatric disorders.

The Canadian Biomarker Integration Network in Depression (CAN-BIND): magnetic resonance imaging protocols

Studies of clinical populations that combine MRI data generated at multiple sites are increasingly common. The Canadian Biomarker Integration Network in Depression (CAN-BIND; www.canbind.ca) is a national depression research program that includes multimodal neuroimaging collected at several sites across Canada. The purpose of the current paper is to provide detailed information on the imaging protocols used in a number of CAN-BIND studies. The CAN-BIND program implemented a series of platform-specific MRI protocols, including a suite of prescribed structural and functional MRI sequences supported by real-time monitoring for adherence and quality control. The imaging data are retained in an established informatics and databasing platform. Approximately 1300 participants are being recruited, including almost 1000 with depression. These include participants treated with antidepressant medications, transcranial magnetic stimulation, cognitive behavioural therapy and cognitive remediation therapy. Our ability to analyze the large number of imaging variables available may be limited by the sample size of the substudies. The CAN-BIND program includes a multimodal imaging database supported by extensive clinical, demographic, neuropsychological and biological data from people with major depression. It is a resource for Canadian investigators who are interested in understanding whether aspects of neuroimaging — alone or in combination with other variables — can predict the outcomes of various treatment modalities.

Neural Correlates of Suicidality in Adolescents with Major Depression: Resting-State Functional Connectivity of the Precuneus and Posterior Cingulate Cortex

OBJECTIVE

Major depressive disorder (MDD) is associated with suicidal thoughts and behaviors ("suicidality"). Of the three components of Joiner's interpersonal theory of suicide, two involve negatively valenced, self-related beliefs: perceived burdensomeness and thwarted belongingness. However, the neurocircuitry underlying self-processing and suicidality has not been fully explored. This study examined the association between suicidality and the neurocircuitry of regions relevant to self-referential processing in adolescents with depression.

METHOD

Fifty-eight adolescents underwent assessment and a resting-state fMRI scan. Resting-state functional connectivity (RSFC) analyses included two brain regions implicated in self-referential processing: precuneus and posterior cingulate cortex (PCC). Suicidality was measured using the Index of Depression and Anxiety Symptoms. While controlling for depression severity, we conducted whole-brain correlation analyses between suicidality and left and right precuneus and PCC connectivity maps.

RESULTS

Suicidality was positively associated with RSFC between left precuneus and left primary motor and somatosensory cortices, and middle and superior frontal gyri. Suicidality was negatively associated with RSFC between left PCC and left cerebellum, lateral occipital cortex, and temporal-occipital fusiform gyrus.

CONCLUSIONS

Findings of hyperconnectivity stemming from the precuneus and hypoconnectivity from the PCC may reflect maladaptive self-reflection and mentalization. However, additional investigation is warranted to further clarify these relationships.

Brain structural thickness and resting state autonomic function in adolescents with major depression

Major depressive disorder (MDD) has been associated with abnormalities in cortical thickness and autonomic function. Adolescence is a time notable for brain development and MDD onset. In healthy adolescents, greater resting state vagal activity (RVA) is associated with lower cortical thickness. The relationship between brain structural thickness and RVA in adolescents with MDD has not previously been studied. This secondary analysis drew on a sample of 37 non-depressed controls and 53 adolescents with MDD. Resting state heart rate and two indices of RVA (HF-HRV and RMSSD) were recorded during a neuroimaging session. Cortical thickness within fronto-limbic regions of interest was measured using Freesurfer analysis of T1-weighted high-resolution structural images. Self-reports of depression severity showed a significant interaction with cortical thickness of the right insula in predicting RMSSD [t = 2.22, P=0.030, β = 5.44; model fit of the interaction term as indicated by the ‘Bayes Factor’ (BF): 7.58] and HF-HRV (t = 2.09, P=0.041, β = 4.72; BF: 7.94). Clinician ratings of depression severity showed further interactions. Findings underscore the important relationships between RVA and cortical development, suggesting two possible explanations: (i) in adolescent MDD, greater fronto-limbic thickness is compensatory for deficits in autonomic regulation or (ii) increased autonomic arousal results in delayed fronto-limbic maturation. Longitudinal research is necessary to further clarify the nature of the relationship between autonomic functioning and cortical development.

Hypoconnectivity of insular resting-state networks in adolescents with Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is characterized by deficits in social interaction and communication. The anterior insula (AI) participates in emotional salience detection; and the posterior insula (PI) participates in sensorimotor integration and response selection. Meta-analyses have noted insula-based aberrant connectivity within ASD. Given the observed social impairments in ASD and the role of the insula in social information processing (SIP), investigating functional organization of this structure in ASD is important. We investigated differences in resting-state functional connectivity (RSFC) using fMRI in male youths with (N=13; mean=14.6 years; range: 10.2-18.0 years) and without ASD (N=17; mean=14.5 years; range: 10.0-17.5 years). With seed-based FC measures, we compared RSFC in insular networks. Hypoconnectivity was observed in ASD (AI-superior frontal gyrus (SFG); AI-thalamus; PI-inferior parietal lobule (IPL); PI-fusiform gyrus (FG); PI-lentiform nucleus/putamen). Using the Social Communication Questionnaire (SCQ) to assess social functioning, regression analyses yielded negative correlations between SCQ scores and RSFC (AI-SFG; AI-thalamus; PI-FG; PI-IPL). Given the insula's connections to limbic regions, and its role in integrating external sensory stimuli with internal states, atypical activity in this structure may be associated with social deficits characterizing ASD. Our results suggest further investigation of the insula's role in SIP across a continuum of social abilities is needed.

A single dose of fluoxetine reduces neural limbic responses to anger in depressed adolescents

Depression in adolescence is frequently characterised by symptoms of irritability. Fluoxetine is the antidepressant with the most favourable benefit:risk ratio profile to treat adolescent depression, but the neural mechanisms underlying antidepressant drugs in the young brain are still poorly understood. Previous studies have characterised the neural effects of long-term fluoxetine treatment in depressed adolescents, but these are limited by concurrent mood changes and a lack of placebo control. There is also recent evidence suggesting that fluoxetine reduces the processing of anger in young healthy volunteers, which is consistent with its effect for the treatment of irritability in this age group, but this remains to be investigated in depressed adolescents. Here we assessed the effects of a single, first dose of 10 mg fluoxetine vs. placebo on neural response to anger cues using fMRI in a sample of adolescents with Major Depressive Disorder (MDD) who had been recently prescribed fluoxetine. As predicted, adolescents receiving fluoxetine showed reduced activity in response to angry facial expressions in the amygdala-hippocampal region relative to placebo. Activity in the dorsal anterior cingulate cortex (dACC) was also increased. No changes in symptoms were observed. These results demonstrate, for the first time in depressed adolescents, that fluoxetine has immediate neural effects on core components of the cortico-limbic circuitry prior to clinical changes in mood. The effect on anger is consistent with our previous work and could represent a key mechanism through which fluoxetine may act to alleviate irritability symptoms in adolescent depression.

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.