Duloxetine effects on striatal resting-state functional connectivity in patients with major depressive disorder

Neural activation signatures in individuals with subclinical depression: A task-fMRI meta-analysis

BACKGROUND

Previous task-related functional magnetic resonance imaging (task-fMRI) investigations have documented abnormal brain activation associated with subclinical depression (SD), defined as a clinically relevant level of depressive symptoms that does not meet the diagnostic criteria for major depressive disorder. However, these task-fMRI studies have not reported consistent conclusions. Performing a voxel-based meta-analysis of task-fMRI studies may yield reliable findings.

METHODS

We extracted the peak coordinates and t values of included studies and analyzed brain activation between individuals with SD and healthy controls (HCs) using anisotropic effect-size signed differential mapping (AES-SDM).

RESULTS

A systematic literature search identified eight studies, including 266 individuals with SD and 281 HCs (aged 14 to 25). The meta-analysis showed that individuals with SD exhibited significantly greater activation in the right lenticular nucleus and putamen according to task-fMRI. The meta-regression analysis revealed a negative correlation between the proportion of females in a group and activation in the right striatum.

LIMITATIONS

The recruitment criteria for individuals with SD, type of tasks and MRI acquisition parameters of included studies were heterogeneous. The results should be interpreted cautiously due to insufficient included studies.

CONCLUSION

Our findings suggest that individuals with SD exhibit increased activation in the right lenticular nucleus, putamen and striatum, which may indicate a compensatory increase in response to an impairment of insular and striatal function caused by depression. These results provide valuable insights into the potential pathophysiology of brain dysfunction in SD.

Striatal Functional Alterations Link to Distinct Symptomatology Across Mood States in Bipolar Disorder

BACKGROUND

As a central hub in cognitive and emotional brain circuits, the striatum is considered likely to be integrally involved in the psychopathology of bipolar disorder (BD). However, it remains unclear how alterations in striatal function contribute to distinct symptomatology of BD during different mood states.

METHODS

Behavioral assessment (i.e., emotional symptoms and cognitive performance) and neuroimaging data were collected from 125 participants comprising 31 (hypo)manic, 31 depressive, and 31 euthymic patients with BD, and 32 healthy control participants. We compared the functional connectivity (FC) of striatal subregions across BD mood states with healthy control participants and then used a multivariate data-driven approach to explore dimensional associations between striatal connectivity and behavioral performance. Finally, we compared the FC and behavioral composite scores, which reflect the individual weighted representation of the associations, among different mood states.

RESULTS

Patients in all mood states exhibited increased FC between the bilateral ventral rostral putamen and ventrolateral thalamus. Bipolar (hypo)mania uniquely exhibited increased ventral rostral putamen connectivity and superior ventral striatum connectivity. One latent component was identified, whereby increased FCs of striatal subregions were associated with distinct psychopathological symptomatology (more manic symptoms, elevated positive mood, less depressive symptoms, and worse cognitive performance). Patients with bipolar (hypo)mania had the highest FC and behavioral composite scores while bipolar patients with depression had the lowest scores.

CONCLUSIONS

Our data demonstrated both trait features of BD and state features specific to bipolar (hypo)mania. The findings underscored the fundamental role of the striatum in the pathophysiological processes underlying specific symptomatology across all mood states.

Altered functional brain activity in first-episode major depressive disorder treated with electro-acupuncture: A resting-state functional magnetic resonance imaging study

Background

Previous studies have found electroacupuncture could improve the clinical symptoms of first-episode major depressive disorder (MDD), but the exact neural mechanism of action needs to be further elucidated.

Methods

Twenty-eight first-episode MDD patients were randomly divided into 14 electro-acupuncture stimulation (EAS) groups and 14 sham-acupuncture stimulation (SAS) groups, and clinical symptoms were assessed and functional magnetic resonance imaging (fMRI) scans were done in both groups. Amplitude of low-frequency fluctuations (ALFF) was used to observe the changes between the pre-treatment and post-treatment in the two groups, and the altered brain areas were selected as region of interest (ROI) to observe the FC changes. Meanwhile, the correlation between the altered clinical symptoms and the altered ALFF and FC of brain regions in the two groups was analyzed.

Results

The EAS significantly decreased the HAMD-24 and HAMA-14 scores of MDD than SAS group. The imaging results revealed that both groups were able to increase the ALFF of the left middle temporal gyrus and the left cerebellar posterior lobe. When using the left middle temporal gyrus and the left posterior cerebellar lobe as ROIs, EAS group increased the FC between the left middle temporal gyrus with the left superior frontal gyrus, the left middle frontal gyrus, and the left hippocampus, and decreased the FC between the left posterior cerebellar lobe and the left calcarine gyrus, while SAS group only increased the FC between the left middle temporal gyrus with the left superior frontal gyrus. The alternations in clinical symptoms after EAS treatment were positively correlated with the altered ALFF values in the left middle temporal gyrus and the altered FC values in the left middle temporal gyrus and the left middle frontal gyrus.

Conclusion

EA demonstrates modulation of functional activity in the default mode network (DMN), sensorimotor network (SMN), cognitive control network (CCN), limbic system, and visual network (VN) for the treatment of the first-episode MDD. Our findings contribute to the neuroimaging evidence for the efficacy of EAS.

Functional connectivity between the habenula and posterior default mode network contributes to the response of the duloxetine effect in major depressive disorder

This study aims to investigate the functional connectivity (FC) changes of the habenula (Hb) among patients with major depressive disorder (MDD) after 12 weeks of duloxetine treatment (MDD12). Patients who were diagnosed with MDD for the first time and were drug-naïve were recruited at baseline as cases. Healthy controls (HCs) matched for sex, age, and education level were also recruited at the same time. At baseline, all participants underwent resting-state functional MRI. FC analyses were performed using the Hb seed region of interest, and three groups including HCs, MDD group and MDD12 group were compared using whole-brain voxel-wise comparisons. Compared to the HCs, the MDD group had decreased FC between the Hb and the right anterior cingulate cortex at baseline. Compared to the HCs, the FC between the Hb and the left medial superior frontal gyrus decreased in the MDD12 group. Additionally, the FC between the left precuneus, bilateral cuneus and Hb increased in the MDD12 group than that in the MDD group. No significant correlation was found between HDRS-17 and the FC between the Hb, bilateral cuneus, and the left precuneus in the MDD12 group. Our study suggests that the FC between the post-default mode network and Hb may be the treatment mechanism of duloxetine and the treatment mechanisms and the pathogenesis of depression may be independent of each other.

A distinctive subcortical functional connectivity pattern linking negative affect and treatment outcome in major depressive disorder

Major depressive disorder (MDD) is associated with functional disturbances in subcortical regions. In this naturalistic prospective study (NCT03294525), we aimed to investigate relationships among subcortical functional connectivity (FC), mood symptom profiles and treatment outcome in MDD using multivariate methods. Medication-free participants with MDD (n = 135) underwent a functional magnetic resonance imaging scan at baseline and completed posttreatment clinical assessment after 8 weeks of antidepressant monotherapy. We used partial least squares (PLS) correlation analysis to explore the association between subcortical FC and mood symptom profiles. FC score, reflecting the weighted representation of each individual in this association, was computed. Replication analysis was undertaken in an independent sample (n = 74). We also investigated the relationship between FC score and treatment outcome in the main sample. A distinctive subcortical connectivity pattern was found to be associated with negative affect. In general, higher FC between the caudate, putamen and thalamus was associated with greater negative affect. This association was partly replicated in the independent sample (similarity between the two samples: r = 0.66 for subcortical connectivity, r = 0.75 for mood symptom profile). Lower FC score predicted both remission and response to treatment after 8 weeks of antidepressant monotherapy. The emphasis here on the role of dorsal striatum and thalamus consolidates prior work of subcortical connectivity in MDD. The findings provide insight into the pathogenesis of MDD, linking subcortical FC with negative affect. However, while the FC score significantly predicted treatment outcome, the low odds ratio suggests that finding predictive biomarkers for depression remains an aspiration.

Uncovering the Neural Correlates of Anhedonia Subtypes in Major Depressive Disorder: Implications for Intervention Strategies

Major depressive disorder (MDD) represents a serious public health concern, negatively affecting individuals' quality of life and making a substantial contribution to the global burden of disease. Anhedonia is a core symptom of MDD and is associated with poor treatment outcomes. Variability in anhedonia components within MDD has been observed, suggesting heterogeneity in psychopathology across subgroups. However, little is known about anhedonia subgroups in MDD and their underlying neural correlates across subgroups. To address this question, we employed a hierarchical cluster analysis based on Temporal Experience of Pleasure Scale subscales in 60 first-episode, drug-naive MDD patients and 32 healthy controls. Then we conducted a connectome-wide association study and whole-brain voxel-wise functional analyses for identified subgroups. There were three main findings: (1) three subgroups with different anhedonia profiles were identified using a data mining approach; (2) several parts of the reward network (especially pallidum and dorsal striatum) were associated with anticipatory and consummatory pleasure; (3) different patterns of within- and between-network connectivity contributed to the disparities of anhedonia profiles across three MDD subgroups. Here, we show that anhedonia in MDD is not uniform and can be categorized into distinct subgroups, and our research contributes to the understanding of neural underpinnings, offering potential treatment directions. This work emphasizes the need for tailored approaches in the complex landscape of MDD. The identification of homogeneous, stable, and neurobiologically valid MDD subtypes could significantly enhance our comprehension and management of this multifaceted condition.

Altered Effective Connectivity Among the Cerebellum and Cerebrum in Patients with Major Depressive Disorder Using Multisite Resting-State fMRI

Major depressive disorder (MDD) is a serious and widespread psychiatric disorder. Previous studies mainly focused on cerebrum functional connectivity, and the sample size was relatively small. However, functional connectivity is undirected. And, there is increasing evidence that the cerebellum is also involved in emotion and cognitive processing and makes outstanding contributions to the symptomology and pathology of depression. Therefore, we used a large sample size of resting-state functional magnetic resonance imaging (rs-fMRI) data to investigate the altered effective connectivity (EC) among the cerebellum and other cerebral cortex in patients with MDD. Here, from the perspective of data-driven analysis, we used two different atlases to divide the whole brain into different regions and analyzed the alterations of EC and EC networks in the MDD group compared with healthy controls group (HCs). The results showed that compared with HCs, there were significantly altered EC in the cerebellum-neocortex and cerebellum-basal ganglia circuits in MDD patients, which implied that the cerebellum may be a potential biomarker of depressive disorders. And, the alterations of EC brain networks in MDD patients may provide new insights into the pathophysiological mechanisms of depression.

Brain connectivity in major depressive disorder: a precision component of treatment modalities?

Major depressive disorder (MDD) is a very prevalent mental disorder that imposes an enormous burden on individuals, society, and health care systems. Most patients benefit from commonly used treatment methods such as pharmacotherapy, psychotherapy, electroconvulsive therapy (ECT), and repetitive transcranial magnetic stimulation (rTMS). However, the clinical decision on which treatment method to use remains generally informed and the individual clinical response is difficult to predict. Most likely, a combination of neural variability and heterogeneity in MDD still impedes a full understanding of the disorder, as well as influences treatment success in many cases. With the help of neuroimaging methods like functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), the brain can be understood as a modular set of functional and structural networks. In recent years, many studies have investigated baseline connectivity biomarkers of treatment response and the connectivity changes after successful treatment. Here, we systematically review the literature and summarize findings from longitudinal interventional studies investigating the functional and structural connectivity in MDD. By compiling and discussing these findings, we recommend the scientific and clinical community to deepen the systematization of findings to pave the way for future systems neuroscience roadmaps that include brain connectivity parameters as a possible precision component of the clinical evaluation and therapeutic decision.

The functional connectivity between left insula and left medial superior frontal gyrus underlying the relationship between rumination and procrastination

Procrastination is regarded as a prevalent problematic behavior that impairs people's physical and mental health. Although previous studies have indicated that trait rumination is robustly positively correlated with procrastination, it remains unknown about the neural substrates underlying the relationship between trait rumination and procrastination. To address this issue, we used voxel-based morphometry (VBM) and resting-state functional connectivity (RSFC) approaches to explore the neural basis of the relationship between trait rumination and procrastination. Our behavior results found that trait rumination was significantly positively correlated to procrastination, while the VBM analysis showed that trait rumination was negatively correlated with gray matter volume of the insula. Furthermore, the RSFC results revealed a negative association of the left insula-lmSFG (left medial superior frontal gyrus) functional connectivity with trait rumination. More importantly, the mediation analysis showed that trait rumination could completely mediate the relationship between left insula-lmSFG functional connectivity and procrastination. These results suggest that the left insula-lmSFG functional connectivity involved in emotion regulation modulates the association between trait rumination and procrastination, which provides neural evidence for the relationship between trait rumination and procrastination.

Prolonged Longitudinal Transcutaneous Auricular Vagus Nerve Stimulation Effect on Striatal Functional Connectivity in Patients with Major Depressive Disorder

BACKGROUND

Transcutaneous auricular vagus nerve stimulation (taVNS) is effective for treating major depressive disorder (MDD). We aimed to explore the modulating effect of prolonged longitudinal taVNS on the striatal subregions' functional connectivity (FC) in MDD patients.

METHODS

Sixteen MDD patients were enrolled and treated with taVNS for 8 weeks. Sixteen healthy control subjects (HCs) were recruited without intervention. The resting-state FC (rsFC) based on striatal subregion seed points and the Hamilton Depression Scale (HAMD) were evaluated in the MDD patients and HCs at baseline and after 8 weeks. A two-way ANCOVA test was performed on each rsFC metric to obtain the (group-by-time) interactions.

RESULTS

The rsFC values between the left ventral caudate (vCa) and right ventral prefrontal cortex (vPFC), and between the right nucleus accumbens (NAc) and right dorsal medial prefrontal cortex (dmPFC) and ventrolateral prefrontal cortex (vlPFC) are lower in the MDD patients compared to the HCs at baseline, and increase following taVNS; the rsFC values between the left vCa and right, superior occipital gyrus (SOG), and between the left dorsal caudate (dCa) and right cuneus are higher in MDD patients and decrease following taVNS.

CONCLUSIONS

Prolonged longitudinal taVNS can modulate the striatum rsFC with the prefrontal cortex, occipital cortex, temporal cortex, and intra-striatum, and these changes partly underlie any symptomatic improvements. The results indicate that prolonged longitudinal taVNS may produce beneficial treatment effects by modulating the cortical striatum circuitry in patients with MDD.

MRI predictors of pharmacotherapy response in major depressive disorder

Major depressive disorder is among the most prevalent psychiatric disorders, exacting a substantial personal, social, and economic toll. Antidepressant treatment typically involves an individualized trial and error approach with an inconsistent success rate. Despite a pressing need, no reliable biomarkers for predicting treatment outcome have yet been discovered. Brain MRI measures hold promise in this regard, though clinical translation remains elusive. In this review, we summarize structural MRI and functional MRI (fMRI) measures that have been investigated as predictors of treatment outcome. We broadly divide these into five categories including three structural measures: volumetric, white matter burden, and white matter integrity; and two functional measures: resting state fMRI and task fMRI. Currently, larger hippocampal volume is the most widely replicated predictor of successful treatment. Lower white matter hyperintensity burden has shown robustness in late life depression. However, both have modest discriminative power. Higher fractional anisotropy of the cingulum bundle and frontal white matter, amygdala hypoactivation and anterior cingulate cortex hyperactivation in response to negative emotional stimuli, and hyperconnectivity within the default mode network (DMN) and between the DMN and executive control network also show promise as predictors of successful treatment. Such network-focused measures may ultimately provide a higher-dimensional measure of treatment response with closer ties to the underlying neurobiology.

The Effects of CPAP Treatment on Resting-State Network Centrality in Obstructive Sleep Apnea Patients

Background and Objectives

Obstructive sleep apnea (OSA) is the most common sleep disorder and previous studies have shown that OSA patients suffer from brain network impairments associated with cognitive deficits, and continuous positive airway pressure (CPAP) treatment can improve clinical symptoms. However, the relationship between CPAP treatment and brain network changes remains unclear. This study explored the characteristics of brain network changes in OSA patients before (pre-CPAP) and after one month of CPAP treatment (post-CPAP).

Methods

We collected data, including sleep monitoring, clinical assessment, and magnetic resonance imaging scans, from 21 OSA patients and 21 age-matched healthy controls (HCs). Voxel-level degree centrality (DC) was used to assess whole-brain network connectivity characteristics, a two-sample t-test was used to compare network differences between pre-CPAP OSA patients and HCs, and a paired sample t-test was used to compare the characteristics of brain network changes in OSA patients before and after treatment. The correlations between the DC value and each of the clinical variables were analyzed in the OSA patients.

Results

Compared with HCs, pre-CPAP OSA patients showed increased DC values in the bilateral cerebellar posterior lobes (CPLs) and decreased DC values in the right superior temporal gyrus, left superior frontal gyrus and right middle frontal gyrus. Compared with pre-CPAP OSA patients, post-CPAP OSA patients showed reduced DC values in the bilateral CPL and increased DC values in several brain regions in the frontal, temporal, and insular lobes after CPAP treatment. The Montreal Cognitive Assessment MoCA (MoCA) scores were positively correlated with the DC value of the bilateral cerebellum posterior lobe, right middle temporal gyrus, left superior temporal gyrus, left paracentral lobule and left paracentral lobule. Also, Pittsburgh Sleep Quality Index (PSQI) scores were negatively correlated with the DC value of the right middle temporal gyrus in post-CPAP OSA patients.

Conclusion

CPAP treatment can effectively reverse the compensatory response of the bilateral CPL and functional network damage brought about by OSA, which may provide potential neuroimaging biomarkers for CPAP treatment evaluation.

Serotonin-norepinephrine reuptake inhibitor antidepressant effects on regional connectivity of the thalamus in persistent depressive disorder: evidence from two randomized, double-blind, placebo-controlled clinical trials

Previous neuroimaging studies have shown that serotonin-norepinephrine reuptake inhibitor antidepressants alter functional activity in large expanses of brain regions. However, it is not clear how these regions are systemically organized on a connectome level with specific topological properties, which may be crucial to revealing neural mechanisms underlying serotonin-norepinephrine reuptake inhibitor treatment of persistent depressive disorder. To investigate the effect of serotonin-norepinephrine reuptake inhibitor antidepressants on brain functional connectome reconfiguration in persistent depressive disorder and whether this reconfiguration promotes the improvement of clinical symptoms, we combined resting-state functional magnetic resonance imaging (fMRI) scans acquired in two randomized, double-blind, placebo-controlled trial studies of serotonin-norepinephrine reuptake inhibitor antidepressant treatment of patients with persistent depressive disorder. One was a randomized, double-blind, placebo-controlled trial of 10-week duloxetine medication treatment, which included 17 patients in duloxetine group and 17 patients in placebo group (ClinicalTrials.gov Identifier: NCT00360724); the other one was a randomized, double-blind, placebo-controlled trial of 12-week desvenlafaxine medication treatment, which included 16 patients in desvenlafaxine group and 15 patients in placebo group (ClinicalTrials.gov Identifier: NCT01537068). The 24-item Hamilton Depression Rating Scale was used to measure clinical symptoms, and graph theory was employed to examine serotonin-norepinephrine reuptake inhibitor antidepressant treatment effects on the topological properties of whole-brain functional connectome of patients with persistent depressive disorder. We adopted a hierarchical strategy to examine the topological property changes caused by serotonin-norepinephrine reuptake inhibitor antidepressant treatment, calculated their small-worldness, global integration, local segregation and nodal clustering coefficient in turn. Linear regression analysis was used to test associations of treatment, graph properties changes and clinical symptom response. Symptom scores were more significantly reduced after antidepressant than placebo administration (η 2 = 0.18). There was a treatment-by-time effect that optimized the functional connectome in a small-world manner, with increased global integration and increased nodal clustering coefficient in the bilateral thalamus (left thalamus η 2 = 0.21; right thalamus η 2 = 0.23). The nodal clustering coefficient increment of the right thalamus (ratio = 29.86; 95% confidence interval, -4.007 to -0.207) partially mediated the relationship between treatment and symptom improvement, and symptom improvement partially mediated (ratio = 21.21; 95% confidence interval, 0.0243-0.444) the relationship between treatment and nodal clustering coefficient increments of the right thalamus. Our study may indicate a putative mutually reinforcing association between nodal clustering coefficient increment of the right thalamus and symptom improvement from serotonin-norepinephrine reuptake inhibitor antidepressant treatments with duloxetine or desvenlafaxine.

Predicting escitalopram treatment response from pre-treatment and early response resting state fMRI in a multi-site sample: A CAN-BIND-1 report

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Baseline measures alone not able to predict escitalopram response above default.

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This poor baseline performance contradicts results from smaller studies.

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Accuracy improved using change in functional connectivity from baseline to week 2.

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Measures of early change following treatment may be crucial for accurate prediction.

Many previous intervention studies have used functional magnetic resonance imaging (fMRI) data to predict the antidepressant response of patients with major depressive disorder (MDD); however, practical constraints have limited many of those attempts to small, single centre studies which may not adequately reflect how these models will generalize when used in clinical practice. Not only does the act of collecting data at multiple sites generally increase sample sizes (a critical point in machine learning development) it also generates a more heterogeneous dataset due to systematic differences in scanners at different sites, and geographical differences in patient populations. As part of the Canadian Biomarker Integration Network in Depression (CAN-BIND-1) study, 144 MDD patients from six sites underwent resting state fMRI prior to starting escitalopram treatment, and again two weeks after the start. Here, we consider ways to use machine learning techniques to produce models that can predict response (measured at eight weeks after initiation), based on various parcellations, functional connectivity (FC) metrics, dimensionality reduction algorithms, and base learners, and also whether to use scans from one or both time points. Models that use only baseline (pre-treatment) or only week 2 (early-response) whole-brain FC features consistently failed to perform significantly better than default models. Utilizing the change in FC between these two time points, however, yielded significant results, with the best performing analytical pipeline achieving 69.6% (SD 10.8) accuracy. These results appear contrary to findings from many smaller single-site studies, which report substantially higher predictive accuracies from models trained on only baseline resting state FC features, suggesting these models may not generalize well beyond data used for development. Further, these results indicate the potential value of collecting data both before and shortly after treatment initiation.

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.

Probiotics alleviate depressive behavior in chronic unpredictable mild stress rat models by remodeling intestinal flora

OBJECTIVE

To explore the effects of probiotics on depressive behavior in a chronic unpredictable mild stress (CUMS) rat model by remodeling intestinal flora.

METHODS

Twenty-four male SD rats aged 6-8 weeks were randomly divided into four groups: control group, depression group (CUMS), depression+paroxetine group (Paro) and depression+probiotics group (Pro). Sucrose preference, open field and forced swimming tests were used to assess depression-like behavior in rats. ELISA was used to detect the levels of adrenocorticotropic hormone (ACTH), and corticosterone, norepinephrine and 5-hydroxytryptamine in rat serum. Real-time PCR was used to determine the changes of Lactobacillus, Bifidobacterium, Enterococcus faecalis and Escherichia coli in rat cecum.

RESULTS

Compared with the control group, CUMS led to significant decreases of body weight, total traveled distance, duration in central area, immobility time, norepinephrine and 5-hydroxytryptamine contents in hippocampal tissues, as well as Lactobacillus and Bifidobacterium in the cecum. It also resulted in marked increases of the contents of E. faecalis and E. coli in the cecum, ACTH and corticosterone contents in the serum of rats. Paroxetine and probiotic treatment each diminished or prevented these changes.

CONCLUSION

By remodeling intestinal flora, probiotics can reduce the CUMS-induced depressive behavior of rats, increase the levels of norepinephrine and 5-hydroxytryptamine, and inhibit the expression of ACTH and corticosterone. Significantly, the effect of both paroxetine and probiotic on microorganisms is similar.

Reward processing as a common diathesis for chronic pain and depression

Pain disorders and psychiatric illness are strongly comorbid, particularly in the context of Major Depressive Disorder (MDD). While these disorders account for a significant amount of global disability, the mechanisms of their overlap remain unclear. Understanding these mechanisms is of vital importance to developing prevention strategies and interventions that target both disorders. Of note, brain reward processing may be relevant to explaining how the comorbidity arises, given pain disorders and MDD can result in maladaptive reward responsivity that limits reward learning, appetitive approach behaviours and consummatory response. In this review, we discuss this research and explore the possibility of reward processing deficits as a common diathesis to explain the manifestation of pain disorders and MDD. Specifically, we hypothesize that contextual physical or psychological events (e.g. surgery, divorce) in the presence of a reward impairment diathesis worsens symptoms and results in a negative feedback loop that increases the chronicity and probability of developing the other disorder. We also highlight the implications for treatment and provide a framework for future research.

Duloxetine effects on striatal resting-state functional connectivity in patients with major depressive disorder

Reward deficits and associated striatal circuitry disturbances have been implicated in the onset and progression of major depressive disorder (MDD). However, no studies have been conducted to investigate how the striatal circuitry changes during standard antidepressant, which is important for development of novel and targeted treatments for MDD. We examined the seed-to-whole-brain functional connectivity (FC) for six striatal subregions based on resting-state fMRI data of 23 MDD patients before and after 8-week duloxetine, a serotonin, and noradrenaline reuptake inhibitor. Twenty-three healthy controls (HCs) were also scanned twice with an 8-week interval. After the analysis of covariance, we observed significant group-by-time interaction on FC of the dorsal caudate (DC), ventral striatum (VS), and putamen seeds. Post hoc analyses revealed that the FC between several right striatal seeds and left superior frontal gyrus (SFG), between right DC and left precuneus, between right superior VS and left inferior parietal lobe, were significantly higher in MDD patients compared to HCs at baseline and were reduced after treatment. Conversely, the FC between right inferior VS and left cerebellum was lower in MDD patients and was increased after treatment. Patients with larger reduction in right superior VS-left SFG FC exhibited larger alleviation of rumination. These findings suggest that duloxetine modulates the striatal FC with dorsolateral prefrontal cortex, posterior default mode network, and cerebellum, and partly, these changes underlie symptomatic improvement. This study adds to our understanding of antidepressant mechanism and future therapeutic development might benefit from considering these striatal circuitry as potential targets.