Promising Neuroimaging Biomarkers in Depression

From Connectivity to Controllability: Unraveling the Brain Biomarkers of Major Depressive Disorder

Major Depressive Disorder (MDD) is a significant neurological condition associated with aberrations in brain functional networks. Traditional studies have predominantly analyzed these from a network topology perspective. However, given the brain's dynamic and complex nature, exploring its mechanisms from a network control standpoint provides a fresh and insightful framework. This research investigates the integration of network controllability and machine learning to pinpoint essential biomarkers for MDD using functional magnetic resonance imaging (fMRI) data. By employing network controllability methods, we identify crucial brain regions that are instrumental in facilitating transitions between brain states. These regions demonstrate the brain's ability to navigate various functional states, emphasizing the utility of network controllability metrics as potential biomarkers. Furthermore, these metrics elucidate the complex dynamics of MDD and support the development of precision medicine strategies that incorporate machine learning to improve the precision of diagnostics and the efficacy of treatments. This study underscores the value of merging machine learning with network neuroscience to craft personalized interventions that align with the unique pathological profiles of individuals, ultimately enhancing the management and treatment of MDD.

The effectiveness of vortioxetine on neurobiochemical metabolites and cognitive of major depressive disorders patients: A 8-week follow-up study

OBJECTIVE

Vortioxetine has been shown to improve cognitive performance in people with depression. This study will look at the changes in neurobiochemical metabolites that occur when vortioxetine improves cognitive performance in MDD patients, with the goal of determining the neuroimaging mechanism through which vortioxetine improves cognitive function.

METHODS

30 depressed patients and 30 demographically matched healthy controls (HC) underwent MCCB cognitive assessment and 1H-MRS. After 8 weeks of vortioxetine medication, MCCB and 1H-MRS tests were retested in the MDD group. Before and after therapy, changes in cognitive performance, NAA/Cr, and Cho/Cr were examined in the MDD group.

RESULTS

Compared with the HC group, the MDD group had significant reduced in verbal learning, social cognition, and total cognition (all p < 0.05). And the MDD group had lower NAA/Cr in Right thalamus and Left PFC; the Cho/Cr in Right thalamus was lower than HC; the Cho/Cr in Left ACC had significantly increase (all p < 0.05). The MDD group showed significant improvements in the areas of verbal learning, attention/alertness, and total cognitive function before and after Vortioxetine treatment (all p < 0.05). The NAA/Cr ratio of the right PFC before and after treatment (t = 2.338, p = 0.026) showed significant changes.

CONCLUSIONS

Vortioxetine can enhance not just the depression symptoms of MDD patients in the initial period, but also their verbal learning, social cognition, and general cognitive capacities after 8 weeks of treatment. Furthermore, vortioxetine has been shown to enhance cognitive function in MDD patients by altering NAA/Cr and Cho/Cr levels in the frontal-thalamic-ACC.

Optimizing Antidepressant Efficacy: Multimodal Neuroimaging Biomarkers for Prediction of Treatment Response

Major depressive disorder (MDD) is a common and often severe condition that profoundly diminishes quality of life for individuals across ages and demographic groups. Unfortunately, current antidepressant and psychotherapeutic treatments exhibit limited efficacy and unsatisfactory response rates in a substantial number of patients. The development of effective therapies for MDD is hindered by the insufficiently understood heterogeneity within the disorder and its elusive underlying mechanisms. To address these challenges, we present a target-oriented multimodal fusion framework that robustly predicts antidepressant response by integrating structural and functional connectivity data (sertraline: R2 = 0.31; placebo: R2 = 0.22). Through the model, we identify multimodal neuroimaging biomarkers of antidepressant response and observe that sertraline and placebo show distinct predictive patterns. We further decompose the overall predictive patterns into constitutive network constellations with generalizable structural-functional co-variation, which exhibit treatment-specific association with personality traits and behavioral/cognitive task performance. Our innovative and interpretable multimodal framework provides novel insights into the intricate neuropsychopharmacology of antidepressant treatment and paves the way for advances in precision medicine and development of more targeted antidepressant therapeutics.

The effects of electroencephalography functional connectivity during emotional recognition among patients with major depressive disorder and healthy controls

BACKGROUND

The brain of major depressive disorder (MDD) is associated with altered functional connectivity (FC) compared to that of healthy individuals when processing positive and negative visual stimuli. Building upon alterations in brain connectivity, some researchers have employed electroencephalography (EEG) to study FC in MDD, aiming to enhance both diagnosis and treatment; however, the results have been inconsistent and the studies involving FC during emotional recognition are limited. This study aims to 1) investigate the effects of MDD on EEG patterns during visual emotional processing, 2) explore the therapeutic effects of antidepressant treatment on brain FC within the first week, and assess whether these effects can be predictive of treatment outcomes four weeks later, and 3) study baseline FC parameter biomarkers that can be used to predict treatment responsiveness in MDD patients.

METHODS

This clinical observational study recruited 38 healthy controls (HC) and 48 MDD patients. Patients underwent an EEG exam while looking at validated images of happy and sad faces at week 0 and 1. MDD patients were categorized into treatment responders and non-responders after 4 weeks of treatment. We conducted the FC analysis (node strength (NS), global efficiency (GE), and cluster coefficient (CC)) on HC and MDD patients using graph theoretical analysis. Multivariable linear regression was used to evaluate the influence of MDD on FC compared to HC, while controlling for confounding variables including age, gender, and academic degrees.

RESULTS

At week 0 and week 1, MDD patients revealed to have significant reductions in FC parameters (NS, GE and CC) compared to HC. When comparing MDD patients at week 1 post-antidepressant treatment and pre-treatment, no significant differences in FC changes were observed. Multivariable regression revealed a significant negative effect on FC of MDD. Compared to the treatment non-responsive group, the responsive group revealed a significantly higher FC in delta band frequency at baseline.

CONCLUSIONS

MDD patient group showed impaired FC during visual emotion-processing and we observed baseline FC parameters to be associated with treatment response at week 4. While signs of FC changes were observed in the brain after a week of treatment, it is possible that one week may still be insufficient to demonstrate significant alterations in the brain. Our results suggest the potential utilization of EEG-based FC as an indicative measure for predicting treatment response and monitoring treatment progress in MDD patients.

[Movement as a Neuromodulator: How Physical Activity Influences the Physiology of Adolescent Depression]

Movement as a Neuromodulator: How Physical Activity Influences the Physiology of Adolescent Depression Abstract: In the context of adolescent depression, physical activity is becoming increasingly recognized for its positive effects on neuropathology. Current scientific findings indicate that physical training affects the biological effects of depression during adolescence. Yet the pathophysiology of adolescent depression is not yet fully understood. Besides psychosocial and genetic influences, various neurobiological factors are being discussed. One explanation model describes a dysfunction of the hypothalamus-pituitary-adrenal axis (HPA axis) with a sustained elevation in cortisol concentration. Recent studies highlight neuroimmunological processes and a reduced concentration of growth factors as causative factors. These changes appear to lead to a dysregulation of the excitation and inhibition balance of the cerebral cortex as well as to cerebral morphological alterations. Regular physical training can potentially counteract the dysregulation of the HPA axis and normalize cortisol levels. The release of proinflammatory cytokines is inhibited, and the expression of growth factors involved in adult neurogenesis is stimulated. One should ensure the synergistic interaction of biological and psychosocial factors when designing the exercise schedule (endurance or strength training, group or individual sports, frequency, duration, and intensity). Addressing these open questions is essential when integrating physical activity into the guidelines for treating depressive disorders in children and adolescents.

Automatic depression diagnosis through hybrid EEG and near-infrared spectroscopy features using support vector machine

Depression is a common mental disorder that seriously affects patients' social function and daily life. Its accurate diagnosis remains a big challenge in depression treatment. In this study, we used electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) and measured the whole brain EEG signals and forehead hemodynamic signals from 25 depression patients and 30 healthy subjects during the resting state. On one hand, we explored the EEG brain functional network properties, and found that the clustering coefficient and local efficiency of the delta and theta bands in patients were significantly higher than those in normal subjects. On the other hand, we extracted brain network properties, asymmetry, and brain oxygen entropy as alternative features, used a data-driven automated method to select features, and established a support vector machine model for automatic depression classification. The results showed the classification accuracy was 81.8% when using EEG features alone and increased to 92.7% when using hybrid EEG and fNIRS features. The brain network local efficiency in the delta band, hemispheric asymmetry in the theta band and brain oxygen sample entropy features differed significantly between the two groups (p < 0.05) and showed high depression distinguishing ability indicating that they may be effective biological markers for identifying depression. EEG, fNIRS and machine learning constitute an effective method for classifying depression at the individual level.

Measuring acute effects of subanesthetic ketamine on cerebrovascular hemodynamics in humans using TD-fNIRS

Quantifying neural activity in natural conditions (i.e. conditions comparable to the standard clinical patient experience) during the administration of psychedelics may further our scientific understanding of the effects and mechanisms of action. This data may facilitate the discovery of novel biomarkers enabling more personalized treatments and improved patient outcomes. In this single-blind, placebo-controlled study with a non-randomized design, we use time-domain functional near-infrared spectroscopy (TD-fNIRS) to measure acute brain dynamics after intramuscular subanesthetic ketamine (0.75 mg/kg) and placebo (saline) administration in healthy participants (n = 15, 8 females, 7 males, age 32.4 ± 7.5 years) in a clinical setting. We found that the ketamine administration caused an altered state of consciousness and changes in systemic physiology (e.g. increase in pulse rate and electrodermal activity). Furthermore, ketamine led to a brain-wide reduction in the fractional amplitude of low frequency fluctuations, and a decrease in the global brain connectivity of the prefrontal region. Lastly, we provide preliminary evidence that a combination of neural and physiological metrics may serve as predictors of subjective mystical experiences and reductions in depressive symptomatology. Overall, our study demonstrated the successful application of fNIRS neuroimaging to study the physiological effects of the psychoactive substance ketamine in humans, and can be regarded as an important step toward larger scale clinical fNIRS studies that can quantify the impact of psychedelics on the brain in standard clinical settings.

Investigating Emotion EEG Patterns for Depression Detection with Attentive Simple Graph Convolutional Network

Depression severely limits daily functioning, diminishes quality of life and possibly leads to self-harm and suicide. Noninvasive electroencephalography (EEG) has been shown effective as biomarkers for objective depression diagnose and treatment response prediction, and dry EEG electrodes further extend its availability for clinical use. Even though many efforts have been made to identify depression biomarkers, searching reliable EEG biomarkers for depression detection remains challenging. This work presents a systematic investigation of capabilities of emotion EEG patterns for depression detection using a dry EEG electrode system. We design an emotion elicitation paradigm with happy, neutral and sad emotions and collect EEG signals during film watching from 33 depressed patients and 40 healthy controls. The mean activation levels at frontal and temporal sites in the alpha, beta and gamma bands of the depressed group are different to those of the healthy group, indicating the impacts of depressive symptoms on the emotion experiences. To leverage the topology information among EEG channels for emotion recognition and depression detection, an Attentive Simple Graph Convolutional network is built. The deep depression-health classifier achieves a sensitivity of 81.93% and a specificity of 91.69% on the happy emotions, suggesting the promising use of the emotion neural patterns for distinguishing the depressed patients from the healthy controls.

Deep Depression Detection with Resting-State and Cognitive-Task EEG

Depression is a common mental disorder that negatively affects physical health and personal, social and occupational functioning. Currently, accurate and objective diagnosis of depression remains challenging, and electroencephalography (EEG) provides promising clinical practice or home use due to considerable performance and low cost. This work investigates the capabilities of deep neural networks with EEG-based neural patterns from both resting states and cognitive tasks for depression detection. We collect EEG signals from 33 depressed patients and 40 healthy controls using wearable dry electrodes and build Attentive Simple Graph Convolutional network and Transformer neural network for objective depression detection. Four experiment stages, including two resting states and two cognitive tasks, are designed to characterize the alteration of relevant neural patterns in the depressed patients, in terms of decreased energy and impaired performance in sustained attention and response inhibition. The Transformer model achieves an AUC of 0.94 on the Continuous Performance Test-Identical Pairs version (sensitivity: 0.87, specificity: 0.91) and the Stroop Color Word Test (sensitivity: 0.93, specificity: 0.88), and an AUC of 0.89 on the two resting states (sensitivity: 0.85 and 0.87, specificity: 0.88 and 0.90, respectively), indicating the potential of EEG-based neural patterns in identifying depression. These findings provide new insights into the research of depression mechanisms and EEG-based depression biomarkers.

Biochemical metabolism in the anterior cingulate cortex and cognitive function in major depressive disorder with or without insomnia syndrome

BACKGROUND

Major depressive disorder (MDD) and insomnia have been linked to deficiencies in cognitive performance. However, the underlying mechanism of cognitive impairment in MDD patients with insomnia symptoms (IS) remains unclear. This study aimed to explore the effects of IS in patients with MDD by comparing cognitive function indices among those with IS, those without insomnia symptoms (NIS), and healthy controls (HCs). In addition, we assessed whether the dysfunction of central nervous system (CNS) is one of the important pathophysiologic mechanisms of IS in patients with MDD by comparing the biochemical metabolism ratios in the anterior cingulate cortex (ACC).

METHOD

Fifty-five MDD with IS, 39 MDD without IS, and 47 demographically matched HCs underwent the MATRICS Consensus Cognitive Battery (MCCB) assessment and proton magnetic resonance spectroscopy (¹H-MRS). MCCB cognitive scores and biochemical metabolism in ACC were assessed and compared between groups.

RESULTS

Compared to the HCs group, IS and NIS groups scored significantly lower in seven MCCB cognitive domains (speed of processing, attention/vigilance, working memory, verbal learning, visual learning, reasoning problem solving and social cognition). IS group showed a lower speed of processing and lower Cho/Cr ratio in the left ACC vs. NIS group and HCs. Also, in IS group, the Cho/Cr ratio in the left ACC was positively correlated with the composite T-score.

CONCLUSION

Patients with comorbidity of MDD with IS may exhibit more common MCCB cognitive impairments than those without IS, particularly speed of processing. Also, dysfunction of ACC may underlie the neural substrate of cognitive impairment in MDD with IS.

Affective neural circuits and inflammatory markers linked to depression and anxiety symptoms in patients with comorbid obesity

Although we have effective treatments for depression and anxiety, we lack mechanistic understanding or evidence-based strategies to tailor these treatments in the context of major comorbidities such as obesity. The current feasibility study uses functional neuroimaging and biospecimen data to determine if changes in inflammatory markers, fecal short-chain fatty acids, and neural circuit-based targets can predict depression and anxiety outcomes among participants with comorbid obesity. Blood and stool samples and functional magnetic resonance imaging data were obtained at baseline and 2 months, during the parent ENGAGE-2 trial. From 30 participants with both biospecimen and fMRI data, this subsample study explored the relationship among changes in inflammatory markers and fecal short-chain fatty acids and changes in neural targets, and their joint relationship with depression and anxiety symptoms. Bivariate and partial correlation, canonical correlation, and partial least squares analyses were conducted, with adjustments for age, sex, and treatment group. Initial correlation analyses revealed three inflammatory markers (IL-1RA, IL-6, and TNF-α) and five neural targets (in Negative Affect, Positive Affect, and Default Mode Circuits) with significantly associated changes at 2 months. Partial least squares analyses then showed that changes in IL-1RA and TNF-α and changes in three neural targets (in Negative Affect and Positive Affect Circuits) at 2 months were associated with changes in depression and anxiety symptoms at 6 months. This study sheds light on the plausibility of incorporation of inflammatory and gastrointestinal biomarkers with neural targets as predictors of depression and comorbid anxiety outcomes among patients with obesity.

Regional metabolic heterogeneity in anterior cingulate cortex in major depressive disorder: A multi-voxel 1H magnetic resonance spectroscopy study

BACKGROUND

Previous studies have shown major depressive disorder (MDD) is associated with altered neuro-metabolites in the anterior cingulate cortex (ACC). However, the regional metabolic heterogeneity in the ACC in individuals with MDD remains unclear.

METHODS

We recruited 59 first-episode, treatment-naive young adults with MDD and 50 healthy controls who underwent multi-voxel ¹H-MRS scanning at 3 T (Tesla) with voxels placed in the ACC, which was divided into two subregions, pregenual ACC (pACC) and anterior midcingulate cortex (aMCC). Between and within-subjects metabolite concentration variations were analyzed with SPSS.

RESULTS

Compared with control subjects, patients with MDD exhibited higher glutamate (Glu) and glutamine (Gln) levels in the pACC and higher myo-inositol (MI) level in the aMCC. We observed higher Glu and Gln levels and lower N-acetyl-aspartate (NAA) level in the pACC than those in the aMCC in both MDD and healthy control (HC) groups. More importantly, the metabolite concentration gradients of Glu, Gln and NAA were more pronounced in MDD patients relative to HCs. In the MDD group, the MI level in the aMCC positively correlated with the age of onset.

LIMITATIONS

The use of the relative concentration of metabolites constitutes a key study limitation.

CONCLUSIONS

We observed inconsistent alterations and distribution of neuro-metabolites concentration in the pACC and aMCC, revealing regional metabolic heterogeneity of ACC in first-episode, treatment-naive young individuals with MDD. These results provided new evidence for abnormal neuro-metabolites of ACC in the pathophysiology of MDD and suggested that pACC and aMCC might play different roles in MDD.

Alterations in brain iron deposition with progression of late-life depression measured by magnetic resonance imaging (MRI)-based quantitative susceptibility mapping

BACKGROUND

Previous studies have revealed abnormality of iron deposition in the brain of patients with depression. The progression of iron deposition associated with depression remains to be elucidated.

METHODS

This is a longitudinal study. We explored brain iron deposition with disease progression in 20 patients older than 55 years with depression and on antidepressants, using magnetic resonance imaging (MRI)-based quantitative susceptibility mapping (QSM). Magnetic susceptibility values of the whole brain were compared between baseline and approximately one-year follow-up scans using permutation testing. Furthermore, we examined the relationship of changes between the susceptibility values and disease improvement using Spearman's partial correlation analysis, controlling for age, gender, and the visit interval.

RESULTS

Compared to the initial scan, increased magnetic susceptibility values were found in the medial prefrontal cortex (mPFC), dorsal anterior cingulate cortex (dACC), occipital areas, habenula, brainstem, and cerebellum (P<0.05, corrected). The susceptibility values decreased in the dorsal part of the mPFC, middle and posterior cingulate cortex (MCC and PCC), right postcentral gyrus, right inferior parietal lobule, right precuneus, right supramarginal gyrus, left lingual gyrus, left dorsal striatum, and right thalamus (P<0.05, corrected). Notably, the increase in susceptibility values at the mPFC and dACC negatively correlated with the changes in depression scores, as calculated using the Hamilton Depression Scale (HAMD) (r=-0.613, P=0.009), and the increase in susceptibility values at the cerebellum and habenula negatively correlated with the changes in cognitive scores, which were calculated using the Mini-Mental State Examination (MMSE) (cerebellum: r=-0.500, P=0.041; habenula: r=-0.588, P=0.013). Additionally, the decreased susceptibility values at the white matter near the mPFC (anterior corona radiata) also correlated with the changes in depression scores (r=-0.541, P=0.025), and the decreased susceptibility values at the left lingual gyrus correlated with the changes in cognitive scores (r=-0.613, P=0.009).

CONCLUSIONS

Our study identified brain areas where iron deposition changed with the progression of depression while on antidepressants. The linear relationship of changes in the magnetic susceptibility values in the mPFC, dACC, and some subcortical areas with changes in depression symptoms and cognitive functions of patients is highlighted. Our results strengthen the understanding of the alterations of brain iron levels associated with disease progression in patients with late-life depression.

Unraveling the mystery of white matter in depression: A translational perspective on recent advances

BACKGROUND

Numerous cortical and subcortical structures have been studied extensively concerning alterations of their integrity as well as their neurotransmitters in depression. However, connections between these structures have received considerably less attention.

OBJECTIVE

This systematic review presents results from recent neuroimaging as well as neuropathologic studies conducted on humans and other mammals. It aims to provide evidence for impaired white matter integrity in individuals expressing a depressive phenotype.

METHODS

A systematic database search in accordance with the PRISMA guidelines was conducted to identify imaging and postmortem studies conducted on humans with a diagnosis of major depressive disorder, as well as on rodents and primates subjected to an animal model of depression.

RESULTS

Alterations are especially apparent in frontal gyri, as well as in structures establishing interhemispheric connectivity between frontal regions. Translational neuropathological findings point to alterations in oligodendrocyte density and morphology, as well as to alterations in the expression of genes related to myelin synthesis. An important role of early life adversities in the development of depressive symptoms and white matter alterations across species is thereby revealed. Data indicating that stress can interfere with physiological myelination patterns is presented. Altered myelination is most notably present in regions that are subject to maturation during the developmental stage of exposure to adversities.

CONCLUSION

Translational studies point to replicable alterations in white matter integrity in subjects suffering from depression across multiple species. Impaired white matter integrity is apparent in imaging as well as neuropathological studies. Future studies should focus on determining to what extent influencing white matter integrity is able to improve symptoms of depression in animals as well as humans.

Electrophysiological correlates and predictors of the antidepressant response to repeated ketamine infusions in treatment-resistant depression

BACKGROUND

Sub-anesthetic ketamine doses rapidly reduce depressive symptoms, although additional investigations of the underlying neural mechanisms and the prediction of response outcomes are needed. Electroencephalographic (EEG)-derived measures have shown promise in predicting antidepressant response to a variety of treatments, and are sensitive to ketamine administration. This study examined their utility in characterizing changes in depressive symptoms following single and repeated ketamine infusions.

METHODS

Recordings were obtained from patients with treatment-resistant major depressive disorder (MDD) (N = 24) enrolled in a multi-phase clinical ketamine trial. During the randomized, double-blind, crossover phase (Phase 1), patients received intravenous ketamine (0.5 mg/kg) and midazolam (30 μg/kg), at least 1 week apart. For each medication, three resting, eyes-closed recordings were obtained per session (pre-infusion, immediately post-infusion, 2 h post-infusion), and changes in power (delta, theta1/2/total, alpha1/2/total, beta, gamma), alpha asymmetry, theta cordance, and theta source-localized anterior cingulate cortex activity were quantified. The relationships between ketamine-induced changes with early (Phase 1) and sustained (Phases 2,3: open-label repeated infusions) decreases in depressive symptoms (Montgomery-Åsberg Depression Rating Score, MADRS) and suicidal ideation (MADRS item 10) were examined.

RESULTS

Both medications decreased alpha and theta immediately post-infusion, however, only midazolam increased delta (post-infusion), and only ketamine increased gamma (immediately post- and 2 h post-infusion). Regional- and frequency-specific ketamine-induced EEG changes were related to and predictive of decreases in depressive symptoms (theta, gamma) and suicidal ideation (alpha). Early and sustained treatment responders differed at baseline in surface-level and source-localized theta.

CONCLUSIONS

Ketamine exerts frequency-specific changes on EEG-derived measures, which are related to depressive symptom decreases in treatment-resistant MDD and provide information regarding early and sustained individual response to ketamine.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov: Action of Ketamine in Treatment-Resistant Depression, NCT01945047.

Neuroimaging correlates of depression after traumatic brain injury: A systematic review

Depression is the most frequent neuropsychiatric complication after traumatic brain injury (TBI) and is associated with poorer outcomes. Neuroimaging has the potential to improve our understanding of the neural correlates of depression after TBI and may improve our capacity to accurately predict and effectively treat this condition. We conducted a systematic review of structural and functional neuroimaging studies that examined the association between depression after TBI, and neuroimaging measures. Electronic searches were conducted in four databases and were complemented by manual searches. In total, 2,035 citations were identified and, ultimately, 38 articles were included totaling 1,793 individuals (median [25%-75%] sample size of 38.5 (21.8-54.3) individuals). The most frequently used modality was structural magnetic resonance imaging (MRI) (n=17, 45%), followed by diffusion tensor imaging (n=11, 29%), resting-state functional MRI (n=10, 26%), task-based functional MRI (n=4, 8%), and positron emission tomography (n=2, 4%). Most studies (n=27, 71%) were cross-sectional. Overall, depression after TBI was associated with lower grey matter measures (volume, thickness, and/or density) and greater white matter damage. However, identification of specific brain areas was somewhat inconsistent. Findings that were replicated in more than one study included reduced grey matter in the rostral anterior cingulate cortex, prefrontal cortex and hippocampus, and damage in five white matter tracts (cingulum, internal capsule, superior longitudinal fasciculi, anterior, and posterior corona radiata). This systematic review found that the available data did not converge on a clear neuroimaging biomarker for depression after TBI. However, there are promising targets that warrant further study.

Inflammatory Process and Immune System in Major Depressive Disorder

Major depressive disorder (MDD) is one of the most common psychiatric illnesses in the general population. In mental disorders, the activation of inflammatory pathways in the brain is a major producer of excitotoxicity and an inducer of oxidative stress. The occurrence of these 2 events is partly responsible for the neuronal damage inherent in patients with mental disorders. In the case of MDD, the release of hormone and increase in pro-inflammatory cytokines in plasma and indicators of oxidative stress have been identified as consequences of this event. The most important affectations in patients with MDD are changes in their cognitive and executive functions due to brain inflammation. Hence, these biomarkers can serve as diagnostic and severity classification tools and treatment. In this work, we described the communication pathway between the immune and neuroendocrine systems in MDD and suggested possible therapeutic options for the disease.

Organization of the social cognition network predicts future depression and interpersonal impairment: a prospective family-based study

Deficits in social cognition and functioning are common in major depressive disorder (MDD). Still, no study into the pathophysiology of MDD has examined the social cognition-related neural pathways through which familial risk for MDD leads to depression and interpersonal impairments. Using resting-state fMRI, we applied a graph theoretical analysis to quantify the influence of nodes within the fronto-temporo-parietal cortical social cognition network in 108 generation 2 and generation 3 offspring at high and low-risk for MDD, defined by the presence or absence, respectively, of moderate to severe MDD in generation 1. New MDD episodes, future depressive symptoms, and interpersonal impairments were tested for associations with social cognition nodal influence, using regression analyses applied in a generalized estimating equations approach. Increased familial risk was associated with reduced nodal influence within the network, and this predicted new depressive episodes, worsening depressive symptomatology, and interpersonal impairments, 5-8 years later. Findings remained significant after controlling for current depressive/anxiety symptoms and current/lifetime MDD and anxiety disorders. Path-analysis models indicate that increased familial risk impacted offspring's brain function in two ways. First, high familial risk was indirectly associated with future depression, both new MDD episodes and symptomatology, via reduced nodal influence of the right posterior superior temporal gyrus (pSTG). Second, high familial risk was indirectly associated with future interpersonal impairments via reduced nodal influence of right inferior frontal gyrus (IFG). Finally, reduced nodal influence was associated with high familial risk in (1) those who had never had MDD at the time of scanning and (2) a subsample (n = 52) rescanned 8 years later. Together, findings reveal a potential pathway for the intergenerational transmission of vulnerability via the aberrant social cognition network organization and suggest using the connectome of neural network related to social cognition to identify intervention and prevention targets for those particularly at risk.

Sex is a defining feature of neuroimaging phenotypes in major brain disorders

Sex is a biological variable that contributes to individual variability in brain structure and behavior. Neuroimaging studies of population-based samples have identified normative differences in brain structure between males and females, many of which are exacerbated in psychiatric and neurological conditions. Still, sex differences in MRI outcomes are understudied, particularly in clinical samples with known sex differences in disease risk, prevalence, and expression of clinical symptoms. Here we review the existing literature on sex differences in adult brain structure in normative samples and in 14 distinct psychiatric and neurological disorders. We discuss commonalities and sources of variance in study designs, analysis procedures, disease subtype effects, and the impact of these factors on MRI interpretation. Lastly, we identify key problems in the neuroimaging literature on sex differences and offer potential recommendations to address current barriers and optimize rigor and reproducibility. In particular, we emphasize the importance of large-scale neuroimaging initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analyses consortium, the UK Biobank, Human Connectome Project, and others to provide unprecedented power to evaluate sex-specific phenotypes in major brain diseases.

Subthreshold depressive symptoms relate to cuneus structure: Thickness asymmetry and sex differences

Despite the prominence of frontolimbic regions in depression research, recent studies also implicate posterior brain regions, including the cuneus. The current study examined the relationship between depressive symptoms and asymmetry in cuneal cortical thickness in healthy adults between the ages of 18 and 81 with primarily subthreshold levels of depressive symptoms. An asymmetry index was calculated for cortical thickness in the cuneus [(left - right) × 100/(left + right)], and regression analyses were conducted with total scores on the Center for Epidemiologic Studies Depression Scale predicting this asymmetry index, controlling for age and sex. Higher depressive symptoms were associated with a left > right asymmetry in cuneal cortical thickness, reflecting greater cortical thickness in the left hemisphere compared to right hemisphere. Follow-up analyses examining CES-D subscales showed significant effects for somatic symptoms of depression, but not negative affect or anhedonia. Analyses stratified by sex yielded significant effects in men but not in women. Results of this preliminary study further support the cuneus' role in depression and highlight the importance of examining symptom dimensions and sex differences in the neurobiology of depression.

How Inflammation Affects the Brain in Depression: A Review of Functional and Structural MRI Studies

This narrative review discusses how peripheral and central inflammation processes affect brain function and structure in depression, and reports on recent peripheral inflammatory marker-based functional and structural magnetic resonance imaging (MRI) studies from the perspective of neural-circuit dysfunction in depression. Chronic stress stimulates the activity of microglial cells, which increases the production of pro-inflammatory cytokines in the brain. In addition, microglial activation promotes a shift from the synthesis of serotonin to the synthesis of neurotoxic metabolites of the kynurenine pathway, which induces glutamate-mediated excitotoxicity in neurons. Furthermore, the region specificity of microglial activation is hypothesized to contribute to the vulnerability of specific brain regions in the depression-related neural circuits to inflammation-mediated brain injury. MRI studies are increasingly investigating how the blood levels of inflammatory markers such as C-reactive protein, interleukin (IL)-1β, IL-6, and tumor necrosis factor-α are associated with functional and structural neuroimaging markers in depression. Functional MRI studies have found that peripheral inflammatory markers are associated with aberrant activation patterns and altered functional connectivity in neural circuits involved in emotion regulation, reward processing, and cognitive control in depression. Structural MRI studies have suggested that peripheral inflammatory markers are related to reduced cortical gray matter and subcortical volumes, cortical thinning, and decreased integrity of white matter tracts within depression-related neural circuits. These neuroimaging findings may improve our understanding of the relationships between neuroinflammatory processes at the molecular level and macroscale in vivo neuralcircuit dysfunction in depression.

Continuous Theta-Burst Stimulation Over the Right Orbitofrontal Cortex in Treatment-Resistant Obsessive-Compulsive Disorder Treatment: A Randomized Sham-Controlled Trial

Purpose

Examining whether modulation of right orbitofrontal cortex (OFC) activity by continuous theta-burst stimulation (cTBS) affects obsessive-compulsive disorder (OCD) symptoms.

Patients and Methods

A total of 28 treatment-resistant OCD participants were treated with either active or sham cTBS of the OFC twice per day, for five days a week, for 2 weeks, in a double-blinded manner. Clinical response to treatment was determined using the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS).

Results

There were no statistically significant differences between the 2 groups after two weeks of treatment in the Yale-Brown Obsessive-Compulsive Scale score (group*time interaction, F2,20=0.996, p=0.387) and other secondary outcome measures, including anxiety symptoms and responder rates. Depressive symptoms improved significantly in the active group (p=0.027), but the significant difference disappeared at 6 weeks (p=0.089).

Conclusion

This is the first randomized controlled study using cTBS in the right OFC to observe the improvement of treatment-resistant OCD symptoms. It is safe to use cTBS, but 2 weeks of treatment is not enough to achieve a curative effect. Future studies are needed to explore more advanced stimulation parameters suitable for the treatment of OCD.

Clinical Trial Registration

www.chictr.org.cn, identifier ChiCTR2000034814.

Fronto-limbic neuroimaging biomarkers for diagnosis and prediction of treatment responses in major depressive disorder

The neuroimaging is an important tool for understanding the biomarkers and predicting treatment responses in major depressive disorder (MDD). The potential biomarkers and prediction of treatment response in MDD will be addressed in the review article. The brain regions of cognitive control and emotion regulation, such as the frontal and limbic regions, might represent the potential targets for MDD biomarkers. The potential targets of frontal lobes might include anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC) and orbitofrontal cortex (OFC). For the limbic system, hippocampus and amygdala might be the potentially promising targets for MDD. The potential targets of fronto-limbic regions have been found in the studies of several major neuroimaging modalities, such as the magnetic resonance imaging, near-infrared spectroscopy, electroencephalography, positron emission tomography, and single-photon emission computed tomography. Additional regions, such as brainstem and midbrain, might also play a part in the MDD biomarkers. For the prediction of treatment response, the gray matter volumes, white matter tracts, functional representations and receptor bindings of ACC, DLPFC, OFC, amygdala, and hippocampus might play a role in the prediction of antidepressant responses in MDD. For the response prediction of psychotherapies, the fronto-limbic, reward regions, and insula will be the potential targets. For the repetitive transcranial magnetic stimulation, the DLPFC, ACC, limbic, and visuospatial regions might represent the predictive targets for treatment. The neuroimaging targets of MDD might be focused in the fronto-limbic regions. However, the neuroimaging targets for the prediction of treatment responses might be inconclusive and beyond the fronto-limbic regions.

Identification and Validation of Distinct Latent Neurodevelopmental Profiles in the Adolescent Brain and Cognitive Development Study

BACKGROUND

Regardless of the precise mechanism, all neurodevelopmental models of risk assume that, at the population level, there exist subgroups of individuals that share similar patterns of neural function and development-and that these subgroups somehow relate to psychiatric risk. However, the existence of multiple neurodevelopmental subgroups at the population level has not been assessed previously.

METHODS

In the current study, cross-validated latent profile analysis was used to test for the presence of empirically derived, brain-based developmental subgroups using functional magnetic resonance imaging data from 6758 individuals (49.4% female; mean age = 9.94 years) in the Adolescent Brain and Cognitive Development (ABCD) study wave 1 release. Data were randomly split into training and testing samples.

RESULTS

Analyses in the training sample (n = 3379) identified a seven-profile solution (entropy = 0.880) that was replicated in the held-out testing data (n = 3379, entropy = 0.890). Identified subgroups included a moderate group (66.8%), high reward (4.3%) and low reward (4.0%) groups, high inhibition (9.8%) and low inhibition (6.7%) groups, and high emotion regulation (4.0%) and low emotion regulation (4.3%) groups. Relative to the moderate group, other subgroups were characterized by more males (χ² = 24.10, p = .0005), higher proportions of individuals from lower-income households (χ² = 122.17, p < .0001), poorer cognitive performance (ps < .0001), more screen time (F = 6.80, p < .0001), heightened impulsivity (ps < .006), and higher rates of neurodevelopmental disorders (χ² = 26.20, p = .0002).

CONCLUSIONS

These data demonstrate the existence of multiple, distinct neurodevelopmental subgroups at the population level. They indicate that these empirically derived, brain-based developmental profiles relate to differences in clinical features, even at a young age, and prior to the peak period of risk for the development of psychopathology.

Altered local and matrix functional connectivity in depressed essential tremor patients

BACKGROUND

Depression in essential tremor (ET) has been constantly studied and reported, while the associated brain activity changes remain unclear. Recently, regional homogeneity (ReHo), a voxel-wise local functional connectivity (FC) analysis of resting-state functional magnetic resonance imaging, has provided a promising way to observe spontaneous brain activity.

METHODS

Local FC analyses were performed in forty-one depressed ET patients, 49 non-depressed ET patients and 43 healthy controls (HCs), and then matrix FC and clinical depression severity correlation analyses were further performed to reveal spontaneous neural activity changes in depressed ET patients.

RESULTS

Compared with the non-depressed ET patients, the depressed ET patients showed decreased ReHo in the bilateral cerebellum lobules IX, and increased ReHo in the bilateral anterior cingulate cortices and middle prefrontal cortices. Twenty-five significant changes of ReHo clusters were observed in the depressed ET patients compared with the HCs, and matrix FC analysis further revealed that inter-ROI FC differences were also observed in the frontal-cerebellar-anterior cingulate cortex pathway. Correlation analyses showed that clinical depression severity was positively correlated with the inter-ROI FC values between the anterior cingulate cortex and bilateral middle prefrontal cortices and was negatively correlated with the inter-ROI FC values of the anterior cingulate cortex and bilateral cerebellum lobules IX.

CONCLUSION

Our findings revealed local and inter-ROI FC differences in frontal-cerebellar-anterior cingulate cortex circuits in depressed ET patients, and among these regions, the cerebellum lobules IX, middle prefrontal cortices and anterior cingulate cortices could function as pathogenic structures underlying depression in ET patients.

Elevated Brain Fatty Acid Amide Hydrolase Induces Depressive-Like Phenotypes in Rodent Models: A Review

Altered activity of fatty acid amide hydrolase (FAAH), an enzyme of the endocannabinoid system, has been implicated in several neuropsychiatric disorders, including major depressive disorder (MDD). It is speculated that increased brain FAAH expression is correlated with increased depressive symptoms. The aim of this scoping review was to establish the role of FAAH expression in animal models of depression to determine the translational potential of targeting FAAH in clinical studies. A literature search employing multiple databases was performed; all original articles that assessed FAAH expression in animal models of depression were considered. Of the 216 articles that were screened for eligibility, 24 articles met inclusion criteria and were included in this review. Three key findings emerged: (1) FAAH expression is significantly increased in depressive-like phenotypes; (2) genetic knockout or pharmacological inhibition of FAAH effectively reduces depressive-like behavior, with a dose-dependent effect; and (3) differences in FAAH expression in depressive-like phenotypes were largely localized to animal prefrontal cortex, hippocampus and striatum. We conclude, based on the animal literature, that a positive relationship can be established between brain FAAH level and expression of depressive symptoms. In summary, we suggest that FAAH is a tractable target for developing novel pharmacotherapies for MDD.

Resting State Functional Connectivity of Brain With Electroconvulsive Therapy in Depression: Meta-Analysis to Understand Its Mechanisms

Introduction: Electroconvulsive therapy (ECT) is a commonly used brain stimulation treatment for treatment-resistant or severe depression. This study was planned to find the effects of ECT on brain connectivity by conducting a systematic review and coordinate-based meta-analysis of the studies performing resting state fMRI (rsfMRI) in patients with depression receiving ECT. Methods: We systematically searched the databases published up to July 31, 2020, for studies in patients having depression that compared resting-state functional connectivity (rsFC) before and after a course of pulse wave ECT. Meta-analysis was performed using the activation likelihood estimation method after extracting details about coordinates, voxel size, and method for correction of multiple comparisons corresponding to the significant clusters and the respective rsFC analysis measure with its method of extraction. Results: Among 41 articles selected for full-text review, 31 articles were included in the systematic review. Among them, 13 articles were included in the meta-analysis, and a total of 73 foci of 21 experiments were examined using activation likelihood estimation in 10 sets. Using the cluster-level interference method, one voxel-wise analysis with the measure of amplitude of low frequency fluctuations and one seed-voxel analysis with the right hippocampus showed a significant reduction (p < 0.0001) in the left cingulate gyrus (dorsal anterior cingulate cortex) and a significant increase (p < 0.0001) in the right hippocampus with the right parahippocampal gyrus, respectively. Another analysis with the studies implementing network-wise (posterior default mode network: dorsomedial prefrontal cortex) resting state functional connectivity showed a significant increase (p < 0.001) in bilateral posterior cingulate cortex. There was considerable variability as well as a few key deficits in the preprocessing and analysis of the neuroimages and the reporting of results in the included studies. Due to lesser studies, we could not do further analysis to address the neuroimaging variability and subject-related differences. Conclusion: The brain regions noted in this meta-analysis are reasonably specific and distinguished, and they had significant changes in resting state functional connectivity after a course of ECT for depression. More studies with better neuroimaging standards should be conducted in the future to confirm these results in different subgroups of depression and with varied aspects of ECT.

Neural substrates for late-life depression: A selective review of structural neuroimaging studies

Recent neuroimaging studies have characterized the pathophysiology of late-life depression (LLD) as a dysfunction of the brain networks involved in the regulation of emotion, motivational behavior, cognitive control, executive function, and self-referential thinking. In this article, we reviewed LLD-associated structural neuroimaging markers such as white matter hyperintensity (WMH), white matter integrity measured by diffusion tensor imaging, cortical and subcortical volumes, and cortical thickness, which may provide a structural basis for brain network dysfunction in LLD. LLD was associated with greater severity or volumes of deep, periventricular, or overall WMH and with decreased white matter integrity in the brain regions belonging to the fronto-striatal-limbic circuits and reduced white matter tract integrity which connects these circuits, such as the cingulum, corpus callosum, or uncinate fasciculus. Decreased volumes or cortical thickness in the prefrontal cortex, orbitofrontal cortex, anterior and posterior cingulate cortex, several temporal and parietal regions, hippocampus, amygdala, striatum, thalamus, and the insula were associated with LLD. These structural neuroimaging findings were also associated with cognitive dysfunction, which is a prominent clinical feature in LLD. Several structural neuroimaging markers including the WMH burden, white matter integrity, and cortical and subcortical volumes predicted antidepressant response in LLD. These structural neuroimaging findings support the hypothesis that disruption of the brain networks involved in emotion regulation and cognitive processing by impaired structural connectivity is strongly associated with the pathophysiology of LLD.

Hypothalamic neurogenesis and its implications for obesity-induced anxiety disorders

Obesity and anxiety are public health problems that have no effective cure. Obesity-induced anxiety is also the most common behavioural trait exhibited amongst obese patients, with the mechanisms linking these disorders being poorly understood. The hypothalamus and hippocampus are reciprocally connected, important neurogenic brain regions that could be vital to understanding these disorders. Dietary, physical activity and lifestyle interventions have been shown to be able to enhance neurogenesis within the hippocampus, while the effects thereof within the hypothalamus is yet to be ascertained. This review describes hypothalamic neurogenesis, its impairment in obesity as well as the effect of interventional therapies. Obesity is characterized by a neurogenic shift towards neuropeptide Y neurons, promoting appetite and weight gain. While, nutraceuticals and exercise promote proopiomelanocortin neuron proliferation, causing diminished appetite and reduced weight gain. Through the furthered development of multimodal approaches targeting both these brain regions could hold an even greater therapeutic potential.

Development of Neuroimaging-Based Biomarkers in Major Depression

A leading goal in the field of biological psychiatry for depression is to find a promising diagnostic biomarker and selection of specific psychiatric treatment mode that is most likely to benefit patients with depression. Recent neuroimaging studies have characterized the pathophysiology of major depressive disorder (MDD) with functional and structural alterations in the neural circuitry involved in emotion or reward processing. Particularly, structural and functional magnetic resonance imaging (MRI) studies have reported that the brain structures deeply involved in emotion regulation or reward processing including the amygdala, prefrontal cortex (PFC), anterior cingulate cortex (ACC), ventral striatum, and hippocampus are key regions that provide useful information about diagnosis and treatment outcome prediction in MDD. For example, it has been consistently reported that elevated activity of the ACC is associated with better antidepressant response in patients with MDD. This chapter will discuss a growing body of evidence that suggests that diagnosis or prediction of outcome for specific treatment can be assisted by a neuroimaging-based biomarker in MDD.

Inflammatory modulation of the associations between prenatal maternal depression and neonatal brain

Inflammatory signaling has a role in sensing intrauterine environment, which may be moderators in altering fetal brain development upon maternal environment. This study integrated cytokine transcriptome of post-mortem fetal brains, neonatal brain imaging and genetic variants (n = 161) to examine whether cytokines are candidates for modulating the relationship between prenatal maternal depression and fetal brain development. This study obtained the transcriptome data of 208 cytokine genes in 12 fetal brain regions from the BrainSpan database. We also included 161 mother-child dyads with prenatal maternal depressive symptoms assessed at 26 weeks of gestation, cytokine genotype data extracted from umbilical cord specimens, and neonatal brain images from a longitudinal prospective birth cohort. We revealed that 22 cytokine genes are expressed in specific brain regions in utero, whose variants have roles in modulating the effects of the prenatal environment on the accelerated fetal development of the hippocampus, auditory, parietal, orbitofrontal, and dorsal prefrontal cortex. Neonates high in the genetic expression score (GES) of TNFRSF19 and IL17RB showed a larger right hippocampal volume, high in the GES of BMPR1B showed the thicker thickness of the sensorimotor cortex, and high in the GES of IL1RAP and CXCR4 demonstrated the thicker thickness of the dorsal and orbital prefrontal cortex in relation with greater prenatal maternal depressive symptoms. Our findings suggest that in humans, the cytokine genes are expressed in a brain region-specific manner in utero and may have potential roles in modulating the fetal development of the corresponding brain regions in response to the maternal environment.

Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation

Multimodal fusion in neuroimaging combines data from multiple imaging modalities to overcome the fundamental limitations of individual modalities. Neuroimaging fusion can achieve higher temporal and spatial resolution, enhance contrast, correct imaging distortions, and bridge physiological and cognitive information. In this study, we analyzed over 450 references from PubMed, Google Scholar, IEEE, ScienceDirect, Web of Science, and various sources published from 1978 to 2020. We provide a review that encompasses (1) an overview of current challenges in multimodal fusion (2) the current medical applications of fusion for specific neurological diseases, (3) strengths and limitations of available imaging modalities, (4) fundamental fusion rules, (5) fusion quality assessment methods, and (6) the applications of fusion for atlas-based segmentation and quantification. Overall, multimodal fusion shows significant benefits in clinical diagnosis and neuroscience research. Widespread education and further research amongst engineers, researchers and clinicians will benefit the field of multimodal neuroimaging.

Brain Imaging Study on the Pathogenesis of Depression & Therapeutic Effect of Selective Serotonin Reuptake Inhibitors

OBJECTIVE

Predefining the most effective treatment for patients with depressive disorders remains a problem. We will examine the differential brain regions of gray matter (GM) in major depressive disorder (MDD) patients and the relationship between changes in their volume and the efficacy of early antidepressant treatment using magnetic resonance imaging (MRI).

METHODS

159 never-medicated patients with first-episode MDD and 53 normal control subjects (NCs) were enrolled. The brains were scanned by MRI and measured with the 17-item Hamilton Depression Rating Scale (HAMD-17) at baseline and after 2 weeks of treatment with selective serotonin reuptake inhibitor (SSRI)s, and the non-responder group and responder group were obtained. The patients were analyzed by voxel-based morphological (VBM) and SPSS software. Receiver operator characteristics (ROC) analysis was performed for the difference between the responder group and the non-responder group in the differential brain regions, and Pearson correlations were computed between volume size and HAMD score reduction rate.

RESULTS

Smaller GM volume of the right superior temporal gyrus (STG), and the orbital parts of the right medial frontal gyrus and right inferior frontal gyrus were observed in MDD versus the NCs. The non-responder group demonstrated a significant volume reduction at the right STG compared with the responders, but no corresponding change in orbital part of right medial frontal gyrus and right inferior frontal gyrus. ROC analysis showed that Accuracy=71.2%. There was a positive correlation between the STG gray matter volume and the HAMD-17 score reduction rate (r=0.347, p=0.002).

CONCLUSION

The study results confirmed the local changes in brain structure in MDD and may initially predict the early treatment response produced by SSRIs as antidepressants.

Transcranial Direct Current Stimulation as an Add-on Treatment to Cognitive-Behavior Therapy in First Episode Drug-Naïve Major Depression Patients: The ESAP Study Protocol

Background: Major Depressive Disorder (MDD) affects more than 264 million people worldwide. Current treatments include the use of psychotherapy and/or drugs, however ~30% of patients either do not respond to these treatments, or do not tolerate the side effects associated to the use of pharmacological interventions. Thus, it is important to study non-pharmacological interventions targeting mechanisms not directly involved with the regulation of neurotransmitters. Several studies demonstrated that transcranial Direct Current Stimulation (tDCS) can be effective for symptoms relief in MDD. However, tDCS seems to have a better effect when used as an add-on treatment to other interventions. Methods/Design: This is a study protocol for a parallel, randomized, triple-blind, sham-controlled clinical trial in which a total of 90 drug-naïve, first-episode MDD patients (45 per arm) will be randomized to one of two groups to receive a 6-weeks of CBT combined with either active or sham tDCS to the dorsolateral prefrontal cortex (DLPFC). The primary outcome will depressive symptoms improvement as assessed by the Montgomery-Asberg Depression Rating Scale (MADRS) at 6-weeks. The secondary aim is to test whether CBT combined with tDCS can engage the proposed mechanistic target of restoring the prefrontal imbalance and connectivity through the bilateral modulation of the DLPFC, as assessed by changes over resting-state and emotional task eliciting EEG. Discussion: This study evaluates the synergetic clinical effects of CBT and tDCS in the first episode, drug-naïve, patients with MDD. First episode MDD patients provide an interesting opportunity, as their brains were not changed by the pharmacological treatments, by the time course, or by the recurrence of MDD episodes (and other comorbidities). Trial Registration: This study is registered with the United States National Library of Medicine Clinical Trials Registry (NCT03548545). Registered June 7, 2018, clinicaltrials.gov/ct2/show/NCT03548545. Protocol Version 1.

Dual Metabolomic Platforms Identified a Novel Urinary Metabolite Signature for Hepatitis B Virus-Infected Patients with Depression

OBJECTIVE

Depression could make the treatment outcome worse. However, up to now, no objective methods were developed to diagnose depression in hepatitis B virus (HBV)-infected patients. Therefore, the dual metabolomic platforms were used here to identify potential biomarkers for diagnosing HBV-infected patients with depression (dHB).

METHODS

Both gas chromatography-mass spectrometry-based and nuclear magnetic resonance-based metabolomic platforms were used to conduct urine metabolic profiling of dHB subjects and HBV-infected patients without depression (HB). Orthogonal partial least-squares discriminant analysis was used to identify the differential metabolites between dHB subjects and HB subjects, and the step-wise logistic regression analysis was used to identify potential biomarkers.

RESULTS

In total, 21 important metabolites responsible for distinguishing dHB subjects from HB subjects were identified. Meanwhile, seven potential biomarkers (α-ydroxyisobutyric acid, hippuric acid, azelaic acid, isobutyric acid, malonic acid, levulinic acid, and phenylacetylglycine) were viewed as potential biomarkers. The simplified biomarker panel consisting of these seven metabolites had an excellent diagnostic performance in discriminating dHB subjects from HB subjects. Moreover, this panel could yield a higher accuracy in separating dHB subjects from HB subjects than our previous panels (identified by single metabolomic platform) did.

CONCLUSION

These results suggested that the dual metabolomic platforms could yield a better urinary biomarker panel for dHB subjects than any single metabolomic platform did, and our results could be helpful for developing an objective method in future to diagnose depression in HBV-infected patients.

CACNA1C Gene rs11832738 Polymorphism Influences Depression Severity by Modulating Spontaneous Activity in the Right Middle Frontal Gyrus in Patients With Major Depressive Disorder

OBJECTIVES

This study aimed to examine whether the CACNA1C gene rs11832738 polymorphism and major depressive disorder (MDD) have an interactive effect on the untreated regional amplitude of low-frequency fluctuation (ALFF) and to determine whether regional ALFF mediates the association between CACNA1C rs11832738 and MDD.

METHODS

A total of 116 patients with MDD and 66 normal controls (NCs) were recruited. The MDD and NC groups were further divided into two groups according to genotype: carriers of the G allele (G-carrier group, GG/GA genotypes; MDD, n = 61; NC, n = 26) and AA homozygous group (MDD, n = 55; NC, n = 40). MDD was diagnosed based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Depression severity was assessed using the Hamilton Depression Scale-24 (HAMD-24) at baseline and follow-up (after 2 and 8 weeks of treatment). All subjects underwent functional MRI (fMRI) scans at baseline, and the ALFF was calculated to reflect spontaneous brain activity. The interactions between MDD and CACNA1C single nucleotide polymorphism rs11832738 were determined using two-way factorial analysis of covariance, with age, sex, education, and head motion as covariates. We performed mediation analysis to further determine whether regional ALFF strength could mediate the associations between rs11832738 and depression severity, MDD treatment efficacy.

RESULTS

MDD had a main effect on regional ALFF distribution in three brain areas: the right medial frontal gyrus (MFG_R), the left anterior cingulate cortex (ACC_L), and the right cerebellum posterior lobe (CPL_R); CACNA1C showed a significant interactive effect with MDD on the ALFF of MFG_R. For CACNA1C G allele carriers, the ALFF of MFG_R had a significant positive correlation with the baseline HAMD-24 score. Exploratory mediation analysis revealed that the intrinsic ALFF in MFG_R significantly mediated the association between the CACNA1C rs11832738 polymorphism and baseline HAMD-24 score.

CONCLUSIONS

A genetic variant in CACNA1C rs11832738 may influence depression severity in MDD patients by moderating spontaneous MFG_R activity.