Increased expression of ER stress, inflammasome activation, and mitochondrial biogenesis-related genes in peripheral blood mononuclear cells in major depressive disorder.

A subset of major depressive disorder (MDD) is characterized by immune system dysfunction, but the intracellular origin of these immune changes remains unclear. Here we tested the hypothesis that abnormalities in endoplasmic reticulum (ER) stress, inflammasome activity and mitochondrial biogenesis contribute to the development of systemic inflammation in MDD. RT-qPCR was used to measure mRNA expression of key organellar genes from peripheral blood mononuclear cells (PBMCs) isolated from 186 MDD and 67 healthy control (HC) subjects. The comparative CT (2-ΔΔCT) method was applied to quantify mRNA expression using GAPDH as the reference gene. After controlling for age, sex, BMI, and medication status using linear regression models, expression of the inflammasome (NLRC4 and NLRP3) and the ER stress (XBP1u, XBP1s, and ATF4) genes was found to be significantly increased in the MDD versus the HC group. Sensitivity analyses excluding covariates yielded similar results. After excluding outliers, expression of the inflammasome genes was no longer statistically significant but expression of the ER stress genes (XBP1u, XBP1s, and ATF4) remained significant and the mitochondrial biogenesis gene, MFN2, was significantly increased in the MDD group. NLRC4 and MFN2 were positively correlated with serum C-reactive protein concentrations, while ASC trended significant. The altered expression of inflammasome activation, ER stress, and mitochondrial biogenesis pathway components suggest that dysfunction of these organelles may play a role in the pathogenesis of MDD.

Cytomegalovirus antibodies are associated with mood disorders, suicide, markers of neuroinflammation, and microglia activation in postmortem brain samples.

Cytomegalovirus (CMV) is a common, neurotrophic herpesvirus that can be reactivated by inflammation and cause central nervous system disease. We hypothesize that CMV may contribute to the neuroinflammation that underlies some psychiatric disorders by (1) exacerbating inflammation through the induction of anti-viral immune responses, and (2) translating peripheral inflammation into neuroinflammation. We investigated whether the presence of anti-CMV antibodies in blood were associated with mental illness, suicide, neuroinflammation, and microglial density in the dorsolateral prefrontal cortex (DLPFC) in postmortem samples. Data (n = 114 with schizophrenia; n = 78 with bipolar disorder; n = 87 with depression; n = 85 controls) were obtained from the Stanley Medical Research Institute. DLPFC gene expression data from a subset of 82 samples were categorized into "high" (n = 30), and "low" (n = 52) inflammation groups based on a recursive two-step cluster analysis using expression data for four inflammation-related genes. Measurements of the ratio of non-ramified to ramified microglia, a proxy of microglial activation, were available for a subset of 49 samples. All analyses controlled for age, sex, and ethnicity, as well as postmortem interval, and pH for gene expression and microglial outcomes. CMV seropositivity significantly increased the odds of a mood disorder diagnosis (bipolar disorder: OR = 2.45; major depression: OR = 3.70) and among the psychiatric samples, of suicide (OR = 2.09). Samples in the upper tercile of anti-CMV antibody titers were more likely to be members of the "high" inflammation group (OR = 4.41, an effect driven by schizophrenia and bipolar disorder samples). CMV positive samples also showed an increased ratio of non-ramified to ramified microglia in layer I of the DLPFC (Cohen's d = 0.81) as well as a non-significant increase in this ratio for the DLPFC as a whole (d = 0.56). The results raise the possibility that the reactivation of CMV contributes to the neuroinflammation that underlies some cases of psychiatric disorders.

State-specific alterations in the neural computations underlying inhibitory control in women remitted from bulimia nervosa.

The neurocomputational processes underlying bulimia nervosa and its primary symptoms, out-of-control overeating and purging, are poorly understood. Research suggests that the brains of healthy individuals form a dynamic internal model to predict whether control is needed in each moment. This study tested the hypothesis that this computational process of inhibitory control is abnormally affected by metabolic state (being fasted or fed) in bulimia nervosa. A Bayesian ideal observer model was fit to behavioral data acquired from 22 women remitted from bulimia nervosa and 20 group-matched controls who completed a stop-signal task during two counterbalanced functional MRI sessions, one after a 16 h fast and one after a meal. This model estimates participants' trial-by-trial updating of the probability of a stop signal based on their experienced trial history. Neural analyses focused on control-related Bayesian prediction errors, which quantify the direction and degree of "surprise" an individual experiences on any given trial. Regardless of group, metabolic state did not affect behavioral performance on the task. However, metabolic state modulated group differences in neural activation. In the fed state, women remitted from bulimia nervosa had attenuated prediction-error-dependent activation in the left dorsal caudate. This fed-state activation was lower among women with more frequent past binge eating and self-induced vomiting. When they are in a fed state, individuals with bulimia nervosa may not effectively process unexpected information needed to engage inhibitory control. This may explain the difficulties these individuals have stopping eating after it begins.

Dose-response in modulating brain function with transcranial direct current stimulation: From local to network levels.

Understanding the dose-response relationship is crucial in studying the effects of brain stimulation techniques, such as transcranial direct current stimulation (tDCS). The dose-response relationship refers to the relationship between the received stimulation dose and the resulting response, which can be described as a function of the dose at various levels, including single/multiple neurons, clusters, regions, or networks. Here, we are focused on the received stimulation dose obtained from computational head models and brain responses which are quantified by functional magnetic resonance imaging (fMRI) data. In this randomized, triple-blind, sham-controlled clinical trial, we recruited sixty participants with methamphetamine use disorders (MUDs) as a sample clinical population who were randomly assigned to receive either sham or active tDCS. Structural and functional MRI data, including high-resolution T1 and T2-weighted MRI, resting-state functional MRI, and a methamphetamine cue-reactivity task fMRI, were acquired before and after tDCS. Individual head models were generated using the T1 and T2-weighted MRI data to simulate electric fields. In a linear approach, we investigated the associations between electric fields (received dose) and changes in brain function (response) at four different levels: voxel level, regional level (using atlas-based parcellation), cluster level (identifying active clusters), and network level (task-based functional connectivity). At the voxel level, regional level, and cluster level, no FDR-corrected significant correlation was observed between changes in functional activity and electric fields. However, at the network level, a significant positive correlation was found between frontoparietal connectivity and the electric field at the frontopolar stimulation site (r = 0.42, p corrected = 0.02; medium effect size). Our proposed pipeline offers a methodological framework for analyzing tDCS effects by exploring dose-response relationships at different levels, enabling a direct link between electric field variability and the neural response to tDCS. The results indicate that network-based analysis provides valuable insights into the dependency of tDCS neuromodulatory effects on the individual's regional current dose. Integration of dose-response relationships can inform dose optimization, customization, or the extraction of predictive/treatment-response biomarkers in future brain stimulation studies.

Are we really targeting and stimulating DLPFC by placing transcranial electrical stimulation (tES) electrodes over F3/F4?

In many clinical trials involving transcranial electrical stimulation (tES), target electrodes are typically placed over DLPFC with the assumption that this will primarily stimulate the underlying brain region. However, our study aimed to evaluate the electric fields (EF) that are actually delivered and identify prefrontal regions that may be inadvertently targeted in DLPFC tES. Head models were generated from the Human Connectome Project database's T1 + T2-weighted MRIs of 80 healthy adults. Two common DLPFC montages were simulated; symmetric-F4/F3, and asymmetric-F4/Fp1. Averaged EF was extracted from (1) the center of the target electrode (F4), and (2) the top 1% of voxels showing the strongest EF in individualized EF maps. Interindividual variabilities were quantified with the standard deviation of EF peak location/value. Similar steps were repeated with 66 participants with methamphetamine use disorder (MUDs) as an independent clinical population. In healthy adults, the group-level location of EF peaks was situated in the medial-frontopolar, and the individualized EF peaks were positioned in a cube with a volume of 29 cm3 /46 cm3 (symmetric/asymmetric montages). EFs in the frontopolar area were significantly higher than EF "under" the target electrode in both symmetric (peak: 0.41 ± 0.06, F4:0.22 ± 0.04) and asymmetric (peak: 0.38 ± 0.04, F4:0.2 ± 0.04) montages (Heges'g > 0.7). Similar results with slight between-group differences were found in MUDs. We highlighted that in common DLPFC tES montages, in addition to interindividual/intergroup variability, the frontopolar received the highest EFs rather than DLPFC as the main target. We specifically recommended considering the potential involvement of the frontopolar area as a mechanism underlying the effectiveness of DLPFC tES protocols.

Intensity of repetitive negative thinking in depression is associated with greater functional connectivity between semantic processing and emotion regulation areas.

BACKGROUND: Repetitive negative thinking (RNT), a cognitive process that encompasses past (rumination) and future (worry) directed thoughts focusing on negative experiences and the self, is a transdiagnostic construct that is especially relevant for major depressive disorder (MDD). Severe RNT often occurs in individuals with severe levels of MDD, which makes it challenging to disambiguate the neural circuitry underlying RNT from depression severity. METHODS: We used a propensity score, i.e., a conditional probability of having high RNT given observed covariates to match high and low RNT individuals who are similar in the severity of depression, anxiety, and demographic characteristics. Of 148 MDD individuals, we matched high and low RNT groups (n = 50/group) and used a data-driven whole-brain voxel-to-voxel connectivity pattern analysis to investigate the resting-state functional connectivity differences between the groups. RESULTS: There was an association between RNT and connectivity in the bilateral superior temporal sulcus (STS), an important region for speech processing including inner speech. High relative to low RNT individuals showed greater connectivity between right STS and bilateral anterior insular cortex (AI), and between bilateral STS and left dorsolateral prefrontal cortex (DLPFC). Greater connectivity in those regions was specifically related to RNT but not to depression severity. CONCLUSIONS: RNT intensity is directly related to connectivity between STS and AI/DLPFC. This might be a mechanism underlying the role of RNT in perceptive, cognitive, speech, and emotional processing. Future investigations will need to determine whether modifying these connectivities could be a treatment target to reduce RNT.

Elevated decision uncertainty and reduced avoidance drives in depression, anxiety and substance use disorders during approach-avoidance conflict: a replication study.

BACKGROUND: Decision-making under approach-avoidance conflict (AAC; e.g., sacrificing quality of life to avoid feared outcomes) may be affected in multiple psychiatric disorders. Recently, we used a computational (active inference) model to characterize information processing differences during AAC in individuals with depression, anxiety and/or substance use disorders. Individuals with psychiatric disorders exhibited increased decision uncertainty (DU) and reduced sensitivity to unpleasant stimuli. This preregistered study aimed to determine the replicability of this processing dysfunction. METHODS: A new sample of participants completed the AAC task. Individual-level computational parameter estimates, reflecting decision uncertainty and sensitivity to unpleasant stimuli ("emotion conflict"; EC), were obtained and compared between groups. Subsequent analyses combining the prior and current samples allowed assessment of narrower disorder categories. RESULTS: The sample in the present study included 480 participants: 97 healthy controls, 175 individuals with substance use disorders and 208 individuals with depression and/or anxiety disorders. Individuals with substance use disorders showed higher DU and lower EC values than healthy controls. The EC values were lower in females, but not males, with depression and/or anxiety disorders than in healthy controls. However, the previously observed difference in DU between participants with depression and/or anxiety disorders and healthy controls did not replicate. Analyses of specific disorders in the combined samples indicated that effects were common across different substance use disorders and affective disorders. LIMITATIONS: There were differences, although with small effect size, in age and baseline intellectual functioning between the previous and current sample, which may have affected replication of DU differences in participants with depression and/or anxiety disorders. CONCLUSION: The now robust evidence base for these clinical group differences motivates specific questions that should be addressed in future research: can DU and EC become behavioural treatment targets, and can we identify neural substrates of DU and EC that could be used to measure severity of dysfunction or as neuromodulatory treatment targets?

Real-Time fMRI Functional Connectivity Neurofeedback Reducing Repetitive Negative Thinking in Depression: A Double-Blind, Randomized, Sham-Controlled Proof-of-Concept Trial.

INTRODUCTION: Repetitive negative thinking (RNT) is a cognitive process focusing on self-relevant and negative experiences, leading to a poor prognosis of major depressive disorder (MDD). We previously identified that connectivity between the precuneus/posterior cingulate cortex (PCC) and right temporoparietal junction (rTPJ) was positively correlated with levels of RNT. OBJECTIVE: In this double-blind, randomized, sham-controlled, proof-of-concept trial, we employed real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) to delineate the neural processes that may be causally linked to RNT and could potentially become treatment targets for MDD. METHODS: MDD-affected individuals were assigned to either active (n = 20) or sham feedback group (n = 19). RNT was measured by the Ruminative Response Scale-brooding subscale (RRS-B) before and 1 week after the intervention. RESULTS: Individuals in the active but not in the sham group showed a significant reduction in the RRS-B; however, a greater reduction in the PCC-rTPJ connectivity was unrelated to a greater reduction in the RRS-B. Exploratory analyses revealed that a greater reduction in the retrosplenial cortex (RSC)-rTPJ connectivity yielded a more pronounced reduction in the RRS-B in the active but not in the sham group. CONCLUSIONS: RtfMRI-nf was effective in reducing RNT. Considering the underlying mechanism of rtfMIR-nf, the RSC and rTPJ could be part of a network (i.e., default mode network) that might collectively affect the intensity of RNT. Understanding the relationship between the functional organization of targeted neural changes and clinical metrics, such as RNT, has the potential to guide the development of mechanism-based treatment of MDD.

AI-based dimensional neuroimaging system for characterizing heterogeneity in brain structure and function in major depressive disorder: COORDINATE-MDD consortium design and rationale.

BACKGROUND: Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states. METHODS: We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants. RESULTS: We are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites. CONCLUSION: We describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project.

The beneficial effect of sleep on behavioral health problems in youth is disrupted by prenatal cannabis exposure: A causal random forest analysis of Adolescent Brain Cognitive Development data.

Studies suggest prenatal cannabis exposure is associated with mood/behavioral problems in children. However, it is unclear if targeting modifiable domains like sleep behaviors would improve outcomes in exposed youth. Using a causal inference framework, the effect of changing sleep-hours on changing internalizing/externalizing problems in children was examined using the Adolescent Brain Cognitive Development™ study baseline (ages 9-10; collected during 2016-2018) and year-1 follow-up data (N = 9825; 4663 female; 5196 white). Average treatment effects (ATE) indicated that more sleep predicted less internalizing (ATE = -.34, SE = .08, p < .001) and externalizing (ATE = -.29, SE = .07, p < .001) problems over time. However, prenatal cannabis exposure moderated the ATE on internalizing (conditional-ATE = .91, SE = .39, p = .019), whereby participants with exposure (n = 605) did not show any effect of changing sleep-hours on mood (B = .09, SE = .24).

Rapid, reliable mobile assessment of affect-related motor processing.

Mobile technologies can be used for behavioral assessments to associate changes in behavior with environmental context and its influence on mental health and disease. Research on real-time motor control with a joystick, analyzed using a computational proportion-derivative (PD) modeling approach, has shown that model parameters can be estimated with high reliability and are related both to self-reported fear and to brain structures important for affective regulation, such as the anterior cingulate cortex. Here we introduce a mobile version of this paradigm, the rapid assessment of motor processing (RAMP) paradigm, and show that it provides robust, reliable, and accessible behavioral measurements relevant to mental health. A smartphone version of a previous joystick sensorimotor task was developed in which participants control a virtual car to a stop sign and stop. A sample of 89 adults performed the task, with 66 completing a second retest session. A PD modeling approach was applied to compute Kp (drive) and Kd (damping) parameters. Both Kp and Kd exhibited high test-retest reliabilities (ICC .81 and .78, respectively). Replicating a previous finding from a different sample with the joystick version of the task, both Kp and Kd were negatively associated with self-reported fear. The RAMP paradigm, a mobile sensorimotor assessment, can be used to assess drive and damping during motor control, which is robustly associated with subjective affect. This paradigm could be useful for examining dynamic contextual modulation of affect-related processing, which could improve assessment of the effects of interventions for psychiatric disorders in a real-world context.

Neural substrates of substance use disorders.

PURPOSE OF REVIEW: Substance use disorders account for a tremendous burden to society, yet despite substantial progress in basic studies, our understanding of the brain-basis of these disorders is still emerging. This review summarizes the recent findings of neuroimaging studies with substance use disorder individuals. RECENT FINDINGS: Resting-state functional connectivity studies support for some but not all substances of abuse and disruption in executive control. Structural neuroimaging findings point towards reduced subcortical volumes, which may emerge as an interaction between preexisting factors and recent substance use. Longitudinal studies implicate some of the same core brain structures and their functional role that have also been identified via case-control studies. Finally, meta-analyses support the idea of dysregulation of cortical control over subcortical salience processing. SUMMARY: Although progress has been made and there is both structural and functional imaging evidence of an imbalance between brain structures involved in executive control and salience processing, there is emerging evidence that brain-behaviour relationships, which are core to discovering the neural processes that lead to and maintain substance use, are small and require larger consortia that prospectively examine individuals with substance use disorder.

Transcranial direct current stimulation to modulate fMRI drug cue reactivity in methamphetamine users: A randomized clinical trial.

Transcranial direct current stimulation (tDCS) has been studied as a therapeutic option to alter maladaptive brain functions associated with chronic substance use. We present a randomized, triple-blind, sham-controlled, clinical trial to determine the neural substrates of tDCS effects on drug craving. Sixty participants with methamphetamine use disorder were assigned to two groups: active tDCS (5 x 7 cm2 , 2 mA, 20 min, anode/cathode over the F4/Fp1) and sham stimulation. Neuroimaging data of a methamphetamine cue reactivity task were collected immediately before and after stimulation. There was a significant reduction in self-reported craving after stimulation without any significant effect of time-by-group interaction. Our whole-brain analysis demonstrated that there was a global decrease in brain reactivity to cues following sham but not active tDCS. There were significant time-by-group interactions in five main clusters in middle and inferior frontal gyri, anterior insula, inferior parietal lobule, and precuneus with higher activations after active stimulation. There was a significant effect of stimulation type in the relationship between electrical current at the individual level and changes in task-modulated activation. Brain regions with the highest electric current in the prefrontal cortex showed a significant time-by-group interaction in task-modulated connectivity in the frontoparietal network. In this trial, there was no significant effect of the one session of active-F4/Fp1 tDCS on drug craving self-report compared to sham stimulation. However, activation and connectivity differences induced by active compared to sham stimulation suggested some potential mechanisms of tDCS to modulate neural response to drug cues.

Predicting alcohol dependence from multi-site brain structural measures.

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega-analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Working Group. Data were grouped into a training set used for internal validation including 1,652 participants (692 AD, 24 sites), and a test set used for external validation with 382 participants (146 AD, 3 sites). An exploratory data analysis was first conducted, followed by an evolutionary search based feature selection to site generalizable and high performing subsets of brain measurements. Exploratory data analysis revealed that inclusion of case- and control-only sites led to the inadvertent learning of site-effects. Cross validation methods that do not properly account for site can drastically overestimate results. Evolutionary-based feature selection leveraging leave-one-site-out cross-validation, to combat unintentional learning, identified cortical thickness in the left superior frontal gyrus and right lateral orbitofrontal cortex, cortical surface area in the right transverse temporal gyrus, and left putamen volume as final features. Ridge regression restricted to these features yielded a test-set area under the receiver operating characteristic curve of 0.768. These findings evaluate strategies for handling multi-site data with varied underlying class distributions and identify potential biomarkers for individuals with current AD.

Self-regulation of the posterior cingulate cortex with real-time fMRI neurofeedback augmented mindfulness training in healthy adolescents: A nonrandomized feasibility study.

Mindfulness training (MT) promotes the development of one's ability to observe and attend to internal and external experiences with objectivity and nonjudgment with evidence to improve psychological well-being. Real-time functional MRI neurofeedback (rtfMRI-nf) is a noninvasive method of modulating activity of a brain region or circuit. The posterior cingulate cortex (PCC) has been hypothesized to be an important hub instantiating a mindful state. This nonrandomized, single-arm study examined the feasibility and tolerability of training typically developing adolescents to self-regulate the posterior cingulate cortex (PCC) using rtfMRI-nf during MT. Thirty-four adolescents (mean age: 15 years; 14 females) completed the neurofeedback augmented mindfulness training task, including Focus-on-Breath (MT), Describe (self-referential thinking), and Rest conditions, across three neurofeedback and two non-neurofeedback runs (Observe, Transfer). Self-report assessments demonstrated the feasibility and tolerability of the task. Neurofeedback runs differed significantly from non-neurofeedback runs for the Focus-on-Breath versus Describe contrast, characterized by decreased activity in the PCC during the Focus-on-Breath condition (z = -2.38 to -6.27). MT neurofeedback neural representation further involved the medial prefrontal cortex, anterior cingulate cortex, dorsolateral prefrontal cortex, posterior insula, hippocampus, and amygdala. State awareness of physical sensations increased following rtfMRI-nf and was maintained at 1-week follow-up (Cohens' d = 0.69). Findings demonstrate feasibility and tolerability of rtfMRI-nf in healthy adolescents, replicates the role of PCC in MT, and demonstrate a potential neuromodulatory mechanism to leverage and streamline the learning of mindfulness practice. ( ClinicalTrials.gov identifier #NCT04053582; August 12, 2019).

Behavioral activation therapy for depression is associated with a reduction in the concentration of circulating quinolinic acid.

BACKGROUND: An inflammation-induced imbalance in the kynurenine pathway (KP) has been reported in major depressive disorder but the utility of these metabolites as predictive or therapeutic biomarkers of behavioral activation (BA) therapy is unknown. METHODS: Serum samples were provided by 56 depressed individuals before BA therapy and 29 of these individuals also provided samples after 10 weeks of therapy to measure cytokines and KP metabolites. The PROMIS Depression Scale (PROMIS-D) and the Sheehan Disability Scale were administered weekly and the Beck depression inventory was administered pre- and post-therapy. Data were analyzed with linear mixed-effect, general linear, and logistic regression models. The primary outcome for the biomarker analyses was the ratio of kynurenic acid to quinolinic acid (KynA/QA). RESULTS: BA decreased depression and disability scores (p's < 0.001, Cohen's d's > 0.5). KynA/QA significantly increased at post-therapy relative to baseline (p < 0.001, d = 2.2), an effect driven by a decrease in QA post-therapy (p < 0.001, uncorrected, d = 3.39). A trend towards a decrease in the ratio of kynurenine to tryptophan (KYN/TRP) was also observed (p = 0.054, uncorrected, d = 0.78). Neither the change in KynA/QA, nor baseline KynA/QA were associated with response to BA therapy. CONCLUSION: The current findings together with previous research show that electronconvulsive therapy, escitalopram, and ketamine decrease concentrations of the neurotoxin, QA, raise the possibility that a common therapeutic mechanism underlies diverse forms of anti-depressant treatment but future controlled studies are needed to test this hypothesis.

C-Reactive protein and the kynurenic acid to quinolinic acid ratio are independently associated with white matter integrity in major depressive disorder.

Kynurenic acid (KynA) and quinolinic acid (QA) are neuroactive kynurenine pathway (KP) metabolites that have neuroprotective and neurotoxic properties, respectively. At least partly as a result of immune activation, the ratio of KynA to QA in the blood is reduced in major depressive disorder (MDD) and has been reported to be positively correlated with gray matter volume in depression. This study examined whether the inflammatory mediator, C-reactive protein (CRP) and the putative neuroprotective index, KynA/QA, were associated with white matter integrity in MDD, and secondly, whether any such associations were independent of each other or whether the effect of CRP was mediated by KynA/QA. One hundred and sixty-six participants in the Tulsa 1000 study with a DSM-V diagnosis of MDD completed diffusion tensor imaging and provided a serum sample for the quantification of CRP, KynA, and QA. Correlational tractography was performed using DSI Studio to map the specific white matter pathways that correlated with CRP and KynA/QA. CRP was negatively related to KynA/QA (standardized beta coefficient, SBC = -0.35 with standard error, Std.E = 0.13, p < 0.01) after controlling for nine possible confounders, i.e., age, sex, body mass index (BMI), medication status, lifetime alcohol use, severity of depression, severity of anxiety, length of illness, and smoking status. Higher concentrations of CRP were associated with decreased white matter integrity (fractional anisotropy, FA) of the bilateral cingulum and fornix after controlling for the nine potential confounders (SBC = -0.43, Std.E = 0.13, p = 0.002). Greater serum KynA/QA was associated with increased white matter integrity of the bilateral fornix, bilateral superior thalamic radiations, corpus callosum, and bilateral cingulum bundles after controlling for the same possible confounders (SBC = 0.26, Std.E = 0.09, p = 0.005). The relationship between CRP and FA was not mediated by KynA/QA. Exploratory analyses also showed that KynA/QA but not CRP was associated with self-reported positive affect, attentiveness, and fatigue measured with the PANASX (SBCs = 0.17-0.23). Taken together, these results are consistent with the hypothesis that within a subgroup of MDD patients, a higher level of systemic inflammation alters the balance of KP metabolism but also raise the possibility that CRP and neuroactive KP metabolites represent independent molecular mechanisms underlying white matter alterations in MDD.

Out-of-step: brain-heart desynchronization in anxiety disorders.

Imaging studies in anxiety disorders (AD) show abnormal functional connectivity primarily in the salience network (SN), somatomotor network (SMN), and default mode network (DMN). However, it is not clear how precisely these network changes occur including their relation to psychopathological symptoms. Here, we show that the functional networks affected in AD overlap with cortical regions that receive visceral inputs (the so-called central/visceral autonomic network). Focusing on cardiac afferents, we suggest that network changes in AD may be due to reduced phase synchronization between ongoing neural and cardiac activity. This neuro-cardiac desynchronization occurs due to the abnormal phase resetting of neural activity at the onset of each heartbeat, as measured by a lower intertrial coherence and heartbeat-evoked potential. Biochemically, cardiac afferents reach subcortical serotonergic raphe nuclei and noradrenergic locus coeruleus (among others) which, in turn, are known to reciprocally modulate the DMN and SMN/SN on the cortical level. Consistent with the network changes in AD, decreases in serotonergic and noradrenergic activity are known to increase connectivity in both SMN and SN while, at the same time, they decrease DMN connectivity. SMN and SN increases, in turn, lead to increased emotional arousal/anxiety and bodily awareness whereas decreased DMN connectivity leads to an unstable sense-of-self in AD. Finally, we integrate our proposal with interoceptive predictive processing models suggesting neuro-cardiac desynchronization as a mechanism for "noisy" bottom-up information leading to a persistently uncertain bodily state in top-down models. In sum, integrating theories on active interference and hyperarousal, we propose a precise neuro-cardiac and biochemically -driven mechanisms for key psychopathological symptoms of AD.

A hidden menace? Cytomegalovirus infection is associated with reduced cortical gray matter volume in major depressive disorder.

Human cytomegalovirus (HCMV) infection is associated with neuropathology in patients with impaired immunity and/or inflammatory diseases. However, the association between gray matter volume (GMV) and HCMV has never been examined in major depressive disorder (MDD) despite the presence of inflammation and impaired viral immunity in a subset of patients. We tested this relationship in two independent samples consisting of 179 individuals with MDD and 41 healthy controls (HC) (sample 1) and 124 MDD participants and 148 HCs (sample 2). HCMV positive (HCMV+) and HCMV negative (HCMV-) groups within each sample were balanced on up to 11 different clinical/demographic variables using inverse probability of treatment weighting. GMV of 87 regions was measured with FreeSurfer. There was a main effect of HCMV serostatus but not diagnosis that replicated across samples. Relative to HCMV- subjects, HCMV+ subjects in sample 1 showed a significant reduction of volume in six regions (puncorrected < 0.05). The reductions in GMV of the right supramarginal gyrus (standardized beta coefficient (SBC) = -0.26) and left fusiform gyrus (SBC = -0.25) in sample 1 were replicated in sample 2: right supramarginal gyrus (puncorrected < 0.05, SBC = -0.32), left fusiform gyrus (PFDR < 0.01, SBC = -0.51). Posthoc tests revealed that the effect of HCMV was driven by differences between the HCMV+ and HCMV- MDD subgroups. HCMV IgG level, a surrogate marker of viral activity, was correlated with GMV in the left fusiform gyrus (r = -0.19, Puncorrected = 0.049) and right supramarginal gyrus (r = -0.19, puncorrected = 0.043) in the HCMV+ group of sample 1. Conceivably, HCMV infection may be a treatable source of neuropathology in vulnerable MDD patients.

Striatal reactivity during emotion and reward relates to approach-avoidance conflict behaviour and is altered in adults with anxiety or depression.

BACKGROUND: We have previously reported activation in reward, salience and executive control regions during functional MRI (fMRI) using an approach-avoidance conflict (AAC) decision-making task with healthy adults. Further investigations into how anxiety and depressive disorders relate to differences in neural responses during AAC can inform their understanding and treatment. We tested the hypothesis that people with anxiety or depression have altered neural activation during AAC. METHODS: We compared 118 treatment-seeking adults with anxiety or depression and 58 healthy adults using linear mixed-effects models to examine group-level differences in neural activation (fMRI) during AAC decision-making. Correlational analyses examined relationships between behavioural and neural measures. RESULTS: Adults with anxiety or depression had greater striatal engagement when reacting to affective stimuli (p = 0.008, d = 0.31) regardless of valence, and weaker striatal engagement during reward feedback (p = 0.046, d = -0.27) regardless of the presence of monetary reward. They also had blunted amygdala activity during decision-making (p = 0.023, d = -0.32) regardless of the presence of conflict. Across groups, approach behaviour during conflict decision-making was inversely correlated with striatal activation during affective stimuli (p < 0.001, r = -0.28) and positively related to striatal activation during reward feedback (p < 0.001, r = 0.27). LIMITATIONS: Our transdiagnostic approach did not allow for comparisons between specific anxiety disorders, and our cross-sectional approach did not allow for causal inference. CONCLUSION: Anxiety and depression were associated with altered neural responses to AAC. Findings were consistent with the role of the striatum in action selection and reward responsivity, and they point toward striatal reactivity as a future treatment target. Blunting of amygdala activity in anxiety or depression may indicate a compensatory response to inhibit affective salience and maintain approach.