Neuroanatomical dimensions in medication-free individuals with major depressive disorder and treatment response to SSRI antidepressant medications or placebo.

Major depressive disorder (MDD) is a heterogeneous clinical syndrome with widespread subtle neuroanatomical correlates. Our objective was to identify the neuroanatomical dimensions that characterize MDD and predict treatment response to selective serotonin reuptake inhibitor (SSRI) antidepressants or placebo. In the COORDINATE-MDD consortium, raw MRI data were shared from international samples (N = 1,384) of medication-free individuals with first-episode and recurrent MDD (N = 685) in a current depressive episode of at least moderate severity, but not treatment-resistant depression, as well as healthy controls (N = 699). Prospective longitudinal data on treatment response were available for a subset of MDD individuals (N = 359). Treatments were either SSRI antidepressant medication (escitalopram, citalopram, sertraline) or placebo. Multi-center MRI data were harmonized, and HYDRA, a semi-supervised machine-learning clustering algorithm, was utilized to identify patterns in regional brain volumes that are associated with disease. MDD was optimally characterized by two neuroanatomical dimensions that exhibited distinct treatment responses to placebo and SSRI antidepressant medications. Dimension 1 was characterized by preserved gray and white matter (N = 290 MDD), whereas Dimension 2 was characterized by widespread subtle reductions in gray and white matter (N = 395 MDD) relative to healthy controls. Although there were no significant differences in age of onset, years of illness, number of episodes, or duration of current episode between dimensions, there was a significant interaction effect between dimensions and treatment response. Dimension 1 showed a significant improvement in depressive symptoms following treatment with SSRI medication (51.1%) but limited changes following placebo (28.6%). By contrast, Dimension 2 showed comparable improvements to either SSRI (46.9%) or placebo (42.2%) (ß = -18.3, 95% CI (-34.3 to -2.3), P = 0.03). Findings from this case-control study indicate that neuroimaging-based markers can help identify the disease-based dimensions that constitute MDD and predict treatment response.

Blunted stimulus-preceding negativity during reward anticipation in major depressive disorder.

BACKGROUND: Reward processing dysfunction is a core characteristic of major depressive disorder (MDD), yet event-related potential (ERP) research in MDD has predominantly focused on reward receipt as opposed to anticipation. The stimulus-preceding negativity (SPN) ERP reflects anticipatory brain processing. This study examines whether individuals with MDD exhibit deficits during reward anticipation as evidenced by altered SPN amplitude. METHODS: We assessed prefeedback-SPN amplitudes during a monetary incentive delay (MID) task in individuals with MDD (n = 142, 99 with comorbid anxiety disorders [MDD + ANX]) compared to Controls (n = 37). A mixed analysis of variance was performed on prefeedback-SPN amplitude and behavioral measures, with group (MDD, MDD + ANX, Control) as the between-subjects factor, and feedback (gain, loss) and electrode (F3, F4, Fz, C3, C4, Cz, P3, P4, Pz) as within-subjects factors. RESULTS: A group main effect revealed faster reaction times for the Control group than MDD and MDD + ANX groups. A group x feedback interaction indicated that the MDD subgroup had smaller prefeedback-SPN amplitudes than MDD + ANX and Control groups when anticipating gain feedback. Additionally, individuals with current MDD, irrespective of past MDD and comorbid anxiety, exhibited smaller SPN amplitudes than Controls prior to gain feedback. LIMITATIONS: The MID paradigm, designed for functional magnetic resonance imaging (fMRI) data acquisition, lacks optimization for ERP analysis. Moreover, the clinical groups included more females than the Control group. CONCLUSIONS: Reduced resource allocation to reward anticipation may differentiate MDD from MDD + ANX and Control groups. Further investigation of the neural mechanisms of distinct MDD phenotypes is warranted.

Exploring the role of neuronal-enriched extracellular vesicle miR-93 and interoception in major depressive disorder.

Major depressive disorder (MDD) is associated with interoceptive processing dysfunctions, but the molecular mechanisms underlying this dysfunction are poorly understood. This study combined brain neuronal-enriched extracellular vesicle (NEEV) technology and serum markers of inflammation and metabolism with Functional Magnetic Resonance Imaging (fMRI) to identify the contribution of gene regulatory pathways, in particular micro-RNA (miR) 93, to interoceptive dysfunction in MDD. Individuals with MDD (n = 41) and healthy comparisons (HC; n = 35) provided blood samples and completed an interoceptive attention task during fMRI. EVs were separated from plasma using a precipitation method. NEEVs were enriched by magnetic streptavidin bead immunocapture utilizing a neural adhesion marker (L1CAM/CD171) biotinylated antibody. The origin of NEEVs was validated with two other neuronal markers - neuronal cell adhesion molecule (NCAM) and ATPase Na+/K+ transporting subunit alpha 3 (ATP1A3). NEEV specificities were confirmed by flow cytometry, western blot, particle size analyzer, and transmission electron microscopy. NEEV small RNAs were purified and sequenced. Results showed that: (1) MDD exhibited lower NEEV miR-93 expression than HC; (2) within MDD but not HC, those individuals with the lowest NEEV miR-93 expression had the highest serum concentrations of interleukin (IL)-1 receptor antagonist, IL-6, tumor necrosis factor, and leptin; and (3) within HC but not MDD, those participants with the highest miR-93 expression showed the strongest bilateral dorsal mid-insula activation during interoceptive versus exteroceptive attention. Since miR-93 is regulated by stress and affects epigenetic modulation by chromatin re-organization, these results suggest that healthy individuals but not MDD participants show an adaptive epigenetic regulation of insular function during interoceptive processing. Future investigations will need to delineate how specific internal and external environmental conditions contribute to miR-93 expression in MDD and what molecular mechanisms alter brain responsivity to body-relevant signals.

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 the 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. After excluding outliers, expression of the inflammasome genes was no longer statistically significant but expression of the ER stress genes (XBP1u, XBP1s, and ATF4) and the mitochondrial biogenesis gene, MFN2, was significantly increased in the MDD group. ASC and MFN2 were positively correlated with serum C-reactive protein concentrations. 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.

The unique face of anxious depression: Increased sustained threat circuitry response during fear acquisition.

Background: Sensitivity to threat with dysregulation of fear learning is thought to contribute to the development of psychiatric disorders, including anxiety disorders (AD) and major depressive disorder (MDD). However, fewer studies have examined fear learning in MDD than in AD. Nearly half of individuals with MDD have an AD and the comorbid diagnosis has worse outcomes. The current study used propensity matching to examine the hypothesis that AD+MDD shows greater neural correlates of fear learning than MDD, suggesting that the co-occurrence of AD+MDD is exemplified by exaggerated defense related processes. Methods: 195 individuals with MDD (N = 65) or AD+MDD (N=130) were recruited from the community and completed multi-level assessments, including a Pavlovian fear learning task during functional imaging. Results: MDD and AD+MDD showed significantly different patterns of activation for [CSplus-CSminus] in the medial amygdala (ηp2=0.009), anterior insula (ηp2=0.01), dorsolateral prefrontal cortex (ηp2=0.002), dorsal anterior cingulate cortex (ηp2=0.01), mid-cingulate cortex (ηp2=0.01) and posterior cingulate cortex (ηp2=0.02). These differences were driven by greater activation to the CS+ in late conditioning phases in ADD+MDD relative to MDD. Conclusions: AD+MDD showed a pattern of increased sustained activation in regions identified with fear learning. Effects were consistently driven by the threat condition, further suggesting fear signaling as the emergent target process. Differences emerged in regions associated with salience processing, attentional orienting/conflict, and self-relevant processing.These findings help to elucidate the fear signaling mechanisms involved in the pathophysiology of comorbid anxiety and depression, thereby highlighting promising treatment targets for this prevalent treatment group.

Polygenic risk for neuroticism is associated with less efficient control in more difficult situations.

Neuroticism is a heritable trait and a risk factor for mental health due to its relevance to poor control of negative events. To examine the relationship between genetic propensity for neuroticism and control processing, we used the polygenic risk score (PRS) approach and a stop signal task during fMRI. We hypothesized that genetic propensity for neuroticism may moderate control processing as a function of control difficulty. PRSs for neuroticism were computed from a transdiagnostic group of individuals (n=406) who completed the stop signal task. The level of control difficulty was a function of the stop signal asynchrony: shorter asynchrony allows easier stopping whereas longer asynchrony makes stopping difficult. The relationship between PRS for neuroticism and neural activity for controlling responses was examined by the stop signal asynchrony. Although PRS for neuroticism did not relate to the overall inhibitory control, individuals with high PRS for neuroticism showed greater activity in left dorsal prefrontal cortex, middle temporal gyrus, and dorsal posterior cingulate cortex for difficult control. Thus, the genetic propensity for neuroticism affects neural processing in a difficult control context, which may help to explain why individuals with high levels of neuroticism exert poor control of negative events in difficult situations.

Exploring the role of neuronal-enriched extracellular vesicle miR-93 and interoception in major depressive disorder.

Major depressive disorder (MDD) is associated with interoceptive processing dysfunctions, but the molecular mechanisms underlying this dysfunction are poorly understood. This study combined brain Neuronal-Enriched Extracellular Vesicle (NEEV) technology and serum markers of inflammation and metabolism with Functional Magnetic Resonance Imaging (fMRI) to identify the contribution of gene regulatory pathways, in particular micro-RNA (miR) 93, to interoceptive dysfunction in MDD. Individuals with MDD (n = 44) and healthy comparisons (HC; n = 35) provided blood samples and completed an interoceptive attention task during fMRI. EVs were separated from plasma using a precipitation method. NEEVs were enriched by magnetic streptavidin bead immunocapture utilizing a neural adhesion marker (CD171) biotinylated antibody. NEEV specificities were confirmed by ow cytometry, western blot, particle size analyzer, and transmission electron microscopy. NEEV small RNAs were purified and sequenced. Results showed that: (1) MDD exhibited lower NEEV miR-93 expression than HC; (2) within MDD but not HC, those individuals with the lowest NEEV miR-93 expression had the highest serum concentrations of interleukin (IL)-1 receptor antagonist, IL-6, tumor necrosis factor, and leptin; and (3) within HC but not MDD, those participants with the highest miR-93 expression showed the strongest bilateral dorsal mid-insula activation. Since miR-93 is regulated by stress and affects epigenetic modulation by chromatin reorganization, these results suggest that healthy individuals but not MDD participants show an adaptive epigenetic regulation of insular function during interoceptive processing. Future investigations will need to delineate how specific internal and external environmental conditions contribute to miR-93 expression in MDD and what molecular mechanisms alter brain responsivity to body-relevant signals.

Elevated serum leptin is associated with attenuated reward anticipation in major depressive disorder independent of peripheral C-reactive protein levels.

Major depressive disorder (MDD) is associated with immunologic and metabolic alterations linked to central processing dysfunctions, including attenuated reward processing. This study investigated the associations between inflammation, metabolic hormones (leptin, insulin, adiponectin), and reward-related brain processing in MDD patients with high (MDD-High) and low (MDD-Low) C-reactive protein (CRP) levels compared to healthy comparison subjects (HC). Participants completed a blood draw and a monetary incentive delay task during functional magnetic resonance imaging. Although groups did not differ in insulin or adiponectin concentrations, both MDD-High (Wilcoxon p = 0.004, d = 0.65) and MDD-Low (Wilcoxon p = 0.046, d = 0.53) showed higher leptin concentrations than HC but did not differ from each other. Across MDD participants, higher leptin levels were associated with lower brain activation during reward anticipation in the left insula (r = - 0.30, p = 0.004) and left dorsolateral putamen (r = -- 0.24, p = 0.025). In contrast, within HC, higher leptin concentrations were associated with higher activation during reward anticipation in the same regions (insula: r = 0.40, p = 0.007; putamen: r = 0.37, p = 0.014). Depression may be characterized by elevated pro-inflammatory signaling via leptin concentrations through alternate inflammatory pathways distinct to CRP.

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.

Single doses of a highly selective inhibitor of phosphodiesterase 1 (lenrispodun) in healthy volunteers: a randomized pharmaco-fMRI clinical trial.

Lenrispodun is a potent and highly selective inhibitor of phosphodiesterase (PDE) type 1, which is thought to prolong intracellular second messenger signaling within cortical and subcortical dopaminergic brain regions. This is the first study of a PDE1 inhibitor in healthy volunteers using behavioral and neuroimaging approaches to examine its effects on neural targets and to provide a safety and tolerability assessment. The primary objectives were to determine whether lenrispodun induces changes in BOLD fMRI signals in the inferior frontal gyrus (IFG) during the stop signal task, and the dorsal anterior insula (dAI) during the extinction phase of a fear conditioning/extinction task. Using a double-blind, placebo-controlled, within-subjects design, 26 healthy individuals (22 completed all fMRI sessions) received in random order a single oral dose of placebo, lenrispodun 1.0 milligram (mg) or lenrispodun 10.0 mg and completed several tasks in the scanner including the stop signal (n = 24) and fear conditioning/extinction tasks (n = 22). Prespecified region-of-interest analyses for the IFG and dAI were computed using linear mixed models. Lenrispodun induced increases in IFG activity during the stop signal task at 1.0 mg (Cohen's d = 0.63) but not 10.0 mg (Cohen's d = 0.07) vs. placebo. Lenrispodun did not induce changes in dAI activity during fear extinction at either dose. Exploratory outcomes revealed changes in cardiac interoception. Lenrispodun administration was well-tolerated. These results provide evidence that 1.0 mg lenrispodun selectively improved neural inhibitory control without altering fear extinction processing. Future investigations should determine whether lenrispodun improves inhibitory control in target populations such as individuals with attention deficit hyperactivity disorder. Trial registration: ClinicalTrials.gov identifier: NCT03489772.

Functional magnetic resonance imaging data for the association between polygenic risk scores for neuroticism and reward-punishment processing.

Neuroticism as a personality trait represents a heritable risk for psychiatric disorders. The polygenic risk score for neuroticism (N-PRS) is used to study genetic vulnerability to neuroticism. The current data present the association of the genetic risk for neuroticism to neural reward-punishment processing using functional magnetic resonance imaging. N-PRS was computed based on the individual's genotype information and a genome-wide association study on the UK Biobank data. While individuals performed a monetary incentive delay task, their neural activations for upcoming incentives (reward: gain, punishment: loss) were measured in blood oxygen level dependent (BOLD) signals during the delay phase. Multivariate ANCOVAs were used to analyze BOLD signals for finding the association between N-PRS and reward-punishment processing by the incentive valence (Related research article: H. Park, K.L. Forthman, R. Kuplicki, T.A. Victor, Tulsa 1000 Investigators, H.W. Yeh, W.K. Thompson, M.P. Paulus, Polygenic risk for neuroticism modulates response to gains and losses in the amygdala and caudate: evidence from a clinical cohort. J. Affect. Disord. 293 (2021) 124-132. https://doi.org/10.1016/j.jad.2021.06.016). These data can be used as reference data for future studies examining the role of the genetic propensity for personality traits in the context of psychiatric disorders.

Methylphenidate augmentation of escitalopram to enhance adherence to antidepressant treatment: a pilot randomized controlled trial.

BACKGROUND: Adherence to treatment, i.e. the extent to which a patient's therapeutic engagement coincides with the prescribed treatment, is among the most important problems in mental health care. The current study investigated the influence of pairing an acute positive reinforcing dopaminergic/noradrenergic effect (methylphenidate, MPH) with a standard antidepressant on the rates of adherence to medication treatment. The primary objective of this study was to determine whether MPH + escitalopram resulted in higher rates of medication adherence relative to placebo + escitalopram. METHODS: Twenty participants with moderate to severe depression were 1-1 randomized to either (1) 5 mg MPH + 10 mg escitalopram or (2) placebo + 10 mg escitalopram with the possibility for a dose increase at 4 weeks. A Bayesian analysis was conducted to evaluate the outcomes. RESULTS: First, neither percent Pill count nor Medication Electronic Monitoring System adherence showed that MPH was superior to placebo. In fact, placebo showed slightly higher adherence rates on the primary (7.82% better than MPH) and secondary (7.07% better than MPH) outcomes. There was a less than 25% chance of MPH augmentation showing at least as good or better adherence than placebo. Second, both groups showed a significant effect of treatment on the QIDS-SR with a median effect of an 8.6-point score reduction. Third, neither subjective measures of adherence attitudes nor socio-demographic covariates had a significant influence on the primary or secondary outcome variables. CONCLUSIONS: These data do not support the use of MPH to increase adherence to antidepressant medication in individuals with moderate to severe depression. CLINICALTRIALS. GOV IDENTIFIER: NCT03388164 , registered on 01/02/2018.

Individuals with substance use disorders have a distinct oral microbiome pattern.

BACKGROUND: Substance use disorder emerges from a complex interaction between genetic predisposition, life experiences, exposure, and subsequent adaptation of biological systems to the repeated use of drugs. Recently, investigators have proposed that the human microbiota may play a role in brain health and disease. In particular, the human oral microbiome is a distinct and diverse ecological niche with its composition influenced by external factors such as lifestyle, diet, and oral hygiene. This investigation examined whether individuals with substance use disorder (SU) show a different oral microbiome pattern and whether this pattern is sufficient to delineate the SU group from healthy comparison (HC) subjects. METHODS: Participants were a sub-sample (N â€‹= â€‹177) of the Tulsa 1000 (T-1000) project. We analyzed 123 SU and 54 HC subjects using 16S rRNA marker gene sequencing to characterize the oral microbiome. RESULTS: The groups differed significantly based on the UniFrac distance, a phylogenetic-based measure of beta diversity, but did not differ in alpha diversity. Using a machine learning approach, microbiome features combined with socio-demographic variables successfully categorized group membership with 87%-92% accuracy, even after controlling for external factors such as smoking or alcohol consumption. SU individuals with relatively lower diversity also reported higher levels of negative reinforcement experiences associated with their primary substance of abuse. CONCLUSIONS: Oral microbiome features are useful to sufficiently differentiate SU from HC subjects. There is some evidence that subjects whose drug use is driven by negative reinforcement show an impoverished oral microbiome. Taken together, the oral microbiome may help to understand the dysfunctional biological processes that promote substance use or may be pragmatically useful as a risk or severity biological marker.

Polygenic risk for neuroticism moderates response to gains and losses in amygdala and caudate: Evidence from a clinical cohort.

BACKGROUND: Neuroticism is a heritable trait that contributes to the vulnerability to depression. We used polygenic risk scores (PRS) to examine genetic vulnerability to neuroticism and its associations with reward/punishment processing in a clinical sample with mood, anxiety, and substance use disorders. It was hypothesized that higher PRS for neuroticism is associated with attenuated neural responses to reward/punishment. METHOD: Four hundred sixty-nine participants were genotyped and their PRSs for neuroticism were computed. Associations between PRS for neuroticism and anticipatory processing of monetary incentives were examined using functional magnetic resonance imaging. RESULTS: Individuals with higher PRS for neuroticism showed less anticipatory activation in the left amygdala and caudate region to incentives regardless of incentive valence. Further, these individuals exhibited altered sensitivity to gain/loss processing in the right anterior insula. Higher PRSs for neuroticism were also associated with reduced processing of gains in the precuneus. LIMITATIONS: The study population consisted of a transdiagnostic sample with dysfunctions in positive and negative valence processing. PRS for neuroticism may be correlated with current clinical symptoms due to the vulnerability to psychiatric disorders. CONCLUSIONS: Greater genetic loading for neuroticism was associated with attenuated anticipatory responsiveness in reward/punishment processing with altered sensitivity to valences. Thus, a higher genetic risk for neuroticism may limit the degree to which positive and/or negative outcomes influence the current mood state, which may contribute to the development of positive and negative affective dysfunctions in individuals with mood, anxiety, and addictive disorders.

Evaluating the resource allocation index as a potential fMRI-based biomarker for substance use disorder.

BACKGROUND: There is a lack of neuroscience-based biomarkers for the diagnosis, treatment and monitoring of individuals with substance use disorders (SUD). The resource allocation index (RAI), a measure of the interrelationship between salience, executive control and default-mode brain networks (SN, ECN, and DMN), has been proposed as one such biomarker. However, the RAI has yet to be extensively tested in SUD samples. METHODS: The present analysis compared RAI scores between individuals with stimulant and/or opioid use disorders (SUD; n = 139, abstinent 4-365 days) and healthy controls (HC; n = 56) who had completed resting-state functional magnetic resonance imaging (fMRI) scans within the context of the Tulsa 1000 cohort. First, we used independent component analysis (ICA) to identify the SN, ECN, and DMN and extract their time series data. Second, we used multiple permutations of automatically identified networks to compute RAI as reported in the fMRI literature. RESULTS: First, the RAI as a metric depended substantially on the approach that was used to define the network components. Second, regardless of the selection of networks, after controlling for multiple testing there was no difference in RAI scores between SUD and HC. Third, the RAI was not associated with any substance use-related self-report measures. CONCLUSION: Taken together, these findings do not provide evidence that RAI can be used as an fMRI-derived biomarker for the severity or diagnosis of individuals with SUD.

Women with Major Depressive Disorder, Irrespective of Comorbid Anxiety Disorders, Show Blunted Bilateral Frontal Responses during Win and Loss Anticipation.

BACKGROUND: Electroencephalography (EEG) studies suggest that major depressive disorder (MDD) is associated with lower left than right frontal brain activity (asymmetry), a pattern appearing stronger in women than men, and when elicited during emotionally-relevant paradigms versus an uncontrolled resting state. However, it is unclear whether this asymmetry pattern generalizes to the common presentation of MDD with co-occurring anxiety. Moreover, asymmetry may differ for anxiety subtypes, wherein anxious apprehension (AnxApp: worry characteristic of generalized anxiety disorder) appears left-lateralized, but anxious arousal (AnxAro: panic characteristic of social anxiety, posttraumatic stress, and panic disorders) may be right-lateralized. METHODS: This analysis attempted to replicate frontal EEG asymmetry patterns using functional magnetic resonance imaging (fMRI). Participants completed clinical interviews and a monetary incentive delay (MID) task during fMRI recording. We compared five groups of right-handed women from the Tulsa 1000 study, MDD (n=40), MDD-AnxApp (n=26), MDD-AnxAro (n=34), MDD-Both (with AnxApp and AnxAro; n=26), and healthy controls (CTL; n=24), as a function of MID anticipation condition (no win/loss, win, loss) and hemisphere on frontal blood oxygen-level-dependent (BOLD) signal. RESULTS: CTL exhibited higher bilateral superior, middle, and inferior middle frontal gyrus BOLD signal than the four MDD groups for high arousal (win and loss) conditions. However, frontal attenuations were unrelated to current depression/anxiety symptoms, suggestive of a trait as opposed to a state marker. LIMITATIONS: This was a cross-sectional analysis restricted to women. CONCLUSIONS: Reduced prefrontal cortex recruitment during processing of both positively and negatively valenced stimuli is consistent with the emotion context insensitivity theory of MDD.

Web-Based Graphic Representation of the Life Course of Mental Health: Cross-Sectional Study Across the Spectrum of Mood, Anxiety, Eating, and Substance Use Disorders.

BACKGROUND: Although patient history is essential for informing mental health assessment, diagnosis, and prognosis, there is a dearth of standardized instruments measuring time-dependent factors relevant to psychiatric disorders. Previous research has demonstrated the potential utility of graphical representations, termed life charts, for depicting the complexity of the course of mental illness. However, the implementation of these assessments is limited by the exclusive focus on specific mental illnesses (ie, bipolar disorder) and the lack of intuitive graphical interfaces for data collection and visualization. OBJECTIVE: This study aimed to develop and test the utility of the Tulsa Life Chart (TLC) as a Web-based, structured approach for obtaining and graphically representing historical information on psychosocial and mental health events relevant across a spectrum of psychiatric disorders. METHODS: The TLC interview was completed at baseline by 499 participants of the Tulsa 1000, a longitudinal study of individuals with depressive, anxiety, substance use, or eating disorders and healthy comparisons (HCs). All data were entered electronically, and a 1-page electronic and interactive graphical representation was developed using the Google Visualization Application Programming Interface. For 8 distinct life epochs (periods of approximately 5-10 years), the TLC assessed the following factors: school attendance, hobbies, jobs, social support, substance use, mental health treatment, family structure changes, negative and positive events, and epoch and event-related mood ratings. We used generalized linear mixed models (GLMMs) to evaluate trajectories of each domain over time and by sex, age, and diagnosis, using case examples and Web-based interactive graphs to visualize data. RESULTS: GLMM analyses revealed main or interaction effects of epoch and diagnosis for all domains. Epoch by diagnosis interactions were identified for mood ratings and the number of negative-versus-positive events (all P values <.001), with all psychiatric groups reporting worse mood and greater negative-versus-positive events than HCs. These differences were most robust at different epochs, depending on diagnosis. There were also diagnosis and epoch main effects for substance use, mental health treatment received, social support, and hobbies (P<.001). User experience ratings (each on a 1-5 scale) revealed that participants found the TLC pleasant to complete (mean 3.07, SD 1.26) and useful for understanding their mental health (mean 3.07, SD 1.26), and that they were likely to recommend it to others (mean 3.42, SD 0.85). CONCLUSIONS: The TLC provides a structured, Web-based transdiagnostic assessment of psychosocial history relevant for the diagnosis and treatment of psychiatric disorders. Interactive, 1-page graphical representations of the TLC allow for the efficient communication of historical life information that would be useful for clinicians, patients, and family members.

Tulsa 1000: a naturalistic study protocol for multilevel assessment and outcome prediction in a large psychiatric sample.

INTRODUCTION: Although neuroscience has made tremendous progress towards understanding the basic neural circuitry underlying important processes such as attention, memory and emotion, little progress has been made in applying these insights to psychiatric populations to make clinically meaningful treatment predictions. The overall aim of the Tulsa 1000 (T-1000) study is to use the NIMH Research Domain Criteria framework in order to establish a robust and reliable dimensional set of variables that quantifies the positive and negative valence, cognition and arousal domains, including interoception, to generate clinically useful treatment predictions. METHODS AND ANALYSIS: The T-1000 is a naturalistic study that will recruit, assess and longitudinally follow 1000 participants, including healthy controls and treatment-seeking individuals with mood, anxiety, substance use and eating disorders. Each participant will undergo interview, behavioural, biomarker and neuroimaging assessments over the course of 1 year. The study goal is to determine how disorders of affect, substance use and eating behaviour organise across different levels of analysis (molecules, genes, cells, neural circuits, physiology, behaviour and self-report) to predict symptom severity, treatment outcome and long-term prognosis. The data will be used to generate computational models based on Bayesian statistics. The final end point of this multilevel latent variable analysis will be standardised assessments that can be developed into clinical tools to help clinicians predict outcomes and select the best intervention for each individual, thereby reducing the burden of mental disorders, and taking psychiatry a step closer towards personalised medicine. ETHICS AND DISSEMINATION: Ethical approval was obtained from Western Institutional Review Board screening protocol #20101611. The dissemination plan includes informing health professionals of results for clinical practice, submitting results to journals for peer-reviewed publication, presenting results at national and international conferences and making the dataset available to researchers and mental health professionals. TRIAL REGISTRATION NUMBER: NCT02450240; Pre-results.

Co-altered functional networks and brain structure in unmedicated patients with bipolar and major depressive disorders.

Bipolar disorder (BD) and major depressive disorder (MDD) share similar clinical characteristics that often obscure the diagnostic distinctions between their depressive conditions. Both functional and structural brain abnormalities have been reported in these two disorders. However, the direct link between altered functioning and structure in these two diseases is unknown. To elucidate this relationship, we conducted a multimodal fusion analysis on the functional network connectivity (FNC) and gray matter density from MRI data from 13 BD, 40 MDD, and 33 matched healthy controls (HC). A data-driven fusion method called mCCA+jICA was used to identify the co-altered FNC and gray matter components. Comparing to HC, BD exhibited reduced gray matter density in the parietal and occipital cortices, which correlated with attenuated functional connectivity within sensory and motor networks, as well as hyper-connectivity in regions that are putatively engaged in cognitive control. In addition, lower gray matter density was found in MDD in the amygdala and cerebellum. High accuracy in discriminating across groups was also achieved by trained classification models, implying that features extracted from the fusion analysis hold the potential to ultimately serve as diagnostic biomarkers for mood disorders.