Showing papers by "Diego A. Pizzagalli published in 2018"

Pretreatment Rostral Anterior Cingulate Cortex Theta Activity in Relation to Symptom Improvement in Depression: A Randomized Clinical Trial

Abstract: Importance Major depressive disorder (MDD) remains challenging to treat. Although several clinical and demographic variables have been found to predict poor antidepressant response, these markers have not been robustly replicated to warrant implementation in clinical care. Increased pretreatment rostral anterior cingulate cortex (rACC) theta activity has been linked to better antidepressant outcomes. However, no prior study has evaluated whether this marker has incremental predictive validity over clinical and demographic measures. Objective To determine whether increased pretreatment rACC theta activity would predict symptom improvement regardless of randomization arm. Design, Setting, and Participants A multicenter randomized clinical trial enrolled outpatients without psychosis and with chronic or recurrent MDD between July 29, 2011, and December 15, 2015 (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care [EMBARC]). Patients were consecutively recruited from 4 university hospitals: 634 patients were screened, 296 were randomized to receive sertraline hydrochloride or placebo, 266 had electroencephalographic (EEG) recordings, and 248 had usable EEG data. Resting EEG data were recorded at baseline and 1 week after trial onset, and rACC theta activity was extracted using source localization. Intent-to-treat analysis was conducted. Data analysis was performed from October 7, 2016, to January 19, 2018. Interventions An 8-week course of sertraline or placebo. Main Outcomes and Measures The 17-item Hamilton Rating Scale for Depression score (assessed at baseline and weeks 1, 2, 3, 4, 6, and 8). Results The 248 participants (160 [64.5%] women, 88 [35.5%] men) with usable EEG data had a mean (SD) age of 36.75 (13.15) years. Higher rACC theta activity at both baseline (b = −1.05; 95% CI, −1.77 to −0.34;P = .004) and week 1 (b = −0.83; 95% CI, −1.60 to −0.06;P Conclusions and Relevance Increased pretreatment rACC theta activity represents a nonspecific prognostic marker of treatment outcome. This is the first study to date to demonstrate that rACC theta activity has incremental predictive validity. Trial Registration clinicaltrials.gov Identifier:NCT01407094

Brain mechanisms mediating effects of stress on reward sensitivity.

Abstract: Acute and chronic stress have dissociable effects on reward sensitivity, and a better understanding of these effects promises to elucidate the pathophysiology of stress-related disorders, particularly depression. Recent preclinical and human findings suggest that stress particularly affects reward anticipation; chronic stress perturbates dopamine signaling in the medial prefrontal cortex and ventral striatum; and such effects are further moderated by early adversities. Additionally, a systems-level approach is uncovering the interplay among striatal, limbic and control networks giving rise to stress-related, blunted reward sensitivity. Together, this cross-species confluence has not only enriched our understanding of stress-reward links but also highlighted the role of neuropeptides and opioid receptors in such effects, and thereby identified novel targets for stress-related neuropsychiatric disorders.

Attention Bias in Rumination and Depression: Cognitive Mechanisms and Brain Networks

Abstract: Depressed individuals exhibit biased attention to negative emotional information. However, much remains unknown about (1) the neurocognitive mechanisms of attention bias (e.g., qualities of negative information that evoke attention bias, or functional brain network dynamics that may reflect a propensity for biased attention) and (2) distinctions in the types of attention bias related to different dimensions of depression (e.g., ruminative depression). Here, in 50 women, clinical depression was associated with facilitated processing of negative information only when such information was self-descriptive and task-relevant. However, among depressed individuals, trait rumination was associated with biases towards negative self-descriptive information regardless of task goals, especially when negative self-descriptive material was paired with self-referential images that should be ignored. Attention biases in ruminative depression were mediated by dynamic variability in frontoinsular resting-state functional connectivity. These findings highlight potential cognitive and functional network mechanisms of attention bias specifically related to the ruminative dimension of depression.

Frontostriatal and Dopamine Markers of Individual Differences in Reinforcement Learning: A Multi-modal Investigation.

Abstract: Prior studies have shown that dopamine (DA) functioning in frontostriatal circuits supports reinforcement learning (RL), as phasic DA activity in ventral striatum signals unexpected reward and may drive coordinated activity of striatal and orbitofrontal regions that support updating of action plans. However, the nature of DA functioning in RL is complex, in particular regarding the role of DA clearance in RL behavior. Here, in a multi-modal neuroimaging study with healthy adults, we took an individual differences approach to the examination of RL behavior and DA clearance mechanisms in frontostriatal learning networks. We predicted that better RL would be associated with decreased striatal DA transporter (DAT) availability and increased intrinsic functional connectivity among DA-rich frontostriatal regions. In support of these predictions, individual differences in RL behavior were related to DAT binding potential in ventral striatum and resting-state functional connectivity between ventral striatum and orbitofrontal cortex. Critically, DAT binding potential had an indirect effect on reinforcement learning behavior through frontostriatal connectivity, suggesting potential causal relationships across levels of neurocognitive functioning. These data suggest that individual differences in DA clearance and frontostriatal coordination may serve as markers for RL, and suggest directions for research on psychopathologies characterized by altered RL.

A Novel Strategy to Identify Placebo Responders: Prediction Index of Clinical and Biological Markers in the EMBARC Trial.

Abstract: Background: One in three clinical trial patients with major depressive disorder report symptomatic improvement with placebo. Strategies to mitigate the effect of placebo responses have focused on modifying study design with variable success. Identifying and excluding or controlling for individuals with a high likelihood of responding to placebo may improve clinical trial efficiency and avoid unnecessary medication trials. Methods: Participants included those assigned to the placebo arm (n = 141) of the Establishing Moderators and Biosignatures for Antidepressant Response in Clinical Care (EMBARC) trial. The elastic net was used to evaluate 283 baseline clinical, behavioral, imaging, and electrophysiological variables to identify the most robust yet parsimonious features that predicted depression severity at the end of the double-blind 8-week trial. Variables retained in at least 50% of the 100 imputed data sets were used in a Bayesian multiple linear regression model to simultaneously predict the probabilities of response and remission. Results: Lower baseline depression severity, younger age, absence of melancholic features or history of physical abuse, less anxious arousal, less anhedonia, less neuroticism, and higher average theta current density in the rostral anterior cingulate predicted a higher likelihood of improvement with placebo. The Bayesian model predicted remission and response with an actionable degree of accuracy (both AUC > 0.73). An interactive calculator was developed predicting the likelihood of placebo response at the individual level. Conclusion: Easy-to-measure clinical, behavioral, and electrophysiological assessments can be used to identify placebo responders with a high degree of accuracy. Development of this calculator based on these findings can be used to identify potential placebo responders.

Development and evaluation of a multimodal marker of major depressive disorder

Abstract: This study aimed to identify biomarkers of major depressive disorder (MDD), by relating neuroimage-derived measures to binary (MDD/control), ordinal (severe MDD/mild MDD/control), or continuous (depression severity) outcomes. To address MDD heterogeneity, factors (severity of psychic depression, motivation, anxiety, psychosis and sleep disturbance) were also used as outcomes. A multi-site, multimodal imaging (diffusion MRI, dMRI, and structural MRI, sMRI) cohort (52 controls and 147 MDD patients) and several modeling techniques- penalized logistic regression (PLR), random forest (RF) and support vector machine (SVM)- were used. An additional cohort (25 controls and 83 MDD patients) was used for validation. The optimally performing classifier (SVM) had a 26.0% misclassification rate (binary), 52.2±1.69% accuracy (ordinal) and r =0.36 correlation coefficient (p-value<0.001, continuous). Using SVM, R2 values for prediction of any MDD factors were <10%. Binary classification in the external dataset resulted in 87.95% sensitivity and 32.00% specificity. Though observed classification rates are too low for clinical utility, four image-based features contributed to accuracy across all models and analyses- two dMRI-based measures (average fractional anisotropy in the right cuneus and left insula) and two sMRI-based measures (asymmetry in the volume of the pars triangularis and the cerebellum) and may serve as a priori regions for future analyses. The poor accuracy of classification and predictive results found here reflects current equivocal findings and sheds light on challenges of using these modalities for MDD biomarker identification. Further, this study suggests a paradigm (e.g. multiple classifier evaluation with external validation) for future studies to avoid non-generalizable results.

Depression is associated with dimensional and categorical effects on white matter pathways.

Abstract: Background Diffusion tensor imaging (DTI) studies report reduced fractional anisotropy (FA) in major depressive disorder (MDD). However, whether FA covaries with key depressive symptoms, such as anhedonia, is unclear. Methods Magnetic resonance imaging data were acquired from 38 unmedicated adults with MDD and 52 healthy controls. DTI metrics were extracted from regions of interest that have consistently shown reduced FA in MDD. Analyses focused first on identifying group differences, and then determining whether reduced FA in depressed adults was related to individual differences in anhedonia and depressive severity. To establish specificity to depression, these analyses controlled for symptoms of anxiety. Results Relative to controls, depressed adults showed reduced FA in the genu of the corpus callosum, the anterior limb of the internal capsule (ALIC), the cingulum bundle near the anterior cingulate cortex, and the uncinate fasciculus (UF). In the depressed group, anhedonia negatively correlated with FA in the genu, cingulum, and UF, but positively correlated with radial diffusivity (RD)-a metric previously linked to demyelination-in the genu and ALIC. Depressive severity positively correlated with RD in the ALIC. These relationships remained significant after accounting for anxiety. Conclusion Anhedonia was positively correlated with reduced FA and increased RD in white matter pathways that connect regions critical for value coding, representing stimulus-reward associations, and guiding value-based action selection. Thus, a cardinal symptom of MDD-anhedonia-was lawfully related to abnormalities in reward network connectivity.

Nicotine Increases Activation to Anticipatory Valence Cues in Anterior Insula and Striatum.

Abstract: Introduction Smoking is associated with significant morbidity and mortality. Understanding the neurobiology of the rewarding effects of nicotine promises to aid treatment development for nicotine dependence. Through its actions on mesolimbic dopaminergic systems, nicotine engenders enhanced responses to drug-related cues signaling rewards, a mechanism hypothesized to underlie the development and maintenance of nicotine addiction. Methods We evaluated the effects of acute nicotine on neural responses to anticipatory cues signaling (nondrug) monetary reward or loss among 11 nonsmokers who had no prior history of tobacco smoking. In a double-blind, crossover design, participants completed study procedures while wearing nicotine or placebo patches at least 1 week apart. In each drug condition, participants underwent functional magnetic resonance imaging while performing the monetary incentive delay task and performed a probabilistic monetary reward task, probing reward responsiveness as measured by response bias toward a more frequently rewarded stimulus. Results Nicotine administration was associated with enhanced activation, compared with placebo, of right fronto-anterior insular cortex and striatal regions in response to cues predicting possible rewards or losses and to dorsal anterior cingulate for rewards. Response bias toward rewarded stimuli correlated positively with insular activation to anticipatory cues. Conclusion Nicotinic enhancement of monetary reward-related brain activation in the insula and striatum in nonsmokers dissociated acute effects of nicotine from effects on reward processing due to chronic smoking. Reward responsiveness predicted a greater nicotinic effect on insular activation to salient stimuli. Implications Previous research demonstrates that nicotine enhances anticipatory responses to rewards in regions targeted by midbrain dopaminergic systems. The current study provides evidence that nicotine also enhances responses to rewards and losses in the anterior insula. A previous study found enhanced insular activation to rewards and losses in smokers and ex-smokers, a finding that could be due to nicotine sensitization or factors related to current or past smoking. Our finding of enhanced anterior insula response after acute administration of nicotine in nonsmokers provides support for nicotine-induced sensitization of insular response to rewards and losses.

Imaging genetics paradigms in depression research: Systematic review and meta-analysis

Abstract: Imaging genetics studies involving participants with major depressive disorder (MDD) have expanded. Nevertheless, findings have been inconsistent. Thus, we conducted a systematic review and meta-analysis of imaging genetics studies that enrolled MDD participants across major databases through June 30th, 2017. Sixty-five studies met eligibility criteria (N = 4034 MDD participants and 3293 controls), and there was substantial between-study variability in the methodological quality of included studies. However, few replicated findings emerged from this literature with only 22 studies providing data for meta-analyses (882 participants with MDD and 616 controls). Total hippocampal volumes did not significantly vary in MDD participants or controls carrying either the BDNF Val66Met ‘Met’ (386 participants with MDD and 376 controls) or the 5-HTTLPR short ‘S’ (310 participants with MDD and 230 controls) risk alleles compared to non-carriers. Heterogeneity across studies was explored through meta-regression and subgroup analyses. Gender distribution, the use of medications, segmentation methods used to measure the hippocampus, and age emerged as potential sources of heterogeneity across studies that assessed the association of 5-HTTLPR short ‘S’ alleles and hippocampal volumes. Our data also suggest that the methodological quality of included studies, publication year, and the inclusion of brain volume as a covariate contributed to the heterogeneity of studies that assessed the association of the BDNF Val66Met ‘Met’ risk allele and hippocampal volumes. In exploratory voxel-wise meta-analyses, MDD participants carrying the 5-HTTLPR short ‘S’ allele had white matter microstructural abnormalities predominantly in the corpus callosum, while carriers of the BDNF Val66Met ‘Met’ allele had larger gray matter volumes and hyperactivation of the right middle frontal gyrus compared to non-carriers. In conclusion, few replicated findings emerged from imaging genetics studies that included participants with MDD. Nevertheless, we explored and identified specific sources of heterogeneity across studies, which could provide insights to enhance the reproducibility of this emerging field.

Functional connectomics of affective and psychotic pathology

Abstract: Converging evidence indicates that groups of patients with nominally distinct psychiatric diagnoses are not separated by sharp or discontinuous neurobiological boundaries. In healthy populations, individual differences in behavior are reflected in variability across the collective set of functional brain connections (functional connectome). These data suggest that the spectra of transdiagnostic symptom profiles observed in psychiatric patients may map onto detectable patterns of network function. To examine the manner through which neurobiological variation might underlie clinical presentation we obtained functional magnetic resonance imaging (fMRI) data from over 1,000 individuals, including 210 diagnosed with a primary psychotic disorder or affective psychosis (bipolar disorder with psychosis and schizophrenia or schizoaffective disorder), 192 presenting with a primary affective disorder without psychosis (unipolar depression, bipolar disorder without psychosis), and 608 demographically and data-quality matched healthy comparison participants recruited through a large-scale study of brain imaging and genetics. Here, we examine variation in functional connectomes across psychiatric diagnoses, finding striking evidence for disease connectomic 9fingerprints9 that are commonly disrupted across distinct forms of pathology and appear to scale as a function of illness severity. Conversely, other properties of network connectivity were preferentially disrupted in patients with psychotic illness, but not patients without psychotic symptoms. This work allows us to establish key biological and clinical features of the functional connectomes of severe mental disease.

Nicotine-induced activation of caudate and anterior cingulate cortex in response to errors in schizophrenia

Abstract: Nicotine improves attention and processing speed in individuals with schizophrenia. Few studies have investigated the effects of nicotine on cognitive control. Prior functional magnetic resonance imaging (fMRI) research demonstrates blunted activation of dorsal anterior cingulate cortex (dACC) and rostral anterior cingulate cortex (rACC) in response to error and decreased post-error slowing in schizophrenia. Participants with schizophrenia (n = 13) and healthy controls (n = 12) participated in a randomized, placebo-controlled, crossover study of the effects of transdermal nicotine on cognitive control. For each drug condition, participants underwent fMRI while performing the stop signal task where participants attempt to inhibit prepotent responses to “go (motor activation)” signals when an occasional “stop (motor inhibition)” signal appears. Error processing was evaluated by comparing “stop error” trials (failed response inhibition) to “go” trials. Resting-state fMRI data were collected prior to the task. Participants with schizophrenia had increased nicotine-induced activation of right caudate in response to errors compared to controls (DRUG × GROUP effect: p corrected < 0.05). Both groups had significant nicotine-induced activation of dACC and rACC in response to errors. Using right caudate activation to errors as a seed for resting-state functional connectivity analysis, relative to controls, participants with schizophrenia had significantly decreased connectivity between the right caudate and dACC/bilateral dorsolateral prefrontal cortices. In sum, we replicated prior findings of decreased post-error slowing in schizophrenia and found that nicotine was associated with more adaptive (i.e., increased) post-error reaction time (RT). This proof-of-concept pilot study suggests a role for nicotinic agents in targeting cognitive control deficits in schizophrenia.

Evidence of a diurnal rhythm in implicit reward learning.

Abstract: Many aspects of hedonic behavior, including self-administration of natural and drug rewards, as well as human positive affect, follow a diurnal cycle that peaks during the species-specific active period. This variation has been linked to circadian modulation of the mesolimbic dopamine system, and is hypothesized to serve an adaptive function by driving an organism to engage with the environment during times where the opportunity for obtaining rewards is high. However, relatively little is known about whether more complex facets of hedonic behavior - in particular, reward learning - follow the same diurnal cycle. The current study aimed to address this gap by examining evidence for diurnal variation in reward learning on a well-validated probabilistic reward learning task (PRT). PRT data from a large normative sample (N = 516) of non-clinical individuals, recruited across eight studies, were examined for the current study. The PRT uses an asymmetrical reinforcement ratio to induce a behavioral response bias, and reward learning was operationalized as the strength of this response bias across blocks of the task. Results revealed significant diurnal variation in reward learning, however in contrast to patterns previously observed in other aspects of hedonic behavior, reward learning was lowest in the middle of the day. Although a diurnal pattern was also observed on a measure of more general task performance (discriminability), this did not account for the variation observed in reward learning. Taken together, these findings point to a distinct diurnal pattern in reward learning that differs from that observed in other aspects of hedonic behavior. The results of this study have important implications for our understanding of clinical disorders characterized by both circadian and reward learning disturbances, and future research is needed to confirm whether this diurnal variation has a truly circadian origin.

Direct Parametric Reconstruction for Improved Characterization of Neurotransmitter Release using Dynamic PET

Abstract: 497 Objectives: Kinetic analyses of dynamic PET data with reversibly binding receptor-ligand radiotracers can be used to detect endogenous neurotransmitter (NT) releases elicited by cognitive tasks or drug stimulation. Conventionally, NT release is characterized by fitting time-activity curves (TACs) with an appropriate kinetic model such as LSRRM (Alpert et al 2003), an extension of the simplified reference region model that incorporates time-varying binding due to tracer displacement by NT. A limitation of this “indirect” approach, however, is the poor signal-to-noise ratio (SNR) of the estimated parametric images. In the current work, we developed a method for estimation of LSRRM parametric maps with significantly higher SNR by direct parameter estimation from raw dynamic PET projection data. We conducted simulation and human 11C-raclopride studies to evaluate the performance of this method against the standard indirect method. Methods: A numerical phantom comprised of 22 different brain regions including 7 striatal sub-divisions was created using the MNI atlas. Kinetic parameters values were assigned to each brain region based on measurements performed on 16 subjects studied with 11C-raclopride. Dopamine (DA) release was simulated in the striatum (executive area). LSRRM was used to generate the corresponding 4-D (i.e., 3-D + time) activity images which were then forward-projected to produce noise-free dynamic sinograms. Attenuation, detector sensitivity, point spread function and radioactive decay were modeled during sinogram data generation. After scaling to standard counts levels, Poisson noise was added to the sinograms to achieve noise levels comparable to our human studies. For empirical evaluation, a 45-min human study was conducted on the Siemens mMR camera using 11C-raclopride (13.5mCi). A reward task was started ~27 min after radiotracer injection to induce striatal DA release. For both simulation and human studies, parametric images of binding potential with non-displaceable reference (BPND) and magnitude of DA release (gamma) were computed using the indirect method and the proposed direct method. For the indirect approach, parameters were estimated by pixel-wise application of LSRRM using the cerebellum as a reference tissue input and weighted least-squares fitting of TACs obtained following fully-3D dynamic OSEM reconstruction. No post-reconstruction smoothing was included. For the direct method, parameters were directly estimated from the dynamic sinograms by preconditioned conjugate gradient based optimization of a four-dimensional Poisson log-likelihood objective function incorporating LSRRM kinetics and accounting for the effects of attenuation, sensitivity, scatter and randoms. Results: In simulation studies, the indirect method estimated striatal BPND and gamma with 7.8% and 79.2% bias, respectively. For the direct reconstruction, bias was reduced to 6.9% and 5.5% for striatal BPND and gamma estimates, respectively. Coefficients of variation (‘CV’, i.e. pixel-wise variability) of striatal BPND and gamma estimates were 65.3% and 72.0% for the indirect method as compared to 17.4% and 17.9% for the direct method. Likewise, in the human study, the direct method yielded BPND and gamma images with improved SNR. CV of BPND and gamma estimates in the putamen were 71.4% and 91.4% for the indirect method and 32.9% and 37.6% for the direct method. Conclusion: Direct reconstruction can reduce bias and increase the SNR of parametric images. The method has the potential to improve the characterization of localized neurotransmitter release, potentially allowing detection of weaker effects, reducing the needed sample size, or reducing radioactivity dose to facilitate repeated experiments or minimize radiation exposure.Acknowledgment: This work was supported in part by NIH grants R01MH102279, R01MH100350 and P41EB022544.