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Dive into the research topics where Sarah Weyandt is active.

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Featured researches published by Sarah Weyandt.


Journal of Psychiatric Research | 2016

Establishing moderators and biosignatures of antidepressant response in clinical care (EMBARC): Rationale and design

Madhukar H. Trivedi; Maurizio Fava; Ramin V. Parsey; Benji T. Kurian; Mary L. Phillips; Maria A. Oquendo; Gerard E. Bruder; Diego A. Pizzagalli; Marisa Toups; Crystal Cooper; Phil Adams; Sarah Weyandt; David W. Morris; Bruce D. Grannemann; R. Todd Ogden; Randy L. Buckner; Melvin G. McInnis; Helena C. Kraemer; Eva Petkova; Thomas Carmody; Myrna M. Weissman

UNLABELLED Remission rates for Major Depressive Disorder (MDD) are low and unpredictable for any given antidepressant. No biological or clinical marker has demonstrated sufficient ability to match individuals to efficacious treatment. Biosignatures developed from the systematic exploration of multiple biological markers, which optimize treatment selection for individuals (moderators) and provide early indication of ultimate treatment response (mediators) are needed. The rationale and design of a multi-site, placebo-controlled randomized clinical trial of sertraline examining moderators and mediators of treatment response is described. The target sample is 300 participants with early onset (≤30 years) recurrent MDD. Non-responders to an 8-week trial are switched double blind to either bupropion (for sertraline non-responders) or sertraline (for placebo non-responders) for an additional 8 weeks. Clinical moderators include anxious depression, early trauma, gender, melancholic and atypical depression, anger attacks, Axis II disorder, hypersomnia/fatigue, and chronicity of depression. Biological moderator and mediators include cerebral cortical thickness, task-based fMRI (reward and emotion conflict), resting connectivity, diffusion tensor imaging (DTI), arterial spin labeling (ASL), electroencephalograpy (EEG), cortical evoked potentials, and behavioral/cognitive tasks evaluated at baseline and week 1, except DTI, assessed only at baseline. The study is designed to standardize assessment of biomarkers across multiple sites as well as institute replicable quality control methods, and to use advanced data analytic methods to integrate these markers. A Differential Depression Treatment Response Index (DTRI) will be developed. The data, including biological samples (DNA, RNA, and plasma collected before and during treatment), will become available in a public scientific repository. CLINICAL TRIAL REGISTRATION Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC). Identifier: NCT01407094. URL: http://clinicaltrials.gov/show/NCT01407094.


Human Brain Mapping | 2015

Test-retest reliability of freesurfer measurements within and between sites: Effects of visual approval process

Zafer Iscan; Tony B. Jin; Alexandria Kendrick; Bryan Szeglin; Hanzhang Lu; Madhukar H. Trivedi; Maurizio Fava; Myrna M. Weissman; Benji T. Kurian; Phillip Adams; Sarah Weyandt; Marisa Toups; Thomas Carmody; Melvin G. McInnis; Cristina Cusin; Crystal Cooper; Maria A. Oquendo; Ramin V. Parsey; Christine DeLorenzo

In the last decade, many studies have used automated processes to analyze magnetic resonance imaging (MRI) data such as cortical thickness, which is one indicator of neuronal health. Due to the convenience of image processing software (e.g., FreeSurfer), standard practice is to rely on automated results without performing visual inspection of intermediate processing. In this work, structural MRIs of 40 healthy controls who were scanned twice were used to determine the test–retest reliability of FreeSurfer‐derived cortical measures in four groups of subjects—those 25 that passed visual inspection (approved), those 15 that failed visual inspection (disapproved), a combined group, and a subset of 10 subjects (Travel) whose test and retest scans occurred at different sites. Test–retest correlation (TRC), intraclass correlation coefficient (ICC), and percent difference (PD) were used to measure the reliability in the Destrieux and Desikan–Killiany (DK) atlases. In the approved subjects, reliability of cortical thickness/surface area/volume (DK atlas only) were: TRC (0.82/0.88/0.88), ICC (0.81/0.87/0.88), PD (0.86/1.19/1.39), which represent a significant improvement over these measures when disapproved subjects are included. Travel subjects’ results show that cortical thickness reliability is more sensitive to site differences than the cortical surface area and volume. To determine the effect of visual inspection on sample size required for studies of MRI‐derived cortical thickness, the number of subjects required to show group differences was calculated. Significant differences observed across imaging sites, between visually approved/disapproved subjects, and across regions with different sizes suggest that these measures should be used with caution. Hum Brain Mapp 36:3472–3485, 2015.


Neuropsychopharmacology | 2016

Neural Correlates of Three Promising Endophenotypes of Depression: Evidence from the EMBARC Study

Christian A. Webb; Daniel G. Dillon; Pia Pechtel; Franziska Goer; Laura Murray; Quentin J. M. Huys; Maurizio Fava; Myrna Weissman; Ramin V. Parsey; Benji T. Kurian; Phillip Adams; Sarah Weyandt; Joseph M. Trombello; Bruce D. Grannemann; Crystal Cooper; Patricia J. Deldin; Craig E. Tenke; Madhukar H. Trivedi; Gerard E. Bruder; Diego A. Pizzagalli

Major depressive disorder (MDD) is clinically, and likely pathophysiologically, heterogeneous. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes. Guided by the NIMH Research Domain Criteria initiative, we used source localization of scalp-recorded EEG resting data to examine the neural correlates of three emerging endophenotypes of depression: neuroticism, blunted reward learning, and cognitive control deficits. Data were drawn from the ongoing multi-site EMBARC study. We estimated intracranial current density for standard EEG frequency bands in 82 unmedicated adults with MDD, using Low-Resolution Brain Electromagnetic Tomography. Region-of-interest and whole-brain analyses tested associations between resting state EEG current density and endophenotypes of interest. Neuroticism was associated with increased resting gamma (36.5–44 Hz) current density in the ventral (subgenual) anterior cingulate cortex (ACC) and orbitofrontal cortex (OFC). In contrast, reduced cognitive control correlated with decreased gamma activity in the left dorsolateral prefrontal cortex (dlPFC), decreased theta (6.5–8 Hz) and alpha2 (10.5–12 Hz) activity in the dorsal ACC, and increased alpha2 activity in the right dlPFC. Finally, blunted reward learning correlated with lower OFC and left dlPFC gamma activity. Computational modeling of trial-by-trial reinforcement learning further indicated that lower OFC gamma activity was linked to reduced reward sensitivity. Three putative endophenotypes of depression were found to have partially dissociable resting intracranial EEG correlates, reflecting different underlying neural dysfunctions. Overall, these findings highlight the need to parse the heterogeneity of MDD by focusing on promising endophenotypes linked to specific pathophysiological abnormalities.


Human Brain Mapping | 2015

Test-retest reliability of freesurfer measurements within and between sites

Zafer Iscan; Tony B. Jin; Alexandria Kendrick; Bryan Szeglin; Hanzhang Lu; Madhukar H. Trivedi; Maurizio Fava; Patrick J. McGrath; Myrna M. Weissman; Benji T. Kurian; Phillip Adams; Sarah Weyandt; Marisa Toups; Thomas Carmody; Cristina Cusin; Crystal Cooper; Maria A. Oquendo; Ramin V. Parsey; Christine DeLorenzo

In the last decade, many studies have used automated processes to analyze magnetic resonance imaging (MRI) data such as cortical thickness, which is one indicator of neuronal health. Due to the convenience of image processing software (e.g., FreeSurfer), standard practice is to rely on automated results without performing visual inspection of intermediate processing. In this work, structural MRIs of 40 healthy controls who were scanned twice were used to determine the test–retest reliability of FreeSurfer‐derived cortical measures in four groups of subjects—those 25 that passed visual inspection (approved), those 15 that failed visual inspection (disapproved), a combined group, and a subset of 10 subjects (Travel) whose test and retest scans occurred at different sites. Test–retest correlation (TRC), intraclass correlation coefficient (ICC), and percent difference (PD) were used to measure the reliability in the Destrieux and Desikan–Killiany (DK) atlases. In the approved subjects, reliability of cortical thickness/surface area/volume (DK atlas only) were: TRC (0.82/0.88/0.88), ICC (0.81/0.87/0.88), PD (0.86/1.19/1.39), which represent a significant improvement over these measures when disapproved subjects are included. Travel subjects’ results show that cortical thickness reliability is more sensitive to site differences than the cortical surface area and volume. To determine the effect of visual inspection on sample size required for studies of MRI‐derived cortical thickness, the number of subjects required to show group differences was calculated. Significant differences observed across imaging sites, between visually approved/disapproved subjects, and across regions with different sizes suggest that these measures should be used with caution. Hum Brain Mapp 36:3472–3485, 2015.


American Journal of Psychiatry | 2015

Moderation of the Relationship Between Reward Expectancy and Prediction Error-Related Ventral Striatal Reactivity by Anhedonia in Unmedicated Major Depressive Disorder: Findings From the EMBARC Study

Tsafrir Greenberg; Henry W. Chase; Jorge Almeida; Richelle Stiffler; Carlos R. Zevallos; Haris A. Aslam; Thilo Deckersbach; Sarah Weyandt; Crystal Cooper; Marisa Toups; Thomas Carmody; Benji T. Kurian; Scott Peltier; Phillip S. Adams; Melvin McInnis; Maria A. Oquendo; Patrick McGrath; Maurizio Fava; Myrna Weissman; Ramin Parsey; Madhukar H. Trivedi; Mary L. Phillips

OBJECTIVE Anhedonia, disrupted reward processing, is a core symptom of major depressive disorder. Recent findings demonstrate altered reward-related ventral striatal reactivity in depressed individuals, but the extent to which this is specific to anhedonia remains poorly understood. The authors examined the effect of anhedonia on reward expectancy (expected outcome value) and prediction error- (discrepancy between expected and actual outcome) related ventral striatal reactivity, as well as the relationship between these measures. METHOD A total of 148 unmedicated individuals with major depressive disorder and 31 healthy comparison individuals recruited for the multisite EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study underwent functional MRI during a well-validated reward task. Region of interest and whole-brain data were examined in the first- (N=78) and second- (N=70) recruited cohorts, as well as the total sample, of depressed individuals, and in healthy individuals. RESULTS Healthy, but not depressed, individuals showed a significant inverse relationship between reward expectancy and prediction error-related right ventral striatal reactivity. Across all participants, and in depressed individuals only, greater anhedonia severity was associated with a reduced reward expectancy-prediction error inverse relationship, even after controlling for other symptoms. CONCLUSIONS The normal reward expectancy and prediction error-related ventral striatal reactivity inverse relationship concords with conditioning models, predicting a shift in ventral striatal responding from reward outcomes to reward cues. This study shows, for the first time, an absence of this relationship in two cohorts of unmedicated depressed individuals and a moderation of this relationship by anhedonia, suggesting reduced reward-contingency learning with greater anhedonia. These findings help elucidate neural mechanisms of anhedonia, as a step toward identifying potential biosignatures of treatment response.


PLOS ONE | 2015

Accounting for Dynamic Fluctuations across Time when Examining fMRI Test-Retest Reliability: Analysis of a Reward Paradigm in the EMBARC Study.

Henry W. Chase; Jay C. Fournier; Tsafrir Greenberg; Jorge Almeida; Richelle Stiffler; Carlos R. Zevallos; Haris A. Aslam; Crystal Cooper; Thilo Deckersbach; Sarah Weyandt; Phillip Adams; Marisa Toups; Thomas Carmody; Maria A. Oquendo; Scott Peltier; Maurizio Fava; Myrna M. Weissman; Ramin V. Parsey; Melvin G. McInnis; Benji T. Kurian; Madhukar H. Trivedi; Mary L. Phillips

Longitudinal investigation of the neural correlates of reward processing in depression may represent an important step in defining effective biomarkers for antidepressant treatment outcome prediction, but the reliability of reward-related activation is not well understood. Thirty-seven healthy control participants were scanned using fMRI while performing a reward-related guessing task on two occasions, approximately one week apart. Two main contrasts were examined: right ventral striatum (VS) activation fMRI BOLD signal related to signed prediction errors (PE) and reward expectancy (RE). We also examined bilateral visual cortex activation coupled to outcome anticipation. Significant VS PE-related activity was observed at the first testing session, but at the second testing session, VS PE-related activation was significantly reduced. Conversely, significant VS RE-related activity was observed at time 2 but not time 1. Increases in VS RE-related activity from time 1 to time 2 were significantly associated with decreases in VS PE-related activity from time 1 to time 2 across participants. Intraclass correlations (ICCs) in VS were very low. By contrast, visual cortex activation had much larger ICCs, particularly in individuals with high quality data. Dynamic changes in brain activation are widely predicted, and failure to account for these changes could lead to inaccurate evaluations of the reliability of functional MRI signals. Conventional measures of reliability cannot distinguish between changes specified by algorithmic models of neural function and noisy signal. Here, we provide evidence for the former possibility: reward-related VS activations follow the pattern predicted by temporal difference models of reward learning but have low ICCs.


Psychological Medicine | 2015

A computational analysis of flanker interference in depression

Daniel G. Dillon; Thomas V. Wiecki; Pia Pechtel; Christian A. Webb; Franziska Goer; Laura Murray; Madhukar H. Trivedi; Maurizio Fava; Myrna M. Weissman; Ramin V. Parsey; Benji T. Kurian; Phillip Adams; Thomas Carmody; Sarah Weyandt; Kathy Shores-Wilson; Marisa Toups; Melvin G. McInnis; Maria A. Oquendo; Cristina Cusin; Patricia J. Deldin; Gerard E. Bruder; Diego A. Pizzagalli

BACKGROUND Depression is characterized by poor executive function, but - counterintuitively - in some studies, it has been associated with highly accurate performance on certain cognitively demanding tasks. The psychological mechanisms responsible for this paradoxical finding are unclear. To address this issue, we applied a drift diffusion model (DDM) to flanker task data from depressed and healthy adults participating in the multi-site Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC) study. METHOD One hundred unmedicated, depressed adults and 40 healthy controls completed a flanker task. We investigated the effect of flanker interference on accuracy and response time, and used the DDM to examine group differences in three cognitive processes: prepotent response bias (tendency to respond to the distracting flankers), response inhibition (necessary to resist prepotency), and executive control (required for execution of correct response on incongruent trials). RESULTS Consistent with prior reports, depressed participants responded more slowly and accurately than controls on incongruent trials. The DDM indicated that although executive control was sluggish in depressed participants, this was more than offset by decreased prepotent response bias. Among the depressed participants, anhedonia was negatively correlated with a parameter indexing the speed of executive control (r = -0.28, p = 0.007). CONCLUSIONS Executive control was delayed in depression but this was counterbalanced by reduced prepotent response bias, demonstrating how participants with executive function deficits can nevertheless perform accurately in a cognitive control task. Drawing on data from neural network simulations, we speculate that these results may reflect tonically reduced striatal dopamine in depression.


Biological Psychiatry: Cognitive Neuroscience and Neuroimaging | 2017

Neuroticism and Individual Differences in Neural Function in Unmedicated Major Depression: Findings From the EMBARC Study

Jay C. Fournier; Henry W. Chase; Tsafrir Greenberg; Amit Etkin; Jorge Almeida; Richelle Stiffler; Thilo Deckersbach; Sarah Weyandt; Crystal Cooper; Marisa Toups; Thomas Carmody; Benji T. Kurian; Scott Peltier; Phillip Adams; Melvin G. McInnis; Maria A. Oquendo; Maurizio Fava; Myrna M. Weissman; Ramin V. Parsey; Madhukar H. Trivedi; Mary L. Phillips

BACKGROUND Personality dysfunction represents one of the only predictors of differential response between active treatments for depression to have replicated. In this study, we examine whether depressed patients with higher neuroticism scores, a marker of personality dysfunction, show differences versus depressed patients with lower scores in the functioning of two brain regions associated with treatment response, the anterior cingulate and anterior insula cortices. METHODS Functional magnetic resonance imaging data during an emotional Stroop task were collected from 135 adults diagnosed with major depressive disorder at four academic medical centers participating in the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) study. Secondary analyses were conducted including a sample of 28 healthy individuals. RESULTS In whole-brain analyses, higher neuroticism among depressed adults was associated with increased activity in and connectivity with the right anterior insula cortex to incongruent compared to congruent emotional stimuli (ks>281, ps<0.05 FWE corrected), covarying for concurrent psychiatric distress. We also observed an unanticipated relationship between neuroticism and reduced activity in the precuneus (k=269, p<0.05 FWE corrected). Exploratory analyses including healthy individuals suggested that associations between neuroticism and brain function may be nonlinear over the full range of neuroticism scores. CONCLUSIONS This study provides convergent evidence for the importance of the right anterior insula cortex as a brain-based marker of clinically meaningful individual differences in neuroticism among adults with depression. This is a critical next step in linking personality dysfunction, a replicated clinical predictor of differential antidepressant treatment response, with differences in underlying brain function.


Human Brain Mapping | 2017

Cortical thickness is not associated with current depression in a clinical treatment study

Greg Perlman; Elizabeth Bartlett; Christine DeLorenzo; Myrna M. Weissman; Todd Ogden; Tony B. Jin; Phillip Adams; Madhukar H. Trivedi; Benji T. Kurian; Maria A. Oquendo; Melvin G. McInnis; Sarah Weyandt; Maurizio Fava; Crystal Cooper; Ashley Malchow; Ramin V. Parsey

Reduced cortical thickness is a candidate biological marker of depression, although findings are inconsistent. This could reflect analytic heterogeneity, such as use of region‐wise cortical thickness based on the Freesurfer Desikan–Killiany (DK) atlas or surface‐based morphometry (SBM). The Freesurfer Destrieux (DS) atlas (more, smaller regions) has not been utilized in depression studies. This could also reflect differential gender and age effects.


F1000Research | 2014

Test-retest reliability of cortical thickness in a multi-site study

Zafer Iscan; Alexandria Kendrick; Christine DeLorenzo; Madhukar H. Trivedi; Maurizio Fava; Patrick J. McGrath; Myrna M. Weissman; Benji T. Kurian; Phillip Adams; Sarah Weyandt; Marisa Toups; Thomas Carmody; Cristina Cusin; Crystal Cooper; Maria A. Oquendo; Ramin V. Parsey

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Benji T. Kurian

University of Texas Southwestern Medical Center

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Crystal Cooper

University of Pittsburgh

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Maria A. Oquendo

Columbia University Medical Center

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Marisa Toups

University of Texas Southwestern Medical Center

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Thomas Carmody

University of Texas Southwestern Medical Center

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