99 research outputs found
Cortical thickness is not associated with current depression in a clinical treatment study
BackgroundReduced cortical thickness is a candidate biological marker of depression, although findings are inconsistent. This could reflect analytic heterogeneity, such as use of regionâwise cortical thickness based on the Freesurfer DesikanâKilliany (DK) atlas or surfaceâbased 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.MethodsCortical thickness was collected from 170 currently depressed adults and 52 neverâdepressed adults. Visually inspected and approved Freesurferâgenerated surfaces were used to extract cortical thickness estimates according to the DK atlas (68 regions) and DS atlas (148 regions) for regionâwise analysis (216 total regions) and for SBM.ResultsOverall, except for small effects in a few regions, the two regionâwise approaches generally failed to discriminate depressed adults from nondepressed adults or current episode severity. Differential effects by age and gender were also rare and small in magnitude. Using SBM, depressed adults showed a significantly thicker cluster in the left supramarginal gyrus than nondepressed adults (Pâ=â0.047) but there were no associations with current episode severity.ConclusionsThree analytic approaches (i.e., DK atlas, DS atlas, and SBM) converge on the notion that cortical thickness is a relatively weak discriminator of current depression status. Differential age and gender effects do not appear to represent key moderators. Robust associations with demographic factors will likely hinder translation of cortical thickness into a clinically useful biomarker. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. Hum Brain Mapp 38:4370â4385, 2017. © 2017 Wiley Periodicals, Inc.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138250/1/hbm23664_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138250/2/hbm23664.pd
Testâretest reliability of freesurfer measurements within and between sites: Effects of visual approval process
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 testâretest reliability of FreeSurferâderived cortical measures in four groups of subjectsâthose 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. Testâretest correlation (TRC), intraclass correlation coefficient (ICC), and percent difference (PD) were used to measure the reliability in the Destrieux and DesikanâKilliany (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 subjectsâ 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 MRIâderived 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 36:3472â3485, 2015. © 2015 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113142/1/hbm22856.pd
Demonstrating testâretest reliability of electrophysiological measures for healthy adults in a multisite study of biomarkers of antidepressant treatment response
Growing evidence suggests that loudness dependency of auditory evoked potentials (LDAEP) and resting EEG alpha and theta may be biological markers for predicting response to antidepressants. In spite of this promise, little is known about the joint reliability of these markers, and thus their clinical applicability. New standardized procedures were developed to improve the compatibility of data acquired with different EEG platforms, and used to examine testâretest reliability for the three electrophysiological measures selected for a multisite projectâEstablishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC). Thirtyânine healthy controls across four clinical research sites were tested in two sessions separated by about 1 week. Resting EEG (eyesâopen and eyesâclosed conditions) was recorded and LDAEP measured using binaural tones (1000 Hz, 40 ms) at five intensities (60â100 dB SPL). Principal components analysis of current source density waveforms reduced volume conduction and provided referenceâfree measures of resting EEG alpha and N1 dipole activity to tones from auditory cortex. Lowâresolution electromagnetic tomography (LORETA) extracted resting theta current density measures corresponding to rostral anterior cingulate (rACC), which has been implicated in treatment response. There were no significant differences in posterior alpha, N1 dipole, or rACC theta across sessions. Testâretest reliability was .84 for alpha, .87 for N1 dipole, and .70 for theta rACC current density. The demonstration of goodâtoâexcellent reliability for these measures provides a template for future EEG/ERP studies from multiple testing sites, and an important step for evaluating them as biomarkers for predicting treatment response.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135271/1/psyp12758_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135271/2/psyp12758.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135271/3/psyp12758-sup-0001-suppinfo1.pd
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99mTc Hexamethyl-Propylene-Aminoxime Single-Photon Emission Computed Tomography Prediction of Conversion From Mild Cognitive Impairment to Alzheimer Disease
ObjectiveâTo examine the utility of single photon emission computed tomography (SPECT) to predict conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD)
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The Concise Health Risk Tracking-self Report: Psychometrics Within A Placebo-controlled Antidepressant Trial Among Depressed Outpatients
Background/aims: While substantial prior research has evaluated the psychometric properties of the 12-item Concise Health Risk Tracking-Self Report (CHRT-SR12), a measure of suicide propensity and suicidal thoughts, no prior research has investigated its factor structure, sensitivity to change over time, and other psychometric properties in a placebo-controlled trial of antidepressant medication, nor determined whether symptoms change throughout treatment. Methods: Participants in the multi-site Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study (n=278) provided data to evaluate the factor structure and sensitivity to change over time of the CHRT-SR12 through eight weeks of a clinical trial in which participants received either placebo or antidepressant medication (sertraline). Results/Outcomes: Factor analysis confirmed two factors: propensity (comprised of first-order factors including pessimism, helplessness, social support, and despair) and suicidal thoughts. Internal consistency (αâs ranged from 0.69â0.92) and external validity were both acceptable, with the total score and propensity factor scores significantly correlated with total scores and single-item suicidal-thoughts scores on the self-report Quick Inventory of Depressive Symptoms and the clinician-rated 17-item Hamilton Rating Scale for Depression. Through analyzing CHRT-SR12 changes over eight treatment weeks, the total score and both the factors decreased regardless of baseline suicidal thoughts. Change in clinician-rated suicidal thoughts was reflected by change in both the total score and propensity factor score. Conclusions/interpretation: These results confirm the reliability, validity, and applicability of the CHRT-SR12 to a placebo-controlled clinical trial of depressed outpatients receiving antidepressant medication
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Childhood Trauma History Is Linked To Abnormal Brain Connectivity In Major Depression
Patients with major depressive disorder (MDD) present with heterogeneous symptom profiles, while neurobiological mechanisms are still largely unknown. Brain network studies consistently report disruptions of resting-state networks (RSNs) in patients with MDD, including hypoconnectivity in the frontoparietal network (FPN), hyperconnectivity in the default mode network (DMN), and increased connection between the DMN and FPN. Using a large, multisite fMRI dataset ( n = 189 patients with MDD, n = 39 controls), we investigated network connectivity differences within and between RSNs in patients with MDD and healthy controls. We found that MDD could be characterized by a network model with the following abnormalities relative to controls: ( i ) lower within-network connectivity in three task-positive RSNs [FPN, dorsal attention network (DAN), and cingulo-opercular network (CON)], ( ii ) higher within-network connectivity in two intrinsic networks [DMN and salience network (SAN)], and ( iii ) higher within-network connectivity in two sensory networks [sensorimotor network (SMN) and visual network (VIS)]. Furthermore, we found significant alterations in connectivity between a number of these networks. Among patients with MDD, a history of childhood trauma and current symptoms quantified by clinical assessments were associated with a multivariate pattern of seven different within- and between-network connectivities involving the DAN, FPN, CON, subcortical regions, ventral attention network (VAN), auditory network (AUD), VIS, and SMN. Overall, our study showed that traumatic childhood experiences and dimensional symptoms are linked to abnormal network architecture in MDD. Our results suggest that RSN connectivity may explain underlying neurobiological mechanisms of MDD symptoms and has the potential to serve as an effective diagnostic biomarker
A Comprehensive Examination Of White Matter Tracts And Connectometry In Major Depressive Disorder
Background
Major depressive disorder (MDD) is a debilitating disorder characterized by widespread brain abnormalities. The literature is mixed as to whether or not white matter abnormalities are associated with MDD. This study sought to examine fractional anisotropy (FA) in white matter tracts in individuals with MDD using diffusion tensor imaging (DTI).
Methods
139 participants with MDD and 39 healthy controls (HC) in a multisite study were included. DTI scans were acquired in 64 directions and FA was determined in the brain using four methods: region of interest (ROI), tract-based spatial statistics (TBSS), and diffusion tractography. Diffusion connectometry was used to identify white matter pathways associated with MDD.
Results
There were no significant differences when comparing FA in MDD and HC groups using any method. In the MDD group, there was a significant relationship between depression severity and FA in the right medial orbitofrontal cortex, and between age of onset of MDD and FA in the right caudal anterior cingulate cortex using the ROI method. There was a significant relationship between age of onset and connectivity in the thalamocortical radiation, inferior longitudinal fasciculus, and cerebellar tracts using diffusion connectometry.
Conclusions
The lack of group differences in FA and connectometry analysis may result from the clinically heterogenous nature of MDD. However, the relationship between FA and depression severity may suggest a state biomarker of depression that should be investigated as a potential indicator of response. Age of onset may also be a significant clinical feature to pursue when studying white matter tracts
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