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39


Effect of Citalopram on Hippocampal Atrophy in First-Episode Psychosis: Structural MRI Results From the DECIFER Trial [Meeting Abstract]

Qi, Wei; Li, Chenxiang; Blessing, Esther; Ardekani, Babak; Freudenreich, Oliver; Cather, Corinne; Holt, Daphne; Bello, Iruma; Diminich, Erica; Tang, Yingying; Worthington, Michelle; Zeng, Botao; Wu, Renrong; Fan, Xiaoduo; Wang, Jijun; Zhao, Jingping; Troxel, Andrea; Goff, Donald C.
ISI:000535308200399
ISSN: 0006-3223
CID: 4560802

Sexual Dimorphism and Hemispheric Asymmetry of Hippocampal Volumetric Integrity in Normal Aging and Alzheimer Disease

Ardekani, B A; Hadid, S A; Blessing, E; Bachman, A H
BACKGROUND AND PURPOSE/OBJECTIVE:Asymmetric atrophy of the hippocampus is an important clinical finding in normal aging and Alzheimer disease. In this study, we investigate the associations between the magnitude and asymmetry of hippocampal volumetric integrity and age, sex, and dementia severity. MATERIALS AND METHODS/METHODS:= 30). We used linear mixed-effects models to analyze the hippocampal parenchymal fraction and its asymmetry with respect to age, sex, dementia severity, and intracranial volume. RESULTS:After controlling for age, sex, and intracranial volume, we found that the magnitude of the hippocampal parenchymal fraction decreased and its asymmetry increased significantly with dementia severity. Also, hippocampal parenchymal fraction asymmetry was significantly higher in men after controlling for all other variables, but there was no sex effect on hippocampal parenchymal fraction magnitude. The magnitude of the hippocampal parenchymal fraction decreased and its asymmetry increased significantly with age in subjects who were cognitively healthy, but associations with age were different in nature in the mild cognitive impairment and Alzheimer disease groups. CONCLUSIONS:Hippocampal atrophy progresses asymmetrically with age in cognitively healthy subjects. Hippocampal parenchymal fraction asymmetry is significantly higher in men than women and in mild cognitive impairment/Alzheimer disease relative to cognitively healthy individuals.
PMID: 30655257
ISSN: 1936-959x
CID: 3595452

Pre-Deployment Risk Factors for PTSD in Afghanistan Veterans: A Machine Learning Approach for Analyzing Multivariate Predictors [Meeting Abstract]

Schultebraucks, Katharina; Qian, Meng; Abu-Amara, Duna; Dean, Kelsey; Laska, Eugene; Siegel, Carole; Gautam, Aarti; Guffanti, Guia; Hammamieh, Rasha; Blessing, Esther; Etkin, Amit; Ressler, Kerry; Doyle, Francis J., III; Jett, Marti; Marmar, Charles
ISI:000472661000741
ISSN: 0006-3223
CID: 3974022

NONLINEAR SMOOTHING OF DATA WITH RANDOM GAPS AND OUTLIERS (DRAGO) IMPROVES ESTIMATION OF CIRCADIAN RHYTHM [Meeting Abstract]

Parekh, Ankit A.; Selesnick, Ivan; Baroni, Argelinda; Miller, Margo; Sanders, Haley; Bubu, Omonigho M.; Cavedoni, Bianca; Varga, Andrew W.; Rapoport, David M.; Ayappa, Indu; Osorio, Ricardo S.; Blessing, Esther
ISI:000471071001105
ISSN: 1550-9109
CID: 4532862

PTSD is Associated With Reduced Anterior and Posterior Hippocampal Connectivity in Combat Veterans [Meeting Abstract]

Blessing, Esther; Maron-Katz, Adi; de los Angeles, Carlo; Abu-Amara, Duna; Li, Meng; Qian, Meng; Etkin, Amit; Marmar, Charles
ISI:000433001900036
ISSN: 0006-3223
CID: 3140462

Metabolomic profiling associated with deployment-related stressors in army personnel [Meeting Abstract]

Gautam, A; Donohue, D; Abu-Amara, D; Hoke, A; Genfi, A; Blessing, E; Hammamieh, R; Marmar, C; Jett, M
Pre-deployment identification of risk and resilience factors is crucial in developing targets to reduce or prevent posttraumatic stress symptoms in military personnel. The Fort Campbell Cohort study was designed to assess pre-deployment biological and behavioral markers and build predictive models to identify risk and resistance for posttraumatic stress disorder (PTSD) following deployment. The aim of the current study was to use high-resolution metabolomics profiling to identify metabolic pathways and networks associated with PTSD checklist score differences and changes across multiple pre and post-deployment time points. In addition, we have investigated how deployment affects metabolomics profile changes within individuals independent of PTSD score changes. Untargeted metabolomics profiling of plasma has been completed using both liquid and gas chromatography with mass spectrometry. Our preliminary data indicates that deployment has complex metabolic effects that must be considered in evaluation of deployment-associated exposures in military personnel. Our in depth-data analysis may further elucidate pathways, novel compounds, and biomarkers associated with PTSD in its relation to military deployment. These findings may have clinical implications for understanding the pathogenesis of PTSD and provide insights to avert chronic PTSD
EMBASE:622544134
ISSN: 1530-6860
CID: 3161142

Clozapine, chlorpromazine and risperidone dose-dependently reduce emotional hyperthermia, a biological marker of salience

Blessing, William W; Blessing, Esther M; Mohammed, Mazher; Ootsuka, Youichirou
RATIONALE: We recently introduced a new rat model of emotional hyperthermia in which a salient stimulus activates brown adipose tissue (BAT) thermogenesis and tail artery constriction. Antipsychotic drugs, both classical and second generation, act to reduce excessive assignment of salience to objects and events in the external environment. The close association between salient occurrences and increases in body temperature suggests that antipsychotic drugs may also reduce emotional hyperthermia. OBJECTIVES: We determined whether chlorpromazine, clozapine, and risperidone dose dependently reduce emotionally elicited increases in BAT thermogenesis, cutaneous vasoconstriction, and body temperature in rats. METHODS: Rats, chronically instrumented for measurement of BAT and body temperature and tail artery blood flow, singly housed, were confronted with an intruder rat (confined within a small wire-mesh cage) after systemic pre-treatment of the resident rat with vehicle or antipsychotic agent. BAT and body temperatures, tail blood flow, and behavioral activity were continuously measured. RESULTS: Clozapine (30 mug-2 mg/kg), chlorpromazine (0.1-5 mg/kg), and risperidone (6.25 mug-1 mg/kg) robustly and dose-relatedly reduced intruder-elicited BAT thermogenesis and tail artery vasoconstriction, with consequent dose-related reduction in emotional hyperthermia. CONCLUSIONS: Chlorpromazine, a first-generation antipsychotic, as well as clozapine and risperidone, second-generation agents, dose-dependently reduce emotional hyperthermia. Dopamine D2 receptor antagonist properties of chlorpromazine do not contribute to thermoregulatory effects. Interactions with monoamine receptors are important, and these monoamine receptor interactions may also contribute to the therapeutic effects of all three antipsychotics. Thermoregulatory actions of putative antipsychotic agents may constitute a biological marker of their therapeutic properties.
PMCID:5660844
PMID: 28812124
ISSN: 1432-2072
CID: 2670782

Biological predictors of insulin resistance associated with posttraumatic stress disorder in young military veterans

Blessing, Esther M; Reus, Victor; Mellon, Synthia H; Wolkowitz, Owen M; Flory, Janine D; Bierer, Linda; Lindqvist, Daniel; Dhabhar, Firdaus; Li, Meng; Qian, Meng; Abu-Amara, Duna; Galatzer-Levy, Isaac; Yehuda, Rachel; Marmar, Charles R
Posttraumatic stress disorder (PTSD) is associated with increased risk for Type 2 diabetes and cardiovascular disease (cardiometabolic disease), warranting research into targeted prevention strategies. In the present case-control study of 160 young (mean age 32.7 years) male military veterans, we aimed to assess whether PTSD status predicted increased markers of cardiometabolic risk in otherwise healthy individuals, and further, to explore biological pathways between PTSD and these increased markers of cardiometabolic risk. Toward these aims, we compared measures of cardiometabolic risk, namely insulin resistance (IR) (HOMA-IR), metabolic syndrome (MetS) and prediabetes, between 80 PTSD cases and 80 controls without PTSD. We then determined whether PTSD-associated increases in HOMA-IR were correlated with select biological variables from pathways previously hypothesized to link PTSD with cardiometabolic risk, including systemic inflammation (increased C-reactive protein, interleukin-6, and tumor necrosis factor alpha), sympathetic over-activity (increased resting heart rate), and neuroendocrine dysregulation (increased plasma cortisol or serum brain-derived neurotrophic factor (BDNF)). We found PTSD diagnosis was associated with substantially higher HOMA-IR (cases 4.3+/-4.3 vs controls 2.4+/-2.0; p<0.001), and a higher frequency of MetS (cases 21.3% vs controls 2.5%; p<0.001), but not prediabetes (cases 20.0% vs controls 18.8%; p>0.05). Cases also had increased pro-inflammatory cytokines (p<0.01), heart rate (p<0.001), and BDNF (p<0.001), which together predicted increased HOMA-IR (adjusted R2=0.68, p<0.001). Results show PTSD diagnosis in young male military veterans without cardiometabolic disease is associated with increased IR, predicted by biological alterations previously hypothesized to link PTSD to increased cardiometabolic risk. Findings support further research into early, targeted prevention of cardiometabolic disease in individuals with PTSD.
PMID: 28521179
ISSN: 1873-3360
CID: 2563012

Marijuana and other cannabinoids as a treatment for posttraumatic stress disorder: A literature review

Steenkamp, Maria M; Blessing, Esther M; Galatzer-Levy, Isaac R; Hollahan, Laura C; Anderson, William T
Posttraumatic stress disorder (PTSD) is common in the general population, yet there are limitations to the effectiveness, tolerability, and acceptability of available first-line interventions. We review the extant knowledge on the effects of marijuana and other cannabinoids on PTSD. Potential therapeutic effects of these agents may largely derive from actions on the endocannabinoid system and we review major animal and human findings in this area. Preclinical and clinical studies generally support the biological plausibility for cannabinoids' potential therapeutic effects, but underscore heterogeneity in outcomes depending on dose, chemotype, and individual variation. Treatment outcome studies of whole plant marijuana and related cannabinoids on PTSD are limited and not methodologically rigorous, precluding conclusions about their potential therapeutic effects. Reported benefits for nightmares and sleep (particularly with synthetic cannabinoid nabilone) substantiate larger controlled trials to determine effectiveness and tolerability. Of concern, marijuana use has been linked to adverse psychiatric outcomes, including conditions commonly comorbid with PTSD such as depression, anxiety, psychosis, and substance misuse. Available evidence is stronger for marijuana's harmful effects on the development of psychosis and substance misuse than for the development of depression and anxiety. Marijuana use is also associated with worse treatment outcomes in naturalistic studies, and with maladaptive coping styles that may maintain PTSD symptoms. Known risks of marijuana thus currently outweigh unknown benefits for PTSD. Although controlled research on marijuana and other cannabinoids' effects on PTSD remains limited, rapid shifts in the legal landscape may now enable such studies, potentially opening new avenues in PTSD treatment research.
PMID: 28245077
ISSN: 1520-6394
CID: 2471462

Brain entropy: Intelligence, personality, and psychopathology [Meeting Abstract]

Saxe, G; Calderone, D; Morales, L; Saxe, R; Blessing, E; Chen, J; Levy, I G; Marmar, C
Background: Entropy has a fundamental relationship with information and the functioning of all computational systems. Entropy is defined as the number of states available to a system. A system with low entropy has access to fewer states than does one with high entropy. A system with low entropy is more ordered and more predicable than a system with high entropy. Since entropy is related to the functioning of computational systems, there is an emerging theoretical and empirical literature about its role in brain function and dysfunction. We present the results of three integrated studies applying resting state fMRI entropy measurement to understand intelligence, personality, and psychopathology. Brain entropy is an index of an individual's access to brain states at a given time and is measured through the predictivity of brain state over time. Thus, we would expect to observe brain entropic differences between conditions known to be associated with high flexibility (e.g. high intelligence, creativity, novelty seeking) vs. conditions associated with high rigidity (e.g. anxiety, depression, Posttraumatic Stress). The three studies are: Brain entropy and intelligence in 926 adults from the Brain Genomic Superstruct Project, 2. Brain entropy and personality in 926 adults from the Brain Genomic Superstruct Project, and 3. Brain entropy and PTSD in 95 veterans from the NYU Cohen Veterans Data Set. Methods: Subjects: Study 1 (Entropy and Intelligence) and Study 2 (Entropy and Personality) were conducted with data from the Brain Genomics Superstruct Project (BGSP). The BGSP includes 1570 healthy adult participants between the ages of 18 and 35. The current study utilized data from the 926 participants who completed intelligence and personality assessments. Study 3 (Entropy and PTSD) was conducted with data from the NYU Cohen Veterans Data Set. This data set includes 95 combat veterans, 46 with PTSD and 49 without PTSD. fMRI Procedures: Brain Genomics Superstruct Project (BGSP). All MRI data were obtained with 3T Trio scanners (Siemens Healthcare, Erlangen, Germany) at Harvard University and Massachusetts General Hospital. MRI scans for each participant included a high resolution structural scan (T1-weighted multi-echo MPRAGE, TR = 2.2 sec, TE = 1.5/3.4/5.2/7.0 msec, slices = 144, resolution = 1.2 x 1.2 x 1.2 mm) and a resting-state functional scan sensitive to blood oxygenation level-dependent (BOLD) contrast (TR = 3.0 sec, TE = 30 msec, slices = 47, resolution = 3.0 x 3.0 x 3.0 mm, 120 measurements). NYU Cohen Veterans Data Set: All MRI data were obtained with a 3T Trio scanner (Siemens AG, Erlangen Germany). Anatomical images were acquired with magnetization prepared rapid gradient echo sequence with TE/TI/TR = 2.98/900/2300 ms, 256 x 240 matrix, 256 mm x 240 mm fieldof-view, flip angle = 9degree, slice thickness = 1 mm and total slice number = 191; resting state fMRI was obtained using an echo-planar imaging sequence (TR/TE = 2000/29 ms, flip angle = 90degree), 64 x 64 matrix, pixel size 3.125 mm x 3.125 mm, total slice number = 32, slice thickness = 3.5 mm (without gaps), total volume number = 200. fMRI Entropy Analysis: Brain entropy was calculated using the Brain Entropy Mapping Toolbox (BENtbx) (Wang et al, 2014) for MATLAB (MATLAB Release R2015b, The MathWorks Inc., Natick, MA, United States). The BENtbx utilizes Sample Entropy (SampEn). For a given time series, SampEn is a single number representing the predictability of the series. The entropy of highly predictable series is small, close to 0, indicating a lack of variation or disorder. The entropy of unpredictable series is large, indicating a high amount of variation or disorder. The Sample Entropy process first breaks a series into smaller sets of size m. For example, for m = 2, and the BOLD time series is broken into pairs of consecutive values. Each pair is then compared with every other pair to find the maximum distance (absolute value difference) between any number in the first pair and any number in the second pair. If the distance is less than the threshold r, the two pairs are considered a 'match.' This process is then repeated for sets of size m + 1. Sample Entropy is then the ratio: SampEn =-log A/B: Where, A = number of matches using sets of size m+1 and B = number of matches using sets of size m. For perfectly predictable series, A and B will be equal, and entropy will be 0. As disorder in a series increases, B will become greater than A, and the equation will yield an increasingly large positive number. Psychometric Measurement: Study 1: Intelligence was measured with the Shipley Estimated IQ, Vocabulary, and Matrix Reasoning scales. Study 2: Personality was measured for Behavioral Inhibition, Harm Avoidance, Risk Taking, and Novelty Seeking. Study 3: PTSD was measured with the Clinician Administered PTSD Scale (CAPS). Results: Study 1: Shipley Estimated IQ, Vocabulary, and Matrix Reasoning were all associated with higher brain entropy. In particular, Vocabulary was related to higher entropy in the L fusiform gyrus, inferior temporal gyrus, parahippocampal gyrus. Matrix Reasoning was associated with higher entropy in the bilateral superior, medial, inferior frontal gyrus, bilateral orbital gyrus, and R middle frontal gyrus. Study 2: Harm avoidance and Behavioral Inhibition were associated with lower entropy and Novelty Seeking and Risk Taking were associated with higher entropy. Study 3: PTSD was associated with lower entropy, particularly in the L hippocampus and parahippocampal gyrus, inferior and middle temporal lobes: and higher entropy in the R precuneus, and R parietal lobe. Conclusions: Brain entropy may provide a novel approach to understand intelligence, personality, and psychopathology such as PTSD
EMBASE:613896860
ISSN: 1740-634x
CID: 2397652