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      Associations between PTSD-Related extinction retention deficits in women and plasma steroids that modulate brain GABA A and NMDA receptor activity

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          Abstract

          Several studies have demonstrated poor retention of extinction learning among individuals with posttraumatic stress disorder (PTSD). Gonadal hormone signaling in brain appears to influence the retention of extinction learning differently in women with and without PTSD. Women with PTSD, compared to trauma-exposed women without PTSD, show relative deficits in extinction retention during the mid-luteal phase (mLP) of the menstrual cycle, compared to the early follicular phase (eFP). A PTSD-related reduction in conversion of progesterone to its GABAergic metabolites allopregnanolone (Allo) and pregnanolone (PA) may contribute to these findings. The current study in trauma-exposed women with (n = 9) and without (n = 9) PTSD investigated associations between extinction retention and plasma Allo + PA levels, as well as the ratio of Allo + PA to 5α-dihydroprogesterone (5α-DHP), the immediate steroid precursor for Allo. The study also investigated the relationship between extinction retention and the ratio of Allo + PA to dehydroepiandrosterone (DHEA), an adrenally-derived GABA A receptor antagonist. Study participants completed differential fear-conditioning during both the eFP and mLP of the menstrual cycle. Analyses revealed a strong positive relationship between resting plasma Allo + PA levels and extinction retention during the mLP in the women with, but not without, PTSD (e.g., diagnosis X Allo + PA interaction controlling for early extinction: β = −.0008, p = .003). A similar pattern emerged for the Allo + PA to 5α-DHP ratio (β = -.165, p = .071), consistent with a PTSD-related block in production of Allo and PA at the enzyme 3α-hydroxysteroid dehydrogenase. The ratio of Allo + PA to DHEA appeared to influence extinction retention only during the eFP when Allo + PA and DHEA levels are comparable and thus may compete for effects on GABA A receptor function. This study aligns with male rodent PTSD models linking experimental reductions in brain Allo levels to deficits in extinction retention and suggests that targeting PTSD-related deficits in GABAergic neurosteroid synthesis may be therapeutic.

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          The development of a Clinician-Administered PTSD Scale.

          Several interviews are available for assessing PTSD. These interviews vary in merit when compared on stringent psychometric and utility standards. Of all the interviews, the Clinician-Administered PTSD Scale (CAPS-1) appears to satisfy these standards most uniformly. The CAPS-1 is a structured interview for assessing core and associated symptoms of PTSD. It assesses the frequency and intensity of each symptom using standard prompt questions and explicit, behaviorally-anchored rating scales. The CAPS-1 yields both continuous and dichotomous scores for current and lifetime PTSD symptoms. Intended for use by experienced clinicians, it also can be administered by appropriately trained paraprofessionals. Data from a large scale psychometric study of the CAPS-1 have provided impressive evidence of its reliability and validity as a PTSD interview.
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            Post-traumatic stress disorder is associated with PACAP and the PAC1 receptor

            Pituitary adenylate cyclase-activating polypeptide (PACAP) is known to broadly regulate the cellular stress response. In contrast, it is unclear if the PACAP/PAC1 receptor pathway has a role in human psychological stress responses, such as posttraumatic stress disorder (PTSD). In heavily traumatized subjects, we find a sex-specific association of PACAP blood levels with fear physiology, PTSD diagnosis and symptoms in females (N=64, replication N=74, p<0.005). Using a tag-SNP genetic approach (44 single nucleotide polymorphisms, SNPs) spanning the PACAP (ADCYAP1) and PAC1 (ADCYAP1R1) genes, we find a sex-specific association with PTSD. rs2267735, a SNP in a putative estrogen response element within ADCYAP1R1, predicts PTSD diagnosis and symptoms in females only (combined initial and replication samples: N=1237; p<2x10 − 5). This SNP also associates with fear discrimination and with ADCYAP1R1 mRNA expression. Methylation of ADCYAP1R1 is also associated with PTSD (p < 0.001). Complementing these human data, ADCYAP1R1 mRNA is induced with fear conditioning or estrogen replacement in rodent models. These data suggest that perturbations in the PACAP/PAC1 pathway are involved in abnormal stress responses underlying PTSD. These sex-specific effects may occur via estrogen regulation of ADCYAP1R1. PACAP levels and ADCYAP1R1 SNPs may serve as useful biomarkers to further our mechanistic understanding of PTSD.
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              Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study

              Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The “true” imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can accommodate nonlinearities and interactions and does not require a particular regression model to be specified. We compared parametric MICE with a random forest-based MICE algorithm in 2 simulation studies. The first study used 1,000 random samples of 2,000 persons drawn from the 10,128 stable angina patients in the CALIBER database (Cardiovascular Disease Research using Linked Bespoke Studies and Electronic Records; 2001–2010) with complete data on all covariates. Variables were artificially made “missing at random,” and the bias and efficiency of parameter estimates obtained using different imputation methods were compared. Both MICE methods produced unbiased estimates of (log) hazard ratios, but random forest was more efficient and produced narrower confidence intervals. The second study used simulated data in which the partially observed variable depended on the fully observed variables in a nonlinear way. Parameter estimates were less biased using random forest MICE, and confidence interval coverage was better. This suggests that random forest imputation may be useful for imputing complex epidemiologic data sets in which some patients have missing data.
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                Author and article information

                Contributors
                Journal
                Neurobiol Stress
                Neurobiol Stress
                Neurobiology of Stress
                Elsevier
                2352-2895
                15 May 2020
                November 2020
                15 May 2020
                : 13
                : 100225
                Affiliations
                [a ]National Center for PTSD Women's Health Sciences Division at VA Boston Healthcare System, Boston, MA, 02130, USA
                [b ]Department of Psychiatry, Boston University School of Medicine, Boston, MA, 02118, USA
                [c ]The Psychiatric Institute, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, 60612, USA
                [d ]The Charles Stark Draper Laboratory, Inc., Cambridge, MA, 02139, USA
                [e ]Framingham State University, Framingham, MA, 01701, USA
                [f ]Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Education and Clinical Center (GRECC), VA Boston Healthcare System Boston, MA, 02130, USA
                [g ]Department of Epidemiology, Boston University School of Public Health, Boston, MA, 02118, USA
                [h ]The MITRE Corporation, Bedford, MA, 01730, USA
                [i ]Center of Excellence for Stress and Mental Health, San Diego VA Healthcare System, San Diego, CA, 9216, USA
                [j ]Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, 92093, USA
                [k ]Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, 27701, USA
                [l ]Psychiatry Department, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, 02129, USA
                Author notes
                []Corresponding author. VA Boston Healthcare System (116B-3), Boston, MA, 02130, USA. Suzanne.Pineles@ 123456va.gov
                Article
                S2352-2895(20)30015-1 100225
                10.1016/j.ynstr.2020.100225
                7256058
                32490055
                6dd2d699-060d-4eb5-9bcf-a211fb624b9a

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 28 October 2019
                : 14 April 2020
                : 25 April 2020
                Categories
                Original Research Article

                allopregnanolone,pregnanolone,progesterone,dehydroepiandrosterone,neurosteroid,ptsd,fear extinction,extinction retention

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