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Brain Signal Variability and Indices of Cellular Protection Predicts Social Anxiety Disorder Treatment Outcome
Stockholm University, Faculty of Social Sciences, Department of Psychology, Clinical psychology. Uppsala University, Sweden.
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2019 (English)In: Proceedings of the 9th World Congress of Behavioural & Cognitive Therapies: Volume I. Research, Applied Issues / [ed] Thomas Heidenreich, Philip Tata, Tübingen: dgvt-Verlag , 2019, Vol. 1, p. 158-158Conference paper, Oral presentation with published abstract (Other academic)
Abstract [en]

We are currently lacking clinically useful predictors of treatment response in common psychiatric disorders. Non-invasive and increasingly accessible neuroimaging techniques like functional magnetic resonance imaging (fMRI) could be a useful tool. In contrast to the conventional approach investigating the brain’s average responses, the brain’s signal variability could be a better estimate of the brain’s dynamic operations (Garrett et al., 2010, 2015). In addition, telomere attrition is a hallmark of cellular aging and shorter telomeres have been reported in mood and anxiety disorders. Telomere shortening is counteracted by the enzyme telomerase and cellular protection is also provided by the antioxidant enzyme glutathione peroxidase (GPx). Here, we investigate if baseline BOLD-fMRI signal variability, and indices of cellular protection, predicts social anxiety disorder patient’s response to internet-delivered cognitive behavior therapy. Forty-six patients with social anxiety disorder (SAD) were scanned twice with a 3 Tesla fMRI before initiating CBT. Treatment outcome was assessed the Liebowitz Social Anxiety Scale (self-report). 1) BOLD-fMRI acquisition was performed while passively viewing emotional faces flashing on the screen for 80 seconds. Raw BOLD-fMRI data was implemented in an Independent Component Analysis in order to manually denoise images by carefully remove noise from neural signal. Across time, each voxel’s standard deviation was calculated and used as an index of variability. Multivariate partial least squares regression models were used for second level analysis. 2) Telomerase activity and telomere length were measured in peripheral blood mononuclear cells and GPx activity in plasma. Significant latent level brain scores, and baseline analytes were implemented in linear regressions with LSAS-SR change score as the outcome. Results will be presented and discussed.

Place, publisher, year, edition, pages
Tübingen: dgvt-Verlag , 2019. Vol. 1, p. 158-158
Keywords [en]
social anxiety disorder, treatment outcome, brain signal variability
National Category
Psychology
Research subject
Psychology
Identifiers
URN: urn:nbn:se:su:diva-174254ISBN: 978-3-87159-851-7 (print)OAI: oai:DiVA.org:su-174254DiVA, id: diva2:1357796
Conference
9th World Congress of Behavioural & Cognitive Therapies, Berlin, Germany, July 17-20, 2019
Note

Unknown total number of authors. All are not listed in the abstract book.

Available from: 2019-10-04 Created: 2019-10-04 Last updated: 2019-10-09Bibliographically approved

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