Literature DB >> 27168345

Neurobiological markers predicting treatment response in anxiety disorders: A systematic review and implications for clinical application.

Ulrike Lueken1, Kathrin C Zierhut2, Tim Hahn3, Benjamin Straube4, Tilo Kircher5, Andreas Reif6, Jan Richter7, Alfons Hamm8, Hans-Ulrich Wittchen9, Katharina Domschke10.   

Abstract

Anxiety disorders constitute the largest group of mental disorders with a high individual and societal burden. Neurobiological markers of treatment response bear potential to improve response rates by informing stratified medicine approaches. A systematic review was performed on the current evidence of the predictive value of genetic, neuroimaging and other physiological markers for treatment response (pharmacological and/or psychotherapeutic treatment) in anxiety disorders. Studies published until March 2015 were selected through search in PubMed, Web of Science, PsycINFO, Embase, and CENTRAL. Sixty studies were included, among them 27 on genetic, 17 on neuroimaging and 16 on other markers. Preliminary evidence was found for the functional 5-HTTLPR/rs25531 genotypes, anterior cingulate cortex function and cardiovascular flexibility to modulate treatment outcome. Studies varied considerably in methodological quality. Application of more stringent study methodology, predictions on the individual patient level and cross-validation in independent samples are recommended to set the next stage of biomarker research and to avoid flawed conclusions in the emerging field of "Mental Health Predictomics".
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Anxiety disorders; Autonomic; Biomarker; Genetic; Machine learning; Neuroimaging; Pharmacotherapy; Prediction; Psychotherapy; SSRI; Stratified medicine; Treatment outcome

Mesh:

Substances:

Year:  2016        PMID: 27168345     DOI: 10.1016/j.neubiorev.2016.04.005

Source DB:  PubMed          Journal:  Neurosci Biobehav Rev        ISSN: 0149-7634            Impact factor:   8.989


  20 in total

Review 1.  Biomarkers for Musculoskeletal Pain Conditions: Use of Brain Imaging and Machine Learning.

Authors:  Jeff Boissoneault; Landrew Sevel; Janelle Letzen; Michael Robinson; Roland Staud
Journal:  Curr Rheumatol Rep       Date:  2017-01       Impact factor: 4.592

Review 2.  Dispositional negativity: An integrative psychological and neurobiological perspective.

Authors:  Alexander J Shackman; Do P M Tromp; Melissa D Stockbridge; Claire M Kaplan; Rachael M Tillman; Andrew S Fox
Journal:  Psychol Bull       Date:  2016-10-10       Impact factor: 17.737

Review 3.  Epigenetic and Neural Circuitry Landscape of Psychotherapeutic Interventions.

Authors:  Christopher W T Miller
Journal:  Psychiatry J       Date:  2017-05-25

Review 4.  Change in neural response during emotion regulation is associated with symptom reduction in cognitive behavioral therapy for anxiety disorders.

Authors:  J Bomyea; T M Ball; A N Simmons; L Campbell-Sills; M P Paulus; M B Stein
Journal:  J Affect Disord       Date:  2020-04-13       Impact factor: 4.839

Review 5.  [Anxiety disorders: which psychotherapy for whom?]

Authors:  A Ströhle; T Fydrich
Journal:  Nervenarzt       Date:  2018-03       Impact factor: 1.214

6.  Pharmacogenomic Studies in Intellectual Disabilities and Autism Spectrum Disorder: A Systematic Review.

Authors:  Kazunari Yoshida; Emiko Koyama; Clement C Zai; Joseph H Beitchman; James L Kennedy; Yona Lunsky; Pushpal Desarkar; Daniel J Müller
Journal:  Can J Psychiatry       Date:  2020-11-23       Impact factor: 5.321

7.  Support Vector Machine Analysis of Functional Magnetic Resonance Imaging of Interoception Does Not Reliably Predict Individual Outcomes of Cognitive Behavioral Therapy in Panic Disorder with Agoraphobia.

Authors:  Benedikt Sundermann; Jens Bode; Ulrike Lueken; Dorte Westphal; Alexander L Gerlach; Benjamin Straube; Hans-Ulrich Wittchen; Andreas Ströhle; André Wittmann; Carsten Konrad; Tilo Kircher; Volker Arolt; Bettina Pfleiderer
Journal:  Front Psychiatry       Date:  2017-06-09       Impact factor: 4.157

8.  Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study.

Authors:  Kevin Hilbert; Ulrike Lueken; Markus Muehlhan; Katja Beesdo-Baum
Journal:  Brain Behav       Date:  2017-02-12       Impact factor: 2.708

9.  Commonalities and differences in the neural substrates of threat predictability in panic disorder and specific phobia.

Authors:  Anna Luisa Klahn; Isabelle A Klinkenberg; Ulrike Lueken; Swantje Notzon; Volker Arolt; Christo Pantev; Peter Zwanzger; Markus Junghoefer
Journal:  Neuroimage Clin       Date:  2017-02-20       Impact factor: 4.881

Review 10.  Genetics of generalized anxiety disorder and related traits.

Authors:  Michael G Gottschalk; Katharina Domschke
Journal:  Dialogues Clin Neurosci       Date:  2017-06       Impact factor: 5.986

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.