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Biomarkers in Psychiatry

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Cover of 'Biomarkers in Psychiatry'

Table of Contents

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    Book Overview
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    Chapter 41 Network Neuroscience: A Framework for Developing Biomarkers in Psychiatry
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    Chapter 42 Reappraising Preclinical Models of Separation Anxiety Disorder, Panic Disorder, and CO 2 Sensitivity: Implications for Methodology and Translation into New Treatments
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    Chapter 43 Immunological Processes in Schizophrenia Pathology: Potential Biomarkers?
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    Chapter 44 Translational Shifts in Preclinical Models of Depression: Implications for Biomarkers for Improved Treatments
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    Chapter 45 Neuroimmune Biomarkers in Mental Illness
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    Chapter 46 Imaging and Genetic Biomarkers Predicting Transition to Psychosis
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    Chapter 47 Using Pattern Classification to Identify Brain Imaging Markers in Autism Spectrum Disorder
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    Chapter 48 Deconstructing Schizophrenia: Advances in Preclinical Models for Biomarker Identification
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    Chapter 49 Imaging and Genetic Approaches to Inform Biomarkers for Anxiety Disorders, Obsessive–Compulsive Disorders, and PSTD
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    Chapter 50 Cognitive Phenotypes for Biomarker Identification in Mental Illness: Forward and Reverse Translation
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    Chapter 52 Genomic and Imaging Biomarkers in Schizophrenia
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    Chapter 57 Stem Cells to Inform the Neurobiology of Mental Illness
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    Chapter 58 Biomarkers in Neuropsychiatry: A Prospect for the Twenty-First Century?
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    Chapter 64 Correction to: Imaging and Genetic Approaches to Inform Biomarkers for Anxiety Disorders, Obsessive–Compulsive Disorders, and PSTD
Attention for Chapter 49: Imaging and Genetic Approaches to Inform Biomarkers for Anxiety Disorders, Obsessive–Compulsive Disorders, and PSTD
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Chapter title
Imaging and Genetic Approaches to Inform Biomarkers for Anxiety Disorders, Obsessive–Compulsive Disorders, and PSTD
Chapter number 49
Book title
Biomarkers in Psychiatry
Published in
Current topics in behavioral neurosciences, January 2018
DOI 10.1007/7854_2018_49
Pubmed ID
Book ISBNs
978-3-31-999641-7, 978-3-31-999642-4
Authors

Eduard Maron, Chen-Chia Lan, David Nutt, Maron, Eduard, Lan, Chen-Chia, Nutt, David

Abstract

Anxiety disorders are the most common mental health problem in the world and also claim the highest health care cost among various neuropsychiatric disorders. Anxiety disorders have a chronic and recurrent course and cause significantly negative impacts on patients' social, personal, and occupational functioning as well as quality of life. Despite their high prevalence rates, anxiety disorders have often been under-diagnosed or misdiagnosed, and consequently under-treated. Even with the correct diagnosis, anxiety disorders are known to be difficult to treat successfully. In order to implement better strategies in diagnosis, prognosis, treatment decision, and early prevention for anxiety disorders, tremendous efforts have been put into studies using genetic and neuroimaging techniques to advance our understandings of the underlying biological mechanisms. In addition to anxiety disorders including panic disorder, generalised anxiety disorder (GAD), specific phobias, social anxiety disorders (SAD), due to overlapping symptom dimensions, obsessive-compulsive disorder (OCD), and post-traumatic stress disorder (PTSD) (which were removed from the anxiety disorder category in DSM-5 to become separate categories) are also included for review of relevant genetic and neuroimaging findings. Although the number of genetic or neuroimaging studies focusing on anxiety disorders is relatively small compare to other psychiatric disorders such as psychotic disorders or mood disorders, various structural abnormalities in the grey or white matter, functional alterations of activity during resting-state or task conditions, molecular changes of neurotransmitter receptors or transporters, and genetic associations have all been reported. With continuing effort, further genetic and neuroimaging research may potentially lead to clinically useful biomarkers for the prevention, diagnosis, and management of these disorders.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 76 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 13%
Student > Bachelor 9 12%
Student > Master 8 11%
Student > Doctoral Student 8 11%
Other 4 5%
Other 10 13%
Unknown 27 36%
Readers by discipline Count As %
Psychology 11 14%
Medicine and Dentistry 9 12%
Neuroscience 7 9%
Nursing and Health Professions 5 7%
Biochemistry, Genetics and Molecular Biology 4 5%
Other 12 16%
Unknown 28 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 May 2021.
All research outputs
#17,973,858
of 23,081,466 outputs
Outputs from Current topics in behavioral neurosciences
#382
of 500 outputs
Outputs of similar age
#310,630
of 442,597 outputs
Outputs of similar age from Current topics in behavioral neurosciences
#10
of 10 outputs
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