A review of systems biology research of anxiety disorders

The development of “omic” technologies and deep phenotyping may facilitate a systems biology approach to understanding anxiety disorders. Systems biology approaches incorporate data from multiple modalities (e.g., genomic, neuroimaging) with functional analyses (e.g., animal and tissue culture model...

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Main Authors: Mary S. Mufford, Dennis van der Meer, Ole A. Andreassen, Raj Ramesar, Dan J. Stein, Shareefa Dalvie
Format: Article
Language:English
Published: Associação Brasileira de Psiquiatria (ABP) 2020-10-01
Series:Brazilian Journal of Psychiatry
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-44462021000400414&tlng=en
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author Mary S. Mufford
Dennis van der Meer
Ole A. Andreassen
Raj Ramesar
Dan J. Stein
Shareefa Dalvie
author_facet Mary S. Mufford
Dennis van der Meer
Ole A. Andreassen
Raj Ramesar
Dan J. Stein
Shareefa Dalvie
author_sort Mary S. Mufford
collection DOAJ
description The development of “omic” technologies and deep phenotyping may facilitate a systems biology approach to understanding anxiety disorders. Systems biology approaches incorporate data from multiple modalities (e.g., genomic, neuroimaging) with functional analyses (e.g., animal and tissue culture models) and mathematical modeling (e.g., machine learning) to investigate pathological biophysical networks at various scales. Here we review: i) the neurobiology of anxiety disorders; ii) how systems biology approaches have advanced this work; and iii) the clinical implications and future directions of this research. Systems biology approaches have provided an improved functional understanding of candidate biomarkers and have suggested future potential for refining the diagnosis, prognosis, and treatment of anxiety disorders. The systems biology approach for anxiety disorders is, however, in its infancy and in some instances is characterized by insufficient power and replication. The studies reviewed here represent important steps to further untangling the pathophysiology of anxiety disorders.
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spelling doaj.art-982e8eb647a647ce9e392d03927a2c322022-12-22T04:16:27ZengAssociação Brasileira de Psiquiatria (ABP)Brazilian Journal of Psychiatry1809-452X2020-10-0143441442310.1590/1516-4446-2020-1090A review of systems biology research of anxiety disordersMary S. Muffordhttps://orcid.org/0000-0002-8409-9217Dennis van der Meerhttps://orcid.org/0000-0002-0466-386XOle A. Andreassenhttps://orcid.org/0000-0002-4461-3568Raj Ramesarhttps://orcid.org/0000-0001-5688-1634Dan J. Steinhttps://orcid.org/0000-0001-7218-7810Shareefa Dalviehttps://orcid.org/0000-0003-2333-4823The development of “omic” technologies and deep phenotyping may facilitate a systems biology approach to understanding anxiety disorders. Systems biology approaches incorporate data from multiple modalities (e.g., genomic, neuroimaging) with functional analyses (e.g., animal and tissue culture models) and mathematical modeling (e.g., machine learning) to investigate pathological biophysical networks at various scales. Here we review: i) the neurobiology of anxiety disorders; ii) how systems biology approaches have advanced this work; and iii) the clinical implications and future directions of this research. Systems biology approaches have provided an improved functional understanding of candidate biomarkers and have suggested future potential for refining the diagnosis, prognosis, and treatment of anxiety disorders. The systems biology approach for anxiety disorders is, however, in its infancy and in some instances is characterized by insufficient power and replication. The studies reviewed here represent important steps to further untangling the pathophysiology of anxiety disorders.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-44462021000400414&tlng=enAnxiety disorderssystems biologybiomarkersmachine learning
spellingShingle Mary S. Mufford
Dennis van der Meer
Ole A. Andreassen
Raj Ramesar
Dan J. Stein
Shareefa Dalvie
A review of systems biology research of anxiety disorders
Brazilian Journal of Psychiatry
Anxiety disorders
systems biology
biomarkers
machine learning
title A review of systems biology research of anxiety disorders
title_full A review of systems biology research of anxiety disorders
title_fullStr A review of systems biology research of anxiety disorders
title_full_unstemmed A review of systems biology research of anxiety disorders
title_short A review of systems biology research of anxiety disorders
title_sort review of systems biology research of anxiety disorders
topic Anxiety disorders
systems biology
biomarkers
machine learning
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-44462021000400414&tlng=en
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