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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Associação Brasileira de Psiquiatria (ABP)
2020-10-01
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| Series: | Brazilian Journal of Psychiatry |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-44462021000400414&tlng=en |
| _version_ | 1828125216925024256 |
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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. |
| first_indexed | 2024-04-11T15:17:24Z |
| format | Article |
| id | doaj.art-982e8eb647a647ce9e392d03927a2c32 |
| institution | Directory Open Access Journal |
| issn | 1809-452X |
| language | English |
| last_indexed | 2024-04-11T15:17:24Z |
| publishDate | 2020-10-01 |
| publisher | Associação Brasileira de Psiquiatria (ABP) |
| record_format | Article |
| series | Brazilian Journal of Psychiatry |
| 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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