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Creation of a gene expression portrait of depression and its application for identifying potential treatments
Depression is a complex mental health disorder and the goal here was to identify a consistent underlying portrait of expression that ranks all genes from most to least dysregulated and indicates direction of change relative to controls. Using large-scale neural gene expression depression datasets, a...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884719/ https://www.ncbi.nlm.nih.gov/pubmed/33589676 http://dx.doi.org/10.1038/s41598-021-83348-0 |
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author | Gammie, Stephen C. |
author_facet | Gammie, Stephen C. |
author_sort | Gammie, Stephen C. |
collection | PubMed |
description | Depression is a complex mental health disorder and the goal here was to identify a consistent underlying portrait of expression that ranks all genes from most to least dysregulated and indicates direction of change relative to controls. Using large-scale neural gene expression depression datasets, a combined portrait (for men and women) was created along with one for men and one for women only. The depressed brain was characterized by a “hypo” state, that included downregulation of activity-related genes, including EGR1, FOS, and ARC, and indications of a lower brain temperature and sleep-like state. MAP kinase and BDNF pathways were enriched with overlapping genes. Expression patterns suggested decreased signaling for GABA and for neuropeptides, CRH, SST, and CCK. GWAS depression genes were among depression portrait genes and common genes of interest included SPRY2 and PSEN2. The portraits were used with the drug repurposing approach of signature matching to identify treatments that could reverse depression gene expression patterns. Exercise was identified as the top treatment for depression for the combined and male portraits. Other non-traditional treatments that scored well were: curcumin, creatine, and albiflorin. Fluoxetine scored best among typical antidepressants. The creation of the portraits of depression provides new insights into the complex landscape of depression and a novel platform for evaluating and identifying potential new treatments. |
format | Online Article Text |
id | pubmed-7884719 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78847192021-02-16 Creation of a gene expression portrait of depression and its application for identifying potential treatments Gammie, Stephen C. Sci Rep Article Depression is a complex mental health disorder and the goal here was to identify a consistent underlying portrait of expression that ranks all genes from most to least dysregulated and indicates direction of change relative to controls. Using large-scale neural gene expression depression datasets, a combined portrait (for men and women) was created along with one for men and one for women only. The depressed brain was characterized by a “hypo” state, that included downregulation of activity-related genes, including EGR1, FOS, and ARC, and indications of a lower brain temperature and sleep-like state. MAP kinase and BDNF pathways were enriched with overlapping genes. Expression patterns suggested decreased signaling for GABA and for neuropeptides, CRH, SST, and CCK. GWAS depression genes were among depression portrait genes and common genes of interest included SPRY2 and PSEN2. The portraits were used with the drug repurposing approach of signature matching to identify treatments that could reverse depression gene expression patterns. Exercise was identified as the top treatment for depression for the combined and male portraits. Other non-traditional treatments that scored well were: curcumin, creatine, and albiflorin. Fluoxetine scored best among typical antidepressants. The creation of the portraits of depression provides new insights into the complex landscape of depression and a novel platform for evaluating and identifying potential new treatments. Nature Publishing Group UK 2021-02-15 /pmc/articles/PMC7884719/ /pubmed/33589676 http://dx.doi.org/10.1038/s41598-021-83348-0 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Gammie, Stephen C. Creation of a gene expression portrait of depression and its application for identifying potential treatments |
title | Creation of a gene expression portrait of depression and its application for identifying potential treatments |
title_full | Creation of a gene expression portrait of depression and its application for identifying potential treatments |
title_fullStr | Creation of a gene expression portrait of depression and its application for identifying potential treatments |
title_full_unstemmed | Creation of a gene expression portrait of depression and its application for identifying potential treatments |
title_short | Creation of a gene expression portrait of depression and its application for identifying potential treatments |
title_sort | creation of a gene expression portrait of depression and its application for identifying potential treatments |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884719/ https://www.ncbi.nlm.nih.gov/pubmed/33589676 http://dx.doi.org/10.1038/s41598-021-83348-0 |
work_keys_str_mv | AT gammiestephenc creationofageneexpressionportraitofdepressionanditsapplicationforidentifyingpotentialtreatments |