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Gene expression signatures differentiating major depressive disorder from subsyndromal symptomatic depression

Subsyndromal symptomatic depression (SSD) and major depressive disorder (MDD) have been classified as distinct diseases, due to their dissimilar gene expression profiles and responses to venlafaxine. To identify specific biomarkers of these two diseases, we conducted a secondary analysis of the gene...

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Autores principales: Hu, Guoqin, Yu, Shunying, Yuan, Chengmei, Hong, Wu, Wang, Zuowei, Zhang, Ran, Wang, Dongxiang, Li, Zezhi, Yi, Zhenghui, Fang, Yiru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8148500/
https://www.ncbi.nlm.nih.gov/pubmed/33971621
http://dx.doi.org/10.18632/aging.202995
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author Hu, Guoqin
Yu, Shunying
Yuan, Chengmei
Hong, Wu
Wang, Zuowei
Zhang, Ran
Wang, Dongxiang
Li, Zezhi
Yi, Zhenghui
Fang, Yiru
author_facet Hu, Guoqin
Yu, Shunying
Yuan, Chengmei
Hong, Wu
Wang, Zuowei
Zhang, Ran
Wang, Dongxiang
Li, Zezhi
Yi, Zhenghui
Fang, Yiru
author_sort Hu, Guoqin
collection PubMed
description Subsyndromal symptomatic depression (SSD) and major depressive disorder (MDD) have been classified as distinct diseases, due to their dissimilar gene expression profiles and responses to venlafaxine. To identify specific biomarkers of these two diseases, we conducted a secondary analysis of the gene expression signatures of SSD patients, MDD patients and healthy controls (n=8/group) from the study of Yi et al. Global, individual, specific, enrichment and co-expression analyses were used to compare the transcriptomic profiles of peripheral blood lymphocytes from the three groups. The global and individual analyses revealed that different genes were up- and downregulated in the SSD and MDD groups. Through our specific analysis, we identified 1719 and 3278 differentially expressed genes specifically associated with MDD and SSD, respectively. Enrichment and co-expression analyses demonstrated that the genes specific to MDD were enriched in pathways associated with hormone levels and immune responses, while those specific to SSD were associated with immune function. The specific hub gene for the MDD co-expression network was transmembrane protein 132B (TMEM132B), while the hub genes for SSD were actin-related protein 2/3 complex (ARPC2) and solute carrier family 5 member 5 (SLC5A5). This bioinformatic analysis has provided potential biomarkers that can distinguish SSD from MDD.
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spelling pubmed-81485002021-05-26 Gene expression signatures differentiating major depressive disorder from subsyndromal symptomatic depression Hu, Guoqin Yu, Shunying Yuan, Chengmei Hong, Wu Wang, Zuowei Zhang, Ran Wang, Dongxiang Li, Zezhi Yi, Zhenghui Fang, Yiru Aging (Albany NY) Research Paper Subsyndromal symptomatic depression (SSD) and major depressive disorder (MDD) have been classified as distinct diseases, due to their dissimilar gene expression profiles and responses to venlafaxine. To identify specific biomarkers of these two diseases, we conducted a secondary analysis of the gene expression signatures of SSD patients, MDD patients and healthy controls (n=8/group) from the study of Yi et al. Global, individual, specific, enrichment and co-expression analyses were used to compare the transcriptomic profiles of peripheral blood lymphocytes from the three groups. The global and individual analyses revealed that different genes were up- and downregulated in the SSD and MDD groups. Through our specific analysis, we identified 1719 and 3278 differentially expressed genes specifically associated with MDD and SSD, respectively. Enrichment and co-expression analyses demonstrated that the genes specific to MDD were enriched in pathways associated with hormone levels and immune responses, while those specific to SSD were associated with immune function. The specific hub gene for the MDD co-expression network was transmembrane protein 132B (TMEM132B), while the hub genes for SSD were actin-related protein 2/3 complex (ARPC2) and solute carrier family 5 member 5 (SLC5A5). This bioinformatic analysis has provided potential biomarkers that can distinguish SSD from MDD. Impact Journals 2021-05-08 /pmc/articles/PMC8148500/ /pubmed/33971621 http://dx.doi.org/10.18632/aging.202995 Text en Copyright: © 2021 Hu et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Hu, Guoqin
Yu, Shunying
Yuan, Chengmei
Hong, Wu
Wang, Zuowei
Zhang, Ran
Wang, Dongxiang
Li, Zezhi
Yi, Zhenghui
Fang, Yiru
Gene expression signatures differentiating major depressive disorder from subsyndromal symptomatic depression
title Gene expression signatures differentiating major depressive disorder from subsyndromal symptomatic depression
title_full Gene expression signatures differentiating major depressive disorder from subsyndromal symptomatic depression
title_fullStr Gene expression signatures differentiating major depressive disorder from subsyndromal symptomatic depression
title_full_unstemmed Gene expression signatures differentiating major depressive disorder from subsyndromal symptomatic depression
title_short Gene expression signatures differentiating major depressive disorder from subsyndromal symptomatic depression
title_sort gene expression signatures differentiating major depressive disorder from subsyndromal symptomatic depression
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8148500/
https://www.ncbi.nlm.nih.gov/pubmed/33971621
http://dx.doi.org/10.18632/aging.202995
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