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Metabonomic Profile and Signaling Pathway Prediction of Depression-Associated Suicidal Behavior
Suicide is the most severe consequence of depression which has become a leading cause of disability and a global disease burden. Recent evidence indicates a central role of small molecules in the pathogenesis of depression and associated suicidal behaviors. However, there lacks a systemic exploratio...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7177018/ https://www.ncbi.nlm.nih.gov/pubmed/32372980 http://dx.doi.org/10.3389/fpsyt.2020.00269 |
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author | Liu, Song |
author_facet | Liu, Song |
author_sort | Liu, Song |
collection | PubMed |
description | Suicide is the most severe consequence of depression which has become a leading cause of disability and a global disease burden. Recent evidence indicates a central role of small molecules in the pathogenesis of depression and associated suicidal behaviors. However, there lacks a systemic exploration of small molecules in the development of depression-associated suicide, and it remains unclear how they affect an individual’s behavior. In order to compare the metabonomic profiles between drug-naïve patients with depression-associated suicidal behaviors and healthy individuals, we conducted a systemic database search for studies of metabolic characteristics in depression-associated suicidal behavior. Manual data curation and statistical analysis and integration were performed in Excel. We further performed an enrichment analysis of signaling pathway prediction using the Reactome Pathway Analysis tool. We have identified 17 metabolites that expressed differently between drug-naïve patients with depression-associated suicidal behaviors and healthy controls. We have integrated these metabolites into biological signaling pathways and provided a visualized signaling network in depressed suicidal patients. We have revealed that “transport of small molecules”, “disease”, “metabolism” and “metabolism of proteins” were the most relevant signaling sections, among which “transport of inorganic cations/anions and amino acids/oligopeptides”, “SLC-mediated transmembrane transport”, and “metabolism of amino acids and derivatives” should be further studied to elucidate their potential pathogenic mechanism in the development of depression and associated suicidal behavior. In conclusion, our findings of these 17 metabolites and associated signaling pathways could provide an insight into the molecular pathogenesis of depression-associated suicidal behavior and potential targets for new drug inventions. |
format | Online Article Text |
id | pubmed-7177018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71770182020-05-05 Metabonomic Profile and Signaling Pathway Prediction of Depression-Associated Suicidal Behavior Liu, Song Front Psychiatry Psychiatry Suicide is the most severe consequence of depression which has become a leading cause of disability and a global disease burden. Recent evidence indicates a central role of small molecules in the pathogenesis of depression and associated suicidal behaviors. However, there lacks a systemic exploration of small molecules in the development of depression-associated suicide, and it remains unclear how they affect an individual’s behavior. In order to compare the metabonomic profiles between drug-naïve patients with depression-associated suicidal behaviors and healthy individuals, we conducted a systemic database search for studies of metabolic characteristics in depression-associated suicidal behavior. Manual data curation and statistical analysis and integration were performed in Excel. We further performed an enrichment analysis of signaling pathway prediction using the Reactome Pathway Analysis tool. We have identified 17 metabolites that expressed differently between drug-naïve patients with depression-associated suicidal behaviors and healthy controls. We have integrated these metabolites into biological signaling pathways and provided a visualized signaling network in depressed suicidal patients. We have revealed that “transport of small molecules”, “disease”, “metabolism” and “metabolism of proteins” were the most relevant signaling sections, among which “transport of inorganic cations/anions and amino acids/oligopeptides”, “SLC-mediated transmembrane transport”, and “metabolism of amino acids and derivatives” should be further studied to elucidate their potential pathogenic mechanism in the development of depression and associated suicidal behavior. In conclusion, our findings of these 17 metabolites and associated signaling pathways could provide an insight into the molecular pathogenesis of depression-associated suicidal behavior and potential targets for new drug inventions. Frontiers Media S.A. 2020-04-16 /pmc/articles/PMC7177018/ /pubmed/32372980 http://dx.doi.org/10.3389/fpsyt.2020.00269 Text en Copyright © 2020 Liu http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychiatry Liu, Song Metabonomic Profile and Signaling Pathway Prediction of Depression-Associated Suicidal Behavior |
title | Metabonomic Profile and Signaling Pathway Prediction of Depression-Associated Suicidal Behavior |
title_full | Metabonomic Profile and Signaling Pathway Prediction of Depression-Associated Suicidal Behavior |
title_fullStr | Metabonomic Profile and Signaling Pathway Prediction of Depression-Associated Suicidal Behavior |
title_full_unstemmed | Metabonomic Profile and Signaling Pathway Prediction of Depression-Associated Suicidal Behavior |
title_short | Metabonomic Profile and Signaling Pathway Prediction of Depression-Associated Suicidal Behavior |
title_sort | metabonomic profile and signaling pathway prediction of depression-associated suicidal behavior |
topic | Psychiatry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7177018/ https://www.ncbi.nlm.nih.gov/pubmed/32372980 http://dx.doi.org/10.3389/fpsyt.2020.00269 |
work_keys_str_mv | AT liusong metabonomicprofileandsignalingpathwaypredictionofdepressionassociatedsuicidalbehavior |