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Transthyretin as a Biomarker to Predict and Monitor Major Depressive Disorder Identified by Whole-Genome Transcriptomic Analysis in Mouse Models
Background: Accumulations of stressful life events result in the onset of major depressive disorder (MDD). Comprehensive genomic analysis is required to elucidate pathophysiological changes and identify applicable biomarkers. Methods: Transcriptomic analysis was performed on different brain parts of...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469805/ https://www.ncbi.nlm.nih.gov/pubmed/34572310 http://dx.doi.org/10.3390/biomedicines9091124 |
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author | Yu, Sung-Liang Chu, Selina Shih-Ting Chien, Min-Hui Kuo, Po-Hsiu Yang, Pan-Chyr Su, Kang-Yi |
author_facet | Yu, Sung-Liang Chu, Selina Shih-Ting Chien, Min-Hui Kuo, Po-Hsiu Yang, Pan-Chyr Su, Kang-Yi |
author_sort | Yu, Sung-Liang |
collection | PubMed |
description | Background: Accumulations of stressful life events result in the onset of major depressive disorder (MDD). Comprehensive genomic analysis is required to elucidate pathophysiological changes and identify applicable biomarkers. Methods: Transcriptomic analysis was performed on different brain parts of a chronic mild stress (CMS)-induced MDD mouse model followed by systemic analysis. QPCR and ELISA were utilized for validation in mice and patients. Results: The highest numbers of genes with significant changes induced by CMS were 505 in the amygdala followed by 272 in the hippocampus (twofold changes; FDR, p < 0.05). Enrichment analysis indicated that the core-enriched genes in CMS-treated mice were positively enriched for IFN-γ response genes in the amygdala, and hedgehog signaling in the hippocampus. Transthyretin (TTR) was severely reduced in CMS-treated mice. In patients with diagnosed MDD, serum concentrations of TTR were reduced by 48.7% compared to controls (p = 0.0102). Paired samples from patients with MDD demonstrated a further 66.3% increase in TTR at remission compared to the acute phase (p = 0.0339). Conclusions: This study provides comprehensive information on molecular networks related to MDD as a basis for further investigation and identifies TTR for MDD monitoring and management. A clinical trial with bigger patient cohort should be conducted to validate this translational study. |
format | Online Article Text |
id | pubmed-8469805 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-84698052021-09-27 Transthyretin as a Biomarker to Predict and Monitor Major Depressive Disorder Identified by Whole-Genome Transcriptomic Analysis in Mouse Models Yu, Sung-Liang Chu, Selina Shih-Ting Chien, Min-Hui Kuo, Po-Hsiu Yang, Pan-Chyr Su, Kang-Yi Biomedicines Article Background: Accumulations of stressful life events result in the onset of major depressive disorder (MDD). Comprehensive genomic analysis is required to elucidate pathophysiological changes and identify applicable biomarkers. Methods: Transcriptomic analysis was performed on different brain parts of a chronic mild stress (CMS)-induced MDD mouse model followed by systemic analysis. QPCR and ELISA were utilized for validation in mice and patients. Results: The highest numbers of genes with significant changes induced by CMS were 505 in the amygdala followed by 272 in the hippocampus (twofold changes; FDR, p < 0.05). Enrichment analysis indicated that the core-enriched genes in CMS-treated mice were positively enriched for IFN-γ response genes in the amygdala, and hedgehog signaling in the hippocampus. Transthyretin (TTR) was severely reduced in CMS-treated mice. In patients with diagnosed MDD, serum concentrations of TTR were reduced by 48.7% compared to controls (p = 0.0102). Paired samples from patients with MDD demonstrated a further 66.3% increase in TTR at remission compared to the acute phase (p = 0.0339). Conclusions: This study provides comprehensive information on molecular networks related to MDD as a basis for further investigation and identifies TTR for MDD monitoring and management. A clinical trial with bigger patient cohort should be conducted to validate this translational study. MDPI 2021-08-31 /pmc/articles/PMC8469805/ /pubmed/34572310 http://dx.doi.org/10.3390/biomedicines9091124 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yu, Sung-Liang Chu, Selina Shih-Ting Chien, Min-Hui Kuo, Po-Hsiu Yang, Pan-Chyr Su, Kang-Yi Transthyretin as a Biomarker to Predict and Monitor Major Depressive Disorder Identified by Whole-Genome Transcriptomic Analysis in Mouse Models |
title | Transthyretin as a Biomarker to Predict and Monitor Major Depressive Disorder Identified by Whole-Genome Transcriptomic Analysis in Mouse Models |
title_full | Transthyretin as a Biomarker to Predict and Monitor Major Depressive Disorder Identified by Whole-Genome Transcriptomic Analysis in Mouse Models |
title_fullStr | Transthyretin as a Biomarker to Predict and Monitor Major Depressive Disorder Identified by Whole-Genome Transcriptomic Analysis in Mouse Models |
title_full_unstemmed | Transthyretin as a Biomarker to Predict and Monitor Major Depressive Disorder Identified by Whole-Genome Transcriptomic Analysis in Mouse Models |
title_short | Transthyretin as a Biomarker to Predict and Monitor Major Depressive Disorder Identified by Whole-Genome Transcriptomic Analysis in Mouse Models |
title_sort | transthyretin as a biomarker to predict and monitor major depressive disorder identified by whole-genome transcriptomic analysis in mouse models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469805/ https://www.ncbi.nlm.nih.gov/pubmed/34572310 http://dx.doi.org/10.3390/biomedicines9091124 |
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