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Identification of a diagnostic model and molecular subtypes of major depressive disorder based on endoplasmic reticulum stress-related genes

SUBJECT: Major depressive disorder (MDD) negatively affects patients’ behaviours and daily lives. Due to the high heterogeneity and complex pathological features of MDD, its diagnosis remains challenging. Evidence suggests that endoplasmic reticulum stress (ERS) is involved in the pathogenesis of MD...

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Autores principales: Huang, Shuwen, Li, Yong, Shen, Jianying, Liang, Wenna, Li, Candong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464956/
https://www.ncbi.nlm.nih.gov/pubmed/37649561
http://dx.doi.org/10.3389/fpsyt.2023.1168516
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author Huang, Shuwen
Li, Yong
Shen, Jianying
Liang, Wenna
Li, Candong
author_facet Huang, Shuwen
Li, Yong
Shen, Jianying
Liang, Wenna
Li, Candong
author_sort Huang, Shuwen
collection PubMed
description SUBJECT: Major depressive disorder (MDD) negatively affects patients’ behaviours and daily lives. Due to the high heterogeneity and complex pathological features of MDD, its diagnosis remains challenging. Evidence suggests that endoplasmic reticulum stress (ERS) is involved in the pathogenesis of MDD; however, relevant diagnostic markers have not been well studied. This study aimed to screen for ERS genes with potential diagnostic value in MDD. METHODS: Gene expression data on MDD samples were downloaded from the GEO database, and ERS-related genes were obtained from the GeneCards and MSigDB databases. Differentially expressed genes (DEGs) in MDD patients and healthy subjects were identified and then integrated with ERS genes. ERS diagnostic model and nomogram were developed based on biomarkers screened using the LASSO method. The diagnostic performance of this model was evaluated. ERS-associated subtypes were identified. CIBERSORT and GSEA were used to explore the differences between the different subtypes. Finally, WGCNA was performed to identify hub genes related to the subtypes. RESULTS: A diagnostic model was developed based on seven ERS genes: KCNE1, PDIA4, STAU1, TMED4, MGST1, RCN1, and SHC1. The validation analysis showed that this model had a good diagnostic performance. KCNE1 expression was positively correlated with M0 macrophages and negatively correlated with resting CD4+ memory T cells. Two subtypes (SubA and SubB) were identified, and these two subtypes showed different ER score. The SubB group showed higher immune infiltration than the SubA group. Finally, NCF4, NCF2, CSF3R, and FPR2 were identified as hub genes associated with ERS molecular subtypes. CONCLUSION: Our current study provides novel diagnostic biomarkers for MDD from an ERS perspective, and these findings further facilitate the use of precision medicine in MDD.
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spelling pubmed-104649562023-08-30 Identification of a diagnostic model and molecular subtypes of major depressive disorder based on endoplasmic reticulum stress-related genes Huang, Shuwen Li, Yong Shen, Jianying Liang, Wenna Li, Candong Front Psychiatry Psychiatry SUBJECT: Major depressive disorder (MDD) negatively affects patients’ behaviours and daily lives. Due to the high heterogeneity and complex pathological features of MDD, its diagnosis remains challenging. Evidence suggests that endoplasmic reticulum stress (ERS) is involved in the pathogenesis of MDD; however, relevant diagnostic markers have not been well studied. This study aimed to screen for ERS genes with potential diagnostic value in MDD. METHODS: Gene expression data on MDD samples were downloaded from the GEO database, and ERS-related genes were obtained from the GeneCards and MSigDB databases. Differentially expressed genes (DEGs) in MDD patients and healthy subjects were identified and then integrated with ERS genes. ERS diagnostic model and nomogram were developed based on biomarkers screened using the LASSO method. The diagnostic performance of this model was evaluated. ERS-associated subtypes were identified. CIBERSORT and GSEA were used to explore the differences between the different subtypes. Finally, WGCNA was performed to identify hub genes related to the subtypes. RESULTS: A diagnostic model was developed based on seven ERS genes: KCNE1, PDIA4, STAU1, TMED4, MGST1, RCN1, and SHC1. The validation analysis showed that this model had a good diagnostic performance. KCNE1 expression was positively correlated with M0 macrophages and negatively correlated with resting CD4+ memory T cells. Two subtypes (SubA and SubB) were identified, and these two subtypes showed different ER score. The SubB group showed higher immune infiltration than the SubA group. Finally, NCF4, NCF2, CSF3R, and FPR2 were identified as hub genes associated with ERS molecular subtypes. CONCLUSION: Our current study provides novel diagnostic biomarkers for MDD from an ERS perspective, and these findings further facilitate the use of precision medicine in MDD. Frontiers Media S.A. 2023-08-15 /pmc/articles/PMC10464956/ /pubmed/37649561 http://dx.doi.org/10.3389/fpsyt.2023.1168516 Text en Copyright © 2023 Huang, Li, Shen, Liang and Li. https://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
Huang, Shuwen
Li, Yong
Shen, Jianying
Liang, Wenna
Li, Candong
Identification of a diagnostic model and molecular subtypes of major depressive disorder based on endoplasmic reticulum stress-related genes
title Identification of a diagnostic model and molecular subtypes of major depressive disorder based on endoplasmic reticulum stress-related genes
title_full Identification of a diagnostic model and molecular subtypes of major depressive disorder based on endoplasmic reticulum stress-related genes
title_fullStr Identification of a diagnostic model and molecular subtypes of major depressive disorder based on endoplasmic reticulum stress-related genes
title_full_unstemmed Identification of a diagnostic model and molecular subtypes of major depressive disorder based on endoplasmic reticulum stress-related genes
title_short Identification of a diagnostic model and molecular subtypes of major depressive disorder based on endoplasmic reticulum stress-related genes
title_sort identification of a diagnostic model and molecular subtypes of major depressive disorder based on endoplasmic reticulum stress-related genes
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464956/
https://www.ncbi.nlm.nih.gov/pubmed/37649561
http://dx.doi.org/10.3389/fpsyt.2023.1168516
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