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A novel 4 immune-related genes as diagnostic markers and correlated with immune infiltrates in major depressive disorder
BACKGROUND: Immune response is prevalently related with major depressive disorder (MDD) pathophysiology. However, the study on the relationship between immune-related genes (IRGs) and immune infiltrates of MDD remains scarce. METHODS: We extracted expression data of 148 MDD patients from 2 cohorts,...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8842937/ https://www.ncbi.nlm.nih.gov/pubmed/35152883 http://dx.doi.org/10.1186/s12865-022-00479-3 |
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author | Ning, Linna Yang, Zhou Chen, Jie Hu, Zhaopeng Jiang, Wenrui Guo, Lixia Xu, Yan Li, Huiming Xu, Fanghua Deng, Dandong |
author_facet | Ning, Linna Yang, Zhou Chen, Jie Hu, Zhaopeng Jiang, Wenrui Guo, Lixia Xu, Yan Li, Huiming Xu, Fanghua Deng, Dandong |
author_sort | Ning, Linna |
collection | PubMed |
description | BACKGROUND: Immune response is prevalently related with major depressive disorder (MDD) pathophysiology. However, the study on the relationship between immune-related genes (IRGs) and immune infiltrates of MDD remains scarce. METHODS: We extracted expression data of 148 MDD patients from 2 cohorts, and systematically characterized differentially expressed IRGs by using limma package in R software. Then, the LASSO and multivariate logistic regression analysis was used to identify the most powerful IRGs. Next, we analyzed the relationship between IRGs and immune infiltrates of MDD. Finally, GSE76826 was used to to verificate of IRGs as a diagnostic markers in MDD. RESULTS: 203 different IRGs s in MDD has been identified (P < 0.05). GSEA revealed that the different IRGs was more likely to be enriched in immune-specific pathways. Then, a 9 IRGs was successfully established to predict MDD based on LASSO. Next, 4 IRGs was obtained by multivariate logistic regression analysis, and AUC for CD1C, SPP1, CD3D, CAMKK2, and IRGs model was 0.733, 0.767, 0.816, 0.800, and 0.861, suggesting that they have a good diagnostic performance. Furthermore, the proportion of T cells CD8, T cells γδ, macrophages M0, and NK cells resting in MDD group was lower than that in the healthy controls, suggesting that the immune system in MDD group is impaired. Simultaneously, CD3D was validated a reliable marker in MDD, and was positively correlated with T cells CD8. GSEA revealed high expression CD3D was more likely to be enriched in immune-specific pathways, and low expression CD3D was more likely to be enriched in glucose metabolism metabolism-specific pathways. CONCLUSIONS: We applied bioinformatics approaches to suggest that a 4 IRGs could serve as diagnostic markers to provide a novel direction to explore the pathogenesis of MDD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12865-022-00479-3. |
format | Online Article Text |
id | pubmed-8842937 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88429372022-02-16 A novel 4 immune-related genes as diagnostic markers and correlated with immune infiltrates in major depressive disorder Ning, Linna Yang, Zhou Chen, Jie Hu, Zhaopeng Jiang, Wenrui Guo, Lixia Xu, Yan Li, Huiming Xu, Fanghua Deng, Dandong BMC Immunol Research BACKGROUND: Immune response is prevalently related with major depressive disorder (MDD) pathophysiology. However, the study on the relationship between immune-related genes (IRGs) and immune infiltrates of MDD remains scarce. METHODS: We extracted expression data of 148 MDD patients from 2 cohorts, and systematically characterized differentially expressed IRGs by using limma package in R software. Then, the LASSO and multivariate logistic regression analysis was used to identify the most powerful IRGs. Next, we analyzed the relationship between IRGs and immune infiltrates of MDD. Finally, GSE76826 was used to to verificate of IRGs as a diagnostic markers in MDD. RESULTS: 203 different IRGs s in MDD has been identified (P < 0.05). GSEA revealed that the different IRGs was more likely to be enriched in immune-specific pathways. Then, a 9 IRGs was successfully established to predict MDD based on LASSO. Next, 4 IRGs was obtained by multivariate logistic regression analysis, and AUC for CD1C, SPP1, CD3D, CAMKK2, and IRGs model was 0.733, 0.767, 0.816, 0.800, and 0.861, suggesting that they have a good diagnostic performance. Furthermore, the proportion of T cells CD8, T cells γδ, macrophages M0, and NK cells resting in MDD group was lower than that in the healthy controls, suggesting that the immune system in MDD group is impaired. Simultaneously, CD3D was validated a reliable marker in MDD, and was positively correlated with T cells CD8. GSEA revealed high expression CD3D was more likely to be enriched in immune-specific pathways, and low expression CD3D was more likely to be enriched in glucose metabolism metabolism-specific pathways. CONCLUSIONS: We applied bioinformatics approaches to suggest that a 4 IRGs could serve as diagnostic markers to provide a novel direction to explore the pathogenesis of MDD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12865-022-00479-3. BioMed Central 2022-02-13 /pmc/articles/PMC8842937/ /pubmed/35152883 http://dx.doi.org/10.1186/s12865-022-00479-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Ning, Linna Yang, Zhou Chen, Jie Hu, Zhaopeng Jiang, Wenrui Guo, Lixia Xu, Yan Li, Huiming Xu, Fanghua Deng, Dandong A novel 4 immune-related genes as diagnostic markers and correlated with immune infiltrates in major depressive disorder |
title | A novel 4 immune-related genes as diagnostic markers and correlated with immune infiltrates in major depressive disorder |
title_full | A novel 4 immune-related genes as diagnostic markers and correlated with immune infiltrates in major depressive disorder |
title_fullStr | A novel 4 immune-related genes as diagnostic markers and correlated with immune infiltrates in major depressive disorder |
title_full_unstemmed | A novel 4 immune-related genes as diagnostic markers and correlated with immune infiltrates in major depressive disorder |
title_short | A novel 4 immune-related genes as diagnostic markers and correlated with immune infiltrates in major depressive disorder |
title_sort | novel 4 immune-related genes as diagnostic markers and correlated with immune infiltrates in major depressive disorder |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8842937/ https://www.ncbi.nlm.nih.gov/pubmed/35152883 http://dx.doi.org/10.1186/s12865-022-00479-3 |
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