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The Pyroptosis-Related Signature Predicts Diagnosis and Indicates Immune Characteristic in Major Depressive Disorder

Pyroptosis is recently identified as an inflammatory form of programmed cell death. However, the roles of pyroptosis-related genes (PS genes) in major depressive disorder (MDD) remain unclear. This study developed a novel diagnostic model for MDD based on PS genes and explored the pathological mecha...

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Autores principales: Deng, Zhifang, Liu, Jue, He, Shen, Gao, Wenqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169094/
https://www.ncbi.nlm.nih.gov/pubmed/35677442
http://dx.doi.org/10.3389/fphar.2022.848939
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author Deng, Zhifang
Liu, Jue
He, Shen
Gao, Wenqi
author_facet Deng, Zhifang
Liu, Jue
He, Shen
Gao, Wenqi
author_sort Deng, Zhifang
collection PubMed
description Pyroptosis is recently identified as an inflammatory form of programmed cell death. However, the roles of pyroptosis-related genes (PS genes) in major depressive disorder (MDD) remain unclear. This study developed a novel diagnostic model for MDD based on PS genes and explored the pathological mechanisms associated with pyroptosis. First, we obtained 23 PS genes that were differentially expressed between healthy controls and MDD cases from GSE98793 dataset. There were obvious variation in immune cell infiltration profiles and immune-related pathway enrichment between healthy controls and MDD cases. Then, a novel diagnostic model consisting of eight PS genes (GPER1, GZMA, HMGB1, IL1RN, NLRC4, NLRP3, UTS2, and CAPN1) for MDD was constructed by random forest (RF) and least absolute shrinkage and selection operator (LASSO) analyses. ROC analysis revealed that our model has good diagnostic performance, AUC = 0.795 (95% CI 0.721–0.868). Subsequently, the consensus clustering method based on 23 differentially expressed PS genes was constructed to divide all MDD cases into two distinct pyroptosis subtypes (cluster A and B) with different immune and biological characteristics. Principal component analysis (PCA) algorithm was performed to calculate the pyroptosis scores (“PS-scores”) for each sample to quantify the pyroptosis regulation subtypes. The MDD patients in cluster B had higher “PS-scores” than those in cluster A. Furthermore, we also found that MDD patients in cluster B showed lower expression levels of 11 interferon (IFN)-α isoforms. In conclusion, pyroptosis may play an important role in MDD and can provide new insights into the diagnosis and underlying mechanisms of MDD.
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spelling pubmed-91690942022-06-07 The Pyroptosis-Related Signature Predicts Diagnosis and Indicates Immune Characteristic in Major Depressive Disorder Deng, Zhifang Liu, Jue He, Shen Gao, Wenqi Front Pharmacol Pharmacology Pyroptosis is recently identified as an inflammatory form of programmed cell death. However, the roles of pyroptosis-related genes (PS genes) in major depressive disorder (MDD) remain unclear. This study developed a novel diagnostic model for MDD based on PS genes and explored the pathological mechanisms associated with pyroptosis. First, we obtained 23 PS genes that were differentially expressed between healthy controls and MDD cases from GSE98793 dataset. There were obvious variation in immune cell infiltration profiles and immune-related pathway enrichment between healthy controls and MDD cases. Then, a novel diagnostic model consisting of eight PS genes (GPER1, GZMA, HMGB1, IL1RN, NLRC4, NLRP3, UTS2, and CAPN1) for MDD was constructed by random forest (RF) and least absolute shrinkage and selection operator (LASSO) analyses. ROC analysis revealed that our model has good diagnostic performance, AUC = 0.795 (95% CI 0.721–0.868). Subsequently, the consensus clustering method based on 23 differentially expressed PS genes was constructed to divide all MDD cases into two distinct pyroptosis subtypes (cluster A and B) with different immune and biological characteristics. Principal component analysis (PCA) algorithm was performed to calculate the pyroptosis scores (“PS-scores”) for each sample to quantify the pyroptosis regulation subtypes. The MDD patients in cluster B had higher “PS-scores” than those in cluster A. Furthermore, we also found that MDD patients in cluster B showed lower expression levels of 11 interferon (IFN)-α isoforms. In conclusion, pyroptosis may play an important role in MDD and can provide new insights into the diagnosis and underlying mechanisms of MDD. Frontiers Media S.A. 2022-05-19 /pmc/articles/PMC9169094/ /pubmed/35677442 http://dx.doi.org/10.3389/fphar.2022.848939 Text en Copyright © 2022 Deng, Liu, He and Gao. 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 Pharmacology
Deng, Zhifang
Liu, Jue
He, Shen
Gao, Wenqi
The Pyroptosis-Related Signature Predicts Diagnosis and Indicates Immune Characteristic in Major Depressive Disorder
title The Pyroptosis-Related Signature Predicts Diagnosis and Indicates Immune Characteristic in Major Depressive Disorder
title_full The Pyroptosis-Related Signature Predicts Diagnosis and Indicates Immune Characteristic in Major Depressive Disorder
title_fullStr The Pyroptosis-Related Signature Predicts Diagnosis and Indicates Immune Characteristic in Major Depressive Disorder
title_full_unstemmed The Pyroptosis-Related Signature Predicts Diagnosis and Indicates Immune Characteristic in Major Depressive Disorder
title_short The Pyroptosis-Related Signature Predicts Diagnosis and Indicates Immune Characteristic in Major Depressive Disorder
title_sort pyroptosis-related signature predicts diagnosis and indicates immune characteristic in major depressive disorder
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169094/
https://www.ncbi.nlm.nih.gov/pubmed/35677442
http://dx.doi.org/10.3389/fphar.2022.848939
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