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Role of necroptosis and immune infiltration in preeclampsia: novel insights from bioinformatics analyses
BACKGROUND: Preeclampsia (PE) is a serious pregnancy complication that can adversely affect the mother and fetus. Necroptosis is a recently discovered new form of programmed cell death involved in the pathological process of various pregnancy complications. Our study aimed to identify the necroptosi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320970/ https://www.ncbi.nlm.nih.gov/pubmed/37403014 http://dx.doi.org/10.1186/s12884-023-05821-0 |
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author | He, Lidan Zhan, Feng Lu, Lin Zhang, Xia Wu, Jianbo |
author_facet | He, Lidan Zhan, Feng Lu, Lin Zhang, Xia Wu, Jianbo |
author_sort | He, Lidan |
collection | PubMed |
description | BACKGROUND: Preeclampsia (PE) is a serious pregnancy complication that can adversely affect the mother and fetus. Necroptosis is a recently discovered new form of programmed cell death involved in the pathological process of various pregnancy complications. Our study aimed to identify the necroptosis-related differentially expressed genes (NRDEGs), create a diagnosis model and related disease subtypes model based on these genes, and further investigate their relationship with immune infiltration. METHODS: In this study, we identified NRDEGs by analyzing data from various databases, including Molecular Signatures, GeneCards, and Gene Expression Omnibus (GEO). Using minor absolute shrinkage and selection operator (LASSO) and logistic Cox regression analysis, we developed a novel PE diagnosis model based on NRDEGs. Furthermore, we developed PE subtype models using consensus clustering analysis based on key gene modules screened out by weighted correlation network analysis (WGCNA). Finally, we identified the difference in immune infiltration between the PE and control groups as well as between both PE subtypes by analyzing the immune cell infiltration across combined datasets and PE datasets. RESULTS: Our study discovered that the necroptosis pathway was significantly enriched and active in PE samples. We identified nine NRDEGs that involved in this pathway, including BRAF, PAWR, USP22, SYNCRIP, KRT86, MERTK, BAP1, CXCL5, and STK38. Additionally, we developed a diagnostic model based on a regression model including six NRDEGs and identified two PE subtypes: Cluster1 and Cluster2, based on key module genes. Furthermore, correlation analysis showed that the abundance of immune cell infiltration was related to necroptosis genes and PE disease subtypes. CONCLUSION: According to the present study, necroptosis is a phenomenon that occurs in PE and is connected to immune cell infiltration. This result suggests that necroptosis and immune-related factors may be the underlying mechanisms of PE pathophysiology. This study opens new avenues for future research into PE's pathogenesis and treatment options. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12884-023-05821-0. |
format | Online Article Text |
id | pubmed-10320970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103209702023-07-06 Role of necroptosis and immune infiltration in preeclampsia: novel insights from bioinformatics analyses He, Lidan Zhan, Feng Lu, Lin Zhang, Xia Wu, Jianbo BMC Pregnancy Childbirth Research BACKGROUND: Preeclampsia (PE) is a serious pregnancy complication that can adversely affect the mother and fetus. Necroptosis is a recently discovered new form of programmed cell death involved in the pathological process of various pregnancy complications. Our study aimed to identify the necroptosis-related differentially expressed genes (NRDEGs), create a diagnosis model and related disease subtypes model based on these genes, and further investigate their relationship with immune infiltration. METHODS: In this study, we identified NRDEGs by analyzing data from various databases, including Molecular Signatures, GeneCards, and Gene Expression Omnibus (GEO). Using minor absolute shrinkage and selection operator (LASSO) and logistic Cox regression analysis, we developed a novel PE diagnosis model based on NRDEGs. Furthermore, we developed PE subtype models using consensus clustering analysis based on key gene modules screened out by weighted correlation network analysis (WGCNA). Finally, we identified the difference in immune infiltration between the PE and control groups as well as between both PE subtypes by analyzing the immune cell infiltration across combined datasets and PE datasets. RESULTS: Our study discovered that the necroptosis pathway was significantly enriched and active in PE samples. We identified nine NRDEGs that involved in this pathway, including BRAF, PAWR, USP22, SYNCRIP, KRT86, MERTK, BAP1, CXCL5, and STK38. Additionally, we developed a diagnostic model based on a regression model including six NRDEGs and identified two PE subtypes: Cluster1 and Cluster2, based on key module genes. Furthermore, correlation analysis showed that the abundance of immune cell infiltration was related to necroptosis genes and PE disease subtypes. CONCLUSION: According to the present study, necroptosis is a phenomenon that occurs in PE and is connected to immune cell infiltration. This result suggests that necroptosis and immune-related factors may be the underlying mechanisms of PE pathophysiology. This study opens new avenues for future research into PE's pathogenesis and treatment options. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12884-023-05821-0. BioMed Central 2023-07-04 /pmc/articles/PMC10320970/ /pubmed/37403014 http://dx.doi.org/10.1186/s12884-023-05821-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 He, Lidan Zhan, Feng Lu, Lin Zhang, Xia Wu, Jianbo Role of necroptosis and immune infiltration in preeclampsia: novel insights from bioinformatics analyses |
title | Role of necroptosis and immune infiltration in preeclampsia: novel insights from bioinformatics analyses |
title_full | Role of necroptosis and immune infiltration in preeclampsia: novel insights from bioinformatics analyses |
title_fullStr | Role of necroptosis and immune infiltration in preeclampsia: novel insights from bioinformatics analyses |
title_full_unstemmed | Role of necroptosis and immune infiltration in preeclampsia: novel insights from bioinformatics analyses |
title_short | Role of necroptosis and immune infiltration in preeclampsia: novel insights from bioinformatics analyses |
title_sort | role of necroptosis and immune infiltration in preeclampsia: novel insights from bioinformatics analyses |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320970/ https://www.ncbi.nlm.nih.gov/pubmed/37403014 http://dx.doi.org/10.1186/s12884-023-05821-0 |
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