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Gene model-related m6A expression levels predict the risk of preeclampsia
BACKGROUND: This is the first study to explore the potential functions and expression patterns of RNA N6-methyladenosine (m6A) and potential related genes in preeclampsia. METHODS: We identified two m6A modification patterns through unsupervised cluster analysis and validated them by principal compo...
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/PMC9069853/ https://www.ncbi.nlm.nih.gov/pubmed/35513840 http://dx.doi.org/10.1186/s12920-022-01254-4 |
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author | Li, Yiwei Chen, Can Diao, Mengyuan Wei, Yanli Zhu, Ying Hu, Wei |
author_facet | Li, Yiwei Chen, Can Diao, Mengyuan Wei, Yanli Zhu, Ying Hu, Wei |
author_sort | Li, Yiwei |
collection | PubMed |
description | BACKGROUND: This is the first study to explore the potential functions and expression patterns of RNA N6-methyladenosine (m6A) and potential related genes in preeclampsia. METHODS: We identified two m6A modification patterns through unsupervised cluster analysis and validated them by principal component analysis. We quantified the relative abundance of specific infiltrating immunocytes using single-sample gene set enrichment analysis (ssGSEA) and the Wilcoxon test. To screen hub genes related to m6A regulators, we performed weighted gene coexpression network analysis. Functional enrichment analysis was conducted for differential signalling pathways and cellular processes. Preeclampsia patients were grouped by consensus clustering based on differentially expressed hub genes and the relationship between different gene-mediated classifications and clinical features. RESULTS: Two m6A clusters in preeclampsia, cluster A and cluster B, were determined based on the expression of 17 m6A modification regulators; ssGSEA revealed seven significantly different immune cell subtypes between the two clusters. A total of 1393 DEGs and nine potential m6A-modified hub genes were screened. We divided the patients into two groups based on the expression of these nine genes. We found that almost all the patients in m6A cluster A were classified into hub gene cluster 1 and that a lower gestational age may be associated with more m6A-associated events. CONCLUSIONS: This study revealed that hub gene-mediated classification is consistent with m6A modification clusters for predicting the clinical characteristics of patients with preeclampsia. Our results provide new insights into the molecular mechanisms of preeclampsia. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01254-4. |
format | Online Article Text |
id | pubmed-9069853 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-90698532022-05-05 Gene model-related m6A expression levels predict the risk of preeclampsia Li, Yiwei Chen, Can Diao, Mengyuan Wei, Yanli Zhu, Ying Hu, Wei BMC Med Genomics Research BACKGROUND: This is the first study to explore the potential functions and expression patterns of RNA N6-methyladenosine (m6A) and potential related genes in preeclampsia. METHODS: We identified two m6A modification patterns through unsupervised cluster analysis and validated them by principal component analysis. We quantified the relative abundance of specific infiltrating immunocytes using single-sample gene set enrichment analysis (ssGSEA) and the Wilcoxon test. To screen hub genes related to m6A regulators, we performed weighted gene coexpression network analysis. Functional enrichment analysis was conducted for differential signalling pathways and cellular processes. Preeclampsia patients were grouped by consensus clustering based on differentially expressed hub genes and the relationship between different gene-mediated classifications and clinical features. RESULTS: Two m6A clusters in preeclampsia, cluster A and cluster B, were determined based on the expression of 17 m6A modification regulators; ssGSEA revealed seven significantly different immune cell subtypes between the two clusters. A total of 1393 DEGs and nine potential m6A-modified hub genes were screened. We divided the patients into two groups based on the expression of these nine genes. We found that almost all the patients in m6A cluster A were classified into hub gene cluster 1 and that a lower gestational age may be associated with more m6A-associated events. CONCLUSIONS: This study revealed that hub gene-mediated classification is consistent with m6A modification clusters for predicting the clinical characteristics of patients with preeclampsia. Our results provide new insights into the molecular mechanisms of preeclampsia. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01254-4. BioMed Central 2022-05-05 /pmc/articles/PMC9069853/ /pubmed/35513840 http://dx.doi.org/10.1186/s12920-022-01254-4 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 Li, Yiwei Chen, Can Diao, Mengyuan Wei, Yanli Zhu, Ying Hu, Wei Gene model-related m6A expression levels predict the risk of preeclampsia |
title | Gene model-related m6A expression levels predict the risk of preeclampsia |
title_full | Gene model-related m6A expression levels predict the risk of preeclampsia |
title_fullStr | Gene model-related m6A expression levels predict the risk of preeclampsia |
title_full_unstemmed | Gene model-related m6A expression levels predict the risk of preeclampsia |
title_short | Gene model-related m6A expression levels predict the risk of preeclampsia |
title_sort | gene model-related m6a expression levels predict the risk of preeclampsia |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9069853/ https://www.ncbi.nlm.nih.gov/pubmed/35513840 http://dx.doi.org/10.1186/s12920-022-01254-4 |
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