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Methylation factors as biomarkers of fibromyalgia
BACKGROUND: Fibromyalgia (FM) is a common and intractable chronic musculoskeletal pain syndrome, but its exact underlying mechanisms are unknown. This study sought to identify biomarkers of FM and the underlying molecular mechanisms of the disease. METHODS: FM-related gene expression profiles (GSE67...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009573/ https://www.ncbi.nlm.nih.gov/pubmed/36923073 http://dx.doi.org/10.21037/atm-22-6631 |
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author | Huang, Chengyu Zhang, Nan Wei, Mengxin Pan, Qinchun Cheng, Chunyan Lu, Ke-Er Mo, Jianwen Chen, Yixuan |
author_facet | Huang, Chengyu Zhang, Nan Wei, Mengxin Pan, Qinchun Cheng, Chunyan Lu, Ke-Er Mo, Jianwen Chen, Yixuan |
author_sort | Huang, Chengyu |
collection | PubMed |
description | BACKGROUND: Fibromyalgia (FM) is a common and intractable chronic musculoskeletal pain syndrome, but its exact underlying mechanisms are unknown. This study sought to identify biomarkers of FM and the underlying molecular mechanisms of the disease. METHODS: FM-related gene expression profiles (GSE67311) and methylation profiles (GSE85506) were obtained from the Gene Expression Omnibus database, and a differential expression analysis was performed to identify the methylation factors. Subsequently, an enrichment analysis and gene set enrichment analysis (GSEA) were conducted to examine the methylation factors. In addition, the transcriptional regulators of the methylation factors were predicted, and key methylation factors were identified by a receiver operating characteristic curve analysis and nomogram models. Finally, the relationship between FM and cell death (pyroptosis, necroptosis, and cuproptosis) was assessed by a GSEA and gene set variation analysis. RESULTS: A total of 455 methylation factors were identified. The enrichment analysis and GSEA results showed that methylation factors were clearly involved in the biological functions and signaling pathways related to neural, immune inflammation, and pain responses. The transcriptional regulator specificity protein 1 (SP1) may have a broad regulatory role. Finally, seven key methylation factors were identified, of which amino beta (A4) precursor protein binding family B member 2 (APBB2), A-kinase anchor protein 12 (AKAP12), and cluster of differentiation 38 (CD38) had strong clinical diagnostic power. In addition, AKAP12 and CD38 were significantly and negatively associated with sepsis, necrotizing sepsis, and cupular sepsis. CONCLUSIONS: Our study suggests that FM is associated with deoxyribonucleic acid methylation. The methylation factors APBB2, AKAP12, and CD38 may be potential biomarkers and should be further examined to provide a new biological framework of the possible disease mechanisms underlying FM. |
format | Online Article Text |
id | pubmed-10009573 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-100095732023-03-14 Methylation factors as biomarkers of fibromyalgia Huang, Chengyu Zhang, Nan Wei, Mengxin Pan, Qinchun Cheng, Chunyan Lu, Ke-Er Mo, Jianwen Chen, Yixuan Ann Transl Med Original Article BACKGROUND: Fibromyalgia (FM) is a common and intractable chronic musculoskeletal pain syndrome, but its exact underlying mechanisms are unknown. This study sought to identify biomarkers of FM and the underlying molecular mechanisms of the disease. METHODS: FM-related gene expression profiles (GSE67311) and methylation profiles (GSE85506) were obtained from the Gene Expression Omnibus database, and a differential expression analysis was performed to identify the methylation factors. Subsequently, an enrichment analysis and gene set enrichment analysis (GSEA) were conducted to examine the methylation factors. In addition, the transcriptional regulators of the methylation factors were predicted, and key methylation factors were identified by a receiver operating characteristic curve analysis and nomogram models. Finally, the relationship between FM and cell death (pyroptosis, necroptosis, and cuproptosis) was assessed by a GSEA and gene set variation analysis. RESULTS: A total of 455 methylation factors were identified. The enrichment analysis and GSEA results showed that methylation factors were clearly involved in the biological functions and signaling pathways related to neural, immune inflammation, and pain responses. The transcriptional regulator specificity protein 1 (SP1) may have a broad regulatory role. Finally, seven key methylation factors were identified, of which amino beta (A4) precursor protein binding family B member 2 (APBB2), A-kinase anchor protein 12 (AKAP12), and cluster of differentiation 38 (CD38) had strong clinical diagnostic power. In addition, AKAP12 and CD38 were significantly and negatively associated with sepsis, necrotizing sepsis, and cupular sepsis. CONCLUSIONS: Our study suggests that FM is associated with deoxyribonucleic acid methylation. The methylation factors APBB2, AKAP12, and CD38 may be potential biomarkers and should be further examined to provide a new biological framework of the possible disease mechanisms underlying FM. AME Publishing Company 2023-02-21 2023-02-28 /pmc/articles/PMC10009573/ /pubmed/36923073 http://dx.doi.org/10.21037/atm-22-6631 Text en 2023 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Huang, Chengyu Zhang, Nan Wei, Mengxin Pan, Qinchun Cheng, Chunyan Lu, Ke-Er Mo, Jianwen Chen, Yixuan Methylation factors as biomarkers of fibromyalgia |
title | Methylation factors as biomarkers of fibromyalgia |
title_full | Methylation factors as biomarkers of fibromyalgia |
title_fullStr | Methylation factors as biomarkers of fibromyalgia |
title_full_unstemmed | Methylation factors as biomarkers of fibromyalgia |
title_short | Methylation factors as biomarkers of fibromyalgia |
title_sort | methylation factors as biomarkers of fibromyalgia |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009573/ https://www.ncbi.nlm.nih.gov/pubmed/36923073 http://dx.doi.org/10.21037/atm-22-6631 |
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