Your browser doesn't support javascript.
loading
Significance of m6A in subtype identification, immunological evolution, and therapeutic sensitivity of RA.
Ma, Chenxi; Wu, Jiasheng; Lei, Hongwei; Huang, He; Li, Yingnan.
Affiliation
  • Ma C; Department of Rheumatology, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China.
  • Wu J; Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China.
  • Lei H; Department of Rheumatology, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China.
  • Huang H; Department of Rheumatology, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China.
  • Li Y; Department of Rheumatology, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China. Electronic address: 13845117361@163.com.
Immunobiology ; 229(1): 152781, 2024 Jan.
Article in En | MEDLINE | ID: mdl-38154164
ABSTRACT
N6-methyladenosine (m6A) is one kind of important epigenetic modification pattern which is extensively involved in immune regulation. The development and progression of autoimmune diseases are closely related to immune dysregulation. Considering that rheumatoid arthritis (RA) is a typical autoimmune disease, the m6A process might be one of the important regulatory mechanisms in the pathogenesis of RA. In this study, we identified five differentially expressed m6A regulators in normal and RA samples from the GEO database. With these five regulators, we constructed the nomogram, and it could accurately identify the risk of RA morbidity. Next, we identified 121 differentially expressed genes (DEGs) between normal and RA samples, of which 36 DEGs were co-expressed with these five m6A regulators. We noted that these DEGs were highly enriched in multiple immunoregulatory signaling pathways, such as cytokine-mediated immune cell chemotaxis, adhesion, and activation. To further characterize the heterogeneity of immunological features, we clustered the RA samples into two subtypes. The C2 subtype has higher infiltration levels of pro-inflammatory cells and activity of pro-inflammatory signaling pathways. Thus, the inflammatory response might be more vigorous in the C2 subtype. Next, we constructed the m6Asig system with the SVM machine learning algorithms and least absolute shrinkage and selection operator (LASSO) regression. The m6Asig could accurately distinguish the C1 and C2 subtypes, which indicated that the m6Asig could be a potential biomarker for the inflammatory activity of RA. Finally, by comparing the information from the CellMiner, TTD, and DrugBank databases, we determined 25 drugs. The targets of these drugs were positively correlated with m6Asig. To be clarified, the above findings were derived from bioinformatics and statistical analyses, and further experimental validation still requires. In summary, this study further revealed the m6A and immunoregulation mechanisms in RA pathogenesis. Also, the m6Asig could be a novel biomarker with potential applicability in the clinical management of RA.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Arthritis, Rheumatoid / Autoimmune Diseases Limits: Humans Language: En Journal: Immunobiology Year: 2024 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Arthritis, Rheumatoid / Autoimmune Diseases Limits: Humans Language: En Journal: Immunobiology Year: 2024 Document type: Article Affiliation country: Country of publication: