Identification of Synovial Fibroblast-Associated Neuropeptide Genes and m6A Factors in Rheumatoid Arthritis Using Single-Cell Analysis and Machine Learning

<div>Clustering results and ligand–receptor interactions in GSE109449. (a) UMAP results for six clusters after dimensional reduction clustering. (b) Cellular annotation of UMAP based on marker genes from previous articles. (c) Relative expression levels of neuropeptide mRNAs with significant expression differences. (d) Cell clusters were annotated with UMAP based on <i>BDKRB2</i>, <i>NPR3</i>, and <i>GHR</i> expression levels in (c). (e) Correlation heat map of receptor–ligand interactions. For example, NPPB released from CD34-THY1+CDH11+ cells interacted with the NPR3 receptor on CD34+THY1-CDH11+ and CD34+THY1+CDH11+ cells. GH1 released from CD34+THY1+CDH11+ cells interacts with the <i>GHR</i> on other cells. Abbreviations: UMAP: Uniform Manifold Approximation and Projection.</div>

Disease Markers

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Figure 2: Identification of Synovial Fibroblast-Associated Neuropeptide Genes and m6A Factors in Rheumatoid Arthritis Using Single-Cell Analysis and Machine Learning 

Figure 2 | Identification of Synovial Fibroblast-Associated Neuropeptide Genes and m6A Factors in Rheumatoid Arthritis Using Single-Cell Analysis and Machine Learning 