{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T04:59:55Z","timestamp":1785214795570,"version":"3.55.0"},"reference-count":31,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T00:00:00Z","timestamp":1785196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Mol. Biosci."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent synovial inflammation, immune dysregulation, and progressive joint destruction. Mast cells (MCs) are important components of the synovial immune microenvironment, but their heterogeneity and regulatory roles in RA remain unclear.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed single-cell RNA-sequencing data from 17 RA synovial samples in our institutional cohort to construct a cellular atlas of the RA synovial microenvironment. MCs within the myeloid compartment were re-clustered to characterize their heterogeneity, followed by differential expression, functional enrichment, cell-cell communication, and transcriptional regulatory analyses. In parallel, bulk RNA-sequencing data from 218 RA synovial samples in our institutional cohort were analyzed. Consensus clustering based on MC-related signature genes was used to identify molecular subtypes, and pathway activity, immune infiltration, hub genes, and diagnostic performance were further evaluated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Eleven major cell populations were identified in the single-cell dataset. MCs exhibited distinct transcriptional features and were classified into three heterogeneous subsets associated with protein processing and RNA metabolism, complement and inflammatory regulation, and TNF\/NF-\u03baB signaling, respectively. Cell-cell communication analysis revealed extensive interactions between MC subsets and macrophages, monocytes, and cDC2 cells. In the bulk transcriptomic cohort, three stable MC-related molecular subtypes were identified. C2 Subtype showed the strongest inflammatory activation and immune infiltration. Notably, overall MC abundance did not differ significantly among risk groups, suggesting that MC state-associated molecular features, rather than MC quantity, may better distinguish RA subtypes. CCNB1, NCAPH, and DLGAP5 were identified as key hub genes, and an MC score-based diagnostic model showed favorable discriminatory performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study reveals substantial MC heterogeneity in the RA synovial microenvironment and suggests that distinct MC subsets may participate in inflammatory regulation and immune-cell crosstalk. MC-related molecular stratification effectively identifies RA subtypes with different inflammatory phenotypes, supporting the potential value of MC-associated signatures as biomarkers for patient stratification and targeted therapeutic exploration.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmolb.2026.1898923","type":"journal-article","created":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T04:25:11Z","timestamp":1785212711000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Heterogeneity and molecular typing characteristics of mast cells in rheumatoid arthritis"],"prefix":"10.3389","volume":"13","author":[{"given":"Wenlong","family":"Fang","sequence":"first","affiliation":[{"name":"Department of Traditional Chinese Medicine, The Second Affiliated Hospital of Harbin Medical University","place":["Harbin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luyu","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Rheumatology and Immunology, The Second Affiliated Hospital of Harbin Medical University","place":["Harbin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huimin","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Traditional Chinese Medicine, The Second Affiliated Hospital of Harbin Medical University","place":["Harbin, China"]},{"name":"Department of Traditional Chinese Medicine, The Second Affiliated Hospital of Zhejiang University","place":["Hangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingkun","family":"Nie","sequence":"additional","affiliation":[{"name":"Department of Rheumatology and Immunology, The Second Affiliated Hospital of Harbin Medical University","place":["Harbin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,28]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1083","DOI":"10.1038\/nmeth.4463","article-title":"SCENIC: single-cell regulatory network inference and clustering","volume":"14","author":"Aibar","year":"2017","journal-title":"Nat. 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