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This concept, which combines high-plex RNA sequencing with spatial data, emerged in the early 2010s. Spatial transcriptomics has rapidly expanded with the development of technologies such as in situ hybridization, in situ sequencing, in situ spatial barcoding, and microdissection-based methods. Each technique offers advanced mapping resolution and precise spatial assessments at the single-cell level. Over the past decade, the use of spatial transcriptomics on clinical samples has enabled researchers to identify gene expressions in specific diseased foci, significantly enhancing our understanding of cellular interactions and disease processes. In the field of rheumatology, the complex and elusive pathophysiology of diseases such as rheumatoid arthritis, systemic lupus erythematosus, and Sj\u00f6gren\u2019s syndrome remains a challenge for personalized treatment. Spatial transcriptomics provides insights into how different cell populations interact within disease foci, such as the synovial tissue, kidneys, and salivary glands. This review summarizes the development of spatial transcriptomics and current insights into the pathophysiology of autoimmune rheumatic diseases, focusing on immune cell distribution and cellular interactions within tissues. We also explore the potential of spatial transcriptomics from a clinical perspective and discuss the possibilities for translating this technology to the bedside.\n<\/jats:p>","DOI":"10.1186\/s41232-025-00369-2","type":"journal-article","created":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T04:36:53Z","timestamp":1740026213000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Spatial transcriptomics in autoimmune rheumatic disease: potential clinical applications and perspectives"],"prefix":"10.1186","volume":"45","author":[{"given":"Atsuko Tsujii","family":"Miyamoto","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hiroshi","family":"Shimagami","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Atsushi","family":"Kumanogoh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6060-1228","authenticated-orcid":false,"given":"Masayuki","family":"Nishide","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,2,20]]},"reference":[{"issue":"5","key":"369_CR1","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1038\/nmeth.1315","volume":"6","author":"F Tang","year":"2009","unstructured":"Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N, et al. mRNA-Seq whole-transcriptome analysis of a single cell. 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