{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T19:23:24Z","timestamp":1792783404062,"version":"4.5.0"},"reference-count":165,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T00:00:00Z","timestamp":1791936000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T00:00:00Z","timestamp":1791936000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Vingroup Joint Stock Company","award":["VUNI.2526.RII.004"],"award-info":[{"award-number":["VUNI.2526.RII.004"]}],"id":[{"id":"https:\/\/ror.org\/03j51tb87","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Clinic Rev Allerg Immunol"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Autoimmune diseases are characterized by loss of immune tolerance and substantial heterogeneity across patients, tissues, and disease stages. Although bulk transcriptomic studies have identified important inflammatory pathways, they cannot directly resolve rare, transitional, and tissue-contextualized cell states that may be relevant to disease mechanisms and therapeutic response. Single-cell RNA sequencing (scRNA-seq) enables transcriptomic profiling at cellular resolution, while complementary multimodal, receptor-repertoire, epigenomic, and spatial approaches can link cellular states to protein phenotype, clonal architecture, regulatory programs, and tissue context. This review critically examines recent single-cell studies in rheumatoid arthritis, systemic lupus erythematosus and lupus nephritis, type 1 diabetes, and multiple sclerosis. Rather than providing a descriptive catalogue of published studies, we assess the strength of available evidence by distinguishing independently replicated findings from observations supported by limited studies, and cross-sectional associations from longitudinal, treatment-response, and functional evidence. Across the selected diseases, studies repeatedly report inflammatory programs involving interferon signaling, chemokine-mediated immune recruitment, and stromal-immune interactions; however, evidence for convergence at the cell-state and regulatory-network levels remains limited, and the extent to which shared signatures represent common pathogenic mechanisms rather than inflammatory context remains uncertain. We evaluate the translational potential of scRNA-seq for biomarker discovery, patient stratification, and treatment response prediction, while considering evidence from related tissue-based molecular stratification approaches, including the R4RA randomized trial in rheumatoid arthritis. R4RA provides prospective randomized evidence that synovial molecular features can enrich for differential therapeutic responses, but its use of bulk synovial transcriptomics and histopathology does not constitute prospective validation of single-cell-derived biomarkers. We further highlight cohort biases, reproducibility challenges, dissociation artifacts, computational ambiguity, and privacy concerns that constrain immediate clinical implementation. Together, these advances position single-cell profiling as a mechanistic discovery platform with substantial translational promise, contingent on standardization, validation across diverse cohorts, and integration with functional perturbation approaches.<\/jats:p>","DOI":"10.1007\/s12016-026-09211-0","type":"journal-article","created":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:08:07Z","timestamp":1792022887000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Single-cell Transcriptomics in Autoimmune Diseases: Mechanistic Insights, Cross-disease Convergence, and Translational Challenges in Rheumatoid Arthritis, Systemic Lupus Erythematosus, Type 1 Diabetes, and Multiple Sclerosis"],"prefix":"10.1007","volume":"69","author":[{"given":"Thanh-Hong","family":"Nguyen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tuan-Dinh","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oanh-Thi","family":"Hoang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thuy-Thu T.","family":"Can","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minh-Huyen T.","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mai-Hoang","family":"Tran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hieu-Chi","family":"Chu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dinh-Van","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,10,14]]},"reference":[{"issue":"4","key":"9211_CR1","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1111\/joim.12395","volume":"278","author":"L Wang","year":"2015","unstructured":"Wang L, Wang F, Gershwin ME (2015) Human autoimmune diseases: a comprehensive update. J Intern Med 278(4):369\u2013395. https:\/\/doi.org\/10.1111\/joim.12395","journal-title":"J Intern Med"},{"issue":"6","key":"9211_CR2","doi-asserted-by":"publisher","first-page":"2228","DOI":"10.1172\/JCI78088","volume":"125","author":"MD Rosenblum","year":"2015","unstructured":"Rosenblum MD, Remedios KA, Abbas AK (2015) Mechanisms of human autoimmunity. J Clin Invest 125(6):2228\u20132233. https:\/\/doi.org\/10.1172\/JCI78088","journal-title":"J Clin Invest"},{"issue":"1","key":"9211_CR3","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1038\/s41392-024-01952-8","volume":"9","author":"Y Song","year":"2024","unstructured":"Song Y, Li J, Wu Y (2024) Evolving understanding of autoimmune mechanisms and new therapeutic strategies of autoimmune disorders. Signal Transduct Target Ther 9(1):263. https:\/\/doi.org\/10.1038\/s41392-024-01952-8","journal-title":"Signal Transduct Target Ther"},{"key":"9211_CR4","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.857269","volume":"13","author":"Y Nagafuchi","year":"2022","unstructured":"Nagafuchi Y, Yanaoka H, Fujio K (2022) Lessons from transcriptome analysis of autoimmune diseases. Front Immunol 13:857269. https:\/\/doi.org\/10.3389\/fimmu.2022.857269","journal-title":"Front Immunol"},{"key":"9211_CR5","doi-asserted-by":"publisher","unstructured":"Nadukkandy AS, Kalaiselvan S, Lin L, Luo Y \u2018Clinical application of single\u2010cell RNA sequencing in disease and therapy Clin Transl Med 15:112025. https:\/\/doi.org\/10.1002\/ctm2.70512.","DOI":"10.1002\/ctm2.70512"},{"issue":"6","key":"9211_CR6","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1038\/s41573-023-00688-4","volume":"22","author":"B Van de Sande","year":"2023","unstructured":"Van de Sande B et al (2023) Applications of single-cell RNA sequencing in drug discovery and development. Nat Rev Drug Discov 22(6):496\u2013520. https:\/\/doi.org\/10.1038\/s41573-023-00688-4","journal-title":"Nat Rev Drug Discov"},{"issue":"8","key":"9211_CR7","doi-asserted-by":"publisher","first-page":"1295","DOI":"10.1038\/s41591-020-0939-8","volume":"26","author":"S Alivernini","year":"2020","unstructured":"Alivernini S et al (2020) Distinct synovial tissue macrophage subsets regulate inflammation and remission in rheumatoid arthritis. Nat Med 26(8):1295\u20131306. https:\/\/doi.org\/10.1038\/s41591-020-0939-8","journal-title":"Nat Med"},{"key":"9211_CR8","doi-asserted-by":"publisher","first-page":"7752024","DOI":"10.1126\/scitranslmed.adl1666","volume":"16","author":"P Danaher","year":"2024","unstructured":"Danaher P et al (2024) Childhood-onset lupus nephritis is characterized by complex interactions between kidney stroma and infiltrating immune cells Sci Transl Med 16:7752024. https:\/\/doi.org\/10.1126\/scitranslmed.adl1666.","journal-title":"Sci Transl Med"},{"key":"9211_CR9","doi-asserted-by":"publisher","unstructured":"A. V. Abdullatypov et al (2025) Single-cell RNA sequencing in studies of type 1 diabetes mellitus: modern state-of-the-art and technical peculiarities. Front Endocrinol 16. https:\/\/doi.org\/10.3389\/fendo.2025.1663728.","DOI":"10.3389\/fendo.2025.1663728"},{"issue":"12","key":"9211_CR10","doi-asserted-by":"publisher","first-page":"2989","DOI":"10.1016\/j.immuni.2025.10.003","volume":"58","author":"R Feng","year":"2025","unstructured":"Feng R et al (2025) Single-cell spatial transcriptomic profiling defines a pathogenic inflammatory niche in chronic active multiple sclerosis lesions. Immunity 58(12):2989-3005.e10. https:\/\/doi.org\/10.1016\/j.immuni.2025.10.003","journal-title":"Immunity"},{"issue":"1","key":"9211_CR11","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1186\/s41232-025-00369-2","volume":"45","author":"AT Miyamoto","year":"2025","unstructured":"Miyamoto AT, Shimagami H, Kumanogoh A, Nishide M (2025) Spatial transcriptomics in autoimmune rheumatic disease: potential clinical applications and perspectives. Inflamm. Regen. 45(1):6\u20136. https:\/\/doi.org\/10.1186\/s41232-025-00369-2","journal-title":"Inflamm. Regen."},{"key":"9211_CR12","doi-asserted-by":"publisher","unstructured":"Xu H et al (2025) Integrative Single-Cell RNA-Seq and ATAC-Seq Analysis of Peripheral Mononuclear Cells in Patients With Ankylosing Spondylitis Front Immunol 12. https:\/\/doi.org\/10.3389\/fimmu.2021.760381.","DOI":"10.3389\/fimmu.2021.760381"},{"key":"9211_CR13","doi-asserted-by":"publisher","first-page":"1580540","DOI":"10.3389\/fimmu.2025.1580540","volume":"16","author":"J Zhang","year":"2025","unstructured":"Zhang J et al (2025) Multi-omics integration identifies NK cell-mediated cytotoxicity as a therapeutic target in systemic lupus erythematosus. Front. Immunol. 16:1580540. https:\/\/doi.org\/10.3389\/fimmu.2025.1580540","journal-title":"Front. Immunol."},{"issue":"9","key":"9211_CR14","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1038\/nmeth.4380","volume":"14","author":"M Stoeckius","year":"2017","unstructured":"Stoeckius M et al (2017) Simultaneous epitope and transcriptome measurement in single cells. Nat Methods 14(9):865\u2013868. https:\/\/doi.org\/10.1038\/nmeth.4380","journal-title":"Nat Methods"},{"issue":"8","key":"9211_CR15","doi-asserted-by":"publisher","first-page":"494","DOI":"10.1038\/s41576-023-00580-2","volume":"24","author":"K Vandereyken","year":"2023","unstructured":"Vandereyken K, Sifrim A, Thienpont B, Voet T (2023) Methods and applications for single-cell and spatial multi-omics. Nat Rev Genet 24(8):494\u2013515. https:\/\/doi.org\/10.1038\/s41576-023-00580-2","journal-title":"Nat Rev Genet"},{"key":"9211_CR16","doi-asserted-by":"publisher","unstructured":"Figueiredo ML (2024) Applications of single-cell RNA sequencing in rheumatoid arthritis. Front. Immunol 15. https:\/\/doi.org\/10.3389\/fimmu.2024.1491318.","DOI":"10.3389\/fimmu.2024.1491318"},{"key":"9211_CR17","doi-asserted-by":"publisher","first-page":"108807","DOI":"10.1016\/j.pharmthera.2025.108807","volume":"267","author":"J Huang","year":"2025","unstructured":"Huang J et al (2025) Single-cell RNA sequencing in autoimmune diseases: new insights and challenges. Pharmacol Ther 267:108807\u2013108807. https:\/\/doi.org\/10.1016\/j.pharmthera.2025.108807","journal-title":"Pharmacol Ther"},{"key":"9211_CR18","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2021.822804","volume":"8","author":"T Kuret","year":"2022","unstructured":"Kuret T, Sodin-\u0160emrl S, Lesko\u0161ek B, Ferk P (2022) Single cell RNA sequencing in autoimmune inflammatory rheumatic diseases: current applications, challenges and a step toward precision medicine. Front Med 8:822804. https:\/\/doi.org\/10.3389\/fmed.2021.822804","journal-title":"Front Med"},{"issue":"1","key":"9211_CR19","doi-asserted-by":"publisher","first-page":"789","DOI":"10.1038\/s41467-018-02892-y","volume":"9","author":"F Mizoguchi","year":"2018","unstructured":"Mizoguchi F et al (2018) Functionally distinct disease-associated fibroblast subsets in rheumatoid arthritis. Nat Commun 9(1):789\u2013789. https:\/\/doi.org\/10.1038\/s41467-018-02892-y","journal-title":"Nat Commun"},{"issue":"7","key":"9211_CR20","doi-asserted-by":"publisher","first-page":"928","DOI":"10.1038\/s41590-019-0378-1","volume":"20","author":"F Zhang","year":"2019","unstructured":"Zhang F et al (2019) Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry. Nat. Immunol. 20(7):928\u2013942. https:\/\/doi.org\/10.1038\/s41590-019-0378-1","journal-title":"Nat. Immunol."},{"issue":"7987","key":"9211_CR21","doi-asserted-by":"publisher","first-page":"616","DOI":"10.1038\/s41586-023-06708-y","volume":"623","author":"F Zhang","year":"2023","unstructured":"Zhang F et al (2023) Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes Nature 623(7987):616\u2013624. https:\/\/doi.org\/10.1038\/s41586-023-06708-y.","journal-title":"Nature"},{"issue":"16","key":"9211_CR22","doi-asserted-by":"publisher","DOI":"10.1172\/jci.insight.178499","volume":"9","author":"M Binvignat","year":"2024","unstructured":"Binvignat M et al (2024) Single-cell RNA-Seq analysis reveals cell subsets and gene signatures associated with rheumatoid arthritis disease activity. JCI Insight 9(16):e178499. https:\/\/doi.org\/10.1172\/jci.insight.178499","journal-title":"JCI Insight"},{"issue":"3","key":"9211_CR23","doi-asserted-by":"publisher","first-page":"356","DOI":"10.1002\/art.42726","volume":"76","author":"D Weisenfeld","year":"2024","unstructured":"Weisenfeld D et al (2024) Associations between rheumatoid arthritis clinical factors and synovial cell types and states. Arthritis Rheumatol 76(3):356\u2013362. https:\/\/doi.org\/10.1002\/art.42726","journal-title":"Arthritis Rheumatol"},{"issue":"7760","key":"9211_CR24","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1038\/s41586-019-1263-7","volume":"570","author":"AP Croft","year":"2019","unstructured":"Croft AP et al (2019) Distinct fibroblast subsets drive inflammation and damage in arthritis. Nature 570(7760):246\u2013251. https:\/\/doi.org\/10.1038\/s41586-019-1263-7","journal-title":"Nature"},{"issue":"7811","key":"9211_CR25","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1038\/s41586-020-2222-z","volume":"582","author":"K Wei","year":"2020","unstructured":"Wei K et al (2020) Notch signalling drives synovial fibroblast identity and arthritis pathology. Nature 582(7811):259\u2013264. https:\/\/doi.org\/10.1038\/s41586-020-2222-z","journal-title":"Nature"},{"issue":"1","key":"9211_CR26","doi-asserted-by":"publisher","first-page":"791","DOI":"10.1038\/s41467-017-02659-x","volume":"9","author":"W Stephenson","year":"2018","unstructured":"Stephenson W et al (2018) Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low-cost microfluidic instrumentation. Nat. Commun. 9(1):791\u2013791. https:\/\/doi.org\/10.1038\/s41467-017-02659-x","journal-title":"Nat. Commun."},{"issue":"1","key":"9211_CR27","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1038\/s42003-022-03050-3","volume":"5","author":"S Vickovic","year":"2022","unstructured":"Vickovic S et al (2022) Three-dimensional spatial transcriptomics uncovers cell type localizations in the human rheumatoid arthritis synovium. Commun. Biol. 5(1):129. https:\/\/doi.org\/10.1038\/s42003-022-03050-3","journal-title":"Commun. Biol."},{"issue":"3","key":"9211_CR28","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1016\/j.cell.2016.03.008","volume":"165","author":"R Banchereau","year":"2016","unstructured":"Banchereau R et al (2016) Personalized Immunomonitoring Uncovers Molecular Networks That Stratify Lupus Patients. Cell 165(3):551\u2013565. https:\/\/doi.org\/10.1016\/j.cell.2016.03.008","journal-title":"Cell"},{"issue":"7","key":"9211_CR29","doi-asserted-by":"publisher","first-page":"902","DOI":"10.1038\/s41590-019-0398-x","volume":"20","author":"A Arazi","year":"2019","unstructured":"Arazi A et al (2019) The immune cell landscape in kidneys of patients with lupus nephritis. Nat. Immunol. 20(7):902\u2013914. https:\/\/doi.org\/10.1038\/s41590-019-0398-x","journal-title":"Nat. Immunol."},{"issue":"1","key":"9211_CR30","doi-asserted-by":"publisher","DOI":"10.1136\/lupus-2019-000329","volume":"6","author":"E Der","year":"2019","unstructured":"Der E, Suryawanshi H, Buyon J, Tuschl T, Putterman C (2019) Single-cell RNA sequencing for the study of lupus nephritis. Lupus Sci. Med. 6(1):e000329. https:\/\/doi.org\/10.1136\/lupus-2019-000329","journal-title":"Lupus Sci. Med."},{"issue":"6589","key":"9211_CR31","doi-asserted-by":"publisher","DOI":"10.1126\/science.abf1970","volume":"376","author":"RK Perez","year":"2022","unstructured":"Perez RK et al (2022) Single-cell RNA-seq reveals cell type\u2013specific molecular and genetic associations to lupus. Science 376(6589):eabf1970. https:\/\/doi.org\/10.1126\/science.abf1970","journal-title":"Science"},{"issue":"4","key":"9211_CR32","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1016\/j.kint.2022.05.033","volume":"102","author":"SV Parikh","year":"2022","unstructured":"Parikh SV et al (2022) Molecular profiling of kidney compartments from serial biopsies differentiate treatment responders from non-responders in lupus nephritis. Kidney Int. 102(4):845\u2013865. https:\/\/doi.org\/10.1016\/j.kint.2022.05.033","journal-title":"Kidney Int."},{"issue":"7","key":"9211_CR33","doi-asserted-by":"publisher","first-page":"1197","DOI":"10.1093\/ndt\/gfy125","volume":"34","author":"JM Mejia-Vilet","year":"2019","unstructured":"Mejia-Vilet JM et al (2019) Immune gene expression in kidney biopsies of lupus nephritis patients at diagnosis and at renal flare. Nephrol. Dial. Transplant. 34(7):1197\u20131206. https:\/\/doi.org\/10.1093\/ndt\/gfy125","journal-title":"Nephrol. Dial. Transplant."},{"issue":"2","key":"9211_CR34","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1038\/s42255-022-00531-x","volume":"4","author":"M Fasolino","year":"2022","unstructured":"Fasolino M et al (2022) Single-cell multi-omics analysis of human pancreatic islets reveals novel cellular states in type 1 diabetes. Nat Metab 4(2):284\u2013299. https:\/\/doi.org\/10.1038\/s42255-022-00531-x","journal-title":"Nat Metab"},{"issue":"10","key":"9211_CR35","doi-asserted-by":"publisher","first-page":"2246","DOI":"10.1007\/s00125-024-06214-4","volume":"67","author":"CM Grenko","year":"2024","unstructured":"Grenko CM et al (2024) Single-cell transcriptomic profiling of human pancreatic islets reveals genes responsive to glucose exposure over 24 h. Diabetologia 67(10):2246\u20132259. https:\/\/doi.org\/10.1007\/s00125-024-06214-4","journal-title":"Diabetologia"},{"issue":"1","key":"9211_CR36","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1186\/s13073-023-01179-2","volume":"15","author":"RB Kang","year":"2023","unstructured":"Kang RB et al (2023) Single-nucleus RNA sequencing of human pancreatic islets identifies novel gene sets and distinguishes \u03b2-cell subpopulations with dynamic transcriptome profiles. Genome Med. 15(1):30\u201330. https:\/\/doi.org\/10.1186\/s13073-023-01179-2","journal-title":"Genome Med."},{"issue":"1","key":"9211_CR37","doi-asserted-by":"publisher","first-page":"4621","DOI":"10.1038\/s41467-025-59626-0","volume":"16","author":"GJ Golden","year":"2025","unstructured":"Golden GJ et al (2025) Immune perturbations in human pancreas lymphatic tissues prior to and after type 1 diabetes onset. Nat. Commun. 16(1):4621. https:\/\/doi.org\/10.1038\/s41467-025-59626-0","journal-title":"Nat. Commun."},{"issue":"7895","key":"9211_CR38","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1038\/s41586-021-04248-x","volume":"602","author":"SV Gearty","year":"2022","unstructured":"Gearty SV et al (2022) An autoimmune stem-like CD8 T cell population drives type 1 diabetes. Nature 602(7895):156\u2013161. https:\/\/doi.org\/10.1038\/s41586-021-04248-x","journal-title":"Nature"},{"issue":"8","key":"9211_CR39","doi-asserted-by":"publisher","first-page":"1990","DOI":"10.4049\/jimmunol.2100362","volume":"207","author":"AE Ciecko","year":"2021","unstructured":"Ciecko AE et al (2021) Self-renewing islet TCF1+ CD8 T cells undergo IL-27\u2013controlled differentiation to become TCF1\u2212 terminal effectors during the progression of type 1 diabetes. J Immunol 207(8):1990\u20132004. https:\/\/doi.org\/10.4049\/jimmunol.2100362","journal-title":"J Immunol"},{"issue":"8","key":"9211_CR40","doi-asserted-by":"publisher","first-page":"116065","DOI":"10.1016\/j.celrep.2025.116065","volume":"44","author":"R D\u2019Oliveira Albanus","year":"2025","unstructured":"D\u2019Oliveira Albanus R et al (2025) Integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D-associated genes and regulatory signals Cell Rep 44(8):116065. https:\/\/doi.org\/10.1016\/j.celrep.2025.116065.","journal-title":"Cell Rep"},{"issue":"4","key":"9211_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.celrep.2025.115425","volume":"44","author":"CA Nicholas","year":"2025","unstructured":"Nicholas CA et al (2025) Activated polyreactive B cells are clonally expanded in autoantibody positive and patients with recent-onset type 1 diabetes. Cell Rep. 44(4):115425. https:\/\/doi.org\/10.1016\/j.celrep.2025.115425","journal-title":"Cell Rep."},{"issue":"1","key":"9211_CR42","doi-asserted-by":"publisher","first-page":"323","DOI":"10.4049\/jimmunol.1700172","volume":"199","author":"K Cerosaletti","year":"2017","unstructured":"Cerosaletti K et al (2017) Single-Cell RNA Sequencing Reveals Expanded Clones of Islet Antigen-Reactive CD4+ T Cells in Peripheral Blood of Subjects with Type 1 Diabetes. J. Immunol. 199(1):323\u2013335. https:\/\/doi.org\/10.4049\/jimmunol.1700172","journal-title":"J. Immunol."},{"issue":"12","key":"9211_CR43","doi-asserted-by":"publisher","first-page":"778","DOI":"10.1007\/s00415-025-13505-2","volume":"272","author":"X Yang","year":"2025","unstructured":"Yang X et al (2025) Single-cell RNA sequencing of cerebrospinal fluid immune cells in relapsing\u2013remitting multiple sclerosis: insights into cellular composition and immune dynamics. J Neurol 272(12):778\u2013778. https:\/\/doi.org\/10.1007\/s00415-025-13505-2","journal-title":"J Neurol"},{"issue":"1","key":"9211_CR44","doi-asserted-by":"publisher","first-page":"7670","DOI":"10.1038\/s41467-022-35357-4","volume":"13","author":"P Kosa","year":"2022","unstructured":"Kosa P et al (2022) Molecular models of multiple sclerosis severity identify heterogeneity of pathogenic mechanisms. Nat. Commun. 13(1):7670. https:\/\/doi.org\/10.1038\/s41467-022-35357-4","journal-title":"Nat. Commun."},{"issue":"7878","key":"9211_CR45","doi-asserted-by":"publisher","first-page":"709","DOI":"10.1038\/s41586-021-03892-7","volume":"597","author":"M Absinta","year":"2021","unstructured":"Absinta M et al (2021) A lymphocyte\u2013microglia\u2013astrocyte axis in chronic active multiple sclerosis. Nature 597(7878):709\u2013714. https:\/\/doi.org\/10.1038\/s41586-021-03892-7","journal-title":"Nature"},{"issue":"7745","key":"9211_CR46","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1038\/s41586-019-0903-2","volume":"566","author":"S J\u00e4kel","year":"2019","unstructured":"J\u00e4kel S et al (2019) Altered human oligodendrocyte heterogeneity in multiple sclerosis. Nature 566(7745):543\u2013547. https:\/\/doi.org\/10.1038\/s41586-019-0903-2","journal-title":"Nature"},{"issue":"7772","key":"9211_CR47","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1038\/s41586-019-1404-z","volume":"573","author":"L Schirmer","year":"2019","unstructured":"Schirmer L et al (2019) Neuronal vulnerability and multilineage diversity in multiple sclerosis. Nature 573(7772):75\u201382. https:\/\/doi.org\/10.1038\/s41586-019-1404-z","journal-title":"Nature"},{"issue":"1","key":"9211_CR48","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1038\/s41467-019-14118-w","volume":"11","author":"D Schafflick","year":"2020","unstructured":"Schafflick D et al (2020) Integrated single cell analysis of blood and cerebrospinal fluid leukocytes in multiple sclerosis. Nat. Commun. 11(1):247\u2013247. https:\/\/doi.org\/10.1038\/s41467-019-14118-w","journal-title":"Nat. Commun."},{"issue":"37","key":"9211_CR49","doi-asserted-by":"publisher","first-page":"22932","DOI":"10.1073\/pnas.2008523117","volume":"117","author":"A Ramesh","year":"2020","unstructured":"Ramesh A et al (2020) A pathogenic and clonally expanded B cell transcriptome in active multiple sclerosis. Proc. Natl. Acad. Sci. 117(37):22932\u201322943. https:\/\/doi.org\/10.1073\/pnas.2008523117","journal-title":"Proc. Natl. Acad. Sci."},{"key":"9211_CR50","doi-asserted-by":"publisher","unstructured":"Jacobs BM et al (2025) Single-cell analysis of cerebrospinal fluid reveals common features of neuroinflammation. Cell Rep Med 6(1). https:\/\/doi.org\/10.1016\/j.xcrm.2024.101733","DOI":"10.1016\/j.xcrm.2024.101733"},{"issue":"7","key":"9211_CR51","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1016\/j.medj.2022.05.002","volume":"3","author":"I Korsunsky","year":"2022","unstructured":"Korsunsky I et al (2022) Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases. Med 3(7):481-518.e14. https:\/\/doi.org\/10.1016\/j.medj.2022.05.002","journal-title":"Med"},{"issue":"1","key":"9211_CR52","doi-asserted-by":"publisher","first-page":"114515","DOI":"10.1016\/j.isci.2025.114515","volume":"29","author":"L Zhu","year":"2026","unstructured":"Zhu L et al (2026) Single-cell landscape of immune cells in multiple autoimmune diseases. iScience 29(1):114515. https:\/\/doi.org\/10.1016\/j.isci.2025.114515.","journal-title":"iScience"},{"key":"9211_CR53","doi-asserted-by":"publisher","unstructured":"Slovin S et al (2021) Single-cell RNA sequencing analysis: a step-by-step overview. In RNA Bioinformatics (E. Picardi, Ed.), New York, NY: Springer US. pp 343\u2013365. https:\/\/doi.org\/10.1007\/978-1-0716-1307-8_19.","DOI":"10.1007\/978-1-0716-1307-8_19"},{"key":"9211_CR54","doi-asserted-by":"publisher","unstructured":"Su M et al (2022) Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications. Mil Med Res 9(1). https:\/\/doi.org\/10.1186\/s40779-022-00434-8.","DOI":"10.1186\/s40779-022-00434-8"},{"issue":"4","key":"9211_CR55","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1016\/j.molcel.2017.01.023","volume":"65","author":"C Ziegenhain","year":"2017","unstructured":"Ziegenhain C et al (2017) Comparative Analysis of Single-Cell RNA Sequencing Methods. Mol. Cell 65(4):631-643.e4. https:\/\/doi.org\/10.1016\/j.molcel.2017.01.023","journal-title":"Mol. Cell"},{"issue":"8","key":"9211_CR56","doi-asserted-by":"publisher","first-page":"2305449","DOI":"10.1002\/advs.202305449","volume":"11","author":"F Ye","year":"2024","unstructured":"Ye F, Wang J, Li J, Mei Y, Guo G (2024) Mapping Cell Atlases at the Single-Cell Level. Adv. Sci. 11(8):2305449. https:\/\/doi.org\/10.1002\/advs.202305449","journal-title":"Adv. Sci."},{"issue":"8","key":"9211_CR57","doi-asserted-by":"publisher","first-page":"1427","DOI":"10.1042\/BCJ20190341","volume":"477","author":"A Wilbrey-Clark","year":"2020","unstructured":"Wilbrey-Clark A, Roberts K, Teichmann SA (2020) Cell Atlas technologies and insights into tissue architecture. Biochem. J. 477(8):1427\u20131442. https:\/\/doi.org\/10.1042\/BCJ20190341","journal-title":"Biochem. J."},{"issue":"10","key":"9211_CR58","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1038\/s41576-020-0236-x","volume":"21","author":"GA Logsdon","year":"2020","unstructured":"Logsdon GA, Vollger MR, Eichler EE (2020) Long-read human genome sequencing and its applications. Nat Rev Genet 21(10):597\u2013614. https:\/\/doi.org\/10.1038\/s41576-020-0236-x","journal-title":"Nat Rev Genet"},{"issue":"1","key":"9211_CR59","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1186\/s40246-023-00522-3","volume":"17","author":"JB Oehler","year":"2023","unstructured":"Oehler JB, Wright H, Stark Z, Mallett AJ, Schmitz U (2023) The application of long-read sequencing in clinical settings. Hum. Genomics 17(1):73. https:\/\/doi.org\/10.1186\/s40246-023-00522-3","journal-title":"Hum. Genomics"},{"issue":"2","key":"9211_CR60","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1016\/j.gpb.2020.02.005","volume":"19","author":"X Wang","year":"2021","unstructured":"Wang X, He Y, Zhang Q, Ren X, Zhang Z (2021) Direct Comparative Analyses of 10X Genomics Chromium and Smart-Seq2. Genomics Proteomics Bioinformatics 19(2):253\u2013266. https:\/\/doi.org\/10.1016\/j.gpb.2020.02.005","journal-title":"Genomics Proteomics Bioinformatics"},{"issue":"2","key":"9211_CR61","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1016\/j.cels.2018.01.014","volume":"6","author":"E Torre","year":"2018","unstructured":"Torre E et al (2018) Rare Cell Detection by Single-Cell RNA Sequencing as Guided by Single-Molecule RNA FISH. Cell Syst. 6(2):171-179.e5. https:\/\/doi.org\/10.1016\/j.cels.2018.01.014","journal-title":"Cell Syst."},{"issue":"1","key":"9211_CR62","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1186\/s13059-019-1739-7","volume":"20","author":"R Wegmann","year":"2019","unstructured":"Wegmann R et al (2019) CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data. Genome Biol. 20(1):142. https:\/\/doi.org\/10.1186\/s13059-019-1739-7","journal-title":"Genome Biol."},{"issue":"1","key":"9211_CR63","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1186\/s13059-020-02048-6","volume":"21","author":"E Denisenko","year":"2020","unstructured":"Denisenko E et al (2020) Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows. Genome Biol. 21(1):130. https:\/\/doi.org\/10.1186\/s13059-020-02048-6","journal-title":"Genome Biol."},{"issue":"7","key":"9211_CR64","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1038\/s41590-019-0386-1","volume":"20","author":"E Der","year":"2019","unstructured":"Der E et al (2019) Tubular cell and keratinocyte single-cell transcriptomics applied to lupus nephritis reveal type I IFN and fibrosis relevant pathways. Nat. Immunol. 20(7):915\u2013927. https:\/\/doi.org\/10.1038\/s41590-019-0386-1","journal-title":"Nat. Immunol."},{"issue":"1","key":"9211_CR65","doi-asserted-by":"publisher","first-page":"3274","DOI":"10.1038\/s41467-020-16905-2","volume":"11","author":"F Song","year":"2020","unstructured":"Song F, Chan GMA, Wei Y (2020) Flexible experimental designs for valid single-cell RNA-sequencing experiments allowing batch effects correction. Nat. Commun. 11(1):3274. https:\/\/doi.org\/10.1038\/s41467-020-16905-2","journal-title":"Nat. Commun."},{"issue":"1","key":"9211_CR66","doi-asserted-by":"publisher","first-page":"39921","DOI":"10.1038\/srep39921","volume":"7","author":"P-Y Tung","year":"2017","unstructured":"Tung P-Y et al (2017) Batch effects and the effective design of single-cell gene expression studies. Sci. Rep. 7(1):39921. https:\/\/doi.org\/10.1038\/srep39921","journal-title":"Sci. Rep."},{"issue":"1","key":"9211_CR67","doi-asserted-by":"publisher","first-page":"20817","DOI":"10.1038\/s41598-022-24371-7","volume":"12","author":"FS Nettersheim","year":"2022","unstructured":"Nettersheim FS et al (2022) Titration of 124 antibodies using CITE-Seq on human PBMCs. Sci. Rep. 12(1):20817. https:\/\/doi.org\/10.1038\/s41598-022-24371-7","journal-title":"Sci. Rep."},{"key":"9211_CR68","doi-asserted-by":"publisher","unstructured":"Nicholas CA, Smith MJ (2023) Application of single-cell RNA sequencing methods to develop B cell targeted treatments for autoimmunity. Front. Immunol 14. https:\/\/doi.org\/10.3389\/fimmu.2023.1103690.","DOI":"10.3389\/fimmu.2023.1103690"},{"issue":"13","key":"9211_CR69","doi-asserted-by":"publisher","first-page":"3573","DOI":"10.1016\/j.cell.2021.04.048","volume":"184","author":"Y Hao","year":"2021","unstructured":"Hao Y et al (2021) Integrated analysis of multimodal single-cell data. Cell 184(13):3573-3587.e29. https:\/\/doi.org\/10.1016\/j.cell.2021.04.048","journal-title":"Cell"},{"issue":"3","key":"9211_CR70","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1038\/s41588-021-00779-1","volume":"53","author":"CJ Frangieh","year":"2021","unstructured":"Frangieh CJ et al (2021) Multimodal pooled Perturb-CITE-seq screens in patient models define mechanisms of cancer immune evasion. Nat Genet 53(3):332\u2013341. https:\/\/doi.org\/10.1038\/s41588-021-00779-1","journal-title":"Nat Genet"},{"issue":"8","key":"9211_CR71","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1038\/s41592-021-01222-3","volume":"18","author":"B Hwang","year":"2021","unstructured":"Hwang B et al (2021) SCITO-seq: single-cell combinatorial indexed cytometry sequencing. Nat. Methods 18(8):903\u2013911. https:\/\/doi.org\/10.1038\/s41592-021-01222-3","journal-title":"Nat. Methods"},{"key":"9211_CR72","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2021.751701","volume":"12","author":"SJ Hanna","year":"2021","unstructured":"Hanna SJ, Tatovic D, Thayer TC, Dayan CM (2021) Insights From Single Cell RNA Sequencing Into the Immunology of Type 1 Diabetes- Cell Phenotypes and Antigen Specificity. Front. Immunol. 12:751701. https:\/\/doi.org\/10.3389\/fimmu.2021.751701","journal-title":"Front. Immunol."},{"key":"9211_CR73","doi-asserted-by":"publisher","unstructured":"K. Quan, H. Wang, P. Su, Y. Xu, and X. Yao (2025) ecoding B cells in autoimmune diseases through ScRNA + BCR-Seq: current knowledge and future directions. Cells 14(7). https:\/\/doi.org\/10.3390\/cells14070539.","DOI":"10.3390\/cells14070539"},{"key":"9211_CR74","doi-asserted-by":"publisher","unstructured":"Ramos-Vicente D, Monterosso P, de F\u00e0bregues O, Roch G, Vila M, Bov\u00e9 J (2025) Single-cell transcriptomics for immune profiling of cerebrospinal fluid in neurological diseases. Front Immunol 16. https:\/\/doi.org\/10.3389\/fimmu.2025.1599303.","DOI":"10.3389\/fimmu.2025.1599303"},{"issue":"12","key":"9211_CR75","doi-asserted-by":"publisher","first-page":"1156","DOI":"10.1038\/nbt.4282","volume":"36","author":"S-Q Zhang","year":"2018","unstructured":"Zhang S-Q et al (2018) High-throughput determination of the antigen specificities of T cell receptors in single cells. Nat. Biotechnol. 36(12):1156\u20131159. https:\/\/doi.org\/10.1038\/nbt.4282","journal-title":"Nat. Biotechnol."},{"issue":"7","key":"9211_CR76","doi-asserted-by":"publisher","first-page":"1636","DOI":"10.1016\/j.cell.2019.11.003","volume":"179","author":"I Setliff","year":"2019","unstructured":"Setliff I et al (2019) High-throughput mapping of B cell receptor sequences to antigen specificity. Cell 179(7):1636-1646.e15. https:\/\/doi.org\/10.1016\/j.cell.2019.11.003","journal-title":"Cell"},{"key":"9211_CR77","doi-asserted-by":"publisher","unstructured":"G. Molla Desta and A. G. Birhanu, \u2018Advancements in single-cell RNA sequencing and spatial transcriptomics: transforming biomedical research\u2019, Acta Biochim. Pol., vol. Volume 72-2025, 2025, [Online]. Available: https:\/\/www.frontierspartnerships.org\/journals\/acta-biochimica-polonica\/articles\/https:\/\/doi.org\/10.3389\/abp.2025.13922","DOI":"10.3389\/abp.2025.13922"},{"key":"9211_CR78","doi-asserted-by":"publisher","unstructured":"Regev A et al (2017) The human cell Atlas. eLife 6:e27041. https:\/\/doi.org\/10.7554\/eLife.27041.","DOI":"10.7554\/eLife.27041"},{"key":"9211_CR79","doi-asserted-by":"publisher","first-page":"6594","DOI":"10.1126\/science.abl5197","volume":"376","author":"C Dom\u00ednguez","year":"2022","unstructured":"Dom\u00ednguez C, Conde et al (2022) Cross-tissue immune cell analysis reveals tissue-specific features in humans Science 376:6594. https:\/\/doi.org\/10.1126\/science.abl5197.","journal-title":"Science"},{"issue":"1","key":"9211_CR80","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1038\/s41592-024-02532-y","volume":"22","author":"K Hrovatin","year":"2025","unstructured":"Hrovatin K et al (2025) Considerations for building and using integrated single-cell atlases. Nat. Methods 22(1):41\u201357. https:\/\/doi.org\/10.1038\/s41592-024-02532-y","journal-title":"Nat. Methods"},{"issue":"6","key":"9211_CR81","doi-asserted-by":"publisher","first-page":"429","DOI":"10.1038\/nri2094","volume":"7","author":"IB McInnes","year":"2007","unstructured":"McInnes IB, Schett G (2007) Cytokines in the pathogenesis of rheumatoid arthritis. Nat Rev Immunol 7(6):429\u2013442. https:\/\/doi.org\/10.1038\/nri2094","journal-title":"Nat Rev Immunol"},{"key":"9211_CR82","doi-asserted-by":"publisher","DOI":"10.1016\/j.jaut.2022.102919","volume":"133","author":"L Zeng","year":"2022","unstructured":"Zeng L et al (2022) Research progress of single-cell transcriptome sequencing in autoimmune diseases and autoinflammatory disease: A review. J. Autoimmun. 133:102919. https:\/\/doi.org\/10.1016\/j.jaut.2022.102919","journal-title":"J. Autoimmun."},{"issue":"3","key":"9211_CR83","doi-asserted-by":"publisher","DOI":"10.1016\/j.celrep.2026.117073","volume":"45","author":"ML Amaral","year":"2026","unstructured":"Amaral ML et al (2026) Single-cell epigenomics uncovers heterochromatin instability and transcription factor dysfunction during mouse brain aging. Cell Rep. 45(3):117073. https:\/\/doi.org\/10.1016\/j.celrep.2026.117073","journal-title":"Cell Rep."},{"issue":"2","key":"9211_CR84","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.abd7600","volume":"7","author":"F Szymczak","year":"2021","unstructured":"Szymczak F, Colli ML, Mamula MJ, Evans-Molina C, Eizirik DL (2021) Gene expression signatures of target tissues in type 1 diabetes, lupus erythematosus, multiple sclerosis, and rheumatoid arthritis. Sci Adv 7(2):eabd7600. https:\/\/doi.org\/10.1126\/sciadv.abd7600","journal-title":"Sci Adv"},{"issue":"2","key":"9211_CR85","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1038\/s41576-020-00292-x","volume":"22","author":"E Armingol","year":"2021","unstructured":"Armingol E, Officer A, Harismendy O, Lewis NE (2021) Deciphering cell-cell interactions and communication from gene expression. Nat Rev Genet 22(2):71\u201388. https:\/\/doi.org\/10.1038\/s41576-020-00292-x","journal-title":"Nat Rev Genet"},{"issue":"10","key":"9211_CR86","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1038\/s41576-021-00370-8","volume":"22","author":"SK Longo","year":"2021","unstructured":"Longo SK, Guo MG, Ji AL, Khavari PA (2021) Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics. Nat. Rev. Genet. 22(10):627\u2013644. https:\/\/doi.org\/10.1038\/s41576-021-00370-8","journal-title":"Nat. Rev. Genet."},{"issue":"6","key":"9211_CR87","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1038\/s41584-025-01253-6","volume":"21","author":"L Marshall","year":"2025","unstructured":"Marshall L, Raychaudhuri S, Viatte S (2025) Understanding rheumatic disease through continuous cell state analysis. Nat Rev Rheumatol 21(6):323\u2013335. https:\/\/doi.org\/10.1038\/s41584-025-01253-6","journal-title":"Nat Rev Rheumatol"},{"key":"9211_CR88","doi-asserted-by":"publisher","DOI":"10.1016\/j.intimp.2026.116530","volume":"179","author":"A Usmani","year":"2026","unstructured":"Usmani A, Siddiqui MA, Kumar D, Gowri S, Webster TJ, Faiyazuddin Md (2026) Next 5 years in autoimmunity: predictive diagnostics, immune signatures, and personalized immune therapy. Int Immunopharmacol 179:116530. https:\/\/doi.org\/10.1016\/j.intimp.2026.116530","journal-title":"Int Immunopharmacol"},{"issue":"4","key":"9211_CR89","doi-asserted-by":"publisher","first-page":"932","DOI":"10.1038\/s43587-026-01099-x","volume":"6","author":"M Sopena-Rios","year":"2026","unstructured":"Sopena-Rios M et al (2026) Single-cell analysis of the human immune system reveals sex-specific dynamics of immunosenescence. Nat. Aging 6(4):932\u2013949. https:\/\/doi.org\/10.1038\/s43587-026-01099-x","journal-title":"Nat. Aging"},{"issue":"7811","key":"9211_CR90","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1038\/s41586-020-2222-z","volume":"582","author":"K Wei","year":"2020","unstructured":"Wei K et al (2020) Notch signalling drives synovial fibroblast identity and arthritis pathology. Nature 582(7811):259\u2013264. https:\/\/doi.org\/10.1038\/s41586-020-2222-z","journal-title":"Nature"},{"issue":"1","key":"9211_CR91","doi-asserted-by":"publisher","first-page":"791","DOI":"10.1038\/s41467-017-02659-x","volume":"9","author":"W Stephenson","year":"2018","unstructured":"Stephenson W et al (2018) Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low-cost microfluidic instrumentation. Nat. Commun. 9(1):791. https:\/\/doi.org\/10.1038\/s41467-017-02659-x","journal-title":"Nat. Commun."},{"issue":"10","key":"9211_CR92","doi-asserted-by":"publisher","DOI":"10.1002\/bies.201900221","volume":"42","author":"M Asp","year":"2020","unstructured":"Asp M, Bergenstr\u00e5hle J, Lundeberg J (2020) Spatially resolved transcriptomes\u2014next generation tools for tissue exploration. Bioessays 42(10):1900221. https:\/\/doi.org\/10.1002\/bies.201900221","journal-title":"Bioessays"},{"issue":"22","key":"9211_CR93","doi-asserted-by":"publisher","first-page":"2110","DOI":"10.1056\/NEJMra1100359","volume":"365","author":"GC Tsokos","year":"2011","unstructured":"Tsokos GC (2011) Systemic lupus erythematosus. N Engl J Med 365(22):2110\u20132121. https:\/\/doi.org\/10.1056\/NEJMra1100359","journal-title":"N Engl J Med"},{"key":"9211_CR94","doi-asserted-by":"publisher","unstructured":"Tzeng SJ, Kim I, Sun KH (2024) Editorial: Single-cell analysis on the pathophysiology of autoimmune diseases. Front Immunol 15. https:\/\/doi.org\/10.3389\/fimmu.2024.1451354.","DOI":"10.3389\/fimmu.2024.1451354"},{"key":"9211_CR95","doi-asserted-by":"publisher","unstructured":"Zeng H, Yang X, Luo S, Zhou Y (2021) The advances of single-cell RNA-Seq in Kidney Immunology. Front. Physiol 12. https:\/\/doi.org\/10.3389\/fphys.2021.752679","DOI":"10.3389\/fphys.2021.752679"},{"issue":"8","key":"9211_CR96","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1038\/s41584-024-01129-1","volume":"20","author":"PS Ramos","year":"2024","unstructured":"Ramos PS, Lim SS (2024) Clarity for the language of race, ethnicity and genetic ancestry in rheumatology. Nat. Rev. Rheumatol. 20(8):453\u2013454. https:\/\/doi.org\/10.1038\/s41584-024-01129-1","journal-title":"Nat. Rev. Rheumatol."},{"issue":"4","key":"9211_CR97","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1038\/s41581-019-0232-6","volume":"16","author":"DA Rao","year":"2020","unstructured":"Rao DA, Arazi A, Wofsy D, Diamond B (2020) Design and application of single-cell RNA sequencing to study kidney immune cells in lupus nephritis. Nat. Rev. Nephrol. 16(4):238\u2013250. https:\/\/doi.org\/10.1038\/s41581-019-0232-6","journal-title":"Nat. Rev. Nephrol."},{"issue":"2","key":"9211_CR98","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1056\/NEJMra1401483","volume":"378","author":"DS Reich","year":"2018","unstructured":"Reich DS, Lucchinetti CF, Calabresi PA (2018) Multiple Sclerosis. N. Engl. J. Med. 378(2):169\u2013180. https:\/\/doi.org\/10.1056\/NEJMra1401483","journal-title":"N. Engl. J. Med."},{"issue":"1","key":"9211_CR99","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1146\/annurev.neuro.30.051606.094313","volume":"31","author":"BD Trapp","year":"2008","unstructured":"Trapp BD, Nave K-A (2008) Multiple Sclerosis: An Immune or Neurodegenerative Disorder? Annu. Rev. Neurosci. 31(1):247\u2013269. https:\/\/doi.org\/10.1146\/annurev.neuro.30.051606.094313","journal-title":"Annu. Rev. Neurosci."},{"issue":"11","key":"9211_CR100","doi-asserted-by":"publisher","first-page":"647","DOI":"10.1038\/nrneurol.2012.168","volume":"8","author":"H Lassmann","year":"2012","unstructured":"Lassmann H, Van Horssen J, Mahad D (2012) Progressive multiple sclerosis: pathology and pathogenesis. Nat Rev Neurol 8(11):647\u20136562012. https:\/\/doi.org\/10.1038\/nrneurol.2012.168","journal-title":"Nat Rev Neurol"},{"issue":"8","key":"9211_CR101","doi-asserted-by":"publisher","first-page":"1953","DOI":"10.1093\/brain\/awl075","volume":"129","author":"R Gold","year":"2006","unstructured":"Gold R (2006) Understanding pathogenesis and therapy of multiple sclerosis via animal models: 70 years of merits and culprits in experimental autoimmune encephalomyelitis research. Brain 129(8):1953\u20131971. https:\/\/doi.org\/10.1093\/brain\/awl075","journal-title":"Brain"},{"issue":"2","key":"9211_CR102","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1007\/s00401-016-1631-4","volume":"133","author":"H Lassmann","year":"2017","unstructured":"Lassmann H, Bradl M (2017) Multiple sclerosis: experimental models and reality. Acta Neuropathol. (Berl.) 133(2):223\u2013244. https:\/\/doi.org\/10.1007\/s00401-016-1631-4","journal-title":"Acta Neuropathol. (Berl.)"},{"key":"9211_CR103","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1016\/j.ejphar.2015.03.042","volume":"759","author":"C Procaccini","year":"2015","unstructured":"Procaccini C, De Rosa V, Pucino V, Formisano L, Matarese G (2015) Animal models of multiple sclerosis. Eur J Pharmacol 759:182\u2013191. https:\/\/doi.org\/10.1016\/j.ejphar.2015.03.042","journal-title":"Eur J Pharmacol"},{"key":"9211_CR104","doi-asserted-by":"publisher","first-page":"14","DOI":"10.17879\/freeneuropathology-2025-6762","volume":"6","author":"L Klotz","year":"2025","unstructured":"Klotz L, Saraste M, Airas L, Kuhlmann T (2025) Multiple sclerosis: 2024 update Free Neuropathol 6:14. https:\/\/doi.org\/10.17879\/freeneuropathology-2025-6762.","journal-title":"Free Neuropathol"},{"issue":"12","key":"9211_CR105","doi-asserted-by":"publisher","first-page":"1574","DOI":"10.1038\/s41590-019-0466-2","volume":"20","author":"FJ Barrat","year":"2019","unstructured":"Barrat FJ, Crow MK, Ivashkiv LB (2019) Interferon target-gene expression and epigenomic signatures in health and disease. Nat Immunol 20(12):1574\u20131583. https:\/\/doi.org\/10.1038\/s41590-019-0466-2","journal-title":"Nat Immunol"},{"issue":"1","key":"9211_CR106","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1146\/annurev-pathol-020117-043952","volume":"14","author":"MK Crow","year":"2019","unstructured":"Crow MK, Olferiev M, Kirou KA (2019) Type I Interferons in Autoimmune Disease. Annu. Rev. Pathol. Mech. Dis. 14(1):369\u2013393. https:\/\/doi.org\/10.1146\/annurev-pathol-020117-043952","journal-title":"Annu. Rev. Pathol. Mech. Dis."},{"issue":"1","key":"9211_CR107","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1038\/nrrheum.2015.167","volume":"12","author":"DM Schwartz","year":"2016","unstructured":"Schwartz DM, Bonelli M, Gadina M, O\u2019Shea JJ (2016) Type I\/II cytokines, JAKs, and new strategies for treating autoimmune diseases. Nat. Rev. Rheumatol. 12(1):25\u201336. https:\/\/doi.org\/10.1038\/nrrheum.2015.167","journal-title":"Nat. Rev. Rheumatol."},{"issue":"7","key":"9211_CR108","doi-asserted-by":"publisher","first-page":"1888","DOI":"10.1016\/j.cell.2019.05.031","volume":"177","author":"T Stuart","year":"2019","unstructured":"Stuart T et al (2019) Comprehensive integration of single-cell data. Cell 177(7):1888-1902.e21. https:\/\/doi.org\/10.1016\/j.cell.2019.05.031","journal-title":"Cell"},{"issue":"6","key":"9211_CR109","doi-asserted-by":"publisher","DOI":"10.3390\/biomedicines12061297","volume":"12","author":"AK McLean","year":"2024","unstructured":"McLean AK, Reynolds G, Pratt AG (2024) Leveraging multi-tissue, single-cell atlases as tools to elucidate shared mechanisms of immune-mediated inflammatory diseases. Biomedicines 12(6):1297. https:\/\/doi.org\/10.3390\/biomedicines12061297","journal-title":"Biomedicines"},{"key":"9211_CR110","doi-asserted-by":"publisher","first-page":"1768719","DOI":"10.3389\/fimmu.2026.1768719","volume":"17","author":"W Wan","year":"2026","unstructured":"Wan W, Zhang S, Jiang Y, Zhao D (2026) Insights into the pathogenesis of rheumatic and immune diseases from single-cell omics. Front. Immunol. 17:1768719. https:\/\/doi.org\/10.3389\/fimmu.2026.1768719","journal-title":"Front. Immunol."},{"issue":"7863","key":"9211_CR111","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1038\/s41586-021-03552-w","volume":"594","author":"J Chiou","year":"2021","unstructured":"Chiou J et al (2021) Interpreting type 1 diabetes risk with genetics and single-cell epigenomics. Nature 594(7863):398\u2013402. https:\/\/doi.org\/10.1038\/s41586-021-03552-w","journal-title":"Nature"},{"issue":"3","key":"9211_CR112","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1038\/s41588-021-00790-6","volume":"53","author":"JM Granja","year":"2021","unstructured":"Granja JM et al (2021) ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis. Nat. Genet. 53(3):403\u2013411. https:\/\/doi.org\/10.1038\/s41588-021-00790-6","journal-title":"Nat. Genet."},{"issue":"1","key":"9211_CR113","doi-asserted-by":"publisher","first-page":"2969","DOI":"10.1038\/s41467-021-23213-w","volume":"12","author":"SE Pierce","year":"2021","unstructured":"Pierce SE, Granja JM, Greenleaf WJ (2021) High-throughput single-cell chromatin accessibility CRISPR screens enable unbiased identification of regulatory networks in cancer. Nat. Commun. 12(1):2969. https:\/\/doi.org\/10.1038\/s41467-021-23213-w","journal-title":"Nat. Commun."},{"issue":"5","key":"9211_CR114","doi-asserted-by":"publisher","first-page":"904","DOI":"10.1038\/s41591-021-01329-2","volume":"27","author":"E Stephenson","year":"2021","unstructured":"Stephenson E et al (2021) Single-cell multi-omics analysis of the immune response in COVID-19. Nat. Med. 27(5):904\u2013916. https:\/\/doi.org\/10.1038\/s41591-021-01329-2","journal-title":"Nat. Med."},{"key":"9211_CR115","doi-asserted-by":"publisher","unstructured":"Elshiekh D et al (2025) Single-cell sequencing in molecular diagnostics: Transformative yet untapped potential. Front Genet 16. https:\/\/doi.org\/10.3389\/fgene.2025.1621081","DOI":"10.3389\/fgene.2025.1621081"},{"issue":"6","key":"9211_CR116","doi-asserted-by":"publisher","first-page":"1256","DOI":"10.1038\/s41591-022-01789-0","volume":"28","author":"F Rivellese","year":"2022","unstructured":"Rivellese F et al (2022) Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial. Nat Med 28(6):1256\u20131268. https:\/\/doi.org\/10.1038\/s41591-022-01789-0","journal-title":"Nat Med"},{"issue":"6","key":"9211_CR117","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1136\/annrheumdis-2018-214539","volume":"78","author":"F Humby","year":"2019","unstructured":"Humby F et al (2019) Synovial cellular and molecular signatures stratify clinical response to csDMARD therapy and predict radiographic progression in early rheumatoid arthritis patients. Ann Rheum Dis 78(6):761\u2013772. https:\/\/doi.org\/10.1136\/annrheumdis-2018-214539","journal-title":"Ann Rheum Dis"},{"issue":"10","key":"9211_CR118","doi-asserted-by":"publisher","first-page":"1964","DOI":"10.2337\/dc15-1419","volume":"38","author":"RA Insel","year":"2015","unstructured":"Insel RA et al (2015) Staging presymptomatic type 1 diabetes: a scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association. Diabetes Care 38(10):1964\u20131974. https:\/\/doi.org\/10.2337\/dc15-1419","journal-title":"Diabetes Care"},{"issue":"5","key":"9211_CR119","doi-asserted-by":"publisher","first-page":"980","DOI":"10.1007\/s00125-015-3514-y","volume":"58","author":"JP Krischer","year":"2015","unstructured":"Krischer JP et al (2015) The 6 year incidence of diabetes-associated autoantibodies in genetically at-risk children: the TEDDY study. Diabetologia 58(5):980\u2013987. https:\/\/doi.org\/10.1007\/s00125-015-3514-y","journal-title":"Diabetologia"},{"issue":"23","key":"9211_CR120","doi-asserted-by":"publisher","first-page":"2473","DOI":"10.1001\/jama.2013.6285","volume":"309","author":"AG Ziegler","year":"2013","unstructured":"Ziegler AG et al (2013) Seroconversion to multiple islet autoantibodies and risk of progression to diabetes in children. JAMA 309(23):2473\u20132479. https:\/\/doi.org\/10.1001\/jama.2013.6285","journal-title":"JAMA"},{"issue":"7","key":"9211_CR121","doi-asserted-by":"publisher","first-page":"1853","DOI":"10.1016\/j.cell.2016.11.038","volume":"167","author":"A Dixit","year":"2016","unstructured":"Dixit A et al (2016) Perturb-Seq: dissecting molecular circuits with scalable single-cell RNA profiling of pooled genetic screens. Cell 167(7):1853-1866.e17. https:\/\/doi.org\/10.1016\/j.cell.2016.11.038","journal-title":"Cell"},{"issue":"14","key":"9211_CR122","doi-asserted-by":"publisher","first-page":"2559","DOI":"10.1016\/j.cell.2022.05.013","volume":"185","author":"JM Replogle","year":"2022","unstructured":"Replogle JM et al (2022) Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq. Cell 185(14):2559-2575.e28. https:\/\/doi.org\/10.1016\/j.cell.2022.05.013","journal-title":"Cell"},{"issue":"8","key":"9211_CR123","doi-asserted-by":"publisher","first-page":"1282","DOI":"10.1038\/s41587-023-01964-9","volume":"42","author":"D Yao","year":"2024","unstructured":"Yao D et al (2024) Scalable genetic screening for regulatory circuits using compressed Perturb-seq. Nat Biotechnol 42(8):1282\u20131295. https:\/\/doi.org\/10.1038\/s41587-023-01964-9","journal-title":"Nat Biotechnol"},{"issue":"3","key":"9211_CR124","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1038\/s41556-025-01622-z","volume":"27","author":"L Jiang","year":"2025","unstructured":"Jiang L et al (2025) Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens. Nat. Cell Biol. 27(3):505\u2013517. https:\/\/doi.org\/10.1038\/s41556-025-01622-z","journal-title":"Nat. Cell Biol."},{"issue":"10","key":"9211_CR125","doi-asserted-by":"publisher","first-page":"935","DOI":"10.1038\/nmeth.4437","volume":"14","author":"SC van den Brink","year":"2017","unstructured":"van den Brink SC et al (2017) Single-cell sequencing reveals dissociation-induced gene expression in tissue subpopulations. Nat. Methods 14(10):935\u2013936. https:\/\/doi.org\/10.1038\/nmeth.4437","journal-title":"Nat. Methods"},{"issue":"1","key":"9211_CR126","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1186\/s13059-019-1830-0","volume":"20","author":"CH O\u2019Flanagan","year":"2019","unstructured":"O\u2019Flanagan CH et al (2019) Dissociation of solid tumor tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses. Genome Biol. 20(1):210. https:\/\/doi.org\/10.1186\/s13059-019-1830-0","journal-title":"Genome Biol."},{"issue":"1","key":"9211_CR127","doi-asserted-by":"publisher","first-page":"52","DOI":"10.4132\/jptm.2022.12.19","volume":"57","author":"N Kim","year":"2023","unstructured":"Kim N, Kang H, Jo A, Yoo S-A, Lee H-O (2023) Perspectives on single-nucleus RNA sequencing in different cell types and tissues. J. Pathol. Transl. Med. 57(1):52\u201359. https:\/\/doi.org\/10.4132\/jptm.2022.12.19","journal-title":"J. Pathol. Transl. Med."},{"issue":"1","key":"9211_CR128","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1186\/s13075-018-1631-y","volume":"20","author":"LT Donlin","year":"2018","unstructured":"Donlin LT et al (2018) Methods for high-dimensional analysis of cells dissociated from cryopreserved synovial tissue. Arthritis Res. Ther. 20(1):139. https:\/\/doi.org\/10.1186\/s13075-018-1631-y","journal-title":"Arthritis Res. Ther."},{"issue":"1","key":"9211_CR129","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1038\/s41592-021-01336-8","volume":"19","author":"MD Luecken","year":"2022","unstructured":"Luecken MD et al (2022) Benchmarking atlas-level data integration in single-cell genomics. Nat Methods 19(1):41\u201350. https:\/\/doi.org\/10.1038\/s41592-021-01336-8","journal-title":"Nat Methods"},{"issue":"6","key":"9211_CR130","doi-asserted-by":"publisher","DOI":"10.15252\/msb.20188746","volume":"15","author":"MD Luecken","year":"2019","unstructured":"Luecken MD, Theis FJ (2019) Current best practices in single\u2010cell RNA\u2010seq analysis: a tutorial. Mol Syst Biol 15(6):MSB188746. https:\/\/doi.org\/10.15252\/msb.20188746","journal-title":"Mol Syst Biol"},{"issue":"1","key":"9211_CR131","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbaf723","volume":"27","author":"AM Nesari","year":"2026","unstructured":"Nesari AM, MotieGhader H, Ghorbian S (2026) Advances and challenges in single-cell RNA sequencing data analysis: a comprehensive review. Brief Bioinform 27(1):bbaf723. https:\/\/doi.org\/10.1093\/bib\/bbaf723","journal-title":"Brief Bioinform"},{"issue":"1","key":"9211_CR132","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1186\/s13059-019-1850-9","volume":"21","author":"HTN Tran","year":"2020","unstructured":"Tran HTN et al (2020) A benchmark of batch-effect correction methods for single-cell RNA sequencing data. Genome Biol. 21(1):12\u201312. https:\/\/doi.org\/10.1186\/s13059-019-1850-9","journal-title":"Genome Biol."},{"key":"9211_CR133","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.semcancer.2017.12.008","volume":"52","author":"L Agrawal","year":"2018","unstructured":"Agrawal L, Engel KB, Greytak SR, Moore HM (2018) Understanding preanalytical variables and their effects on clinical biomarkers of oncology and immunotherapy. Semin Cancer Biol 52:26\u201338. https:\/\/doi.org\/10.1016\/j.semcancer.2017.12.008","journal-title":"Semin Cancer Biol"},{"issue":"1","key":"9211_CR134","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1186\/s13059-019-1795-z","volume":"20","author":"T Abdelaal","year":"2019","unstructured":"Abdelaal T et al (2019) A comparison of automatic cell identification methods for single-cell RNA sequencing data. Genome Biol 20(1):194. https:\/\/doi.org\/10.1186\/s13059-019-1795-z","journal-title":"Genome Biol"},{"key":"9211_CR135","doi-asserted-by":"publisher","first-page":"961","DOI":"10.1016\/j.csbj.2021.01.015","volume":"19","author":"G Pasquini","year":"2021","unstructured":"Pasquini G, Rojo Arias JE, Sch\u00e4fer P, Busskamp V (2021) Automated methods for cell type annotation on scRNA-seq data Comput Struct Biotechnol J 19:961\u2013969. https:\/\/doi.org\/10.1016\/j.csbj.2021.01.015.","journal-title":"Comput Struct Biotechnol J"},{"issue":"14","key":"9211_CR136","doi-asserted-by":"publisher","first-page":"3633","DOI":"10.1016\/j.cell.2025.06.009","volume":"188","author":"MA Skinnider","year":"2025","unstructured":"Skinnider MA, Courtine G, Bloch J, Squair JW (2025) A clinical road map for single-cell omics. Cell 188(14):3633\u20133647. https:\/\/doi.org\/10.1016\/j.cell.2025.06.009","journal-title":"Cell"},{"key":"9211_CR137","doi-asserted-by":"publisher","unstructured":"Cho H. Privacy of single-cell gene expression data. Patterns 5:112024, https:\/\/doi.org\/10.1016\/j.patter.2024.101096.","DOI":"10.1016\/j.patter.2024.101096"},{"issue":"6","key":"9211_CR138","doi-asserted-by":"publisher","first-page":"1077","DOI":"10.1093\/ndt\/gfaf010","volume":"40","author":"R Kramann","year":"2025","unstructured":"Kramann R, Kuppe C, Luyckx V, van Biesen W, Steiger S (2025) Unveiling the risks: protecting privacy in single-cell genomics data. Nephrol. Dial. Transplant. 40(6):1077\u20131080. https:\/\/doi.org\/10.1093\/ndt\/gfaf010","journal-title":"Nephrol. Dial. Transplant."},{"issue":"6117","key":"9211_CR139","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1126\/science.1229566","volume":"339","author":"M Gymrek","year":"2013","unstructured":"Gymrek M, McGuire AL, Golan D, Halperin E, Erlich Y (2013) Identifying personal genomes by surname inference. Science 339(6117):321\u2013324. https:\/\/doi.org\/10.1126\/science.1229566","journal-title":"Science"},{"issue":"1","key":"9211_CR140","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.cell.2019.02.048","volume":"177","author":"G Sirugo","year":"2019","unstructured":"Sirugo G, Williams SM, Tishkoff SA (2019) The Missing Diversity in Human Genetic Studies. Cell 177(1):26\u201331. https:\/\/doi.org\/10.1016\/j.cell.2019.02.048","journal-title":"Cell"},{"key":"9211_CR141","doi-asserted-by":"publisher","unstructured":"Corpas M et al (2025) Bridging genomics\u2019 greatest challenge: the diversity gap. Cell Genomics 5(1). https:\/\/doi.org\/10.1016\/j.xgen.2024.100724.","DOI":"10.1016\/j.xgen.2024.100724"},{"issue":"1","key":"9211_CR142","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1002\/acr.25402","volume":"77","author":"VK Shanmugam","year":"2025","unstructured":"Shanmugam VK et al (2025) Coordination and Collaboration to Support Exposome Research in Autoimmune Diseases. Arthritis Care Res. 77(1):12\u201314. https:\/\/doi.org\/10.1002\/acr.25402","journal-title":"Arthritis Care Res."},{"issue":"2","key":"9211_CR143","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1038\/s41584-024-01204-7","volume":"21","author":"HC Ainsworth","year":"2025","unstructured":"Ainsworth HC, Baker Frost D, Lim SS, Ramos PS (2025) Breaking research silos to achieve equitable precision medicine in rheumatology\u2019 Nat Rev Rheumatol 21(2):98\u2013110. https:\/\/doi.org\/10.1038\/s41584-024-01204-7.","journal-title":"Nat Rev Rheumatol"},{"issue":"726","key":"9211_CR144","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.ade9214","volume":"15","author":"GS Ginsburg","year":"2023","unstructured":"Ginsburg GS, Denny JC, Schully SD (2023) Data-driven science and diversity in the All of Us Research Program. Sci Transl Med 15(726):eade9214. https:\/\/doi.org\/10.1126\/scitranslmed.ade9214","journal-title":"Sci Transl Med"},{"issue":"7","key":"9211_CR145","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0234962","volume":"15","author":"BM Mapes","year":"2020","unstructured":"Mapes BM et al (2020) Diversity and inclusion for the All of Us research program: A scoping review. PLOS ONE 15(7):e0234962. https:\/\/doi.org\/10.1371\/journal.pone.0234962","journal-title":"PLOS ONE"},{"key":"9211_CR146","doi-asserted-by":"publisher","first-page":"59","DOI":"10.2147\/PGPM.S141546","volume":"11","author":"N Mulder","year":"2018","unstructured":"Mulder N et al (2018) H3Africa: current perspectives. Pharmacogenomics Pers. Med. 11:59\u201366. https:\/\/doi.org\/10.2147\/PGPM.S141546","journal-title":"Pharmacogenomics Pers. Med."},{"key":"9211_CR147","doi-asserted-by":"publisher","unstructured":"Parums DV (2024) Editorial: the human cell Atlas. What is it and where could it take us?. Med Sci Monit 30. https:\/\/doi.org\/10.12659\/MSM.947707.","DOI":"10.12659\/MSM.947707"},{"key":"9211_CR148","doi-asserted-by":"publisher","unstructured":"Sengupta D, Choudhury A, Ramsay M (2025) H3Africa: a model for implementing biobank-based genomic research in resource-constrained settings Hum Mol Genet ddaf113. https:\/\/doi.org\/10.1093\/hmg\/ddaf113.","DOI":"10.1093\/hmg\/ddaf113"},{"key":"9211_CR149","unstructured":"NSC, Branch O, \u2018Accelerating Medicines Partnership\u00ae Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP\u00ae RA\/SLE) Program., National Institute of Arthritis and Musculoskeletal and Skin Diseases. Accessed: Aug. 24, 2026. [Online]. Available: https:\/\/www.niams.nih.gov\/grants-funding\/funded-research\/accelerating-medicines\/RA-SLE"},{"issue":"6","key":"9211_CR150","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1097\/BOR.0000000000000646","volume":"31","author":"C Drenkard","year":"2019","unstructured":"Drenkard C, Lim SS (2019) Update on lupus epidemiology: advancing health disparities research through the study of minority populations Curr Opin Rheumatol 31(6):689\u2013696. https:\/\/doi.org\/10.1097\/BOR.0000000000000646.","journal-title":"Curr Opin Rheumatol"},{"issue":"10","key":"9211_CR151","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1038\/s41576-020-0257-5","volume":"21","author":"JB Byrd","year":"2020","unstructured":"Byrd JB, Greene AC, Prasad DV, Jiang X, Greene CS (2020) Responsible, practical genomic data sharing that accelerates research. Nat. Rev. Genet. 21(10):615\u2013629. https:\/\/doi.org\/10.1038\/s41576-020-0257-5","journal-title":"Nat. Rev. Genet."},{"issue":"6","key":"9211_CR152","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1038\/nrg3723","volume":"15","author":"Y Erlich","year":"2014","unstructured":"Erlich Y, Narayanan A (2014) Routes for breaching and protecting genetic privacy. Nat Rev Genet 15(6):409\u2013421. https:\/\/doi.org\/10.1038\/nrg3723","journal-title":"Nat Rev Genet"},{"issue":"8","key":"9211_CR153","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1038\/s41576-023-00586-w","volume":"24","author":"L Heumos","year":"2023","unstructured":"Heumos L et al (2023) Best practices for single-cell analysis across modalities. Nat. Rev. Genet. 24(8):550\u2013572. https:\/\/doi.org\/10.1038\/s41576-023-00586-w","journal-title":"Nat. Rev. Genet."},{"issue":"1","key":"9211_CR154","doi-asserted-by":"publisher","first-page":"4650","DOI":"10.1038\/s41467-024-48620-7","volume":"15","author":"K Weinand","year":"2024","unstructured":"Weinand K et al (2024) The chromatin landscape of pathogenic transcriptional cell states in rheumatoid arthritis. Nat. Commun. 15(1):4650. https:\/\/doi.org\/10.1038\/s41467-024-48620-7","journal-title":"Nat. Commun."},{"issue":"12","key":"9211_CR155","doi-asserted-by":"publisher","first-page":"gkaf536","DOI":"10.1093\/nar\/gkaf536","volume":"53","author":"M Khan","year":"2025","unstructured":"Khan M, Arslanturk S, Draghici S (2025) A comprehensive review of spatial transcriptomics data alignment and integration Nucleic Acids Res 53(12):gkaf536. https:\/\/doi.org\/10.1093\/nar\/gkaf536.","journal-title":"Nucleic Acids Res"},{"issue":"5","key":"9211_CR156","doi-asserted-by":"publisher","DOI":"10.1016\/j.ygeno.2023.110671","volume":"115","author":"Y Wang","year":"2023","unstructured":"Wang Y et al (2023) Spatial transcriptomics: Technologies, applications and experimental considerations. Genomics 115(5):110671. https:\/\/doi.org\/10.1016\/j.ygeno.2023.110671","journal-title":"Genomics"},{"issue":"4","key":"9211_CR157","doi-asserted-by":"publisher","first-page":"2220","DOI":"10.1093\/rheumatology\/keae364","volume":"64","author":"S-Y Bang","year":"2025","unstructured":"Bang S-Y et al (2025) Unveiling the dynamics of B lymphocytes in systemic lupus erythematosus patients treated with belimumab through longitudinal single-cell RNA sequencing. Rheumatology (Oxford) 64(4):2220\u20132226. https:\/\/doi.org\/10.1093\/rheumatology\/keae364","journal-title":"Rheumatology (Oxford)"},{"issue":"5","key":"9211_CR158","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1038\/s41587-019-0071-9","volume":"37","author":"W Saelens","year":"2019","unstructured":"Saelens W, Cannoodt R, Todorov H, Saeys Y (2019) A comparison of single-cell trajectory inference methods. Nat. Biotechnol. 37(5):547\u2013554. https:\/\/doi.org\/10.1038\/s41587-019-0071-9","journal-title":"Nat. Biotechnol."},{"issue":"1","key":"9211_CR159","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1186\/s12864-018-4772-0","volume":"19","author":"K Street","year":"2018","unstructured":"Street K et al (2018) Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics. BMC Genomics 19(1):477. https:\/\/doi.org\/10.1186\/s12864-018-4772-0","journal-title":"BMC Genomics"},{"key":"9211_CR160","doi-asserted-by":"publisher","unstructured":"Weinreb C, Wolock S, Tusi BK, Socolovsky M, Klein AM (2018) Fundamental limits on dynamic inference from single-cell snapshots. Proc Natl Acad Sci 115(10). https:\/\/doi.org\/10.1073\/pnas.1714723115.","DOI":"10.1073\/pnas.1714723115"},{"issue":"3","key":"9211_CR161","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1038\/nmeth.4177","volume":"14","author":"P Datlinger","year":"2017","unstructured":"Datlinger P et al (2017) Pooled CRISPR screening with single-cell transcriptome readout. Nat. Methods 14(3):297\u2013301. https:\/\/doi.org\/10.1038\/nmeth.4177","journal-title":"Nat. Methods"},{"issue":"1","key":"9211_CR162","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1016\/j.cell.2018.11.022","volume":"176","author":"AJ Rubin","year":"2019","unstructured":"Rubin AJ et al (2019) Coupled single-cell CRISPR screening and epigenomic profiling reveals causal gene regulatory networks. Cell 176(1):361-376.e17. https:\/\/doi.org\/10.1016\/j.cell.2018.11.022","journal-title":"Cell"},{"issue":"7539","key":"9211_CR163","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1038\/nature13835","volume":"518","author":"KK-H Farh","year":"2015","unstructured":"Farh KK-H et al (2015) Genetic and epigenetic fine mapping of causal autoimmune disease variants. Nature 518(7539):337\u2013343. https:\/\/doi.org\/10.1038\/nature13835","journal-title":"Nature"},{"issue":"4","key":"9211_CR164","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1038\/s41592-024-02563-5","volume":"22","author":"K B\u00f6rner","year":"2025","unstructured":"B\u00f6rner K et al (2025) Human BioMolecular Atlas Program (HuBMAP): 3D human reference atlas construction and usage. Nat Methods 22(4):845\u2013860. https:\/\/doi.org\/10.1038\/s41592-024-02563-5","journal-title":"Nat Methods"},{"issue":"10271","key":"9211_CR165","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1016\/S0140-6736(20)32341-2","volume":"397","author":"F Humby","year":"2021","unstructured":"Humby F et al (2021) Rituximab versus tocilizumab in anti-TNF inadequate responder patients with rheumatoid arthritis (R4RA): 16-week outcomes of a stratified, biopsy-driven, multicentre, open-label, phase 4 randomised controlled trial. Lancet 397(10271):305\u2013317. https:\/\/doi.org\/10.1016\/S0140-6736(20)32341-2","journal-title":"Lancet"}],"container-title":["Clinical Reviews in Allergy &amp; Immunology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12016-026-09211-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12016-026-09211-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12016-026-09211-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:08:11Z","timestamp":1792022891000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12016-026-09211-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,14]]},"references-count":165,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["9211"],"URL":"https:\/\/doi.org\/10.1007\/s12016-026-09211-0","relation":{},"ISSN":["1559-0267"],"issn-type":[{"value":"1559-0267","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,14]]},"assertion":[{"value":"2 August 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 October 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 October 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Not applicable","order":1,"name":"Ethics","label":"Ethics statement","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"85"}}