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Methods: A bivariate MR framework analysed the causal dynamics between immune cell attributes and AD, using genetic variants as instrumental variables. Summary statistics from a genome-wide association study for 731 immune phenotypes were obtained. Univariable MR analysis was conducted using the inverse-variance weighted method supplemented by sensitivity analyses. Horizontal pleiotropy was assessed using MR-Egger and MR pleiotropy residual sum and outlier. Significant cis-expression quantitative trait loci (eQTL) were identified via the Genotype-Tissue Expression (GTEx) database, followed by tissue-specific expression and pathway analyses. Results:\u00a0Four immunophenotypes exhibited positive causal effects on AD, while one showed a negative effect. Pathogenic traits included the median fluorescence intensity of CD19 on transitional B cells, immunoglobulin D- CD38dim B cells, CD3 on CD39+ CD4+ Treg cells, and CD3 on CD39+ activated Treg cells. The protective trait was the absolute count of CD86+ myeloid dendritic cells. Sensitivity analyses validated these associations. Pathway enrichment analysis highlighted significant arterial enrichments and key biological processes, identifying SLAMF6 and CD28 as key genes. Conclusion: This study suggests potential causal roles for specific immune cell traits in AD pathogenesis, although these findings should be interpreted with caution due to study limitations. The identified immune cell types and associated eQTL genes offer promising targets for clinical risk stratification and therapeutic interventions. Future research should focus on translating these findings into practical strategies for patient care.<\/jats:p>","DOI":"10.15420\/ecr.2024.44","type":"journal-article","created":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T10:48:22Z","timestamp":1743504502000},"source":"Crossref","is-referenced-by-count":4,"title":["Causal Characteristics of Immune Cells Associated with Aortic Dissection: A Mendelian Randomisation Analysis"],"prefix":"10.15420","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-5602-9099","authenticated-orcid":false,"given":"Tian-le","family":"Li","sequence":"first","affiliation":[{"name":"Heart Center, Tianjin Third Central Hospital, Tianjin, China; Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China; Artificial Cell Engineering Technology Research Center, Tianjin, China; Tianjin Institute of Hepatobiliary Disease, Tianjin, China; Tianjin University Central Hospital, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5118-3536","authenticated-orcid":false,"given":"Mao-long","family":"Fu","sequence":"additional","affiliation":[{"name":"Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China; Artificial Cell Engineering Technology Research Center, Tianjin, China; Tianjin Institute of Hepatobiliary Disease, Tianjin, China; Tianjin University Central Hospital, Tianjin, China; Emergency Department, Tianjin Third Central Hospital, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li-hong","family":"Wang","sequence":"additional","affiliation":[{"name":"Paediatrics Department, Port Hospital of Tianjin, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4679-0468","authenticated-orcid":false,"given":"Jian-long","family":"Wang","sequence":"additional","affiliation":[{"name":"Heart Center, Tianjin Third Central Hospital, Tianjin, China; Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China; Artificial Cell Engineering Technology Research Center, Tianjin, China; Tianjin Institute of Hepatobiliary Disease, Tianjin, China; Tianjin University Central Hospital, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-0521-7044","authenticated-orcid":false,"given":"Ying-wu","family":"Liu","sequence":"additional","affiliation":[{"name":"Heart Center, Tianjin Third Central Hospital, Tianjin, China; Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China; Artificial Cell Engineering Technology Research Center, Tianjin, China; Tianjin Institute of Hepatobiliary Disease, Tianjin, China; Tianjin University Central Hospital, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3911-0915","authenticated-orcid":false,"given":"Lei","family":"Huang","sequence":"additional","affiliation":[{"name":"Heart Center, Tianjin Third Central Hospital, Tianjin, China; Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China; Artificial Cell Engineering Technology Research Center, Tianjin, China; Tianjin Institute of Hepatobiliary Disease, Tianjin, China; Tianjin University Central Hospital, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"6096","published-online":{"date-parts":[[2025,4,1]]},"reference":[{"key":"ref0","doi-asserted-by":"publisher","unstructured":"Ma L, Chai T, Yang X, et al. Outcomes of hemi- vs. total arch replacement in acute type A aortic dissection: A systematic review and meta-analysis. Front Cardiovasc Med 2022;9:988619. https:\/\/doi.org\/10.3389\/fcvm.2022.988619; PMID:\u00a036237909.","DOI":"10.3389\/fcvm.2022.988619"},{"key":"ref1","doi-asserted-by":"publisher","unstructured":"Goyal A, Jain H, Usman M, et al. A comprehensive exploration of novel biomarkers for the early diagnosis of aortic dissection. Hellenic J Cardiol 2024:S1109\u20139666(24)00130-1. https:\/\/doi.org\/10.1016\/j.hjc.2024.06.006; PMID:\u00a038909846.","DOI":"10.1016\/j.hjc.2024.06.006"},{"key":"ref2","doi-asserted-by":"crossref","unstructured":"Li S, Li J, Cheng W, et al. Independent and interactive roles of immunity and metabolism in aortic dissection. Int J Mol Sci 2023;24:15908. https:\/\/doi.org\/10.3390\/ijms242115908; PMID:\u00a037958896.","DOI":"10.3390\/ijms242115908"},{"key":"ref3","doi-asserted-by":"publisher","unstructured":"Godugu S, Sinha T, Pradeepan M, et al. Unraveling the enigma of aortic dissection: from genetics to innovative therapies. Cureus 2024;16:e57803. https:\/\/doi.org\/10.7759\/cureus.57803; PMID:\u00a038721226.","DOI":"10.7759\/cureus.57803"},{"key":"ref4","doi-asserted-by":"crossref","unstructured":"Richmond RC, Sanderson E. Methods and practical considerations for performing Mendelian randomization. Int J Epidemiol 2022;51:2031\u20134. https:\/\/doi.org\/10.1093\/ije\/dyac166.","DOI":"10.1093\/ije\/dyac166"},{"key":"ref5","doi-asserted-by":"publisher","unstructured":"Davies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ 2018;362:k601. https:\/\/doi.org\/10.1136\/bmj.k601; PMID:\u00a030002074.","DOI":"10.1136\/bmj.k601"},{"key":"ref6","doi-asserted-by":"crossref","unstructured":"Power GM, Sanderson E, Pagoni P, et al. Methodological approaches, challenges, and opportunities in the application of Mendelian randomisation to lifecourse epidemiology: a systematic literature review. Eur J Epidemiol 2024;39:501\u201320. https:\/\/doi.org\/10.1007\/s10654-023-01032-1; PMID:\u00a037938447.","DOI":"10.1007\/s10654-023-01032-1"},{"key":"ref7","doi-asserted-by":"publisher","unstructured":"Gagliano Taliun SA, Evans DM. Ten simple rules for conducting a Mendelian randomization study. PLoS Comput Biol 2021;17:e1009238. https:\/\/doi.org\/10.1371\/journal.pcbi.1009238; PMID:\u00a034383747.","DOI":"10.1371\/journal.pcbi.1009238"},{"key":"ref8","unstructured":"Kurki MI, Karjalainen J, Palta P, et al. FinnGen provides genetic insights from a well-phenotyped isolated population. Nature 2023;613:508\u201318. https:\/\/doi.org\/10.1038\/s41586-022-05473-8; PMID:\u00a036653562."},{"key":"ref9","doi-asserted-by":"publisher","unstructured":"Orr\u00f9 V, Steri M, Sidore C, et al. Complex genetic signatures in immune cells underlie autoimmunity and inform therapy. Nat Genet 2020;52:1036\u201345. https:\/\/doi.org\/10.1038\/s41588-020-0684-4; PMID:\u00a032929287.","DOI":"10.1038\/s41588-020-0684-4"},{"key":"ref10","doi-asserted-by":"publisher","unstructured":"Pongpanich M, Sullivan PF, Tzeng JY. A quality control algorithm for filtering SNPs in genome-wide association studies. Bioinformatics 2010;26:1731\u20137. https:\/\/doi.org\/10.1093\/bioinformatics\/btq272; PMID:\u00a020501555.","DOI":"10.1093\/bioinformatics\/btq272"},{"key":"ref11","doi-asserted-by":"publisher","unstructured":"Spencer AV, Cox A, Walters K. Comparing the efficacy of SNP filtering methods for identifying a single causal SNP in a known association region. Ann Hum Genet 2014;78:50\u201361. https:\/\/doi.org\/10.1111\/ahg.12043; PMID:\u00a024205929.","DOI":"10.1111\/ahg.12043"},{"key":"ref12","doi-asserted-by":"publisher","unstructured":"Long Y, Tang L, Zhou Y, et al. Causal relationship between gut microbiota and cancers: a two-sample Mendelian randomisation study. BMC Med 2023;21:66. https:\/\/doi.org\/10.1186\/s12916-023-02761-6; PMID:\u00a036810112.","DOI":"10.1186\/s12916-023-02761-6"},{"key":"ref13","doi-asserted-by":"publisher","unstructured":"Tao Y, Zhao R, Yang B, et al. Dissecting the shared genetic landscape of anxiety, depression, and schizophrenia. J Transl Med 2024;22:373. https:\/\/doi.org\/10.1186\/s12967-024-05153-3; PMID:\u00a038637810.","DOI":"10.1186\/s12967-024-05153-3"},{"key":"ref14","doi-asserted-by":"publisher","unstructured":"Burgess S, Davies NM, Thompson SG, EPIC-InterAct Consortium. Instrumental variable analysis with a nonlinear exposure-outcome relationship. Epidemiology 2014;25:877\u201385. https:\/\/doi.org\/10.1097\/EDE.0000000000000161; PMID:\u00a025166881.","DOI":"10.1097\/ede.0000000000000161"},{"key":"ref15","doi-asserted-by":"publisher","unstructured":"Burgess S, Thompson SG, CRP CHD Genetics Collaboration. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol 2011;40:755\u201364. https:\/\/doi.org\/10.1093\/ije\/dyr036; PMID:\u00a021414999.","DOI":"10.1093\/ije\/dyr036"},{"key":"ref16","doi-asserted-by":"publisher","unstructured":"Verbanck M, Chen CY, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet 2018;50:693\u20138. https:\/\/doi.org\/10.1038\/s41588-018-0099-7; PMID:\u00a029686387.","DOI":"10.1038\/s41588-018-0099-7"},{"key":"ref17","doi-asserted-by":"publisher","unstructured":"Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol 2015;44:512\u201325. https:\/\/doi.org\/10.1093\/ije\/dyv080; PMID:\u00a026050253.","DOI":"10.1093\/ije\/dyv080"},{"key":"ref18","doi-asserted-by":"crossref","unstructured":"Yuan Z, Zhu H, Zeng P, et al. Testing and controlling for horizontal pleiotropy with probabilistic Mendelian randomization in transcriptome-wide association studies. Nat Commun 2020;11:3861. https:\/\/doi.org\/10.1038\/s41467-020-17668-6; PMID:\u00a032737316.","DOI":"10.1038\/s41467-020-17668-6"},{"key":"ref19","doi-asserted-by":"publisher","unstructured":"Hemani G, Bowden J, Davey Smith G. Evaluating the potential role of pleiotropy in Mendelian randomization studies. Hum Mol Genet 2018;27:R195\u2013208. https:\/\/doi.org\/10.1093\/hmg\/ddy163; PMID:\u00a029771313.","DOI":"10.1093\/hmg\/ddy163"},{"key":"ref20","doi-asserted-by":"crossref","unstructured":"Morrison J, Knoblauch N, Marcus JH, et al. Mendelian randomization accounting for correlated and uncorrelated pleiotropic effects using genome-wide summary statistics. Nat Genet 2020;52:740\u20137. https:\/\/doi.org\/10.1038\/s41588-020-0631-4; PMID:\u00a032451458.","DOI":"10.1038\/s41588-020-0631-4"},{"key":"ref21","doi-asserted-by":"publisher","unstructured":"Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10:1523. https:\/\/doi.org\/10.1038\/s41467-019-09234-6; PMID:\u00a030944313.","DOI":"10.1038\/s41467-019-09234-6"},{"key":"ref22","doi-asserted-by":"publisher","unstructured":"Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. Omics 2012;16:284\u20137. https:\/\/doi.org\/10.1089\/omi.2011.0118; PMID:\u00a022455463.","DOI":"10.1089\/omi.2011.0118"},{"key":"ref23","doi-asserted-by":"crossref","unstructured":"Zhou Y, Zhang Y, Han J, et al. Transitional B cells involved in autoimmunity and their impact on neuroimmunological diseases. J Transl Med 2020;18:131. https:\/\/doi.org\/10.1186\/s12967-020-02289-w; PMID:\u00a032183811.","DOI":"10.1186\/s12967-020-02289-w"},{"key":"ref24","doi-asserted-by":"publisher","unstructured":"Horna P, Nowakowski G, Endell J, Boxhammer R. Comparative assessment of surface CD19 and CD20 expression on B-cell lymphomas from clinical biopsies: implications for targeted therapies. Blood 2019;134(Suppl 1):5345. https:\/\/doi.org\/10.1182\/blood-2019-129600.","DOI":"10.1182\/blood-2019-129600"},{"key":"ref25","doi-asserted-by":"publisher","unstructured":"Ginaldi L, De Martinis M, Matutes E, et al. Levels of expression of CD19 and CD20 in chronic B cell leukaemias. J Clin Pathol 1998;51:364\u20139. https:\/\/doi.org\/10.1136\/jcp.51.5.364; PMID:\u00a09708202.","DOI":"10.1136\/jcp.51.5.364"},{"key":"ref26","doi-asserted-by":"publisher","unstructured":"Modvig S, \u00d8bro NF, Rosth\u00f8j S, et al. An immature immunophenotype (CD34pos, CD38dim, nTdTdim) on malignant B-cell precursor blasts at diagnosis predicts high minimal residual disease in BCP-ALL. Blood 2016;128:1728. https:\/\/doi.org\/10.1182\/blood.V128.22.1728.1728.","DOI":"10.1182\/blood.v128.22.1728.1728"},{"key":"ref27","doi-asserted-by":"crossref","unstructured":"Camponeschi A, Kl\u00e4sener K, Sundell T, et al. Human CD38 regulates B cell antigen receptor dynamic organization in normal and malignant B cells. J Exp Med 2022;219:e20220201. https:\/\/doi.org\/10.1084\/jem.20220201; PMID:\u00a035819358.","DOI":"10.1084\/jem.20220201"},{"key":"ref28","doi-asserted-by":"publisher","unstructured":"Borsellino G, Kleinewietfeld M, Di Mitri D, et al. Expression of ectonucleotidase CD39 by Foxp3+ Treg cells: hydrolysis of extracellular ATP and immune suppression. Blood 2007;110:1225\u201332. https:\/\/doi.org\/10.1182\/blood-2006-12-064527; PMID:\u00a017449799.","DOI":"10.1182\/blood-2006-12-064527"},{"key":"ref29","doi-asserted-by":"publisher","unstructured":"Fei F, Brar N, Herring MB, et al. Quantification of the median fluorescence intensity of CD3 and CD4 in mycosis fungoides\/Sezary syndrome versus non-neoplastic control cases in peripheral blood. J Hematop 2024;17:191\u20139. https:\/\/doi.org\/10.1007\/s12308-024-00599-2; PMID:\u00a039093388.","DOI":"10.1007\/s12308-024-00599-2"},{"key":"ref30","doi-asserted-by":"crossref","unstructured":"Canale FP, Ramello MC, N\u00fa\u00f1ez N, et al. CD39 expression defines cell exhaustion in tumor-infiltrating CD8+ T cells. Cancer Res 2018;78:115\u201328. https:\/\/doi.org\/10.1158\/0008-5472.CAN-16-2684; PMID:\u00a029066514.","DOI":"10.1158\/0008-5472.CAN-16-2684"},{"key":"ref31","doi-asserted-by":"crossref","unstructured":"Astarita JL, Dominguez CX, Tan C, et al. Treg specialization and functions beyond immune suppression. Clin Exp Immunol 2023;211:176\u201383. https:\/\/doi.org\/10.1093\/cei\/uxac123; PMID:\u00a036571811.","DOI":"10.1093\/cei\/uxac123"},{"key":"ref32","doi-asserted-by":"publisher","unstructured":"Al-Ashmawy GMZ. Dendritic cell subsets, maturation and function. In: Chapoval SP, ed. Dendritic cells. Rijeka, Croatia: IntechOpen, 2018. https:\/\/doi.org\/10.5772\/intechopen.79926.","DOI":"10.5772\/intechopen.79926"},{"key":"ref33","doi-asserted-by":"publisher","unstructured":"Azuma M. Co-signal molecules in T-cell activation. In: Azuma M, Yagita H, eds. Co-signal molecules in T cell activation: immune regulation in health and disease. Singapore: Springer, 2019;3\u201323. https:\/\/doi.org\/10.1007\/978-981-32-9717-3_1; PMID:\u00a031758529.","DOI":"10.1007\/978-981-32-9717-3_1"},{"key":"ref34","doi-asserted-by":"publisher","unstructured":"Liu G, Pan S, Xia H, et al. The causal relationship between thoracic aortic aneurysm and immune cells: a Mendelian randomization study. BMC Cardiovasc Disord 2024;24:212. https:\/\/doi.org\/10.1186\/s12872-024-03876-1; PMID:\u00a038627614.","DOI":"10.1186\/s12872-024-03876-1"},{"key":"ref35","doi-asserted-by":"publisher","unstructured":"Yamawaki-Ogata A, Mutsuga M, Narita Y. A review of current status of cell-based therapies for aortic aneurysms. Inflam Regen 2023;43:40. https:\/\/doi.org\/10.1186\/s41232-023-00280-8; PMID:\u00a037544997.","DOI":"10.1186\/s41232-023-00280-8"},{"key":"ref36","doi-asserted-by":"publisher","unstructured":"Farhangnia P, Ghomi SM, Mollazadehghomi S, et al. SLAM-family receptors come of age as a potential molecular target in cancer immunotherapy. Front Immunol 2023;14:1174138. https:\/\/doi.org\/10.3389\/fimmu.2023.1174138; PMID:\u00a037251372.","DOI":"10.3389\/fimmu.2023.1174138"},{"key":"ref37","doi-asserted-by":"publisher","unstructured":"Dragovich MA, Adam K, Strazza M, et al. SLAMF6 clustering is required to augment T cell activation. PLOS One 2019;14:e0218109. https:\/\/doi.org\/10.1371\/journal.pone.0218109; PMID:\u00a031199820.","DOI":"10.1371\/journal.pone.0218109"},{"key":"ref38","doi-asserted-by":"publisher","unstructured":"Yigit B, Wang N, ten Hacken E, et al. SLAMF6 as a regulator of exhausted CD8+ T cells in cancer. Cancer Immunol Res 2019;7:1485\u201396. https:\/\/doi.org\/10.1158\/2326-6066.CIR-18-0664; PMID:\u00a031315913.","DOI":"10.1158\/2326-6066.cir-18-0664"},{"key":"ref39","doi-asserted-by":"publisher","unstructured":"Oba T, Long MD, Ito KI, Ito F. Clinical and immunological relevance of SLAMF6 expression in the tumor microenvironment of breast cancer and melanoma. Sci Rep 2024;14:2394. https:\/\/doi.org\/10.1038\/s41598-023-50062-y; PMID:\u00a038287061.","DOI":"10.1038\/s41598-023-50062-y"},{"key":"ref40","doi-asserted-by":"publisher","unstructured":"Li Y, Han M, Wei H, et al. Id2 epigenetically controls CD8(+) T-cell exhaustion by disrupting the assembly of the Tcf3-LSD1 complex. Cell Mol Immunol 2024;21:292\u2013308. https:\/\/doi.org\/10.1038\/s41423-023-01118-6; PMID:\u00a038287103.","DOI":"10.1038\/s41423-023-01118-6"},{"key":"ref41","doi-asserted-by":"publisher","unstructured":"Lotze MT, Olejniczak SH, Skokos D. CD28 co-stimulation: novel insights and applications in cancer immunotherapy. Nat Rev Immunol 2024;24:878\u201395. https:\/\/doi.org\/10.1038\/s41577-024-01061-1; PMID:\u00a039054343.","DOI":"10.1038\/s41577-024-01061-1"},{"key":"ref42","doi-asserted-by":"publisher","unstructured":"Nagai S, Azuma M. The CD28\u2013B7 family of co-signaling molecules. In: Azuma M, Yagita H, eds. Co-signal molecules in T cell activation: immune regulation in health and disease. Singapore: Springer, 2019;25\u201351. https:\/\/doi.org\/10.1007\/978-981-32-9717-3_2; PMID:\u00a031758530.","DOI":"10.1007\/978-981-32-9717-3_2"},{"key":"ref43","doi-asserted-by":"publisher","unstructured":"Gartshteyn Y, Askanase AD, Song R, et al. SLAMF6 compartmentalization enhances T cell functions. Life Sci Alliance 2023;6:e202201533. https:\/\/doi.org\/10.26508\/lsa.202201533; PMID:\u00a036622343.","DOI":"10.26508\/lsa.202201533"},{"key":"ref44","doi-asserted-by":"publisher","unstructured":"Dong Z, Davidson D, P\u00e9rez-Quintero LA, et al. The adaptor SAP controls NK cell activation by regulating the enzymes Vav-1 and SHIP-1 and by enhancing conjugates with target cells. Immunity 2012;36:974\u201385. https:\/\/doi.org\/10.1016\/j.immuni.2012.03.023; PMID:\u00a022683124.","DOI":"10.1016\/j.immuni.2012.03.023"},{"key":"ref45","doi-asserted-by":"publisher","unstructured":"M\u00e1rquez-S\u00e1nchez AC, Koltsova EK. Immune and inflammatory mechanisms of abdominal aortic aneurysm. Front Immunol 2022;13:989933. https:\/\/doi.org\/10.3389\/fimmu.2022.989933; PMID:\u00a036275758.","DOI":"10.3389\/fimmu.2022.989933"},{"key":"ref46","doi-asserted-by":"crossref","unstructured":"Yuan Z, Lu Y, Wei J, et al. Abdominal aortic aneurysm: roles of inflammatory cells. Front Immunol 2020;11:609161. https:\/\/doi.org\/10.3389\/fimmu.2020.609161; PMID:\u00a033613530.","DOI":"10.3389\/fimmu.2020.609161"},{"key":"ref47","doi-asserted-by":"publisher","unstructured":"Huang YJ, Chen CH, Yang HC. AI-enhanced integration of genetic and medical imaging data for risk assessment of type 2 diabetes. Nat Commun 2024;15:4230. https:\/\/doi.org\/10.1038\/s41467-024-48618-1; PMID:\u00a038762475.","DOI":"10.1038\/s41467-024-48618-1"},{"key":"ref48","doi-asserted-by":"publisher","unstructured":"Neurath MF, Sands BE, Rieder F. Cellular immunotherapies and immune cell depleting therapies in inflammatory bowel diseases: the next magic bullet? Gut 2024;74:9\u201314. https:\/\/doi.org\/10.1136\/gutjnl-2024-332919; PMID:\u00a039025492.","DOI":"10.1136\/gutjnl-2024-332919"},{"key":"ref49","doi-asserted-by":"publisher","unstructured":"Pilat N, Sprent J. Treg therapies revisited: tolerance beyond deletion. Front Immunol 2020;11:622810. https:\/\/doi.org\/10.3389\/fimmu.2020.622810; PMID:\u00a033633742.","DOI":"10.3389\/fimmu.2020.622810"},{"key":"ref50","doi-asserted-by":"publisher","unstructured":"Gavile CM, Barwick BG, Newman S, et al. CD86 regulates myeloma cell survival. Blood Adv 2017;1:2307\u201319. https:\/\/doi.org\/10.1182\/bloodadvances.2017011601; PMID:\u00a029296880.","DOI":"10.1182\/bloodadvances.2017011601"}],"container-title":["European Cardiology Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.ecrjournal.com\/articleindex\/ecr.2024.44","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T10:54:04Z","timestamp":1743504844000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ecrjournal.com\/articleindex\/ecr.2024.44"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,1]]},"references-count":51,"URL":"https:\/\/doi.org\/10.15420\/ecr.2024.44","relation":{},"ISSN":["1758-3764","1758-3756"],"issn-type":[{"value":"1758-3764","type":"electronic"},{"value":"1758-3756","type":"print"}],"subject":[],"published":{"date-parts":[[2025,4,1]]},"article-number":"e07"}}