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We hypothesised that type 1 diabetes genetic risk factors disrupt tissue-specific biological pathways and gene networks that ultimately lead to beta cell loss.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a multi-tissue multi-omics analysis that integrates human GWAS data for type 1 diabetes with tissue-specific regulatory data for gene expression and gene network models across relevant tissues to highlight key pathways and key driver (KD)\u00a0genes contributing to type 1 diabetes pathogenesis. KD genes were validated using islet-specific gene expression and protein data from non-obese diabetic (NOD) mice compared with type 2 diabetic and non-diabetic mouse models. Drug repositioning predictions were generated using the INCS L1000 and PharmOmics platforms, and candidate drugs were tested using electronic medical records (EMRs) of individuals with type 1 diabetes from the OneFlorida+ Clinical Data Network.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Our integrative genomics approach identified known immune pathways across multiple tissues, such as adaptive immune responses, cytokine-mediated inflammation, primary immunodeficiency, and interactions between lymphoid and non-lymphoid cells. Tissue-specific signals included genes related to type 2 diabetes in lymphocytes, viral response pathways in macrophages and monocytes, and Notch signalling in adipose tissue and immune cells. In pancreatic islet analysis, we observed significant enrichment for type 1 diabetes and type 2 diabetes gene sets alongside immune-related pathways, including antigen processing, systemic lupus erythematosus and IFN signalling. Removing HLA genes from the analysis revealed additional immune pathways, such as retinoic acid-inducible gene\u00a0I (RIG-I)\/melanoma differentiation-associated protein 5 (MDA5) induction of interferons, together with melanogenesis, steroid hormone synthesis and iron transport. Network modelling highlighted the autoimmune basis of disease, with KDs such as FYN, TAP1, WAS and HLA-B\/C\/G, as well as additional immunomodulatory proteins such as LCK, LCP2 and genes such as\n                      <jats:italic>EMR1<\/jats:italic>\n                      and\n                      <jats:italic>GC<\/jats:italic>\n                      . These KDs were further supported by gene and protein expression data from NOD mice. We additionally highlight various drug classes that target the type 1 diabetes genetic networks and may be useful to delay type 1 diabetes development; some of these were supported by our EMR screen.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions\/interpretation<\/jats:title>\n                    <jats:p>Our multi-tissue multi-omics approach provides a detailed landscape of the tissue-specific genetic networks and regulators underlying type 1 diabetes. This analysis confirms the roles of known immune pathways while uncovering additional regulatory elements and disease-associated networks, thus expanding our understanding of type 1 diabetes pathogenesis. The identification of potential drug candidates through network analysis, with supporting evidence from EMRs, offers potential therapeutic strategies for targeting disease pathways and holds promise for delaying or preventing type 1 diabetes progression.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00125-026-06721-6","type":"journal-article","created":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T18:19:34Z","timestamp":1776277174000},"page":"1911-1934","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-tissue multi-omics integration reveals tissue-specific pathways, gene networks and drug candidates for type 1 diabetes"],"prefix":"10.1007","volume":"69","author":[{"given":"Montgomery","family":"Blencowe","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zara","family":"Saleem","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruoshui","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Margaret","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"I-Hsin","family":"Tseng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julian","family":"Wier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan","family":"Mutter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Florin","family":"Vaida","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Niina","family":"Sandholm","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Courtney","family":"Ackeifi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel L.","family":"Kaufman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xia","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,15]]},"reference":[{"key":"6721_CR1","doi-asserted-by":"publisher","unstructured":"Maahs DM, West NA, Lawrence JM, Mayer-Davis EJ (2010) Epidemiology of type 1 diabetes. 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Diabetologia 66(11):2075\u20132086. https:\/\/doi.org\/10.1007\/s00125-023-05991-8","journal-title":"Diabetologia"}],"container-title":["Diabetologia"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00125-026-06721-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00125-026-06721-6","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00125-026-06721-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T14:41:22Z","timestamp":1780584082000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00125-026-06721-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,15]]},"references-count":100,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2026,7]]}},"alternative-id":["6721"],"URL":"https:\/\/doi.org\/10.1007\/s00125-026-06721-6","relation":{},"ISSN":["0012-186X","1432-0428"],"issn-type":[{"value":"0012-186X","type":"print"},{"value":"1432-0428","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,15]]},"assertion":[{"value":"4 October 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 February 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"We thank the Cardiogenics Consortium for providing eQTL resources, which were supported by the European Union FP6 program (LSHM-CT-2006-037593) and the Leducq CAD Genomics Transatlantic Network. We thank J. Inshaw and J. Todd (both University of Oxford) for providing the GWAS datasets. The analysis of electronic health records for drug validation reported in this publication was supported in part by the OneFlorida+ Clinical Data Network, funded by the Patient-Centered Outcomes Research Institute numbers CDRN-1501-26692 and RI-CRN-2020-005, in part by the OneFlorida+ Cancer Control Alliance, funded by the Florida Department of Health\u2019s James and Esther King Biomedical Research Program number 4KB16, and in part by the University of Florida Clinical and Translational Science Institute and its Clinical and Translational Science Award (CTSA) hub partner, Florida State University, which are supported in part by three CTSA Program grants awarded on 15 August 2015, and renewed for five years on 2 July 2019, by the National Center for Advancing Translational Sciences of the National Institutes of Health. The UF\u2013FSU CTSA grant numbers are UL1TR001427, KL2TR001429 and TL1TR001428. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Patient-Centered Outcomes Research Institute (PCORI), its board of governors or methodology, the OneFlorida Clinical Research Consortium, the University of Florida\u2019s Clinical and Translational Science Institute, the Florida Department of Health, or the National Institutes of Health. We also acknowledge that some of the data were previously submitted as part of a Master\u2019s thesis for Montgomery Blencowe.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Acknowledgements"}},{"value":"All data supporting the findings of this study are available within the paper and the ESM.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Data availability"}},{"value":"This work was supported by Breakthrough T1D, previously known as JDRF (JDRF 2-SRA-2021-1028-S-B awarded to XY, DK and MB).","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Funding"}},{"value":"NS is a member of the Editorial Board of\n                      Diabetologia\n                      and declares this position as a potential competing interest in accordance with the journal\u2019s competing interests policy. All other authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Authors\u2019 relationships and activities"}},{"value":"MB and XY conceived and designed the research. MB, ZS, RL, MW, IT and JW analysed the data. MB, ZS and RL prepared the figures. MB, ZS, RL, MW, JW, SM, YG, FV, NS, DK, CA, IT and XY drafted and edited the manuscript. SM, YG, FV, NS, DK and CA participated in study design and provided data sources. MB, ZS, RL, MW, IT, JW, SM, YG, FV, NS, CA, DK and XY approved the final version of manuscript. MB and XY are responsible for the integrity of the work as a whole.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Contribution statement"}}]}}