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We conducted cross-sectional flow cytometric immune profiling on peripheral blood from 826 individuals (stage 3 T1D, their first-degree relatives, those with \u22652 islet autoantibodies, and autoantibody-negative unaffected controls). We constructed an immune age predictive model in unaffected participants and observed accelerated immune aging in T1D. We used generalized additive models for location, shape, and scale to obtain age-corrected data for flow cytometry and complete blood count readouts, which can be visualized in our interactive portal (ImmScape); 46 parameters were significantly associated with age only, 25 with T1D only, and 23 with both age and T1D. Phenotypes associated with accelerated immunological aging in T1D included increased CXCR3\n                    <jats:sup>+<\/jats:sup>\n                    and programmed cell death 1\u2013positive (PD-1\n                    <jats:sup>+<\/jats:sup>\n                    ) frequencies in naive and memory T cell subsets, despite reduced PD-1 expression levels on memory T cells. Phenotypes associated with T1D after age correction were predictive of T1D status. Our findings demonstrate advanced immune aging in T1D and highlight disease-associated phenotypes for biomarker monitoring and therapeutic interventions.\n                  <\/jats:p>","DOI":"10.1172\/jci.insight.170767","type":"journal-article","created":{"date-parts":[[2023,7,27]],"date-time":"2023-07-27T12:00:34Z","timestamp":1690459234000},"source":"Crossref","is-referenced-by-count":37,"title":["Human immune phenotyping reveals accelerated aging in type 1 diabetes"],"prefix":"10.1172","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2090-0877","authenticated-orcid":true,"given":"Melanie R.","family":"Shapiro","sequence":"first","affiliation":[{"name":"Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and"},{"name":"Diabetes Institute 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