Human immune phenotyping reveals accelerated aging in type 1 diabetes

The proportions and phenotypes of immune cell subsets in peripheral blood undergo continual and dramatic remodeling throughout the human life span, which complicates efforts to identify disease-associated immune signatures in type 1 diabetes (T1D). We conducted cross-sectional flow cytometric immune profiling on peripheral blood from 826 individuals (stage 3 T1D, their first-degree relatives, those with ≥2 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+ and programmed cell death 1–positive (PD-1+) 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.


Figure S3 .
Figure S3.T cell panel gating.Gating based on time, forward scatter (FSC), and side scatter (SSC) was performed to select stably

Figure S7 .
Figure S7.Dendrogram of phenotype age trajectories.Hierarchical clustering of the fitted

Figure S8 .
Figure S8.Age-wise trajectory differences.The differences in the estimated trajectory for T1D

Figure S10 .
Figure S10.Immune aging model with CMV status.(A) Predicted immunological age is shown for all CTR (gray), AAb-REL (blue),

Figure S11 .
Figure S11.Residual age analysis in AAb-CTR and REL under 30 years of age.(A) Residual immunological age is calculated as

Figure S12 .
Figure S12.Immune aging model compared to IMM-AGE.(A) The IMM-AGE score

Figure S14 .
Figure S14.Raw data shows CXCR3 and PD-1 expression is increased on naïve T cells but decreased on memory T cell subsets
Age-adjusted quantile values of PD-1 MFI on (B) CD4 Tem, (C) CD4 Temra, (D) CD4 Tcm, and (E) CD8 Tcm of AAb-CTR and AAb-REL according to rs6422701 genotype.Significant p-values shown on graph.Testing was done using a Kruskal Wallis test with a post-hoc Dunn's test.

Table S3 . Multivariable model of disease-relevant features with residual age in T1D, CTR and REL individuals. Standardized
Low Normal High Adj.p Low Normal High Adj.p Low Normal High Adj.p Low Normal High Adj.p *Provision of height and weight was voluntary; thus, these data are available for some, but not all study subjects.† Fisher's exact test, ‡ Kruskal Wallis test A 70 participants in CTR, 23 participants in REL, 5 participants in RSK, 37 participants in T1D are missing.B 1 participants in T1D are missing.C 42 participants in CTR, 7 participants in REL, 1 participants in T1D are missing.D 148 participants in CTR, 62 participants in REL, 11

Table S6 .
QTL analysis.Linear regression analysis of associations between 277 T1D genetic risk loci and 172 GAMLSS-corrected flow cytometric parameters, considering T1D status, sex, and population admixture as covariates.Beta coefficients are shown in the context of the T1D risk allele.False discovery rate (FDR) for total genotype and phenotype combinations determined by Benjamini-Hochberg method.Data are available in a supplementary Excel file.