A Type 1 Diabetes Genetic Risk Score Predicts Progression of Islet Autoimmunity and Development of Type 1 Diabetes in Individuals at Risk

Abstract

Objective: We tested the ability of a type 1 diabetes (T1D) genetic risk score (GRS) to predict progression of islet autoimmunity and T1D in at-risk individuals.

Research design and methods: We studied the 1,244 TrialNet Pathway to Prevention study participants (T1D patients' relatives without diabetes and with one or more positive autoantibodies) who were genotyped with Illumina ImmunoChip (median [range] age at initial autoantibody determination 11.1 years [1.2-51.8], 48% male, 80.5% non-Hispanic white, median follow-up 5.4 years). Of 291 participants with a single positive autoantibody at screening, 157 converted to multiple autoantibody positivity and 55 developed diabetes. Of 953 participants with multiple positive autoantibodies at screening, 419 developed diabetes. We calculated the T1D GRS from 30 T1D-associated single nucleotide polymorphisms. We used multivariable Cox regression models, time-dependent receiver operating characteristic curves, and area under the curve (AUC) measures to evaluate prognostic utility of T1D GRS, age, sex, Diabetes Prevention Trial-Type 1 (DPT-1) Risk Score, positive autoantibody number or type, HLA DR3/DR4-DQ8 status, and race/ethnicity. We used recursive partitioning analyses to identify cut points in continuous variables.

Results: Higher T1D GRS significantly increased the rate of progression to T1D adjusting for DPT-1 Risk Score, age, number of positive autoantibodies, sex, and ethnicity (hazard ratio [HR] 1.29 for a 0.05 increase, 95% CI 1.06-1.6; P = 0.011). Progression to T1D was best predicted by a combined model with GRS, number of positive autoantibodies, DPT-1 Risk Score, and age (7-year time-integrated AUC = 0.79, 5-year AUC = 0.73). Higher GRS was significantly associated with increased progression rate from single to multiple positive autoantibodies after adjusting for age, autoantibody type, ethnicity, and sex (HR 2.27 for GRS >0.295, 95% CI 1.47-3.51; P = 0.0002).

Conclusions: The T1D GRS independently predicts progression to T1D and improves prediction along T1D stages in autoantibody-positive relatives.

Figure 1

Time to T1D in patients’ relatives who were initially without diabetes and islet autoantibody–positive (Ab+), by DPT-1 Risk Score (≤7 vs. >7), number of positive autoantibodies (i.e., single vs. multiple autoantibody positivity), and T1D GRS (<0.250 vs. ≥0.250) (P < 0.0001). While the T1D GRS did not further increase the predictive ability in the group with DPT-1 Risk Score >7, which already had high risk of T1D, it was able to stratify risk in individuals with DPT-1 Risk Score <7, with either a single positive autoantibody or multiple positive autoantibodies. DPTRS, DPT-1 Risk Score.

Figure 2

Comparison of 2-year AUC for models to predict progression to T1D in participants with DPT-1 Risk Scores ≤7. The clinical model (i.e., DPT-1 Risk Score, age, and islet autoantibody number) in addition to HLA had a 2-year AUC of 0.78, compared with 0.82 for the clinical model in addition to GRS (P < 0.0001).

Figure 3

Time to T1D in multiple islet autoantibody–positive (Ab+) relatives, by DPT-1 Risk Score (≤7 vs. >7), age (<10 vs. ≥10 years), and T1D GRS (<0.250 vs. ≥0.250) (P = 0.0001). While the T1D GRS did not further increase the predictive ability in participants with DPT-1 Risk Score >7, it did stratify risk in individuals with DPT-1 Risk Score <7, aged <10 years or ≥10 years. DPTRS, DPT-1 Risk Score.

Figure 4

Time from single to multiple islet autoantibody positivity (Ab+) in relatives of patients, by age (<35 vs. ≥35 years) and T1D GRS group (<0.295 vs. ≥0.295) (P = 0.0001). While the T1D GRS did not further increase the predictive ability in participants aged ≥35 years, it was able to stratify risk in individuals aged <35 years.