Single Blood Sample Test Could Improve Efficiency of T1D Progression Screening


A team of Australian researchers created and validated a model that may boost efficiency of type 1 diabetes (T1D) progression screening.

A team of researchers devised a single finger prick blood test that could be used in place of multiple venous blood samples taken during an oral glucose tolerance test (OGTT) to improve screening efficiency for type 1 diabetes (T1D). Findings were published in Diabetologia.

“Accurate prediction of disease progression in individuals with presymptomatic T1D has potential to prevent ketoacidosis and accelerate development of disease-modifying therapies,” researchers wrote.

T1D is diagnosed when 2 or more islet autoantibodies (against insulin [IAA], GAD [GADA], insulinoma antigen-2 [IA-2A], and zinc transporter-8 [ZnT8A]) are detected in patients, while 3 stages of the disease—based on oral glucose tolerance and glycated hemoglobin (A1C)—have been identified.

“To differentiate between T1D stages 1, 2, and 3, autoantibody-positive individuals undergo OGTTs, in which glucose is measured at baseline and 120 min after the glucose load. OGTTs performed in a number of research studies have collected glucose values at the 30-, 60-, and 90-minute time points to further define risk characteristics,” the authors explained.

However, this process can be costly and time consuming, warranting the development of a more broadly applicable and easily administered tool to better assess risk progression from stage 1 or 2 to stage 3 T1D.

Using information from multiple T1D datasets, the investigators developed and validated models based on a single OGTT time point.

In one dataset, TrialNet, all individuals aged up to 45 years have a first-degree relative with T1D. Those aged up to 20 have a first-, second-, or third-degree relative with T1D and are screened for IAA, GADA, IA-2A and ZnT8A.

The researchers developed models using data from relatives with T1D, and validated models in those at high genetic risk of T1D (TEDDY cohort, among others). Models were also validated using data from the general population of Bavarian children enrolled in Fr1da.

“Models to predict risk of progression from stage 1 or 2 to stage 3 type 1 diabetes were developed using data from 1208 TrialNet participants who screened positive to at least 2 of IAA, GADA, IA-2A and ZnT8A and underwent an OGTT at the same time or at their next study visit,” authors wrote. The median (interquartile range) age of this training cohort was 9.3 years (6.3-13.3).

These models were then validated in a cohort of 864 TrialNet participants, whose median time of follow-up after their first OGTT was significantly greater than the training population. Risk scores from the validation cohort were also significantly higher.

Because 120-minute sampling is most relevant for presymptomatic screening, the researchers chose to focus analyses of additional at-risk populations at this time mark.

Overall, analyses revealed:

  • The Cox proportional hazards models combining plasma glucose, C-peptide, sex, age, body mass index, A1C, and IA-2A status predicted disease progression in all populations
  • In TrialNet, the AUC for receiver operating characteristic curves for models named M60, M90, and M120, based on sampling at 60, 90, and 120 min, was 0.760, 0.761, and 0.745, respectively
  • These were not significantly different from the AUC of 0.760 for the gold standard Diabetes Prevention Trial Risk Score, which requires 5 OGTT blood samples
  • In the TEDDY cohort, where only 120-min blood sampling had been performed, the M120 AUC was 0.865
  • In Fr1da, the M120 AUC of 0.742 was significantly greater than the M60 AUC of 0.615

“For several years, we have believed that multiple blood samples increased the accuracy of the oral glucose tolerance tests,” said John Wentworth, PhD, FRACP, a lead study author.

“What we found, is that the blood sample taken 2 hours after the glucose drink predicted a clinical diagnosis with high accuracy. Information collected from the study is expected to lead to improved screening efficiency and early diagnosis and treatment for T1D,” he added.

The authors explained their model could be integrated into current clinical workflows, improve clinical trial efficiency, and potentially identify autoantibody-positive individuals at greatest risk of ketoacidosis.

When the model was tested in an additional cohort, the Diabetes Prevention Trial–Type 1 (DPT-1), it was less accurate than traditional risk assessments. The esearchers hypothesized differences could be explained “by the requirement in DPT-1 for participants to screen positive for islet cell antibodies by indirect immunofluorescence, the use of different autoantibody and C-peptide assays in DPT-1 that at times were performed many years after sample collection, and, potentially, by changes in the contribution of environment to disease risk since the start of DPT-1.”

As participants in TrialNet, Fr1da, and TEDDY are largely of European descent, the performance of the model in other contexts remains unknown and marks a limitation to the study. Further testing is warranted to confirm the utility of the 120-min test in a general population setting, the authors concluded.


Bediaga NG, Li-Wai-Suen CSN, Haller MJ, et al. Simplifying prediction of disease progression in pre-symptomatic type 1 diabetes using a single blood sample. Diabetologia. Published online August 2, 2021. doi:10.1007/s00125-021-05523-2

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