Large-scale prospective T cell function assays in shipped, unfrozen blood samples:experiences from the multicenter TRIGR trial

Broad consensus assigns T lymphocytes fundamental roles in inflammatory, infectious, and autoimmune diseases. However, clinical investigations have lacked fully characterized and validated procedures, equivalent to those of widely practiced biochemical tests with established clinical roles, for measuring core T cell functions. The Trial to Reduce Insulin-dependent diabetes mellitus in the Genetically at Risk (TRIGR) type 1 diabetes prevention trial used consecutive measurements of T cell proliferative responses in prospectively collected fresh heparinized blood samples shipped by courier within North America. In this article, we report on the quality control implications of this simple and pragmatic shipping practice and the interpretation of positive- and negative-control analytes in our assay. We used polyclonal and postvaccination responses in 4,919 samples to analyze the development of T cell immunocompetence. We have found that the vast majority of the samples were viable up to 3 days from the blood draw, yet meaningful responses were found in a proportion of those with longer travel times. Furthermore, the shipping time of uncooled samples significantly decreased both the viabilities of the samples and the unstimulated cell counts in the viable samples. Also, subject age was significantly associated with the number of unstimulated cells and T cell proliferation to positive activators. Finally, we observed a pattern of statistically significant increases in T cell responses to tetanus toxin around the timing of infant vaccinations. This assay platform and shipping protocol satisfy the criteria for robust and reproducible long-term measurements of human T cell function, comparable to those of established blood biochemical tests. We present a stable technology for prospective disease-relevant T cell analysis in immunological diseases, vaccination medicine, and measurement of herd immunity

Growth and development of islet autoimmunity and type 1 diabetes in children genetically at risk

Aims/hypothesis: We aimed to evaluate the relationship between childhood growth measures and risk of developing islet autoimmunity (IA) and type 1 diabetes in children with an affected first-degree relative and increased HLA-conferred risk. We hypothesised that being overweight or obese during childhood is associated with a greater risk of IA and type 1 diabetes. Methods: Participants in a randomised infant feeding trial (N = 2149) were measured at 12 month intervals for weight and length/height and followed for IA (at least one positive out of insulin autoantibodies, islet antigen-2 autoantibody, GAD autoantibody and zinc transporter 8 autoantibody) and development of type 1 diabetes from birth to 10–14 years. In this secondary analysis, Cox proportional hazard regression models were adjusted for birthweight and length z score, sex, HLA risk, maternal type 1 diabetes, mode of delivery and breastfeeding duration, and stratified by residence region (Australia, Canada, Northern Europe, Southern Europe, Central Europe and the USA). Longitudinal exposures were studied both by time-varying Cox proportional hazard regression and by joint modelling. Multiple testing was considered using family-wise error rate at 0.05. Results: In the Trial to Reduce IDDM in the Genetically at Risk (TRIGR) population, 305 (14.2%) developed IA and 172 (8%) developed type 1 diabetes. The proportions of children overweight (including obese) and obese only were 28% and 9% at 10 years, respectively. Annual growth measures were not associated with IA, but being overweight at 2–10 years of life was associated with a twofold increase in the development of type 1 diabetes (HR 2.39; 95% CI 1.46, 3.92; p \u3c 0.001 in time-varying Cox regression), and similarly with joint modelling. Conclusions/interpretation: In children at genetic risk of type 1 diabetes, being overweight at 2–10 years of age is associated with increased risk of progression from multiple IA to type 1 diabetes and with development of type 1 diabetes, but not with development of IA. Future studies should assess the impact of weight management strategies on these outcomes. Trial registration: ClinicalTrials.gov NCT00179777 Graphical abstract: [Figure not available: see fulltext.