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Temporal Intra-Individual Variation of Immunological Biomarkers in Type 1 Diabetes Patients: Implications for Future Use in Cross-Sectional Assessment
Authors:Ghanashyam Sarikonda  Jeremy Pettus  Sowbarnika Sachithanantham  Sonal Phatak  Jacqueline F Miller  Lakshmi Ganesan  Ji Chae  Ronna Mallios  Steve Edelman  Bjoern Peters  Matthias von Herrath
Institution:1. Type 1 Diabetes Center, La Jolla Institute for Allergy and Immunology, La Jolla, California, United States of America.; 2. University of California San Diego, San Diego, California, United States of America.; 3. Type 1 Diabetes R&D Center, Novo Nordisk Inc., Seattle, Washington, United States of America.; University of Siena, Italy,
Abstract:Multiple immune parameters such as frequencies of autoreactive CD4+, CD8+ T-cells and CD4+CD25+Foxp3+ T-cells have been explored as biomarkers in human T1D. However, intra-individual temporal variation of these parameters has not been assessed systematically over time. We determined the variation in each of these parameters in a cohort of T1D and healthy donors (HDs), at monthly intervals for one year. Despite low intra- and inter-assay co-efficient of variation (CV), mean CVs for each of the immune parameters were 119.1% for CD4+ T-cell-derived IFN-γ, 50.44% for autoreactive CD8+ T-cells, and 31.24% for CD4+CD25+Foxp3+ T-cells. Further, both HDs and T1D donors had similar CVs. The variation neither correlated with BMI, age, disease duration or insulin usage, nor were there detectable cyclical patterns of variation. However, averaging results from multiple visits for an individual provided a better estimate of the CV between visits. Based on our data we predict that by averaging values from three visits a treatment effect on these parameters with a 50% effect size could be detected with the same power using 1.8–4-fold fewer patients within a trial compared to using values from a single visit. Thus, our present data contribute to a more robust, accurate endpoint design for future clinical trials in T1D and aid in the identification of truly efficacious therapies.
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