Abstract
Significant progress has been made in elucidating genetic risk factors influencing Type 1 diabetes (T1D); however, features other than genetic variants that initiate and/or accelerate islet autoimmunity that lead to the development of clinical T1D remain largely unknown. We hypothesized that genetic and environmental risk factors can both contribute to T1D through dynamic alterations of molecular interactions in physiologic networks. To test this hypothesis, we utilized longitudinal blood transcriptomic profiles in The Environmental Determinants of Diabetes in the Young (TEDDY) study to generate gene co-expression networks. In network modules that contain immune response genes associated with T1D, we observed highly dynamic differences in module connectivity in the 600 days (~ 2 years) preceding clinical diagnosis of T1D. Our results suggest that gene co-expression is highly plastic and that connectivity differences in T1D-associated immune system genes influence the timing and development of clinical disease.
Highlights
Significant progress has been made in elucidating genetic risk factors influencing Type 1 diabetes (T1D); features other than genetic variants that initiate and/or accelerate islet autoimmunity that lead to the development of clinical T1D remain largely unknown
T1D is typically preceded by islet autoimmunity, defined by persistence of at least one of three islet autoantibodies—insulin autoantibody (IAA), insulinoma antigen-2 autoantibody (IA-2A), or glutamic acid decarboxylase autoantibody (GADA)
To better understand the dynamic nature of co-expression networks and their role in T1D, we examined gene expression from participants in The Environmental Determinants of Diabetes in the Young (TEDDY) study[9]
Summary
Significant progress has been made in elucidating genetic risk factors influencing Type 1 diabetes (T1D); features other than genetic variants that initiate and/or accelerate islet autoimmunity that lead to the development of clinical T1D remain largely unknown. We hypothesized that genetic and environmental risk factors can both contribute to T1D through dynamic alterations of molecular interactions in physiologic networks To test this hypothesis, we utilized longitudinal blood transcriptomic profiles in The Environmental Determinants of Diabetes in the Young (TEDDY) study to generate gene co-expression networks. Staging of disease progression has been defined by both the presence and number of autoantibodies[3] Both islet autoimmunity and development of clinical T1D are influenced by genetic and environmental factors[4,5]. Gene expression should be obtained from pre-clinical subjects (those “at risk”) and followed over time This optimal study design would provide information on the transitions in disease stages (from “at risk” to “disease initiation” to “disease progression” to “disease onset”) and the changes in network topology, thereby providing insight on the features leading from risk to islet autoimmunity and, T1D. From an initial cohort of over 8000 children, TEDDY has obtained samples at multiple time points prior to development of islet autoimmunity and T1D
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