Chih-Wei Liu, Lisa Bramer, Bobbie-Jo Webb-Robertson, Kathleen Waugh, Marian J. Rewers, Qibin Zhang (2017). Temporal expression profiling of plasma proteins reveals oxidative stress in early stages of Type 1 Diabetes progression. Journal of Proteomics.
Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC, United States
Applied Statistics & Computational Modeling, Pacific Northwest National Laboratory, Richland, WA, United States
Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, CO, United States
Department of Chemistry & Biochemistry, University of North Carolina at Greensboro, Greensboro, NC, United States
Blood markers other than islet autoantibodies are greatly needed to indicate the pancreatic beta cell destruction process as early as possible, and more accurately reflect the progression of Type 1 Diabetes Mellitus (T1D). To this end, a longitudinal proteomic profiling of human plasma using TMT-10plex-based LC-MS/MS analysis was performed to track temporal proteomic changes of T1D patients (n = 11) across 9 serial time points, spanning the period of T1D natural progression, in comparison with those of the matching healthy controls (n = 10). To our knowledge, the current study represents the largest (> 2000 proteins measured) longitudinal expression profiles of human plasma proteome in T1D research. By applying statistical trend analysis on the temporal expression patterns between T1D and controls, and Benjamini-Hochberg procedure for multiple-testing correction, 13 protein groups were regarded as having statistically significant differences during the entire follow-up period. Moreover, 16 protein groups, which play pivotal roles in response to oxidative stress, have consistently abnormal expression trend before seroconversion to islet autoimmunity. Importantly, the expression trends of two key reactive oxygen species-decomposing enzymes, Catalase and Superoxide dismutase were verified independently by ELISA.