Abstract
Better understanding of the early events in the development of type 1 diabetes is needed to improve prediction and monitoring of the disease progression during the substantially heterogeneous presymptomatic period of the beta cell damaging process. To address this concern, we used mass spectrometry-based proteomics to analyse longitudinal pre-onset plasma sample series from children positive for multiple islet autoantibodies who had rapidly progressed to type 1 diabetes before 4 years of age (n = 10) and compared these with similar measurements from matched children who were either positive for a single autoantibody (n = 10) or autoantibody negative (n = 10). Following statistical analysis of the longitudinal data, targeted serum proteomics was used to verify 11 proteins putatively associated with the disease development in a similar yet independent and larger cohort of children who progressed to the disease within 5 years of age (n = 31) and matched autoantibody negative children (n = 31). These data reiterated extensive age-related trends for protein levels in young children. Further, these analyses demonstrated that the serum levels of two peptides unique for apolipoprotein C1 (APOC1) were decreased after the appearance of the first islet autoantibody and remained relatively less abundant in children who progressed to type 1 diabetes, in comparison to autoantibody negative children.
| Original language | English |
|---|---|
| Article number | 15941 |
| Number of pages | 11 |
| Journal | Scientific Reports |
| Volume | 13 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 24 Sept 2023 |
| MoE publication type | A1 Journal article-refereed |
Funding
The authors are grateful to the DIPP families for their participation and the clinical personnel for excellent collaboration, working with the families and obtaining the samples and clinical data for the study. We also thank the staff of the DIPP Immunogenetics laboratory at University of Turku and the DIPP autoantibody laboratory at University of Oulu. The mass spectrometry analyses presented in this work were performed at the Proteomics Core Facility of the Turku Bioscience Centre that belongs to Biocenter Finland infrastructure network. We thank Pekka Haapaniemi (Proteomics Facility, Turku Bioscience Centre, Finland) for his invaluable help in sample preparation, and also other facility members for the excellent technical support. L. C. and H. L. acknowledges the computational resources provided by the Aalto Science-IT project and CSC—IT Center for Science, Finland. Figure was created with Biorender.com. The authors are grateful to the DIPP families for their participation and the clinical personnel for excellent collaboration, working with the families and obtaining the samples and clinical data for the study. We also thank the staff of the DIPP Immunogenetics laboratory at University of Turku and the DIPP autoantibody laboratory at University of Oulu. The mass spectrometry analyses presented in this work were performed at the Proteomics Core Facility of the Turku Bioscience Centre that belongs to Biocenter Finland infrastructure network. We thank Pekka Haapaniemi (Proteomics Facility, Turku Bioscience Centre, Finland) for his invaluable help in sample preparation, and also other facility members for the excellent technical support. L. C. and H. L. acknowledges the computational resources provided by the Aalto Science-IT project and CSC—IT Center for Science, Finland. Figure 1 was created with Biorender.com.