학술논문
Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity
Document Type
Author
Nakayasu, Ernesto S; Bramer, Lisa M; Ansong, Charles; Schepmoes, Athena A; Fillmore, Thomas L; Gritsenko, Marina A; Clauss, Therese R; Gao, Yuqian; Piehowski, Paul D; Stanfill, Bryan A; Engel, Dave W; Orton, Daniel J; Moore, Ronald J; Qian, Wei-Jun; Sechi, Salvatore; Frohnert, Brigitte I; Toppari, Jorma; Ziegler, Anette-G; Lernmark, Åke; Hagopian, William; Akolkar, Beena; Smith, Richard D; Rewers, Marian J; Webb-Robertson, Bobbie-Jo M; Metz, Thomas O
Source
Cell Reports Medicine EXODIAB: Excellence of Diabetes Research in Sweden. 4(7)
Subject
Language
English
ISSN
2666-3791
Abstract
Type 1 diabetes (T1D) results from autoimmune destruction of β cells. Insufficient availability of biomarkers represents a significant gap in understanding the disease cause and progression. We conduct blinded, two-phase case-control plasma proteomics on the TEDDY study to identify biomarkers predictive of T1D development. Untargeted proteomics of 2,252 samples from 184 individuals identify 376 regulated proteins, showing alteration of complement, inflammatory signaling, and metabolic proteins even prior to autoimmunity onset. Extracellular matrix and antigen presentation proteins are differentially regulated in individuals who progress to T1D vs. those that remain in autoimmunity. Targeted proteomics measurements of 167 proteins in 6,426 samples from 990 individuals validate 83 biomarkers. A machine learning analysis predicts if individuals would remain in autoimmunity or develop T1D 6 months before autoantibody appearance, with areas under receiver operating characteristic curves of 0.871 and 0.918, respectively. Our study identifies and validates biomarkers, highlighting pathways affected during T1D development.