2023-06-29 パシフィック・ノースウェスト国立研究所(PNNL)
◆この研究は、糖尿病の予測や治療の進歩につながる可能性があります。今後の研究で追加の血液サンプルを分析し、1型糖尿病の発症を予測する手段を開発する予定です。
<関連情報>
- https://www.pnnl.gov/news-media/proteins-predict-significant-step-toward-development-diabetes
- https://www.cell.com/cell-reports-medicine/fulltext/S2666-3791(23)00212-4
血漿タンパク質バイオマーカーは自己免疫発症の6ヵ月前に持続性自己抗体と1型糖尿病の発症を予測する Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity
Ernesto S. Nakayasu,Lisa M. Bramer,Charles Ansong,Athena A. Schepmoes,Thomas L. Fillmore,Marina A. Gritsenko,Therese R. Clauss,Yuqian Gao,Paul D. Piehowski,Bryan A. Stanfill,Dave W. Engel,Daniel J. Orton,Ronald J. Moore,Wei-Jun Qian,Salvatore Sechi,Brigitte I. Frohnert,Jorma Toppari,Anette-G. Ziegler,Åke Lernmark,William Hagopian,Beena Akolkar,Richard D. Smith,Marian J. Rewers,Bobbie-Jo M. Webb-Robertson,Thomas O. Metz,The TEDDY Study Group
Cell Reports Medicine Published:June 29, 2023
DOI:https://doi.org/10.1016/j.xcrm.2023.101093
Highlights
•Untargeted proteomics across 184 individuals identifies 376 regulated proteins
•Extracellular matrix and antigen presentation are regulated pre-type 1 diabetes
•Targeted proteomics validates 83 biomarkers in 990 individuals
•Machine learning predicts islet autoimmunity and type 1 diabetes development
Summary
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.
