Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity
(2023) In Cell Reports Medicine 4(7).- 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... (More)
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.
(Less)
- 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
LU
; Hagopian, William
; Akolkar, Beena
; Smith, Richard D
; Rewers, Marian J
; Webb-Robertson, Bobbie-Jo M
and Metz, Thomas O
(Less) - author collaboration
- organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Cell Reports Medicine
- volume
- 4
- issue
- 7
- article number
- 101093
- publisher
- Elsevier
- external identifiers
-
- scopus:85165290518
- pmid:37390828
- ISSN
- 2666-3791
- DOI
- 10.1016/j.xcrm.2023.101093
- language
- English
- LU publication?
- yes
- id
- f7b25941-20c9-40ab-adc5-a3a9cc8161d6
- date added to LUP
- 2023-07-06 11:20:42
- date last changed
- 2024-04-19 23:16:04
@article{f7b25941-20c9-40ab-adc5-a3a9cc8161d6,
abstract = {{<p>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.</p>}},
author = {{Nakayasu, Ernesto S and Bramer, Lisa M and Ansong, Charles and Schepmoes, Athena A and Fillmore, Thomas L and Gritsenko, Marina A and Clauss, Therese R and Gao, Yuqian and Piehowski, Paul D and Stanfill, Bryan A and Engel, Dave W and Orton, Daniel J and Moore, Ronald J and Qian, Wei-Jun and Sechi, Salvatore and Frohnert, Brigitte I and Toppari, Jorma and Ziegler, Anette-G and Lernmark, Åke and Hagopian, William and Akolkar, Beena and Smith, Richard D and Rewers, Marian J and Webb-Robertson, Bobbie-Jo M and Metz, Thomas O}},
issn = {{2666-3791}},
language = {{eng}},
number = {{7}},
publisher = {{Elsevier}},
series = {{Cell Reports Medicine}},
title = {{Plasma protein biomarkers predict the development of persistent autoantibodies and type 1 diabetes 6 months prior to the onset of autoimmunity}},
url = {{http://dx.doi.org/10.1016/j.xcrm.2023.101093}},
doi = {{10.1016/j.xcrm.2023.101093}},
volume = {{4}},
year = {{2023}},
}