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Expert Rev Proteomics. 2019 Jul;16(7):569-582. doi: 10.1080/14789450.2019.1634548. Epub 2019 Jun 24.

The role of proteomics in assessing beta-cell dysfunction and death in type 1 diabetes.

Author information

1
a Biological Sciences Division , Pacific Northwest National Laboratory , Richland , WA , USA.
2
b Center for Diabetes and Metabolic Diseases, Herman B. Wells Center for Pediatric Research, Department of Pediatrics , Indiana University School of Medicine , Indianapolis , IN , USA.
3
c ULB Center for Diabetes Research, Medical Faculty , Université Libre de Bruxelles , Brussels , Belgium.

Abstract

Introduction: Type 1 diabetes (T1D) is characterized by autoimmune-induced dysfunction and destruction of the pancreatic beta cells. Unfortunately, this process is poorly understood, and the current best treatment for type 1 diabetes is the administration of exogenous insulin. To better understand these mechanisms and to develop new therapies, there is an urgent need for biomarkers that can reliably predict disease stage. Areas covered: Mass spectrometry (MS)-based proteomics and complementary techniques play an important role in understanding the autoimmune response, inflammation and beta-cell death. MS is also a leading technology for the identification of biomarkers. This, and the technical difficulties and new technologies that provide opportunities to characterize small amounts of sample in great depth and to analyze large sample cohorts will be discussed in this review. Expert opinion: Understanding disease mechanisms and the discovery of disease-associated biomarkers are highly interconnected goals. Ideal biomarkers would be molecules specific to the different stages of the disease process that are released from beta cells to the bloodstream. However, such molecules are likely to be present in trace amounts in the blood due to the small number of pancreatic beta cells in the human body and the heterogeneity of the target organ and disease process.

KEYWORDS:

beta cell dysfunction and death; neoantigens; type 1 diabetes

PMID:
31232620
PMCID:
PMC6628911
[Available on 2020-07-01]
DOI:
10.1080/14789450.2019.1634548

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