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Title: Serum biomarkers for diagnosis and prediction of type 1 diabetes

Journal Article · · Translational Research
 [1];  [1];  [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Here, Type 1 diabetes (T1D) culminates in the autoimmune destruction of the pancreatic β-cells, leading to insufficient production of insulin and development of hyperglycemia. Serum biomarkers including a combination of glucose, glycated molecules, c-peptide, and autoantibodies have been well established for the diagnosis of T1D. However, these molecules often mark a late stage of the disease when ~90% of the pancreatic insulin-producing β-cells have already been lost. With the prevalence of T1D increasing worldwide and because of the physical and psychological burden induced by this disease, there is a great need for prognostic biomarkers to predict T1D development or progression. This would allow us to identify individuals at high risk for early prevention and intervention. Therefore, considerable efforts have been dedicated to the understanding of disease etiology and the discovery of novel biomarkers in the last few decades. The advent of high-throughput and sensitive ‘-omics’ technologies for the study of proteins, nucleic acids, and metabolites have allowed large scale profiling of protein expression and gene changes in T1D patients relative to disease-free controls. In this review, we briefly discuss the classical diagnostic biomarkers of T1D but mainly focus on the novel biomarkers that are identified as markers of β-cell destruction and screened with the use of state-of-the-art ‘-omics’ technologies.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
DP3 DK110844; UC4 DK104167; AC05-76RL01830
OSTI ID:
1464493
Report Number(s):
PNNL-SA-134879; PII: S1931524418301105
Journal Information:
Translational Research, Vol. 201; ISSN 1931-5244
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 29 works
Citation information provided by
Web of Science

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