Biological Sciences Division
Biomarkers for Type 1 Diabetes Found Using Proteomics
Research highlighted in proteomic journal
Researchers at Pacific Northwest National Laboratory recently conducted a proteomics study to identify novel protein biomarkers that potentially could be used to predict type 1 diabetes with higher sensitivity and specificity than those biomarkers currently available. Their results have been published in the February 2008 Journal for Proteome Research and were highlighted in that issue's Research Profiles.
The researchers used capillary liquid chromatography-mass spectrometry analyses to analyze the plasma proteomes of 10 healthy individuals and 10 patients recently diagnosed with type 1 diabetes. They then applied the accurate mass and time tag strategy developed at PNNL to quantitate proteins in the samples.
From these and subsequent steps, the researchers found five candidate biomarkers that differed in abundance between the patients and control individuals. However, they could not yet determine whether these five proteins are predictive or diagnostic of type 1 diabetes. They are conducting follow-up studies with more samples to confirm and extend the results of their study.
The research team included Tom Metz, Weijun Qian, Jon Jacobs, Marina Gritsenko, Ron Moore, Ashoka Polpitiya, Matt Monroe and Dick Smith, all PNNL, and Patricia Mueller, Centers for Disease Control. This work was supported by the National Institutes of Health, while portions of the research were supported by the NIH National Center for Research Resources. Work was performed in the Environmental Molecular Sciences Laboratory, a national scientific user facility located at PNNL and sponsored by the U.S. Department of Energy Office of Biological and Environmental Research.
Metz TO, W-J Qian, JM Jacobs, MA Gritsenko, RJ Moore, AD Polpitiya, ME Montroe, DG Camp II, PW Mueller, and RD Smith. 2008. "Application of proteomics in the discovery of candidate protein biomarkers in a diabetes autoantibody standardization program sample subset." Journal of Proteome Research 7(2):698-707.