Type 2 diabetes affects approximately 6% of the global population and it is estimated that as many as one half of diabetics are undiagnosed. Current OGTT and FBS tests for diabetes require fasting and are not always reproducible, and a least effective for diagnosing diabetes in more elderly individuals, who are the most at risk. Thus there is a need for a simpler and more reliable assay for diagnosis of diabetes, and particularly pre-diabetes without the need for fasting, which is the overall goal of this proposal. This application is thus based upon the assumption that the composition of the plasma proteome reflects the general physiologic state of the human body, thus quantitative proteomic measurements of the plasma proteome can yield information that is diagnostic for a healthy or a disease state, in this case diabetes.
The specific aims of this R21/R33 proposal are: 1) to develop a robust, sensitive, reproducible and high-throughput platform for quantitative plasma protein profiling, based upon our recently developed method for solid-phase extraction of glycopeptides (SPEG) and peptide detection and identification by mass spectrometry (MS); 2) the application of software tools for determination of individual peptide features or sets of features that collectively distinguish between plasma samples derived from individuals with normal glucose tolerance (NOT), impaired glucose tolerance (IGT) and newly diagnosed type 2 diabetes (to be supplied by the NIDDK), and the subsequent identification of peptide sequences by tandem MS; 3) validation of candidate markers that can reliably distinguish between NGT, IGT and newly diagnosed type 2 diabetes and determination of their absolute concentration ranges in a large sample pool by use of synthetic peptide standards and stable isotope labeling; 4) the generation of immunological reagents to validated markers and their testing in immunoassays for distinguishing between NGT, IGT, and newly diagnosed type 2 diabetes. SPEG has been found to be a highly effective method for plasma analysis since most blood proteins are glycosylated, while albumin (approximately 50% total plasma protein) is not and is thus transparent to the analysis. The most abundant proteins in plasma also produce few glycopeptides upon proteolysis. Thus liquid chromatography MS analysis with prior SPEG enrichment allows for at least a 100-fold increase in sensitivity over whole serum analysis. This facilitates the monitoring of potential candidate disease markers at the low ng/ml concentration exhibited by other known clinical markers such as the prostate cancer marker, PSA.
