Identification of serum protein markers for type1 diabetes using mass-spectrometry techniques

Early studies have shown that individuals at risk for type 1 diabetes (T1D) can be identified by using a combination of genetic, metabolic and immunologic (autoantibodies against islet-cell antigens) markers. However, the currently available biomarkers have high false positive rate (low specificity) and cannot identify all subjects who will become diabetic (low sensitivity). In addition, biomarkers with high specificity prior to the appearance of autoantibodies are not available but would be of tremendous value for early disease prevention. In order to identify better and earlier disease prediction markers, we have been using a novel approach to study the entire collection of proteins in serum (proteomics) from a large prospective cohort (PANDA). This technique known as SELDI-TOF is a novel mass-spectrometry platform that enables a high throughput characterization of a large number of proteins simultaneously. This is the best protein biomarker discovery technique currently available. In our preliminary studies, we have demonstrated the high reproducibility of the technique and identified a total of 23 proteins as potential biomarkers for T1D. Eleven of the protein peaks were found to be lower in serum samples with T1D or multiple autoantibodies (Ab+) and 12 peaks showed higher concentration in Ab+/T1D versus antibody-negative subjects. Our preliminary studies demonstrated the power of our high throughput approach using modern technology. However, the preliminary findings have to be confirmed in a large cohort before it can be used in clinical trials. This project seeks to accomplish two important goals: 1) To perform SELDI-TOF analysis in a larger number of subjects to confirm the preliminary data and to select the best predictive markers. The expanded study may also identify novel protein markers as well. 2) To sequence the discovered biomarkers so that the exact identity and the function of the proteins can be determined.