The
detection of early markers is the key issue in predicting the outcome of
inflammatory diseases such as type 1 diabetes and atherosclerosis. Whilst
biochemical testing approaches have improved prediction of inflammatory
diseases, validated biomarkers with better diagnostic specificities are still
needed. Currently, majority of the disease-related proteomics studies have
focused on their endpoints. The work presented in this thesis includes the
first comprehensive proteomics analyses on serum samples collected from two
unique Finnish longitudinal cohorts, namely The Diabetes Prediction and
Prevention Project (DIPP) and The Cardiovascular Risk in Young Finns Study
(YFS), to identify early markers associated with type 1 diabetes and carotid
atherosclerosis.

Using mass
spectrometry (MS)-based quantitative serum proteomics, profiling was carried
out to the study temporal variation in pre-diabetic samples and early markers
of plaque formation with the T1D and YFS cohorts, respectively. The analyses
revealed consistent differences in the abundance of a number of proteins in
subjects having an ongoing asymptomatic changes, several of which are
functionally relevant to the disease process. Taken together, the discovered
markers are candidates for further validation studies in an independent cohorts
and may be used to characterize an increased risk, progression and early onset
of these diseases.