In addition to the classical proteomics approach described above, the alternative proteomics approach has also been applied to DN using CE-TOF MS to differentiate urinary proteome profile of patients with type 2 diabetes from that of the healthy controls (84). The urinary polypeptide pattern of patients with diabetes significantly differs from the normal. Moreover, there is a specific polypeptide pattern of "diabetic renal damage" in patients with high-grade albuminuria (urine albumin >100 mg/L). The urinary polypeptide profiles in diabetic patients can be classified into four types. Type A pattern is typically found in the diabetic state and the occurrence in healthy subjects is low. Type B pattern represents polypeptide profile observed mainly in healthy subjects and the frequency in patients with diabetes is low. Types C and D are the typical patterns of markers for diabetic renal damage of which the frequency in diabetes is increased and decreased, respectively (84). These data underscore the usefulness of the alternative proteomics approach in clinical diagnostics and biomarker discovery.
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