Clinical Proteomics in Application to Predictive Diagnostics and Personalized Treatment of Diabetic Patients

Olga      Golubnitschaja

doi:10.2174/157016408783955092

Abstract

Healthcare of permanently growing cohort of diabetic patients is a serious economical problem in most industrialized countries including China and India. Diabetes mellitus (DM) frequently results in diverse severe complications, such as retinopathy, nephropathy, silent ischemia, dementia, and cancer. Oxidative damage to DNA is well documented for DM-patients. Individual sensitivity to oxidative stress varies among DM-patients and results in a cascade of chronic complications appearing as the “domino-effect”. Proliferative diabetic retinopathy is an early indicator for individual predisposition to chronic complications responsible for the majority of morbidity and mortality. In DM, changes in mitochondrial protein repertoire result in premature aging and plenty of pathologies including neurodegeneration and cancer. In diabetic care, much attention is focused on renal and urinary proteomics. However, the diagnosis of nephropathy can be reliably made only in patients with macroalbuminuria in the presence of diabetic retinopathy. Since 1/3-part of urinary proteome consists of plasma proteins and changes in plasma proteome occur up-stream towards chronic damage of organ systems, plasma proteomics possesses particular predictive power. Promising approach of a combination of plasma proteome and gene expression profiling in circulating leukocytes is currently discussed for development of potent diagnostic/ therapeutic targets. Estimation of gelatinase activity in serum combined with expression profiling of selected stress proteome genes in circulating leukocytes has been proposed for predictive imaging system of chronic DM-complications that allows initiation of appropriate therapy and consequent planning of personalized treatment. Expected long-term deliverables of nutri-proteomics is a nutrition individually optimized for prevention of chronic DM-complications.

Keywords: Chronic complications, cancer, predictive diagnostics, urinary/ blood/ nutritional proteomics, interactomics, mitochondrial/stress proteome, aging/ longevity, personalized treatment