The inadequate metabolic control in diabetes mellitus (DM), a high prevalence disease, lead to chronic macro and microvascular complications in long term, with impact in the morbility and mortality of this population. Retinopathy, nefropathy, cardiovascular disautonomic neuropathy, distal neuropathy and diabetic encephalopathy (DE) are among the DM clinical complications, and DE may lead to cognitive impairment. The aim of the present study is to identify potential markers in peripheral blood and urine that allow the selection of DM patients with higher risk to develop cognitive decline. Approximately 1,000 individuals with type 2 DM (T2D) will be included in the study and will be follow up at least for 12 months. The microvascular diabetic complications including renal disease, distal symmetric neuropathy, cardiovascular dysautonomy and retinopathy will be evaluated. The miR profile by NGS and proteomic profile by MALDI-TOF-MS of peripheral blood, urine and extracelular vesicles isolated from these fluids will be determined. The distribution of APOE polymorphisms will be analyzed in the groups stratified by clinical complications. The generated results will be analyzed by machine learning approach for the identification of markers associated with DE. The selected targets will be followed longitudinally to analyze their association with the progression of cognitive decline. A patent will be required if a target or a combination of targets present high accuracy to predict the cognitive decline in T2D.
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