Abstract
Today diagnosis of Alzheimer's disease (AD) is limited to the mental and cognitive examinations of patients and impedes preventive screening. Moreover, the diagnosis of patients is particularly difficult at the early stage of the disease when only minor cognitive impairment meets the criteria for being classified as dementia. These patients are generally considers to have mild cognitive impairment (MCI). The onset and/or progression of brain degeneration in MCI and AD have been linked to abnormal interactions between brain proteins resulting in the their aggregation. Unfortunately, the use of biomarkers to detect aggregated proteins has thus far not succeeded into early detection. As a consequence, new approaches are required to support existing clinical characterization. We recently investigated in two independent studies the potential of the Ultrasonic Resonator Technology (URT) for the diagnosis of AD. A clear differentiation of AD from healthy controls was obtained by comparison of the hydration profiles over increasing temperature. In the present study, we further evaluated the potential of URT in particular for the detection of very early AD stages. We therefore investigated a new set of samples from patients with MCI and age–matched and educational–matched healthy controls and characterized the disease specific hydration behaviour, during thermal destabilization. CSF samples classified according to Clinical Dementia Rating from volunteer subjects were obtained by lumbal puncture of healthy controls and individuals with MCI. All ultrasonic measurements were performed using the ResoScan® System. We could demonstrate the sensitivity of URT by detecting early stages of AD. The hydration behavior of the MCI group differed significantly from the control group. Quantification of the difference based on the selection of the hydration behavior at six defined temperatures allowed differentiation with more than 85% significance by simple cluster analysis. These results suggests that URT represents a new technical approach for the characterization of early stages of neurodegenerative disorders and may provide a new entry point for diagnostic strategies of misfolding disorders.
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