Characterization of plasma metal profiles in Alzheimer's disease using multivariate statistical analysis.

Abstract

The exact cause of Alzheimer's disease (AD) and the role of metals in its etiology remain unclear. We have used an analytical approach, based on inductively coupled plasma mass spectrometry coupled with multivariate statistical analysis, to study the profiles of a wide range of metals in AD patients and healthy controls. AD cannot be cured and the lack of sensitive biomarkers that can be used in the early stages of the disease may contribute to this treatment failure. In the present study, we measured plasma levels of amyloid-β1-42(0.142±0.029μg/L)and furin(2.292±1.54μg/L), together with those of the metalloproteinases, insulin-degrading enzyme(1.459±1.14μg/L) and neprilysin(0.073±0.015μg/L), in order to develop biomarkers for AD. Partial least squares discriminant analysis models were used to refine intergroup differences and we discovered that four metals(Mn, Al, Li, Cu) in peripheral blood were strongly associated with AD. Aberration in homeostasis of these metals may alter levels of proteinases, such as furin, which are associated with neurodegeneration in AD and can be a used as plasma-based biomarkers.