Prediction of Alzheimer's disease using a cerebrospinal fluid pattern of C-terminally truncated beta-amyloid peptides.

BACKGROUND: Identifying individuals at high risk of developing Alzheimer's disease (AD) is important for future therapeutic strategies, and there is a clinical need for diagnostic biomarkers to identify incipient AD.

OBJECTIVE: The aim of the present study was to investigate if the AD-associated Abeta peptide pattern recently found in cerebrospinal fluid (CSF) could discriminate between patients with incipient AD and those with stable mild cognitive impairment (MCI) by analyzing CSF from patients with MCI at baseline.

METHODS: The levels of Abeta(1-37, -38, -39, -40, -42) were analyzed by Abeta-SDS-PAGE/immunoblot in CSF from 19 healthy controls, 25 patients with stable MCI and from 25 patients with MCI who later developed AD during 4- to 6-year follow-up.

RESULTS: All healthy controls and 20 out of 22 patients who developed AD were correctly classified by their baseline Abeta peptide pattern. In 9 out of 25 stable MCI patients, the pattern indicated incipient AD in spite of clinical nonconversion. Interestingly, these individuals had apolipoprotein E genotypes and CSF levels of tau and phospho-tau that are known to be associated with high risk of AD.

CONCLUSION: Altogether, our study reveals the novel finding that the Abeta peptide pattern is able to predict AD in patients with MCI with a sensitivity of 91% and specificity of 64%. The specificity would increase to 94% if the high-risk patients in the stable MCI cohort developed AD during extended follow-up.