Combining Cerebrospinal Fluid Biomarkers and Neuropsychological Assessment: A Simple and Cost-Effective Algorithm to Predict the Progression from Mild Cognitive Impairment to Alzheimer’s Disease Dementia

Article type: Research Article

Authors: Mazzeo, Salvatore^{a; 1} | Santangelo, Roberto^{a; *; 1} | Bernasconi, Maria Paola^a | Cecchetti, Giordano^a | Fiorino, Agnese^a | Pinto, Patrizia^b | Passerini, Gabriella^c | Falautano, Monica^a | Comi, Giancarlo^a | Magnani, Giuseppe^a

Affiliations: [a] Department of Neurology, INSPE, Vita-Salute University and IRCCS-San Raffaele Hospital, Milan, Italy | [b] Department of Neurology, Papa Giovanni XXIII Hospital, Bergamo, Italy | [c] Laboraf, IRCCS-San Raffaele Hospital, Milan, Italy

Correspondence: [*] Correspondence to: Roberto Santangelo, Department of Neurology, INSPE, Vita-Salute University and IRCCS-San Raffaele Hospital, Milan, Italy E-mail: E-mail: santangelo.roberto@hsr.it.

Note: [1] These authors contributed equally to this work.

Abstract: Background: Correctly diagnosing Alzheimer’s disease (AD) in prodromal phases would allow the adoption of experimental therapeutic strategies that could selectively interrupt the pathogenetic process before neuronal damage becomes irreversible. Therefore, great efforts have been aimed at finding early reliable disease markers. Objective: The aim of this study was to identify a simple, cost effective, and reliable diagnostic algorithm to predict conversion from mild cognitive impairment (MCI) to AD. Methods: 96 consecutive MCI patients admitted to the Neurology department of San Raffaele Hospital in Milan between January 2009 and January 2015 were included. All patients underwent neuropsychological assessment and lumbar puncture with CSF analysis of amyloid-β 42 (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau) levels. Each patient underwent clinical and neuropsychological follow-up, in order to identify a possible progression from MCI to AD. The mean follow up time was 36.73 months. Results: 37 out of 96 MCI converted to AD during follow up. CSF analysis and neuropsychological assessment reliably detected MCI patients who developed AD. In a subsample of 43 subjects, a Composite Cognitive Score (CCS) was calculated including episodic memory, executive function, and verbal fluency tests. Combining together CSF biomarkers and CCS increased the accuracy of the single predictors, correctly classifying 86% of patients with a specificity of 96% and a Positive Predictive Value of 93%. Discussion: Even if preliminary, our data seem to suggest that CSF analysis and neuropsychological assessment could detect MCI patients who will convert to AD with high confidence. Their relative low cost and availability could make them worldwide essential tools in future clinical trials.

Keywords: Amyloid-β₄₂, composite cognitive score, diagnostic algorithm, mild cognitive impairment, neuropsychological tests, tau protein

DOI: 10.3233/JAD-160360

Journal: Journal of Alzheimer's Disease, vol. 54, no. 4, pp. 1495-1508, 2016