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Am J Neurodegener Dis 2013;2(1):40-45

Original Article
Multiplex assessment of a panel of 16 serum molecules for the dif-
ferential diagnosis of Alzheimer’s disease

Gloria Biella, Massimo Franceschi, Francesca De Rino, Annalisa Davin, Giacomo Giacalone, Paola Brambilla,
Panagiotis Bountris, Maria Haritou, Giuseppe Magnani, Filippo Martinelli Boneschi, Gianluigi Forloni, Diego Albani
Department of Neuroscience, Istituto di Ricerche Famacologiche “Mario Negri”-IRCCS, Milan, Italy; Department of
Neurology, IRCCS Multimedica, Milan, Italy; Golgi Cenci Foundation, Abbiategrasso, Milan, Italy; Laboratory of genetics
of neurological complex disorders, Divi-sion of Neuroscience, INSPE, San Raffaele Scientific Institute, Milan, Italy;
Biomedical Engineering Laboratory, School of Electrical and Com-puter Engineering, National Technical University of
Athens, Athens, Greece; Institute of Communication and Computer Systems, Athens, Greece; Department of
Neurology, Clinical Neurophysiology and Neurorehabilitation, San Raffaele Scientific Institute, Milan, Italy. *These
authors contributed equally to the work.

Received January 15, 2013; Accepted February 5, 2013; Epub March 8, 2013; Published March 18, 2013

Abstract: One of the current challenge in Alzheimer’s disease (AD) is the identification of reliable biomarkers that
might improve diagnostic accuracy, possibly correlating with the disease progression and patient’s response to
therapy. As the clinically validated AD biomarkers evaluate cerebrospinal fluid (CSF) parameters, the need for less
invasive diagnostic markers is well evident. To this respect, blood circulating cytokines or growth factors have provided
some encouraging results, even though no clinically validated to date. In 2007 Ray et al suggested a panel of 18
circulating molecules that might increase AD diagnostic accuracy. In an attempt of replicating their data, we designed a
multiplex fluorimetric assay comprising 16 independent analytes and covering 15 out of the 18 described proteins. We
collected serum samples from three diagnostic groups: probable AD (n=33), matched healthy controls (CNT, n=23)
and non AD demented (NAD, n=14). After correction for age, we found an increased level of EGF-1 in AD in comparison
to CNT and NAD, while an increase of TRAIL-R4 was found in NAD. However, evaluation of specificity/sensitivity by
ROC curve analysis gave weak evidence of diagnostic accuracy (area under the curve = 0.63 and 0.66 for EGF and
TRAIL-R4, respectively). Finally, we tried to find a diagnostic classifier by a multivariate algorithm. We found indication
of diagnostic evidence for AD only, while NAD samples did not show a diagnostic pattern. (AJND1301003)

Keywords: Alzheimer’s disease, diagnosis, peripheral biomarkers, multiplex analysis, EGF-1, multivariate classifier,
machine learning, artificial neural networks

Address correspondence to: Dr. Diego Albani, Department of Neuroscience, Istituto di Ricerche Famacologiche
“Mario Negri”-IRCCS, Via La Masa 19, 20156 Milan, Italy. Tel: +39 02 39014594; Fax: +39 02 3546277; E-mail: diego.
albani@marionegri.it