Introduction: Blood-based biomarkers of pathophysiological brain amyloid β (Aβ) accumulation, particularly for preclinical target and large-scale interventions, are warranted to effectively enrich Alzheimer's disease clinical trials and management. Methods: We investigated whether plasma concentrations of the Aβ1–40/Aβ1–42 ratio, assessed using the single-molecule array (Simoa) immunoassay, may predict brain Aβ positron emission tomography status in a large-scale longitudinal monocentric cohort (N = 276) of older individuals with subjective memory complaints. We performed a hypothesis-driven investigation followed by a no-a-priori hypothesis study using machine learning. Results: The receiver operating characteristic curve and machine learning showed a balanced accuracy of 76.5% and 81%, respectively, for the plasma Aβ1–40/Aβ1–42 ratio. The accuracy is not affected by the apolipoprotein E (APOE)ε4 allele, sex, or age. Discussion: Our results encourage an independent validation cohort study to confirm the indication that the plasma Aβ1–40/Aβ1–42 ratio, assessed via Simoa, may improve future standard of care and clinical trial design.

Plasma amyloid β 40/42 ratio predicts cerebral amyloidosis in cognitively normal individuals at risk for Alzheimer's disease / Vergallo, A.; Megret, L.; Lista, S.; Cavedo, E.; Zetterberg, H.; Blennow, K.; Vanmechelen, E.; De Vos, A.; Habert, M. -O.; Potier, M. -C.; Dubois, B.; Neri, C.; Hampel, H.; Bakardjian, H.; Benali, H.; Bertin, H.; Bonheur, J.; Boukadida, L.; Boukerrou, N.; Cavedo, E.; Chiesa, P.; Colliot, O.; Dubois, B.; Dubois, M.; Epelbaum, S.; Gagliardi, G.; Genthon, R.; Habert, M. O.; Hampel, H.; Houot, M.; Kas, A.; Lamari, F.; Levy, M.; Lista, S.; Metzinger, C.; Mochel, F.; Nyasse, F.; Poisson, C.; Revillon, M.; Santos, A.; Andrade, K. S.; Sole, M.; Surtee, M.; de Schotten M, T.; Vergallo, A.; Younsi, N.; Aguilar, L. F.; Babiloni, C.; Baldacci, F.; Benda, N.; Black, K. L.; Bokde, A. L. W.; Bonuccelli, U.; Broich, K.; Cacciola, F.; Castrillo, J.; Ceravolo, R.; Chiesa, P. A.; Corvol, J. -C.; Cuello, A. C.; Cummings, J. L.; Depypere, H.; Duggento, A.; Escott-Price, V.; Federoff, H.; Ferretti, M. T.; Fiandaca, M.; Frank, R. A.; Garaci, F.; Geerts, H.; Giorgi, F. S.; Graziani, M.; Haberkamp, M.; Herholz, K.; Karran, E.; Kim, S. H.; Koronyo, Y.; Koronyo-Hamaoui, M.; Lamari, F.; Langevin, T.; Lehericy, S.; Lorenceau, J.; Mango, D.; Mapstone, M.; Nistico, R.; O'Bryant, S. E.; Perry, G.; Ritchie, C.; Rossi, S.; Saidi, A.; Santarnecchi, E.; Schneider, L. S.; Sporns, O.; Toschi, N.; Verdooner, S. R.; Villain, N.; Welikovitch, L. A.; Woodcock, J.; Younesi, E.. - In: ALZHEIMER'S & DEMENTIA. - ISSN 1552-5260. - 15:6(2019), pp. 764-775. [10.1016/j.jalz.2019.03.009]

Plasma amyloid β 40/42 ratio predicts cerebral amyloidosis in cognitively normal individuals at risk for Alzheimer's disease

Babiloni C.
Membro del Collaboration Group
;
2019

Abstract

Introduction: Blood-based biomarkers of pathophysiological brain amyloid β (Aβ) accumulation, particularly for preclinical target and large-scale interventions, are warranted to effectively enrich Alzheimer's disease clinical trials and management. Methods: We investigated whether plasma concentrations of the Aβ1–40/Aβ1–42 ratio, assessed using the single-molecule array (Simoa) immunoassay, may predict brain Aβ positron emission tomography status in a large-scale longitudinal monocentric cohort (N = 276) of older individuals with subjective memory complaints. We performed a hypothesis-driven investigation followed by a no-a-priori hypothesis study using machine learning. Results: The receiver operating characteristic curve and machine learning showed a balanced accuracy of 76.5% and 81%, respectively, for the plasma Aβ1–40/Aβ1–42 ratio. The accuracy is not affected by the apolipoprotein E (APOE)ε4 allele, sex, or age. Discussion: Our results encourage an independent validation cohort study to confirm the indication that the plasma Aβ1–40/Aβ1–42 ratio, assessed via Simoa, may improve future standard of care and clinical trial design.
2019
Alzheimer's disease; Amyloid PET; classification and regression trees (CART); machine learning; Plasma amyloid β; Simoa immunoassay; subjective memory complainers
01 Pubblicazione su rivista::01a Articolo in rivista
Plasma amyloid β 40/42 ratio predicts cerebral amyloidosis in cognitively normal individuals at risk for Alzheimer's disease / Vergallo, A.; Megret, L.; Lista, S.; Cavedo, E.; Zetterberg, H.; Blennow, K.; Vanmechelen, E.; De Vos, A.; Habert, M. -O.; Potier, M. -C.; Dubois, B.; Neri, C.; Hampel, H.; Bakardjian, H.; Benali, H.; Bertin, H.; Bonheur, J.; Boukadida, L.; Boukerrou, N.; Cavedo, E.; Chiesa, P.; Colliot, O.; Dubois, B.; Dubois, M.; Epelbaum, S.; Gagliardi, G.; Genthon, R.; Habert, M. O.; Hampel, H.; Houot, M.; Kas, A.; Lamari, F.; Levy, M.; Lista, S.; Metzinger, C.; Mochel, F.; Nyasse, F.; Poisson, C.; Revillon, M.; Santos, A.; Andrade, K. S.; Sole, M.; Surtee, M.; de Schotten M, T.; Vergallo, A.; Younsi, N.; Aguilar, L. F.; Babiloni, C.; Baldacci, F.; Benda, N.; Black, K. L.; Bokde, A. L. W.; Bonuccelli, U.; Broich, K.; Cacciola, F.; Castrillo, J.; Ceravolo, R.; Chiesa, P. A.; Corvol, J. -C.; Cuello, A. C.; Cummings, J. L.; Depypere, H.; Duggento, A.; Escott-Price, V.; Federoff, H.; Ferretti, M. T.; Fiandaca, M.; Frank, R. A.; Garaci, F.; Geerts, H.; Giorgi, F. S.; Graziani, M.; Haberkamp, M.; Herholz, K.; Karran, E.; Kim, S. H.; Koronyo, Y.; Koronyo-Hamaoui, M.; Lamari, F.; Langevin, T.; Lehericy, S.; Lorenceau, J.; Mango, D.; Mapstone, M.; Nistico, R.; O'Bryant, S. E.; Perry, G.; Ritchie, C.; Rossi, S.; Saidi, A.; Santarnecchi, E.; Schneider, L. S.; Sporns, O.; Toschi, N.; Verdooner, S. R.; Villain, N.; Welikovitch, L. A.; Woodcock, J.; Younesi, E.. - In: ALZHEIMER'S & DEMENTIA. - ISSN 1552-5260. - 15:6(2019), pp. 764-775. [10.1016/j.jalz.2019.03.009]
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