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.
Original language | English |
---|---|
Pages (from-to) | 764-775 |
Number of pages | 12 |
Journal | Alzheimer's and Dementia |
Volume | 15 |
Issue number | 6 |
DOIs | |
State | Published - 1 Jun 2019 |
Keywords
- Alzheimer's disease
- Amyloid PET
- Classification and regression trees (CART)
- Machine learning
- Plasma amyloid β
- Simoa immunoassay
- Subjective memory complainers
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In: Alzheimer's and Dementia, Vol. 15, No. 6, 01.06.2019, p. 764-775.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Plasma amyloid β 40/42 ratio predicts cerebral amyloidosis in cognitively normal individuals at risk for Alzheimer's disease
AU - INSIGHT-preAD Study Group
AU - Alzheimer Precision Medicine Initiative (APMI)
AU - Vergallo, Andrea
AU - Mégret, Lucile
AU - Lista, Simone
AU - Cavedo, Enrica
AU - Zetterberg, Henrik
AU - Blennow, Kaj
AU - Vanmechelen, Eugeen
AU - De Vos, Ann
AU - Habert, Marie Odile
AU - Potier, Marie Claude
AU - Dubois, Bruno
AU - Neri, Christian
AU - Hampel, Harald
AU - Bakardjian, H.
AU - Benali, H.
AU - Bertin, H.
AU - Bonheur, J.
AU - Boukadida, L.
AU - Boukerrou, N.
AU - Chiesa, P.
AU - Colliot, O.
AU - Dubois, B.
AU - Dubois, M.
AU - Epelbaum, S.
AU - Gagliardi, G.
AU - Genthon, R.
AU - Habert, M. O.
AU - Houot, M.
AU - Kas, A.
AU - Lamari, F.
AU - Levy, M.
AU - Metzinger, C.
AU - Mochel, F.
AU - Nyasse, F.
AU - Poisson, C.
AU - Revillon, M.
AU - Santos, A.
AU - Andrade, K. S.
AU - Sole, M.
AU - Surtee, M.
AU - de Schotten M, Thiebaud
AU - Vergallo, A.
AU - Younsi, N.
AU - Aguilar, Lisi Flores
AU - Babiloni, Claudio
AU - Baldacci, Filippo
AU - Benda, Norbert
AU - Black, Keith L.
AU - Bokde, Arun L.W.
AU - O'Bryant, Sid E.
N1 - Funding Information: The authors thank Antoine Chambaz (Université Paris Descartes) for expert advice on machine learning techniques. The study was promoted by INSERM in collaboration with ICM, IHU-A-ICM, and Pfizer and has received support within the “Investissement d'Avenir” (ANR-10-AIHU-06) program. The study was promoted in collaboration with the “CHU de Bordeaux” (coordination CIC EC7), the promoter of Memento cohort, funded by the Foundation Plan-Alzheimer . The study was further supported by AVID / Lilly . Funding Information: This research benefited from the support of the program ?PHOENIX? led by the Sorbonne University Foundation and sponsored by la Fondation pour la Recherche sur Alzheimer. This study was financially supported by the Agency for Innovation and Technology (IWT O&O 140105) and Flanders Innovation and Entrepreneurship (VLAIO 160548). H.Z. is a Wallenberg Academy Fellow and holds grants from the Swedish and European Research Councils as well as the Medical Research Council (UK). K.B. holds the Torsten S?derberg Professorship of Medicine. C.N. is supported by INSERM, CNRS, and Sorbonne Universit?. H.H. is supported by the AXA Research Fund, the ?Fondation partenariale Sorbonne Universit?,? and the ?Fondation pour la Recherche sur Alzheimer,? Paris, France. Ce travail a b?n?fici? d'une aide de l'Etat ?Investissements d'avenir? ANR-10-IAIHU-06. The research leading to these results has received funding from the program ?Investissements d'avenir? ANR-10-IAIHU-06 (Agence Nationale de la Recherche-10-IA Agence Institut Hospitalo-Universitaire-6). INSIGHT-preAD Study Group: 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 MO, Hampel H, Houot M, Kas A, Lamari F, Levy M, Lista S, Metzinger C, Mochel F, Nyasse F, Poisson C, Potier MC, Revillon M, Santos A, Andrade KS, Sole M, Surtee M, Thiebaud de Schotten M, Vergallo A, and Younsi N. INSIGHT-preAD Scientific Committee Members: Dubois B, Hampel H, Bakardjian H, Benali H, Colliot O, Habert Marie-O, Lamari F, Mochel F, Potier MC, and Thiebaut de Schotten M. Contributors to the Alzheimer Precision Medicine Initiative?Working Group (APMI?WG): Mohammad Afshar (Paris), Lisi Flores Aguilar (Montr?al), Leyla Akman-Anderson (Sacramento), Joaqu?n Arenas (Madrid), Jesus Avila (Madrid), Claudio Babiloni (Rome), Filippo Baldacci (Pisa), Richard Batrla (Rotkreuz), Norbert Benda (Bonn), Keith L. Black (Los Angeles), Arun L.W. Bokde (Dublin), Ubaldo Bonuccelli (Pisa), Karl Broich (Bonn), Francesco Cacciola (Siena), Filippo Caraci (Catania), Juan Castrillo? (Derio), Enrica Cavedo (Paris), Roberto Ceravolo (Pisa), Patrizia A. Chiesa (Paris), Jean-Christophe Corvol (Paris), Augusto Claudio Cuello (Montr?al), Jeffrey L. Cummings (Las Vegas), Herman Depypere (Gent), Bruno Dubois (Paris), Andrea Duggento (Rome), Enzo Emanuele (Robbio), Valentina Escott-Price (Cardiff), Howard Federoff (Irvine), Maria Teresa Ferretti (Z?rich), Massimo Fiandaca (Irvine), Richard A. Frank (Malvern), Francesco Garaci (Rome), Hugo Geerts (Berwyn), Filippo S. Giorgi (Pisa), Edward J. Goetzl (San Francisco), Manuela Graziani (Roma), Marion Haberkamp (Bonn), Marie-Odile Habert (Paris), Harald Hampel (Paris), Karl Herholz (Manchester), Felix Hernandez (Madrid), Dimitrios Kapogiannis (Baltimore), Eric Karran (Cambridge), Steven J. Kiddle (Cambridge), Seung H. Kim (Seoul), Yosef Koronyo (Los Angeles), Maya Koronyo-Hamaoui (Los Angeles), Todd Langevin (Minneapolis-Saint Paul), St?phane Leh?ricy (Paris), Alejandro Luc?a (Madrid), Simone Lista (Paris), Jean Lorenceau (Paris), Dalila Mango (Rome), Mark Mapstone (Irvine), Christian Neri (Paris), Robert Nistic? (Rome), Sid E. O'Bryant (Fort Worth), Giovanni Palmero (Pisa), George Perry (San Antonio), Craig Ritchie (Edinburgh), Simone Rossi (Siena), Amira Saidi (Rome), Emiliano Santarnecchi (Siena), Lon S. Schneider (Los Angeles), Olaf Sporns (Bloomington), Nicola Toschi (Rome), Steven R. Verdooner (Sacramento), Andrea Vergallo (Paris), Nicolas Villain (Paris), Lindsay A. Welikovitch (Montr?al), Janet Woodcock (Silver Spring), Erfan Younesi (Esch-sur-Alzette). The authors thank Antoine Chambaz (Universit? Paris Descartes) for expert advice on machine learning techniques. The study was promoted by INSERM in collaboration with ICM, IHU-A-ICM, and Pfizer and has received support within the ?Investissement d'Avenir? (ANR-10-AIHU-06) program. The study was promoted in collaboration with the ?CHU de Bordeaux? (coordination CIC EC7), the promoter of Memento cohort, funded by the Foundation Plan-Alzheimer. The study was further supported by AVID/Lilly. S.L. received lecture honoraria from Roche. H.Z. and K.B. are cofounders of Brain Biomarker Solutions in Gothenburg AB, a GU venture-based platform company at the University of Gothenburg. A.D.V. is an employee and shareholder of ADx NeuroSciences. E.V. is a cofounder of ADx NeuroSciences. B.D. reports personal fees from Eli Lilly and company. H.H. serves as a senior associate editor for the Journal Alzheimer's & Dementia; he received lecture fees from Biogen, Roche, and Eisai, research grants from Pfizer, Avid, and MSD Avenir (paid to the institution), travel funding from Functional Neuromodulation, Axovant, Eli Lilly and company, Takeda and Zinfandel, GE-Healthcare and Oryzon Genomics, consultancy fees from Qynapse, Jung Diagnostics, Cytox Ltd. Axovant, Anavex, Takeda and Zinfandel, GE Healthcare and Oryzon Genomics, and Functional Neuromodulation, and participated in scientific advisory boards of Functional Neuromodulation, Axovant, Eli Lilly and company, Cytox Ltd. GE Healthcare, Takeda and Zinfandel, Oryzon Genomics, and Roche Diagnostics. He is a co-inventor in the following patents as a scientific expert and has received no royalties: (1) In Vitro Multiparameter Determination Method for the Diagnosis and Early Diagnosis of Neurodegenerative Disorders Patent Number: 8916388; (2) In Vitro Procedure for Diagnosis and Early Diagnosis of Neurodegenerative Diseases Patent Number: 8298784; (3) Neurodegenerative Markers for Psychiatric Conditions Publication Number: 20120196300; (4) In Vitro Multiparameter Determination Method for The Diagnosis and Early Diagnosis of Neurodegenerative Disorders Publication Number: 20100062463; (5) In Vitro Method for The Diagnosis and Early Diagnosis of Neurodegenerative Disorders Publication Number: 20100035286; (6) In Vitro Procedure for Diagnosis and Early Diagnosis of Neurodegenerative Diseases Publication Number: 20090263822; (7) In Vitro Method for the Diagnosis of Neurodegenerative Diseases Patent Number: 7547553; (8) CSF Diagnostic in Vitro Method for Diagnosis of Dementias and Neuroinflammatory Diseases Publication Number: 20080206797; (9) In Vitro Method for The Diagnosis of Neurodegenerative Diseases Publication Number: 20080199966; and (10) Neurodegenerative Markers for Psychiatric Conditions Publication Number: 20080131921. A.V. L.M. C.N. M.-O.H. M.-C.P. and E.C. declared no conflicts of interest. Authors' contributions: A.V. wrote the article and provided data interpretation and a critical review of the literature. L.M. performed the data modeling and statistical analyses, contributed to the writing of the article, and made artwork. S.L. contributed to the writing of the article and provided a critical review of the literature. E.C. contributed to the writing of the article and provided a critical review of the literature. H.Z. provided the plasma biomarkers assessment and data interpretation. K.B. provided the plasma biomarkers assessment and data interpretation. E.V. provided the plasma biomarkers assessment and data interpretation. A.D.V. provided the plasma biomarkers assessment and data interpretation. M.-O.H. provided the amyloid-PET biomarkers assessment. M.-C.P. provided the APOE genotype assessment. B.D. contributed the writing of the article and conceptualization. C.N. contributed to the writing and conceptualization of the article and perfomed data modeling and interpretation. H.H. wrote the article and provided data interpretation and a critical review of the whole manuscript. Funding Information: This research benefited from the support of the program “ PHOENIX ” led by the Sorbonne University Foundation and sponsored by la Fondation pour la Recherche sur Alzheimer . This study was financially supported by the Agency for Innovation and Technology (IWT O&O 140105) and Flanders Innovation and Entrepreneurship (VLAIO 160548). H.Z. is a Wallenberg Academy Fellow and holds grants from the Swedish and European Research Councils as well as the Medical Research Council (UK). K.B. holds the Torsten Söderberg Professorship of Medicine. C.N. is supported by INSERM , CNRS , and Sorbonne Université . H.H. is supported by the AXA Research Fund , the “ Fondation partenariale Sorbonne Université ,” and the “ Fondation pour la Recherche sur Alzheimer ,” Paris, France. Ce travail a bénéficié d'une aide de l'Etat “Investissements d'avenir” ANR-10-IAIHU-06. The research leading to these results has received funding from the program “Investissements d'avenir” ANR-10-IAIHU-06 (Agence Nationale de la Recherche-10-IA Agence Institut Hospitalo-Universitaire-6). Publisher Copyright: © 2019 the Alzheimer's Association
PY - 2019/6/1
Y1 - 2019/6/1
N2 - 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.
AB - 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.
KW - Alzheimer's disease
KW - Amyloid PET
KW - Classification and regression trees (CART)
KW - Machine learning
KW - Plasma amyloid β
KW - Simoa immunoassay
KW - Subjective memory complainers
UR - http://www.scopus.com/inward/record.url?scp=85065799769&partnerID=8YFLogxK
U2 - 10.1016/j.jalz.2019.03.009
DO - 10.1016/j.jalz.2019.03.009
M3 - Article
C2 - 31113759
AN - SCOPUS:85065799769
SN - 1552-5260
VL - 15
SP - 764
EP - 775
JO - Alzheimer's and Dementia
JF - Alzheimer's and Dementia
IS - 6
ER -