1. Aptamarker prediction of brain amyloid-β status in cognitively normal individuals at risk for Alzheimer’s disease
- Author
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Penner, G, Lecocq, S, Chopin, A, Vedoya, X, Lista, S, Vergallo, A, Cavedo, E, Lejeune, F, Dubois, B, Hampel, H, Bakardjian, H, Benali, H, Bertin, H, Bonheur, J, Boukadida, L, Boukerrou, N, Chiesa, Pa, Colliot, O, Dubois, M, Epelbaum, S, Gagliardi, G, Genthon, R, Habert, M, Houot, M, Kas, A, Lamari, F, Levy, M, Metzinger, C, Mochel, F, Nyasse, F, Poisson, C, Potier, M, Revillon, M, Santos, A, Andrade, Ks, Sole, M, Surtee, M, de Schotten, Mt, Younsi, N, Afshar, M, Aguilar, Lf, Akman-Anderson, L, Aremas, J, Avila, J, Babiloni, C, Baldacci, F, Batrla, R, Benda, N, Black, Kl, Bokde, Alw, Bonuccelli, U, Broich, K, Cacciola, F, Caraci, F, Caruso, G, Castrillo, J, Ceravolo, R, Corbo, M, Corvol, J, Cuello, Ac, Cummings, Jl, Depypere, H, Duggento, A, Emanuele, E, Escott-Price, V, Federoff, H, Ferretti, Mt, Fiandaca, M, Frank, Ra, Garaci, F, Geerts, H, Giacobini, E, Giorgi, Fs, Goetzl, Ej, Graziani, M, Haberkamp, M, Hanisch, B, Herholz, K, Hernandez, F, Imbimbo, Bp, Kapogiannis, D, Karran, E, Kiddle, Sj, Kim, Sh, Koronyo, Y, Koronyo-Hamaoui, M, Langevin, T, Lehericy, S, Lemercier, P, Llavero, F, Lorenceau, J, Lucia, A, Mango, D, Mapstone, M, Neri, C, Nistico, R, O'Bryant, Se, Palermo, G, Perry, G, Ritchie, C, Rossi, S, Saidi, A, Santarnecchi, E, Schneider, Ls, Sporns, O, Toschi, N, Valenzuela, Pl, Vellas, B, Verdooner, Sr, Villain, N, Giudici, Kv, Watling, M, Welikovitch, La, Woodcock, J, Younesi, E, Zugaza, Jl, Alzheimer Precision Medicine [CHU Pitié-Salpétriêre] (GRC 21 AMP), CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Sorbonne Université (SU), Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Gasset, Maria
- Subjects
Male ,Aging ,Amyloid β ,MESH: SELEX Aptamer Technique ,[SDV]Life Sciences [q-bio] ,Oligonucleotides ,Artificial Gene Amplification and Extension ,Disease ,Neurodegenerative ,Alzheimer's Disease ,Pathology and Laboratory Medicine ,Biochemistry ,Polymerase Chain Reaction ,Diagnostic Radiology ,Negative selection ,Medical Conditions ,Mathematical and Statistical Techniques ,0302 clinical medicine ,MESH: Aged, 80 and over ,MESH: Early Diagnosis ,80 and over ,Medicine and Health Sciences ,Biomarker discovery ,Tomography ,Aged, 80 and over ,MESH: Aged ,screening and diagnosis ,0303 health sciences ,Multidisciplinary ,Nucleotides ,Mathematical Models ,Radiology and Imaging ,SELEX Aptamer Technique ,Settore MED/37 - Neuroradiologia ,Neurodegenerative Diseases ,MESH: Case-Control Studies ,MESH: Amyloid beta-Peptides ,Detection ,Neurology ,Neurological ,Medicine ,Biomedical Imaging ,Female ,Biotechnology ,4.2 Evaluation of markers and technologies ,Research Article ,Amyloid ,General Science & Technology ,Imaging Techniques ,Science ,Aptamer ,Neuroimaging ,and over ,Computational biology ,Biology ,Research and Analysis Methods ,03 medical and health sciences ,Clinical Research ,Diagnostic Medicine ,Alzheimer Disease ,Mental Health and Psychiatry ,Acquired Cognitive Impairment ,Humans ,Risk factor ,Molecular Biology Techniques ,Molecular Biology ,Aged ,030304 developmental biology ,Amyloid beta-Peptides ,MESH: Humans ,Prevention ,Neurosciences ,Alzheimer Precision Medicine Initiative ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Biology and Life Sciences ,Omics ,MESH: Male ,Brain Disorders ,4.1 Discovery and preclinical testing of markers and technologies ,Early Diagnosis ,Case-Control Studies ,MESH: Biomarkers ,Dementia ,INSIGHT-preAD study group ,MESH: Female ,Biomarkers ,Positron Emission Tomography ,030217 neurology & neurosurgery ,MESH: Alzheimer Disease ,Neuroscience - Abstract
International audience; The traditional approach to biomarker discovery for any pathology has been through hypothesis-based research one candidate at a time. The objective of this study was to develop an agnostic approach for the simultaneous screening of plasma for consistent molecular differences between a group of individuals exhibiting a pathology and a group of healthy individuals. To achieve this, we focused on developing a predictive tool based on plasma for the amount of brain amyloid-β deposition as observed in PET scans. The accumulation of brain amyloid-β (Aβ) plaques is a key risk factor for the development of Alzheimer's disease. A contrast was established between cognitively normal individuals above the age of 70 that differed for the amount of brain amyloid-β observed in PET scans (INSIGHT study group). Positive selection was performed against a pool of plasma from individuals with high brain amyloid and negative selection against a pool of plasma from individuals with low brain amyloid This enriched, selected library was then applied to plasma samples from 11 individuals with high levels of brain amyloid and 11 individuals with low levels of brain Aβ accumulation. Each of these individually selected libraries was then characterized by next generation sequencing, and the relative frequency of 10,000 aptamer sequences that were observed in each selection was screened for ability to explain variation in brain amyloid using sparse partial least squares discriminant analysis. From this analysis a subset of 44 aptamers was defined, and the individual aptamers were synthesized. This subset was applied to plasma samples from 70 cognitively normal individuals all above the age of 70 that differed for brain amyloid deposition. 54 individuals were used as a training set, and 15 as a test set. Three of the 15 individuals in the test set were mis-classified resulting in an overall accuracy of 80% with 86% sensitivity and 75% specificity. The aptamers included in the subset serve directly as biomarkers, thus we have named them Aptamarkers. There are two potential applications of these results: extending the predictive capacity of these aptamers across a broader range of individuals, and/or using the individual aptamers to identify targets through covariance analysis and reverse omics approaches. We are currently expanding applications of the Aptamarker platform to other diseases and target matrices.
- Published
- 2021