Alzheimer’s disease; Automated volumetry; Biomarkers; Event-based modelling; Magnetic resonance imaging; tau Proteins; Amyloid beta-Peptides; Humans; Male; Female; Aged; Disease Progression; tau Proteins/cerebrospinal fluid; Cognitive Dysfunction/cerebrospinal fluid; Aged, 80 and over; Amyloid beta-Peptides/cerebrospinal fluid; Cohort Studies; Biomarkers/cerebrospinal fluid; Middle Aged; Neuropsychological Tests; Magnetic Resonance Imaging; Mental Status and Dementia Tests; Alzheimer Disease/cerebrospinal fluid; Alzheimer Disease/diagnosis; Alzheimer Disease/diagnostic imaging; Alzheimer Disease/pathology
Abstract :
[en] BACKGROUND: Event-based modeling (EBM) traces sequential progression of events in complex processes like neurodegenerative diseases, adept at handling uncertainties. This study validated an EBM for Alzheimer's disease (AD) staging designed by EuroPOND, an EU-funded Horizon 2020 project, using research and real-world datasets, a crucial step towards application in multi-center trials.
METHODS: The training dataset comprised 1737 subjects from ADNI-1/GO/2, using the EuroPOND EBM toolbox. Testing datasets included a research cohort from University of Antwerp (controls, CN (n = 46), subjective cognitive decline, SCD (n = 10), mild cognitive impairment, MCI (n = 47), AD dementia, ADD (n = 16)) and a real-world cohort from 9 Belgian Dementia Council memory clinics (CN (n = 91), SCD (n = 66), (non-amnestic) naMCI (n = 54), aMCI (n = 255), and ADD (n = 220). Biomarkers included: 2 clinical scores (Mini Mental State Examination (MMSE), Rey Auditory Verbal Learning Test (RAVLT)); 3 CSF-biomarkers (Aβ1-42, P-tau181, total-Tau); and 4 magnetic resonance imaging (MRI) biomarkers (volumes of the hippocampi, temporal, parietal, and frontal cortices) computed with icobrain dm. The naMCI and aMCI groups were compared by EBM stage proportions, and the model's effectiveness at patient level was evaluated.
RESULTS: The research cohort's maximum likelihood event sequence comprised CSF Aβ1-42, P-tau181, T-tau, RAVLT, MMSE, and cortical volumes. The clinical cohort's order was frontal cortex volume, MMSE, and remaining cortical regions. aMCI subjects showed higher staging than naMCI, with 54% in the two most advanced stages compared to 38% in naMCI. In the research cohort, 10 outliers were identified with potential mismatches between assigned stages and clinical or biomarker profiles, with CN (n = 4) and SCD (n = 2) subjects assigned in stage 4, one control in stage 9 with abnormal imaging, and three aMCI cases in stage 0 despite clinical or volumetric signs of impairment.
CONCLUSIONS: This study highlights the generalizability of EuroPOND's AD EBM model across research and real-world clinical datasets, supporting its use in multi-center trials. aMCI subjects generally reside in more advanced stages than naMCI, who may not necessarily have AD, demonstrating utility for precision recruitment/screening.
Disciplines :
Neurosciences & behavior
Author, co-author :
Wittens, Mandy M J; Dep. of Biomedical Sciences, University of Antwerp, Antwerp, Belgium ; Dep. of Neurology, Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium ; Neuroprotection & Neuromodulation (NEUR) Research Group, Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, Brussel, 1090, Belgium
Sima, Diana M; icometrix, Leuven, Belgium
Brys, Arne; icometrix, Leuven, Belgium
Struyfs, Hanne; Dep. of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
Niemantsverdriet, Ellis; Dep. of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
De Roeck, Ellen; Dep. of Biomedical Sciences, University of Antwerp, Antwerp, Belgium ; Department of Neurology and Memory Clinic, ZAS-Hoge Beuken, Antwerp, Belgium
Bastin, Christine ; Université de Liège - ULiège > GIGA > GIGA Neurosciences - Aging & Memory ; Fonds de la Recherche Scientifique-FNRS, Liège, Belgium
Benoit, Florence; Geriatrics Department, Brugmann University Hospital, Université Libre de Bruxelles, Brussels, Belgium
Bergmans, Bruno; Neurology Department, AZ St-Jan Brugge, Ghent University and Ghent University Hospital, Bruges, Gent, Belgium
Bier, Jean-Christophe; Neurology Department, H. U. B. - Erasme Hospital, Université Libre de Bruxelles (ULB), Brussels, Belgium
de Deyn, Peter Paul; Laboratory of Neurochemistry and Behaviour, Experimental Neurobiology unit, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium ; Department of Neurology and Alzheimer Research Center, University of Groningen and University Medical Center Groningen, Groningen, the Netherlands
Deryck, Olivier; Department of Neurology, AZ Sint-Lucas, Brugge, Belgium
Hanseeuw, Bernard; WELBIO department, WEL Research Institute, Wavre, 1300, Belgium ; Institute of Neuroscience, Université Catholique de Louvain, Brussels, 1200, Belgium ; Department of Neurology, Clinique Universitaires Saint-Luc, Brussels, 1200, Belgium
Ivanoiu, Adrian; Institute of Neuroscience, Université Catholique de Louvain, Brussels, 1200, Belgium ; Department of Neurology, Clinique Universitaires Saint-Luc, Brussels, 1200, Belgium
Picard, Gaëtane; Department of Neurology, Clinique Saint-Pierre, Ottignies, Belgium
Salmon, Eric ; Université de Liège - ULiège > Département des sciences cliniques
Segers, Kurt; Neurology & Geriatrics Dpt, Brugmann University Hospital, Van Gehuchtenplein 4, Brussels, 1020, Belgium
Sieben, Anne; Neuropathology lab, IBB-NeuroBiobank BB190113, Born Bunge Institute, Antwerp, Belgium ; Department of Pathology, Antwerp University Hospital - UZA, Antwerp, Belgium ; Laboratory of Neurology, Translational Neurosciences, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
Thiery, Evert; Department of Neurology, University Hospital Ghent, Ghent University, Ghent, Belgium
Tournoy, Jos; Gerontology & Geriatrics, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium ; Department of Geriatric Medicine, UZ Leuven, Leuven, Belgium
G.B.D.D. Collaborators Global, regional, and National burden of alzheimer’s disease and other dementias, 1990–2016: a systematic analysis for the global burden of disease study 2016 Lancet Neurol 18 1 88 106
R.A. Sperling P.S. Aisen L.A. Beckett D.A. Bennett S. Craft A.M. Fagan et al. Toward defining the preclinical stages of alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s association workgroups on diagnostic guidelines for alzheimer’s disease Alzheimers Dement 7 3 280 92 21514248
L. Parnetti E. Chipi N. Salvadori K. D’Andrea P. Eusebi Prevalence and risk of progression of preclinical alzheimer’s disease stages: a systematic review and meta-analysis Alzheimers Res Ther 11 1 7 30646955 6334406
D. Bertens S. Vos P. Kehoe H. Wolf F. Nobili A. Mendonça et al. Use of mild cognitive impairment and prodromal AD/MCI due to AD in clinical care: a European survey Alzheimers Res Ther 11 1 74 31439020 6706888
K. Blennow H. Zetterberg Biomarkers for alzheimer’s disease: current status and prospects for the future J Intern Med 284 6 643 63 1:STN:280:DC%2BB3c7isFSmsA%3D%3D 30051512
R.A. Huynh C. Mohan Alzheimer’s disease: biomarkers in the genome, blood, and cerebrospinal fluid Front Neurol 8 102 28373857 5357660
G. Chetelat J. Arbizu H. Barthel V. Garibotto I. Law S. Morbelli et al. Amyloid-PET and (18)F-FDG-PET in the diagnostic investigation of alzheimer’s disease and other dementias Lancet Neurol 19 11 951 62 1:CAS:528:DC%2BB3cXit1OjsLvK 33098804
N. Sheikh-Bahaei S.A. Sajjadi R. Manavaki J.H. Gillard Imaging biomarkers in alzheimer’s disease: A practical guide for clinicians J Alzheimers Dis Rep 1 1 71 88 30480230 6159632
C.R. Jack Jr D.S. Knopman W.J. Jagust L.M. Shaw P.S. Aisen M.W. Weiner et al. Hypothetical model of dynamic biomarkers of the alzheimer’s pathological cascade Lancet Neurol 9 1 119 28 1:CAS:528:DC%2BC3cXhtFeru74%3D 20083042 2819840
C.R. Jack Jr D.S. Knopman W.J. Jagust R.C. Petersen M.W. Weiner P.S. Aisen et al. Tracking pathophysiological processes in alzheimer’s disease: an updated hypothetical model of dynamic biomarkers Lancet Neurol 12 2 207 16 1:CAS:528:DC%2BC3sXhslCht7o%3D 23332364 3622225
C.R. Jack Jr J.S. Andrews T.G. Beach T. Buracchio B. Dunn A. Graf et al. Revised criteria for diagnosis and staging of alzheimer’s disease: alzheimer’s association workgroup Alzheimers Dement 20 8 5143 69 38934362 11350039
C.R. Jack Jr D.A. Bennett K. Blennow M.C. Carrillo H.H. Feldman G.B. Frisoni et al. A/T/N: an unbiased descriptive classification scheme for alzheimer disease biomarkers Neurology 87 5 539 47 1:CAS:528:DC%2BC28Xht12jtrrK 27371494 4970664
C.R. Jack Jr D.A. Bennett K. Blennow M.C. Carrillo B. Dunn S.B. Haeberlein et al. NIA-AA research framework: toward a biological definition of alzheimer’s disease Alzheimers Dement 14 4 535 62 29653606
D. Aguillon S. Langella Y. Chen J.S. Sanchez Y. Su C. Vila-Castelar et al. Plasma p-tau217 predicts in vivo brain pathology and cognition in autosomal dominant alzheimer’s disease Alzheimers Dement 19 6 2585 94 1:CAS:528:DC%2BB3sXjslOmtg%3D%3D 36571821
C. Della Monica V. Revell G. Atzori R. Laban S.S. Skene A. Heslegrave et al. P-tau217 and other blood biomarkers of dementia: variation with time of day Transl Psychiatry 14 1 373 1:CAS:528:DC%2BB2cXhvFynurfE 39271655 11399374
N.J. Ashton W.S. Brum G. Di Molfetta A.L. Benedet B. Arslan E. Jonaitis et al. Diagnostic accuracy of a plasma phosphorylated Tau 217 immunoassay for alzheimer disease pathology JAMA Neurol 81 3 255 63 38252443 10804282
S. Karantzoulis J.E. Galvin Distinguishing alzheimer’s disease from other major forms of dementia Expert Rev Neurother 11 11 1579 91 22014137 3225285
G. Wei M. Irish J.R. Hodges O. Piguet F. Kumfor Disease-specific profiles of apathy in alzheimer’s disease and behavioural-variant frontotemporal dementia differ across the disease course J Neurol 267 4 1086 96 31873787
R. Landin-Romero F. Kumfor C.E. Leyton M. Irish J.R. Hodges O. Piguet Disease-specific patterns of cortical and subcortical degeneration in a longitudinal study of alzheimer’s disease and behavioural-variant frontotemporal dementia NeuroImage 151 72 80 27012504
B.S. Ye S. Lee H. Yoo S.J. Chung Y.H. Lee Y. Choi et al. Distinguishing between dementia with lewy bodies and alzheimer’s disease using metabolic patterns Neurobiol Aging 87 11 7 1:CAS:528:DC%2BC1MXit1CrtL%2FK 31791660
V. Venkatraghavan E.E. Bron W.J. Niessen S. Klein Alzheimer’s disease neuroimaging I. disease progression timeline Estimation for alzheimer’s disease using discriminative event based modeling NeuroImage 186 518 32 30471388
H.M. Fonteijn M. Modat M.J. Clarkson J. Barnes M. Lehmann N.Z. Hobbs et al. An event-based model for disease progression and its application in Familial alzheimer’s disease and huntington’s disease NeuroImage 60 3 1880 9 22281676
Y. Iturria-Medina R.C. Sotero P.J. Toussaint J.M. Mateos-Pérez A.C. Evans Early role of vascular dysregulation on late-onset alzheimer’s disease based on multifactorial data-driven analysis Nat Commun 7 11934 1:CAS:528:DC%2BC28XhtVKitb%2FL 27327500 4919512
A.L. Young N.P. Oxtoby S. Garbarino N.C. Fox F. Barkhof J.M. Schott et al. Data-driven modelling of neurodegenerative disease progression: thinking outside the black box Nat Rev Neurosci 25 2 111 30 1:CAS:528:DC%2BB2cXntFSnsQ%3D%3D 38191721
D. Archetti S. Ingala V. Venkatraghavan V. Wottschel A.L. Young M. Bellio et al. Multi-study validation of data-driven disease progression models to characterize evolution of biomarkers in alzheimer’s disease Neuroimage Clin 24 101954 31362149 6675943
A.L. Young N.P. Oxtoby P. Daga D.M. Cash N.C. Fox S. Ourselin et al. A data-driven model of biomarker changes in sporadic alzheimer’s disease Brain 137 Pt 9 2564 77 25012224 4132648
D. Archetti A.L. Young N.P. Oxtoby D. Ferreira G. Martensson E. Westman et al. Inter-Cohort validation of sustain model for alzheimer’s disease Front Big Data 4 661110 34095821 8173213
M. Bilgel B.M. Jedynak Predicting time to dementia using a quantitative template of disease progression Alzheimers Dement (Amst) 11 205 15 30859120
A. O’Connor P.S.J. Weston I.M. Pavisic N.S. Ryan J.D. Collins K. Lu et al. Quantitative detection and staging of presymptomatic cognitive decline in Familial alzheimer’s disease: a retrospective cohort analysis Alzheimers Res Ther 12 1 126 33023653 7539456
A.M. Staffaroni M. Quintana B. Wendelberger H.W. Heuer L.L. Russell Y. Cobigo et al. Temporal order of clinical and biomarker changes in Familial frontotemporal dementia Nat Med 28 10 2194 206 1:CAS:528:DC%2BB38XisVKnsLjF 36138153 9951811
P.A. Wijeratne A. Eshaghi W.J. Scotton M. Kohli L. Aksman N.P. Oxtoby et al. The Temporal event-based model: learning event timelines in progressive diseases Imaging Neurosci (Camb) 1 1 19 37719837
E. Niemantsverdriet J. Ottoy C. Somers E. De Roeck H. Struyfs F. Soetewey et al. The cerebrospinal fluid Abeta1-42/Abeta1-40 ratio improves concordance with Amyloid-PET for diagnosing alzheimer’s disease in a clinical setting J Alzheimers Dis 60 2 561 76 1:CAS:528:DC%2BC2sXhsFClt73I 28869470 5611891
M.M.J. Wittens D.M. Sima R. Houbrechts A. Ribbens E. Niemantsverdriet E. Fransen et al. Diagnostic performance of automated MRI volumetry by icobrain Dm for alzheimer’s disease in a clinical setting: A REMEMBER study J Alzheimers Dis 83 2 623 39 1:CAS:528:DC%2BB3MXitVWqtLvF 34334402 8543261
E. Niemantsverdriet A. Ribbens C. Bastin F. Benoit B. Bergmans J.C. Bier et al. A retrospective Belgian Multi-Center MRI biomarker study in alzheimer’s disease (REMEMBER) J Alzheimers Dis 63 4 1509 22 29782314 6004934
M.M.J. Wittens S. Denissen D.M. Sima E. Fransen E. Niemantsverdriet C. Bastin et al. Brain age as a biomarker for pathological versus healthy ageing - a REMEMBER study Alzheimers Res Ther 16 1 128 1:CAS:528:DC%2BB2cXhsValu7bJ 38877568 11179390
M. Rakic S. Vercruyssen S. Van Eyndhoven E. de la Rosa S. Jain S. Van Huffel et al. Icobrain Ms 5.1: combining unsupervised and supervised approaches for improving the detection of multiple sclerosis lesions Neuroimage Clin 31 102707 34111718 8193144
A.J. Mitchell A meta-analysis of the accuracy of the mini-mental state examination in the detection of dementia and mild cognitive impairment J Psychiatr Res 43 4 411 31 18579155
K.R. Chapman H. Bing-Canar M.L. Alosco E.G. Steinberg B. Martin C. Chaisson et al. Mini mental state examination and logical memory scores for entry into alzheimer’s disease trials Alzheimers Res Ther 8 1 9 26899835 4762168
F. Salis D. Costaggiu A. Mandas Mini-Mental state examination: optimal Cut-Off levels for mild and severe cognitive impairment Geriatrics 8 1 12 36648917 9844353
S. O’Dowd J. Schumacher D.J. Burn L. Bonanni M. Onofrj A. Thomas et al. Fluctuating cognition in the lewy body dementias Brain 142 11 3338 50 31411317
E. Matar J.M. Shine G.M. Halliday S.J.G. Lewis Cognitive fluctuations in lewy body dementia: towards a pathophysiological framework Brain 143 1 31 46
E. Matar K.A. Ehgoetz Martens J.R. Phillips G. Wainstein G.M. Halliday S.J.G. Lewis et al. Dynamic network impairments underlie cognitive fluctuations in lewy body dementia Npj Parkinson’s Disease 8 1 16 35177652 8854384
M.J. Grothe A. Moscoso J. Silva-Rodriguez C. Lange K. Nho A.J. Saykin et al. Differential diagnosis of amnestic dementia patients based on an FDG-PET signature of autopsy-confirmed LATE-NC Alzheimers Dement 19 4 1234 44 1:CAS:528:DC%2BB38XisVegu7nM 35971593
L. Barba S. Abu-Rumeileh H. Barthel F. Massa M. Foschi G. Bellomo et al. Clinical and diagnostic implications of alzheimer’s disease copathology in lewy body disease Brain 147 10 3325 43 38991041
P.T. Nelson J.A. Schneider G.A. Jicha M.T. Duong D.A. Wolk When alzheimer’s is LATE: why does it matter?? Ann Neurol 94 2 211 22 37245084 10516307
A. Jannati C. Toro-Serey J. Gomes-Osman R. Banks M. Ciesla J. Showalter et al. Digital clock and recall is superior to the Mini-Mental state examination for the detection of mild cognitive impairment and mild dementia Alzheimers Res Ther 16 1 2 1:CAS:528:DC%2BB2cXptFSrsg%3D%3D 38167251 10759368
