title: Quantifying the pathophysiological timeline of Alzheimer's disease.
abstract: Hypothetical models of AD progression typically relate clinical stages of AD to sequential changes in CSF biomarkers, imaging, and cognition. However, quantifying the continuous trajectories proposed by these models over time is difficult because of the difficulty in relating the dynamics of different biomarkers during a clinical trial that is significantly shorter than the duration of the disease. We seek to show that through proper synchronization, it is possible to de-convolve these trends and quantify the periods of time associated with different pathophysiological changes associated with Alzheimer's disease (AD). We developed a model that replicated the observed progression of ADAS-Cog 13 scores and used this as a more precise estimate of disease-duration and thus pathologic stage. We then synchronized cerebrospinal fluid (CSF) and imaging biomarkers according to our new disease timeline. By de-convolving disease progression via ADAS-Cog 13, we were able to confirm the predictions of previous hypothetical models of disease progression as well as establish concrete timelines for different pathobiological events. Specifically, our work supports a sequential pattern of biomarker changes in AD in which reduction in CSF Aβ(42) and brain atrophy precede the increases in CSF tau and phospho-tau.
authors.affiliation: Johnson and Johnson, PRDUS. Eyang3@its.jnj.com
authors.forename: Eric
authors.initials: E
authors.lastname: Yang
authors.forename: Michael
authors.initials: M
authors.lastname: Farnum
authors.forename: Victor
authors.initials: V
authors.lastname: Lobanov
authors.forename: Tim
authors.initials: T
authors.lastname: Schultz
authors.forename: Rudi
authors.initials: R
authors.lastname: Verbeeck
authors.forename: Nandini
authors.initials: N
authors.lastname: Raghavan
authors.forename: Mahesh N
authors.initials: MN
authors.lastname: Samtani
authors.forename: Gerald
authors.initials: G
authors.lastname: Novak
authors.forename: Vaibhav
authors.initials: V
authors.lastname: Narayan
authors.forename: Allitia
authors.initials: A
authors.lastname: DiBernardo
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000544:Alzheimer Disease / Q000378:metabolism / Q000503:physiopathology* / Q000523:psychology; D016229:Amyloid beta-Peptides / Q000134:cerebrospinal fluid; D001057:Apolipoproteins E / Q000235:genetics; D001284:Atrophy; D015415:Biomarkers; D003071:Cognition; D016208:Databases, Factual; D003710:Demography; D018450:Disease Progression; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009483:Neuropsychological Tests; D010446:Peptide Fragments / Q000134:cerebrospinal fluid; D049268:Positron-Emission Tomography; D016875:tau Proteins / Q000134:cerebrospinal fluid
chemical_list: D016229:Amyloid beta-Peptides; D001057:Apolipoproteins E; D015415:Biomarkers; D010446:Peptide Fragments; C075222:amyloid beta-protein (1-42); D016875:tau Proteins