Donohue, Michael

AbstractIntroductionAlzheimer's disease (AD) is characterized by the accumulation of β‐amyloid (Aβ) associated with brain atrophy and cognitive decline. The functional form to model the association between Aβ and regional brain atrophy has not been well defined. To determine the relationship between Aβ and atrophy, we compared the performance of the usual dichotomization of cerebrospinal fluid (CSF) Aβ to identify subjects as Aβ+ and Aβ− with a trilinear spline model of CSF Aβ.MethodsOne hundred and eighty‐three subjects with mild cognitive impairment and 108 cognitively normal controls with baseline CSF Aβ and up to 4 years of longitudinal magnetic resonance imaging data from the Alzheimer's Disease Neuroimaging Initiative were analyzed using mixed‐effects regression. Piecewise‐linear splines were used to evaluate the nonlinear nature of the association between CSF Aβ and regional atrophy and to identify points of acceleration of atrophy with respect to Aβ. Several parameterizations of CSF Aβ were compared using likelihood ratio tests and the Akaike information criterion. Periods of acceleration of atrophy in which subjects transition from CSF Aβ negativity to CSF Aβ positivity were estimated from the spline models and tested for significance.ResultsSpline models resulted in better fits for many temporal and parietal regions compared with the dichotomous models. The trilinear model showed that periods of acceleration of atrophy varied greatly by region with early changes seen in the insula, amygdala, precuneus, hippocampus, and other temporal regions, occurring before the clinical threshold for CSF Aβ positivity.DiscussionThe use of piecewise‐linear splines provides an improved model of the nonlinear association between CSF Aβ and regional atrophy in regions implicated in the progression of AD. The important biological finding of this work is that some brain regions show periods of accelerated volume loss well before the CSF Aβ42 threshold. This implies that signs of brain atrophy develop before the current conventional definition of “preclinical AD”.

IntroductionLittle is known about the utility of plasma amyloid beta (Aβ) in clinical trials of Alzheimer's disease (AD).MethodsWe analyzed longitudinal plasma samples from two large multicenter clinical trials: (1) donezepil and vitamin E in mild cognitive impairment (n = 405, 24 months) and (2) simvastatin in mild to moderate AD (n = 225, 18 months).ResultsBaseline plasma Aβ was not related to cognitive or clinical progression. We observed a decrease in plasma Aβ40 and 42 among apolipoprotein E epsilon 4 (APOE ε4) carriers relative to noncarriers in the mild cognitive impairment trial. Patients treated with simvastatin showed a significant increase in Aβ compared with placebo. We found significant storage time effects and considerable plate‐to‐plate variation.DiscussionWe found no support for the utility of plasma Aβ as a prognostic factor or correlate of cognitive change. Analysis of stored specimens requires careful standardization and experimental design, but plasma Aβ may prove useful in pharmacodynamic studies of antiamyloid drugs.

AbstractMotivationDiseases that progress slowly are often studied by observing cohorts at different stages of disease for short periods of time. The Alzheimer's Disease Neuroimaging Initiative (ADNI) follows elders with various degrees of cognitive impairment, from normal to impaired. The study includes a rich panel of novel cognitive tests, biomarkers, and brain images collected every 6 months for as long as 6 years. The relative timing of the observations with respect to disease pathology is unknown. We propose a general semiparametric model and iterative estimation procedure to estimate simultaneously the pathological timing and long‐term growth curves. The resulting estimates of long‐term progression are fine‐tuned using cognitive trajectories derived from the long‐term “Personnes Agées Quid” study.ResultsWe demonstrate with simulations that the method can recover long‐term disease trends from short‐term observations. The method also estimates temporal ordering of individuals with respect to disease pathology, providing subject‐specific prognostic estimates of the time until onset of symptoms. When the method is applied to ADNI data, the estimated growth curves are in general agreement with prevailing theories of the Alzheimer's disease cascade. Other data sets with common outcome measures can be combined using the proposed algorithm.AvailabilitySoftware to fit the model and reproduce results with the statistical software R is available as the grace package. ADNI data can be downloaded from the Laboratory of NeuroImaging.