Koscik RL, Betthauser TJ, Jonaitis EM, Allison SL, Clark LR, Hermann BP, Cody KA, Engle JW, Barnhart TE, Stone CK, Chin NA, Carlsson CM, Asthana S, Christian BT, Johnson SC. Amyloid duration is associated with preclinical cognitive decline and tau PET. Alzheimers Dement (Amst). 2020;12(1):e12007. Epub 2020 Feb 13 PubMed.

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  1. This manuscript by Koscik et al. on amyloid duration—or “chronicity”—presents an innovative and valuable approach to a well-trodden research question: How can we best model brain amyloid accumulation to analyze its associations with tau pathology, cognitive function, and clinical decline? As the paper notes, multiple previous studies have employed longitudinal amyloid PET data to examine progression along the AD continuum. However, this work, by using group-based trajectory modeling to “[recast] the magnitude of amyloid elevation along the time dimension,” in effect cleans up the noise in amyloid accumulation trajectories along a new and more functional x-axis. It does so by producing a chronicity variable that does a statistically superior job (relative to chronological age, continuous PiB DVR, or PiB positivity) of predicting biomarker, cognitive, and clinical outcomes.

    In clearly demonstrating trajectory group membership in initially asymptomatic individuals and predicting the time to conversion to amyloid positivity in currently amyloid-negative individuals, this research helps us better understand the earliest stages of pathological amyloid accumulation. In addition, by using this chronicity measure—in particular, to quantify how long an individual has been amyloid-positive—to provide improved predictions of not only entorhinal tau pathology using MK-6240 PET but also progression to MCI and AD, this work enhances our ability to quantify disease progression and the impacts of brain amyloid deposition even in the prodromal phase of AD. Further, the aforementioned improved ability to predict clinical progression may be beneficial for disease prognosis in clinically asymptomatic individuals as well. Of course, notable limitations are the family-history enriched sample with a relatively low level of underrepresented minorities, so the results may not necessarily generalize to other, more diverse populations with different risk levels. However, this study is an important proof-of-concept work that may increase our knowledge of the early transitions from normal cognition to cognitive impairment and dementia.

    View all comments by Samuel Lockhart

  2. This is an interesting approach to obtain additional information from amyloid PET scans beyond dichotomization (A+/-) or a composite measure of amyloid PET signal. This fits a series of studies taking alternative approaches to increase the predictive value of amyloid PET measures for cognition or other AD biomarkers, e.g. “time-to-amyloid-positivity” (Insel et al., 2017), subthreshold amyloid PET uptake (Landau et al., 2018) or amyloid PET signal in CSF+/PET- groups (Palmqvist et al., 2017). The measure called “amyloid chronicity” reflects the modeled number of years for which an individual has been exposed to significant amyloid burden (A+) or the time it will take to become A+ in the future. This is an inventive idea. Strengths of the approach include the non-linear modelling to account for the presumed sigmoidal shape of amyloid accrual over time and the fact that amyloid chronicity could be reasonably well established based on a single amyloid PET scan. The added value of the amyloid chronicity measure compared to binarized amyloid PET results is clear, but further studies are needed to evaluate whether it also outperforms a global or regional amyloid measure (on some outcomes it showed better model fit, but not on others). An inherent disadvantage of the approach is that it still needs a threshold for amyloid-positivity and that the potential value of subthreshold levels of amyloid pathology is potentially not fully utilized. I look forward to studies applying this method to F18-labeled amyloid PET tracers and/or in other study populations.

    References:

    Insel PS, Ossenkoppele R, Gessert D, Jagust W, Landau S, Hansson O, Weiner MW, Mattsson N, Alzheimer's Disease Neuroimaging Initiative. Time to Amyloid Positivity and Preclinical Changes in Brain Metabolism, Atrophy, and Cognition: Evidence for Emerging Amyloid Pathology in Alzheimer's Disease. Front Neurosci. 2017;11:281. Epub 2017 May 17 PubMed.

    Landau SM, Horng A, Jagust WJ, Alzheimer's Disease Neuroimaging Initiative. Memory decline accompanies subthreshold amyloid accumulation. Neurology. 2018 Apr 24;90(17):e1452-e1460. Epub 2018 Mar 23 PubMed.

    Palmqvist S, Schöll M, Strandberg O, Mattsson N, Stomrud E, Zetterberg H, Blennow K, Landau S, Jagust W, Hansson O. Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity. Nat Commun. 2017 Oct 31;8(1):1214. PubMed.

    View all comments by Rik Ossenkoppele

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  1. Amyloid—It’s Not Whether, but for How Long You’ve Had It