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Tytuł pozycji:

Estimating an individual's placement on a theoretical continuum using longitudinal cognitive trajectories: Relationships with longitudinal amyloid and Tau‐PET: Neuropsychology: Longitudinal cognitive assessment in early stages of AD.

Tytuł :
Estimating an individual's placement on a theoretical continuum using longitudinal cognitive trajectories: Relationships with longitudinal amyloid and Tau‐PET: Neuropsychology: Longitudinal cognitive assessment in early stages of AD.
Autorzy :
Properzi, Michael J.
Buckley, Rachel F.
Papp, Kathryn V.
Farrell, Michelle E.
Jacobs, Heidi I.L.
Hanseeuw, Bernard J.
Rabin, Jennifer S.
Chhatwal, Jasmeer P.
Rentz, Dorene M.
Johnson, Keith A.
Sperling, Reisa A.
Schultz, Aaron P.
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Źródło :
Alzheimer's & Dementia: The Journal of the Alzheimer's Association; Dec2020 Supplement S6, Vol. 16 Issue 6, p1-3, 3p
Czasopismo naukowe
Background: Theoretical models of the Alzheimer's disease (AD) continuum posit a curvilinear trajectory of declining cognition, with accumulating AD pathology catalyzing an accelerated rate of decline. Assuming this continuum can be modelled, individuals can be placed along the curve based on their longitudinal cognitive performance. In this way, we can reduce multi‐dimensional data to a single parameter (simplification/parsimony) and remove non‐linearity in the cognitive data. Method: 317 participants from the Harvard Aging Brain Study (72 years (7.6); Female:61.5%) underwent longitudinal neuropsychological assessments (follow‐up: 5.9years (2.1) range:1.7‐9.1) and PIB‐PET imaging. A subset of participants (n=230) also underwent FTP‐PET imaging. Cognition was measured using the Preclinical Alzheimer Cognitive Composite (PACC). Using iterative non‐linear least squares optimization, we defined a curvilinear function (incorporating linear, quadratic and exponential components) that best described the group level PACC trajectory of all participants (Figure 1). Each subject's longitudinal PACC trajectory was then located on the resulting curve using trust‐region‐reflective non‐linear least squares optimization, solving for an individual's time offset (toffset). We examined associations between toffset, age, sex, apoe4 status, cross‐sectional PIB‐PET and FTP‐PET. We also examined toffset in relation to changing PIB‐PET and FTP‐PET. Result: Individuals with a more advanced toffset had higher levels of entorhinal (EC) and inferior temporal (IT) FTP‐PET (r=0.42, p=<<0.001; Figure 2A&B.), and also showed higher PiB‐PET signal (r=0.36, p=<<0.001; Figure 2C.) PIB accumulation appears earlier in toffset followed by EC TAU and finally IT TAU, suggesting that a biomarker cascade is being captured by toffset (Figure 3). FTP‐PET and PIB‐PET did not interact to predict toffset. There was no effect of age or APOE4, or an interaction between the two, on toffset. Conclusion: Using toffset, estimating an individual's position along a hypothetical clinical continuum can inform the unique contributions of AD biomarkers, and test hypotheses about temporal sequences of events. This data‐reduction approach is superior to that of pulling cognitive slopes, as the tpffest removes complex non‐linearities inherent in the data (Figure 4). We also illustrate that an interaction between FTP‐PET and PIB‐PET does not predict toffset, suggesting a common upstream mechanism that may underlie both Aβ and tau to drive decline, at least during the preclinical stages of disease. [ABSTRACT FROM AUTHOR]
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