Determinants of cognitive and brain resilience to tau pathology: a longitudinal analysis

Abstract

Mechanisms of resilience against tau pathology in individuals across the Alzheimer's disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We used a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicentre study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer's disease dementia with baseline 18F-flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβinteraction = -0.062, P = 0.032), higher education level (Stβinteraction = -0.072, P = 0.011) and higher intracranial volume (Stβinteraction = -0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer's disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences.

Keywords: Alzheimer’s disease; MRI; PET; cognition; resilience; tau.

Figure 1

Association of baseline tau-PET burden with rate of cognitive decline, stratified per determinant of interest. For visualization purposes, annual change in MMSE (points/year) was calculated for each participant through an individual level regression of all available MMSE observation on time (in years). Continuous determinants were divided in tertiles. ICV = intracranial volume; MMSE = Mini-Mental State Examination; ROI = region of interest; SUVR = standardized uptake value ratio.

Figure 2

Cognitive resilience moderating determinants. This figure illustrates the statistical interaction of age (top row), education (middle row) and intracranial volume (ICV) (bottom row) with temporal meta-ROI tau-PET burden on rate of cognitive decline. Model-predicted associations and trajectories for representative values (low, intermediate, high) are shown, where the three levels of tau burden and of determinants variables were defined as the average value within the tertiles for each variable (note that the linear mixed models with continuous predictors were used to predict the decline trajectories; the tertile mean representative values were selected as that allowed plotting of raw individual trajectories within each level of tau burden). Older age at baseline (A and B), higher education (C and D) and higher ICV (E and F) adversely modified the negative effect of tau-PET burden on rate of cognitive decline. Temporal meta-ROI tau uptake levels: higher = 2.2 SUVR; intermediate = 1.6 SUVR; lower = 1.2 SUVR. Age levels: higher = 82 years old; intermediate = 74 years old; lower = 64 years old. Education levels: higher = 18 years; intermediate = 15 years; lower = 11 years. ICV levels: higher = 1.64 dm³; intermediate = 1.45 dm³; lower = 1.29 dm³. Horizontal bars with asterisk in A, C and E indicate regions of temporal meta-ROI tau-PET uptake values for which age, education and ICV were significantly associated with rate of cognitive decline, as derived from a Johnson-Neyman analysis on simplified models of MMSE slopes regressed onto the interaction between tau burden and each determinant. Note that this figure shows model-predicted relationships, in contrast to Fig. 1, which plots relationships based on the raw data. MMSE = Mini-Mental State Examination; ROI = region of interest.

Figure 3

Regional interaction effects of investigated determinants with localized tau-PET uptake on rate of global cognitive decline. (A) Significant associations (P < 0.05 uncorrected and FDR < 0.05 corrected for multiple comparisons) between regional tau tracer binding and rate of change in MMSE. (B) Coefficients of the three-way interaction of age with local tau burden and time from (separate) linear mixed models across the 68 Desikan-Killiany atlas-based cortical regions of interest. Older age at baseline was associated with a strengthened negative effect of tau burden in the regions highlighted in blue on cognitive decline. (C) Coefficients of the three-way interaction of APOE-ε4 genotype with local tau burden and time from (separate) linear mixed models across the 68 cortical ROIs. APOE-ε4 positivity was associated with an attenuated effect of tau burden in the entorhinal cortex (region highlighted in red) on cognitive decline.

Figure 4

Brain resilience moderating determinants. This figure illustrates the statistical interaction of education with temporal meta-ROI tau-PET burden on rate of cortical thinning in the AD-signature composite region. Model-predicted associations and trajectories for representative values (low, intermediate, high) are shown, where the three levels of tau burden and of education were defined as the average value within the tertiles for each variable (note that the linear mixed models with continuous predictors were used to predict the decline trajectories; the tertile mean values were selected as that allowed plotting of raw individual trajectories within each level of tau burden). (A and B) Higher education adversely modified the negative effect of tau-PET burden on rate of cognitive decline. Temporal meta-ROI tau uptake levels: higher = 2.1 SUVR; intermediate = 1.5 SUVR; lower = 1.2 SUVR. Education levels: higher = 18 years; intermediate = 16 years; lower = 12 years. Bar with asterisk in A indicates regions of temporal meta-ROI tau-PET uptake values for which education was significantly associated with rate of cortical thinning, as derived from a Johnson-Neyman analysis on simplified models of cortical thinning slopes regressed onto the interaction between tau burden and education.

Figure 5

Theoretical scenarios depicting the relationship of the determinant variable (low/high) and rates of cognitive decline/atrophy. (A) Preserved differentiation is observed if an existing baseline difference in intercepts is preserved over time (i.e. slopes for the low/high groups are the same). (B) Differential preservation is observed, on the other hand, when, rather than a difference in intercepts, there is a differential association of the determinant with the decline rate. (C) Enhanced differentiation depicts the scenario in which the initial difference in intercepts is further enhanced (the lines diverge further) given also a ‘protective’ relationship of the determinant with the slope. (D) Reduced differentiation illustrates the opposite case, in which the group starting higher at baseline declines faster with accumulating tau pathology, closing the gap between the two lines.