Identifying longitudinal cognitive resilience from cross-sectional amyloid, tau, and neurodegeneration

Abstract

Background: Leveraging Alzheimer's disease (AD) imaging biomarkers and longitudinal cognitive data may allow us to establish evidence of cognitive resilience (CR) to AD pathology in-vivo. Here, we applied latent class mixture modeling, adjusting for sex, baseline age, and neuroimaging biomarkers of amyloid, tau and neurodegeneration, to a sample of cognitively unimpaired older adults to identify longitudinal trajectories of CR.

Methods: We identified 200 Harvard Aging Brain Study (HABS) participants (mean age = 71.89 years, SD = 9.41 years, 59% women) who were cognitively unimpaired at baseline with 2 or more timepoints of cognitive assessment following a single amyloid-PET, tau-PET and structural MRI. We examined latent class mixture models with longitudinal cognition as the dependent variable and time from baseline, baseline age, sex, neocortical Aβ, entorhinal tau, and adjusted hippocampal volume as independent variables. We then examined group differences in CR-related factors across the identified subgroups from a favored model. Finally, we applied our favored model to a dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI; n = 160, mean age = 73.9 years, SD = 7.6 years, 60% women).

Results: The favored model identified 3 latent subgroups, which we labelled as Normal (71% of HABS sample), Resilient (22.5%) and Declining (6.5%) subgroups. The Resilient subgroup exhibited higher baseline cognitive performance and a stable cognitive slope. They were differentiated from other groups by higher levels of verbal intelligence and past cognitive activity. In ADNI, this model identified a larger Normal subgroup (88.1%), a smaller Resilient subgroup (6.3%) and a Declining group (5.6%) with a lower cognitive baseline.

Conclusion: These findings demonstrate the value of data-driven approaches to identify longitudinal CR groups in preclinical AD. With such an approach, we identified a CR subgroup who reflected expected characteristics based on previous literature, higher levels of verbal intelligence and past cognitive activity.

Keywords: Alzheimer’s disease; Amyloid; Cognition; Cognitive Reserve; Cognitive Resilience; Longitudinal analysis; MRI; PET; Tau.

Fig. 1

Separable latent subgroups of PACC-5 trajectories in HABS. A PACC-5 vs time from baseline (years) colored by latent subgroup. B Smoothed group-level trajectories for HABS colored by subgroup. C PACC-5 vs time from baseline (years) faceted and colored by subgroup

Fig. 2

Examining PACC-5 trajectories in Aβ + participants suggests that the Resilient subgroup shows steep decline only in the presence of elevated Aβ, elevated tau and hippocampal atrophy. Aβ positivity was classified based on a threshold of > 1.185 DVR. Bottom panel shows trajectories of individuals who were positive for hippocampal atrophy (< 6,723mm). Top panel shows trajectories of individuals who were negative for hippocampal atrophy (> = 6,723mm). Aβ positivity and hippocampal atrophy were classified based on previously published thresholds < 6,723mm [–59]

Fig. 3

Pairwise comparisons of characteristics with significant differences across latent trajectory subgroups. A Baseline PACC-5. B CR residual. C AMNART VIQ. D Past Cognitive Activity

Fig. 4

Separable subgroups of PACC-5 trajectories in ADNI. A PACC-5 vs time from baseline (years) colored by subgroup. B Smoothed group-level trajectories for HABS colored by subgroup. C PACC-5 vs time from baseline (years) faceted and colored by subgroup