The influence of tau, amyloid, alpha-synuclein, TDP-43, and vascular pathology in clinically normal elderly individuals

Abstract

Many individuals live to older ages without clinical impairment. It is unknown whether brain pathologies in these individuals are associated with subtle clinical deficits. We analyzed the brains of 161 clinically normal (Clinical Dementia Rating score = 0) older individuals enrolled in the Mayo Clinic Patient Registry or Study of Aging. We assessed for the presence and burden of beta-amyloid, tau, alpha-synuclein, TDP-43, and vascular pathology. We investigated whether pathologies were associated with antemortem cognitive and motor function, depression, MRI volumetric measures, or the apolipoprotein E (APOE) ε4 allele. Eighty-six percent had at least 1 pathology, and 63% had mixed pathologies. Tau and vascular pathology were associated with poorer memory scores. Tau was also associated with poorer general cognition scores and smaller amygdala, hippocampi, and entorhinal cortex volumes. Beta-amyloid neuritic plaque burden was associated with greater depression scores. The presence of a greater number of pathologies was associated with APOE e4 carrier status and with poorer memory performance. Some dementia-related pathologies are associated with poorer performance in clinical measures and brain atrophy in the unimpaired elderly.

Keywords: Brain volume; Clinically normal aging; Cognition; Depression; Neurodegenerative pathology; TDP-43; Vascular pathology.

Figure 1:

Plot showing the different types of pathologies for each subject grouped by number of pathologies

Figure 2:

Plots of estimates from age-adjusted linear regression models with neuropsychological tests as an outcome with pathological measures assessed as binary variables. Models were adjusted for age at neurological exams. (*p<0.05, **p<0.01, ***p<0.001.)

Figure 3:

Plots of estimates from age-adjusted linear regression models with gray matter volumes (cm³) as an outcome (N=102) with pathological measures assessed as binary variables. Models were adjusted for age at MRI scan, years from MRI scan to death and log-transformed TIV (*p<0.05, **p<0.01, ***p<0.001).

Figure 4:

Plots of estimates from age-adjusted linear regression models with neuropsychological tests as an outcome with pathological measures assessed as ordinal variables. Models were adjusted for age at neurological exams. (*p<0.05, **p<0.01, ***p<0.001.)

Figure 5:

Plots of estimates from age-adjusted linear regression models with gray matter volumes (cm³) as an outcome (N=102) with pathological measures assessed as ordinal variables. Models were adjusted for age at MRI scan, years from MRI scan to death and log-transformed TIV (*p<0.05, **p<0.01, ***p<0.001).