Age-specific population frequencies of cerebral β-amyloidosis and neurodegeneration among people with normal cognitive function aged 50-89 years: a cross-sectional study

Abstract

Background: As preclinical Alzheimer's disease becomes a target for therapeutic intervention, the overlap between imaging abnormalities associated with typical ageing and those associated with Alzheimer's disease needs to be recognised. We aimed to characterise how typical ageing and preclinical Alzheimer's disease overlap in terms of β-amyloidosis and neurodegeneration.

Methods: We measured age-specific frequencies of amyloidosis and neurodegeneration in individuals with normal cognitive function aged 50-89 years. Potential participants were randomly selected from the Olmsted County (MN, USA) population-based study of cognitive ageing and invited to participate in cognitive and imaging assessments. To be eligible for inclusion, individuals must have been judged clinically to have no cognitive impairment and have undergone amyloid PET, (18)F-fluorodeoxyglucose ((18)F-FDG) PET, and MRI. Imaging results were obtained from March 28, 2006, to Dec 3, 2013. Amyloid status (positive [A(+)] or negative [A(-)]) was determined by amyloid PET with (11)C Pittsburgh compound B. Neurodegeneration status (positive [N(+)] or negative [N(-)]) was determined by an Alzheimer's disease signature (18)F-FDG PET or hippocampal volume on MRI. We determined age-specific frequencies of the four groups (amyloid negative and neurodegeneration negative [A(-)N(-)], amyloid positive and neurodegeneration negative [A(+)N(-)], amyloid negative and neurodegeneration positive [A(-)N(+)], or amyloid positive and neurodegeneration positive [A(+)N(+)]) cross-sectionally using multinomial regression models. We also investigated associations of group frequencies with APOE ɛ4 status (assessed with DNA extracted from blood) and sex by including these covariates in the multinomial models.

Findings: The study population consisted of 985 eligible participants. The population frequency of A(-)N(-) was 100% (n=985) at age 50 years and fell to 17% (95% CI 11-24) by age 89 years. The frequency of A(+)N(-) increased to 28% (24-32) at age 74 years, then decreased to 17% (11-25) by age 89 years. The frequency of A(-)N(+) increased from age 60 years, reaching 24% (16-34) by age 89 years. The frequency of A(+)N(+) increased from age 65 years, reaching 42% (31-52) by age 89 years. The results from our multinomial models suggest that A(+)N(-) and A(+)N(+) were more frequent in APOE ɛ4 carriers than in non-carriers and that A(+)N(+) was more, and A(+)N(-) less frequent in men than in women.

Interpretation: Accumulation of amyloid and neurodegeneration are nearly inevitable by old age, but many people are able to maintain normal cognitive function despite these imaging abnormalities. Changes in the frequency of amyloidosis and neurodegeneration with age, which seem to be modified by APOE ɛ4 and sex, suggest that pathophysiological sequences might differ between individuals.

Funding: US National Institute on Aging and Alexander Family Professorship of Alzheimer's Disease Research.

Figure 1. Estimated percentage of participants in each biomarker group by age

Estimates are from a multinomial model adjusted for sex. Nonlinearity in age was allowed in the model by fitting age as a spline with knots at 60, 70, and 80 years. 95% parametric bootstrap confidence intervals are also shown.

Figure 2. Estimated differences in percentage of participants in each biomarker group by age

Probabilities in each group were estimated from a multinomial model adjusted for sex. Nonlinearity in age was allowed in the model by fitting age as a spline with knots at 60, 70, and 80 years. Differences in probabilities are plotted with 95% parametric bootstrap confidence intervals.

Figure 3. Estimated percentage in each biomarker group by age, sex, and APOE genotype

Percentages are estimated from a multinomial model with age, sex, and APOE genotype. Nonlinearity in age was allowed in the model by fitting age as a spline with knots at 60, 70, and 80 years. 95% parametric bootstrap confidence intervals are also shown.

Figure 4. Possible transitions from one A/N group to another conditioned on remaining cognitively normal

Fig 4a illustrates the pathophysiological sequence of pre-clinical AD without major comorbid non-AD pathology, A−N− to A+N− to A+N+. Fig 4b illustrates the pathophysiological sequence someone who first develops SNAP neurodegeneration, then later enters the AD pathophysiological pathway, denoted by a positive amyloid PET study, A−N− to A N+ to A+N+. Fig 4c illustrates the pathophysiological sequence of someone who develops SNAP neurodegeneration without progressing into the AD pathophysiological pathway, A−N− to A−N+.