The Role of Alzheimer’s and Cerebrovascular Pathology in Mediating the Effects of Age, Race, and Apolipoprotein E Genotype on Dementia Severity in Pathologically-Confirmed Alzheimer’s Disease

Abstract

Background Dementia severity can be modeled as the construct δ, representing the “cognitive correlates of functional status.” Objective We recently validated a model for estimating δ in the National Alzheimer’s Coordinating Center’s Uniform Data Set; however, δ’s association with neuropathology remains untested. Methods We used data from 727 decedents evaluated at Alzheimer’s Disease (AD) Centers nationwide. Participants spoke English, had no genetic abnormalities, and were pathologically diagnosed with AD as a primary or contributing etiology. Clinical data from participants’ last visit prior to death were used to estimate dementia severity (δ). Results A structural equation model using age, education, race, and apolipoprotein E (APOE) genotype (number of ε2 and ε4 alleles) as predictors and latent AD pathology and cerebrovascular disease (CVD) pathology as mediators fit the data well (RMSEA = 0.031; CFI = .957). AD pathology mediated the effects of age and APOE genotype on dementia severity. An older age at death and more ε2 alleles were associated with less AD pathology and, in turn, with less severe dementia. In contrast, more ε4 alleles were associated with more pathology and more severe dementia. Although age and race contributed to differences in CVD pathology, CVD pathology was not related to dementia severity in this sample of decedents with pathologically confirmed AD. Conclusions Using δ as an estimate of dementia severity fits well within a structural model in which AD pathology directly affects dementia severity and mediates the relationship between age and APOE genotype on dementia severity.

Risk Factors and Pathological Substrates Associated with Agitation/Aggression in Alzheimer’s Disease: A Preliminary Study using NACC Data

“…Following a tradition at this exploratory stage, we have not corrected for multiple testing. Precisely for this reason we kept the statistics simple and did not include covariate analysis [13]. We chose not to exclude patients based presence of coexisting pathologies, and thus the sample does not represent “pure AD”, but is closer to clinical reality with multiple pathologies.…”

δ scores predict mild cognitive impairment and Alzheimer's disease conversions from nondemented states

“…However, TARCC is a highly selected convenience sample enriched with clinical AD. In similar highly selected samples, δ is associated with AD pathology [5] and outperforms the CERAD and the ADAS‐COG as a predictor of both hippocampal volume and AD‐specific CSF biomarkers [6].…”

“…Hippocampal volume may be an AD‐specific biomarker related to domain‐specific memory performance, but it is a relatively poor predictor (vs. δ) of dementia severity [32]. Similarly, δ is unrelated to ischemic pathology (the quintessential regional pathology) in the NACC [5]. The dementing aspect of “vascular cognitive impairment” must therefore be mediated by other mechanisms.…”

Blood‐based protein predictors of dementia severity as measured by δ: Replication across biofluids and cohorts

“…It remains to be seen (i.e., in the ADNI) whether AD‐specific neuroimaging and/or CSF biomarkers mediate those effects on δ, or whether they contribute independently to δ's variance. Age and depression (at least) do not appear to be mediated through AD‐specific neurodegeneration [51,52]. δ's vulnerability to multiple independent processes provides a rationale for cognitive “reserve” and intelligence's relevance to that concept.…”