Alzheimer's disease is not "brain aging": neuropathological, genetic, and epidemiological human studies

Abstract

Human studies are reviewed concerning whether "aging"-related mechanisms contribute to Alzheimer's disease (AD) pathogenesis. AD is defined by specific neuropathology: neuritic amyloid plaques and neocortical neurofibrillary tangles. AD pathology is driven by genetic factors related not to aging per se, but instead to the amyloid precursor protein (APP). In contrast to genes involved in APP-related mechanisms, there is no firm connection between genes implicated in human "accelerated aging" diseases (progerias) and AD. The epidemiology of AD in advanced age is highly relevant but deceptively challenging to address given the low autopsy rates in most countries. In extreme old age, brain diseases other than AD approximate AD prevalence while the impact of AD pathology appears to peak by age 95 and decline thereafter. Many distinct brain diseases other than AD afflict older human brains and contribute to cognitive impairment. Additional prevalent pathologies include cerebrovascular disease and hippocampal sclerosis, both high-morbidity brain diseases that appear to peak in incidence later than AD chronologically. Because of these common brain diseases of extreme old age, the epidemiology differs between clinical "dementia" and the subset of dementia cases with AD pathology. Additional aging-associated mechanisms for cognitive decline such as diabetes and synapse loss have been linked to AD and these hypotheses are discussed. Criteria are proposed to define an "aging-linked" disease, and AD fails all of these criteria. In conclusion, it may be most fruitful to focus attention on specific pathways involved in AD rather than attributing it to an inevitable consequence of aging.

Fig. 1

United States Census Bureau data and projections illustrate the practical need to understand the correlation between aging and Alzheimer’s disease (AD). Raw numbers for the United States population (2000) rand projected (2010 and 2020) are shown (a). Note that the demographic changes between 2000 and 2020 in the US are not projected to affect all age groups the same. Projected increases over time (2000–2020) are shown in b. The number of persons between ages 85 and 89 years of age will increase by approximately 30% in that time period, whereas the number of people between ages 95–99 years of age will increase by over 100%. If aging itself is linked mechanistically to AD, then Western cultures are at gravely increased AD risk. However, it may be a mistake to conflate AD with other causes of cognitive impairment. Source: US Census Bureau

Fig. 2

Aβ deposition in the hippocampus of a 5-month-old infant with Down syndrome (DS). DS is caused by triplication of chromosome 21 genes including the amyloid precursor protein (APP) locus. This Caucasian female died after 148 days due to complications of congenital heart disease. At autopsy, brain weight was 550 g with foreshortening of the anterior–posterior dimension as is characteristic of DS. Photomicrographs show hippocampus counterstained with Nissl stain (blue) and immunostained (brown) using anti-Aβ (6E10). Sections showed diffuse plaque-like structures (a) and smaller, more filamentous-looking Aβ deposits (b). Separate controls run in parallel without primary or secondary antibodies were completely negative (c, d). All persons with DS eventually develop Alzheimer’s disease (AD). This drives home the point that although much is still unknown about AD pathobiology, genetic risk factors related to APP are of paramount relevance. Scale bars 50 μM (a), 20 μM (b), and 100 μM (c, d)

Fig. 3

Death rates for prostate and kidney carcinoma (CA) in American males according to the SEER database [87]. These data are presented to show the different epidemiology of two different urothelial-derived cancers in men. This is a case where the epidemiology can help guide important research questions related to the biology of the cancers and the impact of aging and senescence. Although cancer is considered an aging-associated disease, the particular subtypes of cancer tend to inhabit particular ranges of the human age spectrum. This paradigm also applies to human neurodegenerative diseases which (like kidney cancer) may peak prior to extreme old age

Fig. 4

National Alzheimer’s Coordinating Center (NACC) Registry data provide important clues about the correlations between aging, Alzheimer’s disease (AD), and cerebrovascular disease (CVD). Data were obtained from 25 different Alzheimer’s Disease research centers as described previously [23]. For the assessment of CVD pathology (a), all cases in the relevant age range (N = 4,423) were included. These show that CVD is strongly increased in advanced age with ~90% of centenarians showing at least subtle CVD pathology. In assessing AD (b), we only evaluated individuals with Braak stages V or VI neurofibrillary pathology (N = 2,073). Note that among brains with “definite” AD pathology, there is an increasing tendency for Braak V (instead of VI) in older individuals

Fig. 5

In a large clinical–pathological study that incorporated the UK-ADC autopsy cohort, The Nun Study [209], and The Georgia Centenarian Study [173], we evaluated 106 cases with hippocampal sclerosis (HS-Aging) and 1,004 controls [152], including many with AD. Collectively, these cohorts may be enriched for individuals with cognitive impairment at death because of recruitment bias; however, N = 625/1,110 or 57% had neither HS-Aging nor AD. Beyond 95 years of age at death, the prevalence of AD pathology (defined by numerous neuritic amyloid plaques and Braak stages V or VI on autopsy) appeared to decline, whereas the prevalence of HS-Aging pathology became almost as high as AD pathology

Fig. 6

Epidemiology of clinical dementia and specific pathologies that contribute to dementia. The epidemiology of dementia (a) is based on well-characterized clinical cohorts (for review see [112]). The epidemiology of the different brain diseases—with autopsy confirmation—is far harder to know for sure because the data are critically dependent on autopsy-derived information including the neuropathological practices used at autopsy. Most autopsy series lack large numbers of individuals of extreme advanced age, and each study has distinct biases in terms of recruitment, inclusion, and neuropathological assessments. The chart (b) is a subjective amalgamation of multiple published studies pertinent to this important topic [19, 21, 61, 76, 79, 80, 96, 102, 105, 106, 115, 140, 145, 150, 156, 158, 171, 176, 184, 193, 198, 211, 217, 228, 231]