Brain Aging and Late-Onset Alzheimer’s Disease: A Matter of Increased Amyloid or Reduced Energy?

Abstract

Alzheimer’s disease (AD) represents the most common form of dementia in old age subjects, and despite decades of studies, the underlying etiopathogenetic mechanisms remain unsolved. The definition of AD has changed over the past years, offering an ever more detailed definition of pre-morbid and pre-clinical status, but without a similar strong emphasis on the role of aging as the main risk factor. In fact, while early-onset AD is a clear consequence of gene mutations, late-onset AD is more likely due to a gradual accumulation of age-related damages. The pathogenetic amyloid cascade hypothesis has been recently questioned due to multiple clinical failures. Furthermore, several studies reported that cognitively normal elderly have a high amyloid deposition in the brain comparable to the levels observed in old age subjects with AD. This suggests that amyloid accumulation enters into the normal process of aging and what really triggers neuronal death and clinical manifestation in late-onset AD still needs further explanation. In this context, ‘normal brain aging’ and AD might represent a different pathway of successful or failed capability to adapt brain structures and cerebral functions. Cellular senescence and age-related changes affecting the brain may be considered as biologic manifestations of increasing entropy. Bioenergetic deficits due to mitochondrial dysfunction may lead to progressive neuronal death and clinical expression of dementia. So, increased amyloid in the brain of old age subjects may represent the downstream event expression of a biological system that is cooling down because of its exhaustion and not the core causative factor of late-onset dementia.

Keywords

Aging Alzheimer’s disease amyloid energy entropy mitochondria old age

A BRIEF HISTORICAL VIEW

Over 110 years have passed since Alois Alzheimer first described the pathology and symptoms of a young subject with dementia whose brain contained characteristic and histopathologic features called ‘neuritic plaques’ and ‘neurofibrillary tangles’ [1]. In the same year, Oskar Fischer also detected neuritic plaques in brains of old age subjects suffering from dementia [2]. Upon these observations, the scientific community considered the first situation as a disease, named Alzheimer’s disease (AD), and the second one as a consequence of aging, and thus defined senile dementia [3]. So, at that time, old age subjects with dementia were not diagnosed with AD, even though their brains frequently contained neuritic plaques and neurofibrillary tangles, as confirmed in postmortem studies. Upon such classification, in the following decades, AD was considered a rather uncommon entity of pre-senile dementia while senile dementia became progressively prevalent as life expectancy increased worldwide. In 1976, Katzman broke again what had become a certainty and with an editorial stated, “Alzheimer disease and senile dementia are a single process and should, therefore, be considered a single disease” [4, 5]. Since then, the definition changed and included all subjects, independently of age, with cognitive impairment as well as brain histopathological feature of AD.

After that, accumulation of epidemiologic data allowed researchers to identify two distinct AD populations: those with clearly recognizable autosomal dominant inheritance and those without evident genetic influence. The former typically present at younger ages and were thus defined as early-onset AD. The late onset group instead tends to manifest either sporadic or pseudo-sporadic epidemiology, considering that they are more likely to have AD-affected relatives.

Persons with autosomal dominant AD usually show clinical signs in their fourth or fifth decade of life. In this context, mutations in three ‘deterministic’ autosomal dominant genes have been identified. These genes include the amyloid precursor protein gene on chromosome 21, the presenilin 1 gene on chromosome 14, and the presenilin 2 gene on chromosome 1. Mutations in each gene increase production of the amyloid-β (Aβ) derivatives from the cleavage of amyloid-β protein precursor (AβPP) [6].

On the contrary, late-onset or pseudo-sporadic AD is not associated with deterministic gene mutations, but often genetically influenced. The most established genetic risk factor is the allele ɛ4 of the apolipoprotein E (APOE) gene on chromosome 19 [7], that is associated with the most common late-onset familial and with sporadic forms of AD. Although the mechanism by which APOE ɛ4 participates in pathogenesis is still under debate, the protein encoded by this gene is immunoreactive in plaques and neurofibrillary tangles that define the phenotype. The question of whether pathogenesis of ‘early’ and ‘late’ onset cases is similar enough to qualify them as a single disease was previously raised although not conclusively settled. Undoubtedly, they have many common traits, but they also exhibit numerous differences, as reported in Table 1.

Table 1

General characteristics of early and late-onset Alzheimer’s disease

	Early-Onset Alzheimer’s Disease	Late-Onset Alzheimer’s Disease
Age at onset	Younger than 65 years	65 years and older
Progression	Faster	Slower
Neuropsychology	Poor writing tasks, executive functions, visuospatial functions, motor behaviors	Poor memory and language
Neuropathology	Greater and more diffuse distribution of senile plaque, neurofibrillary tangles, and neuronal loss	Senile plaque and neurofibrillary tangles, neuronal loss
Cerebrospinal fluid markers	Similar values in amyloid-β, total tau protein, and phosphorylated tau protein
Genotype	Absence of ɛ4 alleles	Favored by 1 or 2 ɛ4 alleles
Structural and functional neuroimaging	Frontal/temporoparietal atrophy and decreased metabolism in temporoparietal cortex	Hippocampal atrophy; decreased metabolism in medial temporal lobe

Modified from van der Flier et al. [60].

However, the fact that they display a similar pathological process, which is the main diagnostic criterion for AD, led to the conclusion that they are technically variants of the same disease. Considering that the onset of cognitive deficits generally occurs within the 6th decade of life and severity increases along with time, advancing age represents the major known risk factor for AD. Interestingly, most people now diagnosed with dementia are old and would not have been diagnosed with AD as originally conceived. Accordingly, younger patients that qualify for a diagnosis of AD under both original and current AD constructs now represent an exceptionally small percentage of the diagnosed population.

In 1985, Stewart Shapiro and collaborators wrote a review entitled “Alzheimer’s disease: an emerging affliction of the aging population” stating that “the number of people who will have Alzheimer’s disease will double by the year 2030 because of the rising elderly population”. Again, they concluded, “Currently, there is no agreement relative to the etiology of Alzheimer’s disease, no effective cure, and no effective symptomatic therapy.”

THE AMYLOID HYPOTHESIS AND THE AGING BRAIN

Because of the progressive aging of population thanks to significant increase in life expectancy worldwide, current projections on incidence and prevalence of dementia look worse and scary [8]. Nowadays, AD represents the sixth leading cause of death in the USA, with five million subjects with AD, that could triplicate in three decades. The reason why the aging brain is particularly and extremely susceptible to dementia and what features can distinguish age-associated brain changes from those typical of AD is still unclear. Despite a long-lasting research in this area, the underlying mechanisms that trigger such a neuropathology remain unresolved.

The most supported and established pathogenetic hypothesis of AD in recent years is the so-called “amyloid hypothesis”. It postulates that high levels Aβ, in a variety of forms, but mainly as Aβ₄₂, triggers a cascade of events producing the pathological presentations of Aβ plaques, tau tangles, synapse loss, and neurodegeneration, which induces cognitive impairment. In detail, Aβ is a proteolytic degradation product of the larger amyloid-β protein precursor (AβPP), that can easily aggregate. Proteolysis by α-secretase can occur 83 amino acids from the AβPP intracellular carboxyl-terminal [9 –12]. Alternatively, proteolysis by β-secretase (BACE1) cuts 99 amino acids upstream of the AβPP carboxyl end. An enzyme complex, the γ-secretase, further processes the remaining carboxyl end of α-secretase (C-terminal fragment α; CTFα) or β-secretase (C-terminal fragment β; CTFβ) digested AβPP. In AβPP, mutations around the γ-secretase cleavage site cause a change in amino acids adjacent to the BACE1 cleavage site. PSEN-1 gene mutations (which give rise to proteins called presenilins) predominantly alter the amino acids in their nine transmembrane domains. The common thread to all these mutations is an increased production of the less soluble and more toxic Aβ₄₂. Several studies using postmortem tissue from patients with AD have demonstrated the presence of soluble oligomeric Aβ species in AD brains [9 –12]. Thus, oligomerization of Aβ has been proposed to be a key event in the pathogenesis of AD. Aβ is thought to go through a process of progressive aggregation from monomers to oligomers until plaque formation [13]. Recent evidence shows that soluble oligomeric species of Aβ have direct adverse effects, whereas fibrillar or monomeric Aβ seems to be less harmful in vitro and in animal models [21 –24]. Aβ oligomers are in fact responsible for synaptic dysfunction and for initiating processes leading to cell death and neurodegeneration. Indeed, studies using stable isotope labeled kinetic (SILK) techniques have recently better clarified that the main abnormality of Aβ in late-onset AD is a reduced clearance, in contrast with the autosomal dominant form of early-onset AD, where mutations in the AβPP or presenilin component of γ-secretase result in an overproduction of Aβ [25]. Amyloid depositions are part of the histopathological definition of AD, and thus much effort has been made on in vivo biomarkers of amyloid in contemporary AD research, as reflected in the NIA-AA proposed diagnostic guidelines for AD and its preclinical stages [26, 27]. They state that brain alteration in AD start years before clinical symptoms, causing neuronal functional damage and then clinical manifestation [27]. However, it has been suggested that once initiated, neurodegeneration in AD progresses independently of its amyloid-trigger, leading to the commonly expressed concern that the therapeutic window for anti-amyloid drugs is quite narrow, particularly when the amyloid cascade starts to accelerate and neurodegeneration become irreversible.

The recent failures of drugs targeting amyloid pathways have raised questions not only about this approach but also on the validity of the amyloid hypothesis itself. Moreover, studies of oldest-old individuals indicate that the occurrence of AD dementia is not a mandatory phenomenon of increasing chronological age. Approximately 20% to 30% of cognitively normal elderly have a similar amyloid deposition in the brain compared to the levels observed in AD dementia [28]. To further complicate the story, neuritic plaques also occur in cognitively healthy old age subjects. In old-age subjects with dementia, amyloid levels in cerebrospinal fluid (CSF) and amyloid cerebral load in PET-imaging do not correlate with cognitive decline [29]. Measurement of Aβ_1 - 42 in CSF shows reduced levels already in the preclinical phase of AD that remain low throughout the prodromal and dementia phases [30]. Similarly, amyloid imaging has confirmed that amyloid deposition begins before significant cognitive symptoms occur and Aβ burden in the brain remains approximately the same throughout the remainder of the disease [31]. Among old age subjects, there are patients with evident, sometimes severe, clinical expression of AD, but with low brain amyloid pathology while subjects with cognitive complaints, not severe enough to meet clinical criteria for dementia, have a brain amyloid load compatible with the diagnosis of AD [32 –36]. Some of them will die without becoming demented [37].

These observations suggest that in many old age subjects brain can tolerate a high amyloid accumulation without cognitive dysfunctions and, vice versa, that in old age patients with dementia other events are required to cause neurodegeneration and cognitive impairment. Moreover, autopsy studies of patients in the AN1792 Aβ vaccination trial showed that cognitive decline continues despite the effective removal of Aβ plaques [38]. Indeed, a recent study demonstrated that neuroradiological, biochemical, and neuropathological measures of neurodegeneration do not correlate with each other in a cohort of very old men. These measures also do not reflect the cognitive performances, suggesting that biomarkers of AD are less informative in the oldest-old [39]. Altogether, these data suggest that while amyloid can be considered as a hallmark of AD in younger subjects, its relationship to cell dysfunction and cognitive decline in the elderly is not so consequential. Rather, it seems that in the old age amyloid accumulation enters into the normal process of aging and what really triggers neuronal death and clinical manifestation has not evaluated in detail yet.

An unresolved conundrum is why Aβ and Aβ oligomers can be resident in the brain for many years without producing sufficient detectable cognitive dysfunction. Possibly, oligomers need to reach specific concentrations or be present in the brain for prolonged periods of time before neurotoxicity is triggered. The relationship between Aβ and cell death in the course of AD requires further clarification. The repeated failures of clinical trials with molecules acting on amyloid have been justified by the inclusion of subjects with too advanced brain pathology, unresponsive to any therapeutic intervention. But, on the other hand, these results provide additional data suggesting that amyloid might not be causal in late-onset AD pathophysiology [40 –47]. Although the oldest olds represent the largest and fastest growing population with dementia, most studies on dementia are focused on a younger population, in which amyloid is probably the only or the main cause of the disease. This is probably not true in the oldest-old, where other aspects, more related to the aging process at the molecular and subcellular level, better define the pathway leading to dementia.

For these reasons, it is necessary to better understand the relationship between amyloid, brain integrity, and cognitive function in healthy old age subjects. The core question is: what amyloid-related changes in the aging brain represent AD-related pathology, and what, if any, such changes can be expected as part of the ‘normal’ aging process? With this perspective, normal aging and AD might represent a different pathway of successful or failed capability to adapt brain structures and cerebral functions to aging processes. Thus, understanding their similarities and differences might be the key to solve such an enigma.

In this context, amyloid in the elderly may represent only a marker of the aged brain, which accumulates along with time and then contributing to, but not causing by itself alone, neuronal dysfunction. Therefore, some other mechanisms must be evaluated and put under the microscope.

AGING AS THE MAIN RISK FACTOR FOR OLD-AGE DEMENTIA: THE ROLE OF ENERGY AND MITOCHONDRIA

In order to re-formulate hypotheses on the pathogenesis of old-age dementia, we should put aging at the center of the debate. Aging is the inevitable biological process that results in a progressive structural and functional decline, from the cellular level to the whole body, causing a reduced ability to adapt to environmental changes and stressors. ‘Cellular senescence’ is one of the main contributing factors to age-associated cerebral dysfunction [48] and represents the core feature of the so-called age-related changes (ARCs) producing an overall reduction in the brain volume and weight and enlargement of cerebral ventricles [49]. Somatic cells are not able to proliferate indefinitely, but they arrest irreversibly after a limited number of divisions leading to complex changes in cellular metabolism, gene expression, and epigenetic regulation [50]. Increasing evidence shows that senescent cells are detectable in mammalian brains along with aging, and may also be implicated in neurodegenerative disorders [51]. For example, in brains of subjects affected by AD, microglial cells show a significant increase of biomarkers of senescence [52], which precedes the tau pathology in neurons [53]. These observations suggest that microglia are subjected to ARCs, and the impairment of microglial neuroprotective function is likely to have detrimental consequences for neurons, such as the development of neurofibrillary pathology. ARCs can occur in two fundamental ways: by a purposeful program driven by genes or by random, accidental events, both affecting brain cells viability and vulnerability. Intrinsic ARCs are those resulting from the programmed neuronal decline or due to the accumulation of waste byproducts. Extrinsic ARCs are the result of stochastic damaging events that can reduce the effective functioning of the brain below its expected duration.

The effects of such changes can be seen as the biological manifestation of increasing entropy of the system—defined as a measure of disorder according to the second law of thermodynamics. Entropy is the tendency for concentrated energy to disperse. The hindrance of entropy change is the relative strength of chemical bonds. The prevention of chemical bond breakage, among other structural changes, is essential for life. Through evolution, natural selection has favored energy states capable of maintaining fidelity in most molecules until reproductive maturation, after which there is no value for those energy states to be maintained indefinitely to keep alive a not reproductive organism. So, the aging process occurs because the decreased energy state alters structure and function of biomolecules leading to a progressive cellular damage and inactivity, until death.

Disruption of energy metabolism is commonly observed in senescent cells. In this context, mitochondria have a central role in the energy metabolism, representing the coal power plant. Most of the energy derived from the oxidation of nutritional substrates by the mitochondrial respiratory chain and transformed into ATP, the cellular energy currency. Aging is characterized by increased levels of mitochondrial DNA mutations, a declined function of the respiratory chain and abnormal mitochondrial elongation, likely due to increased expression of mitochondrial fusion proteins [54]. Overall, structural as well as functional abnormalities of mitochondria may lead to reduced energy level and to enhanced cellular damages which in turn leads cells to senescence or apoptosis. The decline of energy production causes an increased entropy, and biological aging represents the biomedical counterpart of the irreversible increasing entropy of any living system (cell, tissue, organ, body) where ARCs are the specific molecular components. Thus, along with aging, as entropy increases in the brain, the biological processes that normally maintain its structure and function start to decline, and altered misfolded proteins start to accumulate. Therefore we could hypothesize that the protein misfolding and aggregation we observed in aging brain, and then in late-onset dementia, is the final effect of a reduced energy production, due to exhausted mitochondria, and an increased entropy in the brain.

The impact of increasing entropy on the aging brain is highly visible for its unique complexity and shaped not only by the brain specialized neural functions, but also by the many ARCs, and opposing intrinsic and extrinsic homeostatic mechanisms. In this context, diet, lifestyle, and education may strongly modify the speed and the course of the process. However, when deterioration exceeds the capacities of these modulating factors, a progressive but irreversible functional decline appears.

One intriguing feature of the physiological aging the mammalian brain aging is the relatively slow rate of neuronal loss compared to the greater rate of decrease of cerebral myelinated nerve fibers [55]. However, when senescent neurons start to accumulate, the homeostatic equilibrium shifts from a gradual and linear decline to an accelerated degeneration. By recognizing sporadic late-onset AD as a disorder linked to senescence, driven by an increasing entropy and due to ARCs, several approaches to the understanding of the etiology and proposal of specific treatment could be scientifically re-evaluated.

The concept of late-onset AD as a consequence of increasing entropy—with an accelerated, catastrophic decline when homeostatic mechanisms fail—suggests that strategies designed to modify the course should precede the shift from gradual decline with normal aging to rapid tissue loss with AD. Thus, it seems important to reconsider late-onset AD as a complex condition with a prolonged trajectory of changes in the brain, characterized by progressively reduced metabolism and impaired bioenergetics. These changes start many years before the clinical onset, what supports and, in the meantime reflects, the incapacity of a biological system to maintain the molecular order that guarantees life thanks to a constantly high energetic support.

In this view, considering the fundamental role of mitochondria in cellular bioenergetics, the decline in mitochondrial function represents probably the pivotal factor. The ‘mitochondrial cascade hypothesis’ places the mitochondrial dysfunction as the leading factor in the pathological cascade of late-onset AD, underlying the individual genetic background able to regulate since birth its mitochondrial function and sustainability. When the mitochondrial function declines and falls below a critical threshold, AD-typical dysfunction may ensue at the cellular level, including Aβ production, tau phosphorylation, synaptic degeneration, and oxidative stress [56 –58]. In fact, perturbations in mitochondrial function have long been observed in samples derived from clinically confirmed AD, including altered mitochondrial morphology, compromised enzyme complexes in the tricarboxylic acid cycle, and reduced cytochrome c oxidase activity protein (reviewed in [57]). Moreover, Aβ accumulates within mitochondria and interacts with mitochondrial proteins (reviewed in [59]). All these processes create a vicious cycle in which excessive Aβ accumulation and sustained mitochondrial dysfunction synergize to activate a cascade of neurodegenerative pathways [59]. This unique trajectory enables a bioenergetic-centric strategy that targets disease-stage specific profile of brain metabolism for disease prevention and treatment: it depends on modifying as many ARCs as possible to delay and slow the increasing disorder due to entropy and avoid loss of brain function and increased neural vulnerability as long as possible.

In this perspective, the progressive reduction of capacity in producing, storing, and maintaining a high energy level, which is the main strategic role of mitochondria in eukaryotic cells, reflects the increased entropy that progressively leads the organism from function to dysfunction and then to death, the expression of the maximal entropic status. Reconsidering late-onset AD as a matter of energy rather than as a matter of amyloid could open new perspectives regarding pathogenesis and, overall, regarding prevention and therapy. Some strategies for delaying ARCs already have been identified such as avoiding vascular risks or limiting oxidative stress production. Many others may represent attractive targets against neurodegeneration.

In conclusion, the role of aging as a progressive status of energy decline can represent the key to recollect many theories around the main phenomenon that characterizes life: the fatal attraction toward its end.

Footnotes

ACKNOWLEDGMENTS

Virginia Boccardi is supported by Fondazione Cassa di Risparmio di Perugia.

Authors’ disclosures available online ().

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