ReviewA metabolic perspective of late onset Alzheimer’s disease
Graphical abstract
Introduction
The study of Alzheimer’s disease (AD) began in the early twentieth century, when the German physician Alois Alzheimer described the first case of this pathology in a 51-year old woman called Auguste Deter [1]. Her symptoms included remarkable memory loss, language difficulties and personality changes. After the post-mortem examination, the brain autopsy revealed specific neuropathological changes in the cerebral cortex [[1], [2], [3], [4]], now known as the classical morphological symptoms of AD: amyloid β (Aβ) peptide plaques derived of the activity of the amyloidogenic pathway and neurofibrillary tangles (NFTs), composed by hyperphosphorylated tau protein [[3], [4], [5], [6], [7], [8]].
At present, the aetiological hypothesis most supported by the scientific community is the “amyloid cascade hypothesis”, which is summarized in Fig. 1. According to this hypothesis, under physiological conditions amyloid β protein percussor (AβPP) is cleaved by the enzyme α-secretase, following the non-amyloidogenic pathway. This precludes formation of amyloidogenic peptides and leads to a release of secreted AβPP alpha (sAβPPα), which has neuroprotective properties [5]. On the contrary, in the amyloidogenic pathway, AβPP is cleaved by β-secretase (BACE-1) at N-terminus and, in turn, γ/ε-secretase cleaves it at the C-terminus to yield secreted AβPP (sAβPP), Aβ40/42 fragments (which remain in the extracellular space) and a C-terminal fragment with 99 amino acids (C99) that can be translocated to the nucleus. Here, it may induce expression of genes that promote neuronal death by apoptosis. Moreover, the soluble Aβ oligomers generated in this way affect synapse function, decrease neuronal plasticity, alter energy and glucose metabolism, induce oxidative stress and mitochondrial dysfunction, and disturb celular calcium homeostasis [2,5].
During the early 1990s, some genetic factors -apart from AβPP- were shown to increase the risk of developing the disease, such as apolipoprotein E (APOE) or presenilin 1 and 2 (PS1 and PS2) [[7], [8], [9], [10], [11]]. These factors were also involved in the amyloid cascade. For instance, the allele for APOE ε4 was been shown to impair Aβ clearance and promote its aggregation, leading to increased severity of this amyloid pathology [[7], [8], [9], [10], [11], [12]]. In spite of this, the existence of other factors that can contribute to the pathogenesis of AD emphasizes its complexity. Some of these risk factors are shown in Fig. 2.
Against this background, AD patients were classified into two groups. The first one was formed for those subjects that developed the pathology due to genetic causes leading to the production of classical biomarkers like Aβ. This group covered about 3% of AD patients and was dubbed “familial or early-onset AD”. The remaining 97% of patients were categorized as “sporadic or late-onset AD” (LOAD), whose progression was associated with advanced age, hypertension, hyperlipidaemia, coronary disease, obesity and type 2 diabetes mellitus (T2DM) [[12], [13], [14]].
T2DM is a complex disease with a chronic evolution that requires continuous medical care, mainly focused on the reduction of global cardiovascular risk, peripheral complications and cognitive loss [15]. Unlike type 1 diabetes mellitus (T1DM), an autoimmune disorder characterized by the selective destruction of insulin-producing β-cells [16,17], in T2DM there is an alteration in the mechanisms of uptake and/or secretion of insulin. This leads to a chronic increase in blood levels of glucose, resulting in a higher risk of macro and microvascular complications. T2DM is also associated with insulin resistance (IR), which is characterized by lower insulin activity at the cellular level, and affects the metabolism of carbohydrates, lipids and proteins [15]. As we have mentioned, in addition to a risk factor for cardiovascular pathologies, T2DM is also an independent risk factor for LOAD [[11], [12], [13], [14]]. Specifically, it is widely recognized that T2DM and AD share several kinds of abnormalities, including increased oxidative stress, impaired glucose metabolism and insulin resistance characterized by continuous hyperinsulinemia [12,12,13,14,18]. Likewise, some studies have focused on the role of insulin receptor (IR), which might be an important player in the pathology of AD, by contributing to the biochemical, molecular and histopathological characteristics of the pathology [13,[19], [20], [21], [22], [23], [24], [25], [26], [27]].
Given that the origin of the pathology is still unknown, and that there seem to be many players involved in its development, AD has been defined as a multifactorial disease (Fig. 2). Consequently, there are different research areas, in addition to neuroscience, trying to elucidate the origin of this pathology. In fact, prospective epidemiological studies have identified metabolic syndrome and T2MD as risk factors for multiple diseases of the nervous system [[18], [19], [20]]. Furthermore, animal studies have shown that hypercaloric diets affect the structure and functions of the hippocampus, although the specific mechanisms are unclear [28], [29]. Thus, it has been reported that AβPPswe/PS1dE9 (AβPP/PS1) transgenic mice fed with a diet enriched in palmitic acid, showed reduced IR and increased insoluble Aβ peptide levels, as well as cognitive deficits [30]. Moreover, Ho and colleagues found evidence linking insulin resistance and increased relative risk for AD neuropathology development, by demonstrating that IR signalling can influence Aβ production in the brain [31]. These results evidenced the relationship between metabolic alterations and progression of AD features, thus reinforcing the hypothesis of a metabolic aetiology of AD. Indeed, it has been proposed to re-name AD as “type 3 diabetes mellitus” (T3DM) or brain-specific diabetes [32].
The present review is a state-of-the-art about the relation among obesity, Aβ oligomers and the IR modulation. In addition, we discuss the potential application of drugs modulating the brain insulin receptor pathway as targets for AD prevention.
Section snippets
An historical overview of AD’s hypotheses and available pharmacological treatments
Altghough over a century has passed since AD was first described, the pathogenesis of this complex disease is still unclear. A number of theories about AD origin have been postulated so far and several drugs have been tested in accordance. The first one, proposed in the 80 s, was the “cholinergic hypothesis”, which suggested that a dysfunction of acetylcholine-containing neurons in the brain contributes substantially to the cognitive decline observed in AD patients [[33], [34], [35]]. This
Mechanisms linking obesity and cognitive decline: results from preclinical models
Nearly 20 years ago, the Rotterdam study reported that T2DM patients had increased risk to suffer dementia [71,72]. Today, obesity and diabetes, two T2DM-related disorders, are well established risk factors for AD [11,23,[71], [72], [73], [74]]. In fact, it is of general concern that accumulation of fat in the adipose tissue favours the emergence of metabolic syndrome and T2DM, due to IR signalling deficits in peripheral tissues. What is, perhaps, not so widely known is that obesity also
Are ceramides the bridge between peripheral type II diabetes and neurodegeneration in Alzheimer’s disease?
As discussed above, preclinical studies demonstrated that HFDs enhance cognitive loss, stressing its central effects. However, HFDs can also favour cognitive loss through peripheral alterations, specifically in the liver and adipose tissue. In an interesting study, Lyn-Cook and co-workers reported that HFDs induce liver damage (non-alcoholic steatohepatitis), by increasing the levels of pro-inflammatory cytokines (mainly TNFα) and ceramides [113]. Ceramides are toxic lipids which play key roles
Endoplasmic reticulum (ER) stress: a link between obesity and cognitive loss
Some research studies have indicated that the ER stress is involved in the appearance of degenerative diseases in the brain [120,121]. Obesity seems to exacerbate this situation, favouring cognitive loss and promoting AD-like neuropathology [[122], [123], [124], [125]]. As we have discussed above, the accumulation of disease-specific misfolded proteins is a hallmark of AD, and ER could have a key role in this process.
In eukaryotic cells, such as neurons, the ER is a cellular compartment
Synaptic loss mediated by neuroinflammation in obesity
Obesity has been associated with chronic inflammatory processes derived from the activity of hypertrophic adipocytes, free fatty acids and reactive oxygen species [[143], [144], [145]]. In the CNS, microglia have significant roles in the control of these mechanisms.
Under physiological conditions, microglial cells present a branched morphology and are responsible for the production of anti-inflammatory and neurotrophic factors (inactive or unreactive state (M2) [146]. However, in some conditions
Pharmacological approaches for metabolic late onset Alzheimer’s disease treatment
According to the metabolic hypothesis of AD, therapies capable of restoring normal brain insulin signalling in the CNS may have beneficial effects on brain function. In this sense, a growing body of evidence suggest that insulin receptor have multiple brain functions related to cognition, neuroprotection through the activation of Akt, modulation of AβPP and Aβ levels, neuroinflammation and synapsis formation. Hence, brain insulin dysregulation could contribute to AD pathogenesis, and drugs
Concluding remarks
It has been described that obesity enhances the loss of neurons [189]. Therefore, it is paramount to investigate how this condition is associated with soluble Aβ and how it promotes age-related pathologies [190,191]. Ceramides are generated in peripheral tissues during the obesogenic process. In the brain, these toxic lipids could amplify and potentiate the neurotoxic effects of Aβ1–42 [192]. Hence, drugs with antidiabetic peripheral effects are expected to be capable of preventing the
Conflict of interest
The authors do not have any current or potential conflict of interest, including any financial, personal or other relationships with other people or organizations. All authors have reviewed the contents of the manuscript being submitted and approved its content.
Acknowledgements
This work was supported by the Spanish Ministry of Science and InnovationSAF2017-84283-R, PI2016/01, CB06/05/0024 (CIBERNED), the European Regional Development Founds and MAT2014-59134-R project. NIA 1R15AG050292 from Generalitat de Catalunya. Research team from UB and URV belongs to 2014SGR-525 from Generalitat de Catalunya. ESL and MLG belong to 2014SGR-1023. CBZ is supported by grants from CONACyT Mexico (No. 0177594) and RDCT from Postdoctoral fellowship CONACYT No. 298337 and the Doctoral
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Both authors have contributed equally.