introduction alzheimer's disease research paper

Alzheimer’s Disease Research

What Has Guided Research So Far and Why It Is High Time for a Paradigm Shift

• © 2023
• Christian Behl 0

Institute of Pathobiochemistry, University Medical Center of the Johannes Gutenberg University, Mainz, Germany

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• Aims to answer why—after more than 100 years of Alzheimer's research—there is still no convincing therapy available
• Informs on leading perspectives and key developments of Alzheimer's research from its beginnings up until today
• Promotes a paradigm shift in Alzheimer's Disease research and a greater openness towards new disease hypotheses

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Table of contents (21 chapters)

Front matter, introduction.

Christian Behl

The Psychiatrist and Pathologist Aloysius Alzheimer and His Seminal Findings

Alzheimer’s disease research after 1945: the recommencement, alzheimer’s research goes deeper: ultrastructural electron microscopy studies, focus on neurochemistry led to the cholinergic hypothesis of alzheimer’s disease, the glutamatergic hypothesis of alzheimer’s disease, biochemistry and genetics point out a prime suspect for causing alzheimer’s disease, getting to the bottom of it: amyloid beta peptide is derived from a larger precursor, step by step toward an amyloid beta peptide-based hypothesis of alzheimer’s disease, concerns about the amyloid cascade hypothesis and reappraisals, ignorance or conspiracy or just an amyloid firewall that blocks alternative ideas, in the slip stream of amyloid: the tau and tangle hypothesis, focus on tauopathies and beyond, alzheimer’s research gains momentum and spreads out, the amyloid cascade hypothesis has to deliver, finally, beyond app , psen1 , psen2 , and apoe : what else does the genome tell us, alternative hypotheses and observations that were somehow lost on the way, is the persistence of the amyloid cascade hypothesis a result of constant confirmation bias, driving forces of alzheimer’s research directions.

• Alzheimer Clinics
• Alzheimer Therapy
• Alzheimer's Disease
• Amyloid Plaques
• Amyloid-Cascade-Hypothesis
• Agenda Setting
• Aternative Hypotheses
• Risk Factors

About this book

This book highlights the key phases and central findings of Alzheimer’s Disease research since the introduction of the label ‘Alzheimer’s Disease’ in 1910. The author, Christian Behl, puts dementia research in the context of the respective zeitgeist and summarizes the paths that have led to the currently available Alzheimer’s drugs. As the reader is taken through the major developments in Alzheimer's Disease research, particularly over the past thirty years, Behl poses critical questions: Why are the exact causes of Alzheimer's Disease still in the dark, despite all the immense, worldwide research efforts in academia as well as in the pharmaceutical industry? Why has the majority of an entire research field kept focusing on a single hypothesis that establishes the deposition of the amyloid beta peptide in the brain as the key trigger of Alzheimer's pathology, even though this concept has still not been convincingly proven in the clinics? Are there other hypotheses that might explainthe pathogenesis of this complex brain disease, and if so, why were these perspectives not adequately followed?

In this book, Behl tries to answer these questions. Starting with the historical background, the author illustrates the long and arduous research journey, its numerous setbacks, and the many alternative explanations for the disease, which have started gaining increasing attention and acceptance in the Alzheimer’s research community only more recently. 

With his deep dive into the history and progression of this research, including the most recent developments, Behl explains why he believes that it is high time to promote a paradigm shift in Alzheimer’s Disease research.

Authors and Affiliations

About the author.

Christian Behl is Professor of Pathobiochemistry and Director of the Institute of Pathobiochemistry at the University Medical Center of the Johannes Gutenberg University Mainz, Germany. He has been closely following Alzheimer’s Disease research since the early 1990’s, when he first got involved into the field himself during his time at the Salk Institute for Biological Studies, La Jolla, USA. He stayed active in the field all through his research station at the Max Planck Institute of Psychiatry, Munich, Germany, and later in Mainz. There his current research (in Mainz) focuses on the cellular degradation mechanism autophagy in the context of neurodegeneration and aging. For quite some time Behl has been an active advocate for widening the focus of Alzheimer’s Disease research to improve the understanding of this complex, age-related brain disorder. Behl is member of several scientific boards, including the German Alzheimer Foundation.

Bibliographic Information

Book Title : Alzheimer’s Disease Research

Book Subtitle : What Has Guided Research So Far and Why It Is High Time for a Paradigm Shift

Authors : Christian Behl

DOI : https://doi.org/10.1007/978-3-031-31570-1

Publisher : Springer Cham

eBook Packages : Biomedical and Life Sciences , Biomedical and Life Sciences (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

Hardcover ISBN : 978-3-031-31569-5 Published: 14 July 2023

Softcover ISBN : 978-3-031-31572-5 Due: 14 August 2023

eBook ISBN : 978-3-031-31570-1 Published: 13 July 2023

Edition Number : 1

Number of Pages : XXV, 652

Number of Illustrations : 9 b/w illustrations, 107 illustrations in colour

Topics : Neurosciences , Neurology , Physiology , Cognitive Psychology , Neurosciences , Neurosciences

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• Published: 09 May 2019

Alzheimer’s disease: risk factors and potentially protective measures

• Marcos Vinícius Ferreira Silva 1 ,
• Cristina de Mello Gomide Loures 1 ,
• Luan Carlos Vieira Alves 1 ,
• Leonardo Cruz de Souza 2 ,
• Karina Braga Gomes Borges 1 &
• Maria das Graças Carvalho 1  

Journal of Biomedical Science volume  26 , Article number:  33 ( 2019 ) Cite this article

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Alzheimer’s disease (AD) is the most common type of dementia and typically manifests through a progressive loss of episodic memory and cognitive function, subsequently causing language and visuospatial skills deficiencies, which are often accompanied by behavioral disorders such as apathy, aggressiveness and depression. The presence of extracellular plaques of insoluble β-amyloid peptide (Aβ) and neurofibrillary tangles (NFT) containing hyperphosphorylated tau protein (P-tau) in the neuronal cytoplasm is a remarkable pathophysiological cause in patients’ brains. Approximately 70% of the risk of developing AD can be attributed to genetics. However, acquired factors such as cerebrovascular diseases, diabetes, hypertension, obesity and dyslipidemia increase the risk of AD development. The aim of the present minireview was to summarize the pathophysiological mechanism and the main risk factors for AD. As a complement, some protective factors associated with a lower risk of disease incidence, such as cognitive reserve, physical activity and diet will also be addressed.

Introduction

Alzheimer’s disease (AD) is the most common type of dementia [ 1 ], affecting at least 27 million people and corresponding from 60 to 70% of all dementias cases [ 2 ]. The occurrence of this disease also has a huge impact on life of patient’s family, in addition to a high financial cost to society [ 3 ]. From an anatomopathological point of view, AD is characterized by two prototypical lesions: 1) senile plaques, composed of a nucleus of β-amyloid protein accumulation (Aβ42), as extra-cellular lesions and 2) neurofibrillary tangles composed of phosphorylated tau protein (P-tau) and which are intraneuronal findings [ 4 ]. Deposition of β-amyloid protein can also occur in capillaries walls, arteries and arterioles causing amyloid cerebral angiopathy leading to degeneration of vascular wall componentes and worsening of blood flow, besides predisposing to intraparenchymal hemorrhages [ 5 ].

AD typically manifests through a progressive loss of episodic memory and cognitive function, with later deficiency of language and visuospatial abilities. Such changes are often accompanied by behavioral disorders such as apathy, aggressiveness and depression [ 6 ]. It should be noted that there is an important subgroup of AD patients who do not present a typically amnestic picture, manifesting non-amnestic deficits from the onset of symptoms [ 7 ]. Structural neuroimaging, with a pattern of hippocampal and parietal atrophy in typical cases reinforces the diagnosis [ 8 ]. Patients who meet typical disease characteristics, excluding other causes such as vascular and fronto-temporal dementias, have a probable diagnosis of AD [ 6 ]. Definitive diagnosis of the disease is usually carried out only through postmortem examination, whose purpose is to demonstrate histologically the neurofibrillary tangles and the senile plaques [ 9 ].

Pathophysiology of Alzheimer’s disease

The presence of extracellular plaques of insoluble β-amyloid peptide (Aβ) and neurofibrillary tangles (NFT) of P-tau in neuronal cytoplasm is the hallmark of AD [ 10 ]. Although the mechanisms by which these changes lead to cognitive decline are still debated, these deposits are believed to lead to atrophy and death of neurons resulting from excitotoxicity processes [excessive stimulation of neurotransmitter receptors in neuronal membranes], collapse in calcium homeostasis, inflammation and depletion of energy and neuronal factors. As a result of this process, damage to neurons and synapses involved in memory processes, learning and other cognitive functions lead to the aforementioned cognitive decline [ 11 ].

According to amyloid cascade theory (one of the most accepted theories about AD pathogenesis, although still debated), the cerebral accumulation of Aβ peptide, resulting from the imbalance between production and clearance of this protein, is the main event causing the disease, being other events observed (including the formation of NFT) resulting from this process [ 12 ].

The Aβ peptide, which has 36 to 43 aminoacids, is derived from amyloid precursor protein (APP) enzymatic proteolysis, a physiologically produced protein that plays important roles in brain homeostasis [ 13 , 14 ]. The APP gene is located on chromosome 21, which explains the higher incidence of early-onset AD in individuals with 21 trisomy (Down Syndrome) and in individuals with APP gene locus duplication [a rare form of early onset of familial origin]. It is believed that overexpression of APP results in an increase of cerebral Aβ peptide, and consequently, in its deposition [ 15 ].

Two main pathways for APP processing are now recognized: a non-amyloidogenic α-secretase-mediated pathway and an amyloidogenic β-and γ-secretase-mediated pathway. Cleavage of APP by α-secretase results in a soluble molecule, sAPPα, which has probable neuroprotective function, playing important roles in the plasticity and survival of neurons and protection against excitotoxicity [ 16 , 17 ]. The Aβ peptide is produced by APP cleavage by a β-secretase (mainly BACE1 enzyme). In this pathway, APP is cleaved by β-secretase to give a APP soluble fragment (sAPPβ, a mediator related to neuronal death), and a carboxy-terminal complex linked to cell membrane. The latter is cleaved by a γ-secretase complex composed by 4 proteins: presenilin 1 or 2, nicastrin, APH-1 (formerly pharynx-defective-1) and and PEN-2 (presenilin enhancer-2), to give rise to the Aβ peptide. Aβ peptides ranging in size from 38 to 43 aminoacids are generated with predominance of the 40 aminoacid form (Aβ 40), followed by 42 (Aβ 42) [ 17 , 18 ]. In physiological conditions, the amyloidogenic and non-amyloidogenic pathways coexist in equilibrium, the latter being favored preferentially [ 19 ].

The Aβ42 peptide is more prone to aggregation than Aβ40. Immunohistochemical analyses indicate that Aβ42 is initially deposited and found at higher concentrations in the amyloid plaques observed in AD patients [ 20 ]. Several studies showed that CSF Aβ42 levels are surrogate markers of underlying brain amyloidosis [ 21 , 22 ]. On the contrary, the correlation between serum Aβ42 levels and cerebral amyloidosis is not yet demonstrated. A decrease in Aβ42 levels is observed in cerebrospinal fluid of AD subjects, which can be explained in part by higher deposition of β-amyloid plaques [ 23 ]. As additional evidence of Aβ42 peptide and the AD pathophysiology, it is further noted that mutations in APP and presenilin genes, which give rise to early-onset familial AD forms, lead to a relative increase in Aβ42 levels [ 20 ].

Aβ peptides, under physiological conditions, are produced primarily in monomeric forms with synapses protective function. However, the accumulation of this protein leads to formation of fibrils that accumulate in senile plaques. High levels of Aβ may lead to oligomeric products formation (dimers, trimers, tetramers) leading to neuronal toxicity and degeneration (both by interaction with cell membranes and their receptors, and by direct interference in intracellular processes), interfering with the function and survival of cholinergic, serotonergic, noradrenergic and dopaminergic neurons, reducing their control over the amyloidogenic pathway and favoring the accumulation of insoluble Aβ peptide [ 19 , 24 ].

The exact mechanism by which deposition of Aβ peptide promotes NFT formation of hyperphosphorylated tau protein is not known. Blurton-Jones & Laferla (2006) [ 25 ] suggest four basic mechanisms:

The Aβ peptide promotes the activation of specific kinases (GSK3β, e.g.) that catalyze the hyperphosphorylation of tau protein, leading to its conformation change and formation of NFT;

Neuroinflammation promoted by the deposition of Aβ peptide leads to the production of proinflammatory cytokines that stimulate the phosphorylation of tau protein;

Reduced capacity of degradation of tau protein by the proteasome, in a process induced by Aβ peptide;

Defects in axonal transport promoted by Aβ peptide lead to inadequate localization of tau protein and its messenger RNA, which can lead to hyperphosphorylation and aggregation in NFT.

Tau protein is a microtubule-associated protein, produced by alternative splicing of the MAPT gene, located on chromosome 17 (17q21). Six isoforms of tau protein are produced by this process [ 26 ]. The main known physiological functions of this protein are the stimulation of tubulin polymerization, microtubules stabilization and intracellular organelles transport by microtubules. Once hyperphosphorylated, the protein loses its functions in the synthesis and stabilization of microtubules, leading to neuronal damage and promoting cytotoxicity [ 27 ]. Histological analyses demonstrate that both the load and the distribution of NFT in brain tissue correlate better with the severity of cognitive deficit than the Aβ peptide deposits [ 28 ].

• Genetic risk factors

AD can be classified by the age of onset of the first symptoms. Early-onset AD affects individuals under 65 years of age, accounting for about 4–6% of cases of AD, while the late form AD affects individuals aged 65 years or older. Besides the age of onset of symptoms, the early and late forms of AD differ in other clinical, neuropsychological, neuropathological and neuroimaging variables [ 29 ].

According to Ballard et al. (2011) [ 1 ] about 70% of the risk of developing AD can be attributed to genetics. Early AD usually occurs due to mutations in genes APP, PSEN1 and PSEN2 (genes of amyloid precursor protein, presenilin 1 and presenilin 2, respectively), whereas late-form AD is mainly associated with a polymorphism in APOE gene (apolipoprotein E gene), especially the presence of ε4 allele [ 30 , 31 ].

More than 30 dominant mutations have already been found in APP gene (located in chromosome 21q21) and are associated with about 15% of cases of early-onset autosomal dominant AD. Mutations in PSEN1 gene (located at 14q24.3) are associated with 80% of cases of early-onset AD, whereas 5% of cases are associated with PSEN2 mutations (located at 1q31-q42) [ 32 ]. Most of APP gene mutations, as well as PSEN1 mutations, lead to an increase in Aβ42: Aβ40 ratio, either by Aβ42 increased expression, reduction of Aβ40, or both. This deregulation favors early Aβ deposition in brain tissue favoring the amyloidogenic cascade [ 33 ]. It is believed that there are other genes besides APP, PSEN1 and PSEN2 involved in the pathogenesis of early-onset AD, as demonstrated by Campion et al. (1999) [ 34 ].

Apolipoprotein E (ApoE) is a protein involved in lipid metabolism encoded by APOE gene, located on chromosome 19. There are three APOE alleles described (ε2, ε3 and ε4, giving rise to apoE2, apoE3 and apoE4 isoforms), present in population at different frequencies (ε2: 5–10%, ε3: 65–70% and ε4: 15–20%). A study by Corbo and Scacchi (1999) [ 35 ] showed that there is a great variability in the APOE allele distribution among the different populations, with ε2 frequencies varying from 0.0 in some Native American populations up to 0.145 in Papuans. The ε 4 frequencies obtained by the authors range from 0.052 (Sardinians) to 0.407 (Pygmies). The ε4 allele is the main risk factor for late-onset AD. The presence of ε4 in heterozygosity increases 3-fold the risk of AD developing, whereas in homozygosis, the risk is increased 12-fold. Conversely, the presence of ε2 allele reduces the risk of AD developing [ 36 , 37 ].

The causes of the association between apoE are not yet fully understood, although some mechanisms have been proposed, and presented consistent results in clinical and in vitro studies. Among these studies, some show that apoE is able to bind to Aβ peptide. While the apoE4 isoform binds to Aβ peptide promoting its polymerization in fibrils and its deposition, apoE2 and apoE3 forms are more efficient in promoting the clearance of this peptide, reducing its deposition in brain tissue [ 38 ]. ApoE has neuroprotective effects and is able to act on neurons development, with apoE2 and apoE3 performing better than apoE4. Additionally, it is observed that protease-generated apoE fragments have toxic effects, which may lead to neuronal injury and favor Aβ peptide deposition [ 38 , 39 ].

More recently it was observed that rare alterations in the triggering receptor expressed on myeloid cells 2 ( TREM2 ) gene elevated the risk ratio by 2.9% for AD development [ 40 , 41 ]. The pathophysiological mechanism by which the deficiency in the gene increases the risk ratio for AD still needs to be better clarified. The gene is located on chromosome 6p21 [ 42 ] and the TREM2 protein is a highly expressed receptor on the surface of microglia, phagocytic cells of central nervous system, and has the function of modulating phagocytic and inflammatory responses in central nervous system [ 43 ]. Activation of microglia through the interaction of TREM2 and DAP12 stimulates the production of CCL19 and CCL21 chemokines and phagocytosis [ 44 ]. In knockout models for the TREM2 receptor it was observed that phagocytic capacity of apoptotic neuronal cell bodies was deficient [ 44 ]. Thus the accumulation of these cellular debris would promote a proinflammatory microenvironment [ 44 ]. Xiang et al. (2016) [ 45 ] observed that the removal capacity of Aβ peptide deposits is impaired in TREM2 receptor deficiency and would favor amyloid plaques accumulation.

• Acquired risk factors

A number of acquired factors increase the risk of developing AD. Among those factors are cerebrovascular diseases (most commonly reported risk factor), diabetes, hypertension, obesity and dyslipidemia [ 46 ]. The association of these risk factors to AD development will be described in the following subsections, as well as some protective factors associated with a lower risk of disease incidence, such as cognitive reserve, physical activity and diet as reported by Mayeux & Stern (2012) [ 46 ].

Cerebrovascular diseases

Cerebrovascular diseases and AD share many risk factors, which often overlap. Cerebrovascular changes such as hemorrhagic infarcts, small and large ischemic cortical infarcts, vasculopathies, and changes in cerebral white matter are known to increase the risk of dementia. Postmortem analyses of the brains of patients with AD indicate the presence of parenchymal vascular disease (amyloid angiopathy by Aβ peptide and small vessels arteriolosclerotic disease), with hemorrhagic outbreaks and infarcts being found in more than 50% of them [ 47 , 48 ]. According to Liu et al., (2015) [ 49 ], neuropathological findings indicate that between 6 and 47% of individuals with dementia have a simultaneous occurrence of cerebrovascular disease. These observations point to the potential role of homeostatic mechanisms in AD and lead to question whether the dementias in which vascular processes are involved are fundamentally different from those related to accumulation of Aβ42 and tau proteins or if both pathological processes produce synergistic effects on cognitive function [ 9 ].

According to the “double-stroke” theory of AD, vascular risk factors (“first stroke”) lead to dysfunction in blood-brain barrier and reduction in cerebral blood flow, with decreased blood supply to the region (oligoemia). This event leads to neuronal damage by non-amyloidogenic and amyloidogenic pathways. Firstly, the dysfunction of blood-brain barrier leads to oligoemia and the accumulation of neurotoxic molecules, events associated with the occurrence of multiple focal ischemic infarcts and micro-injuries resulting from hypoxia, causing neuronal damage. In the amyloidogenic pathway, vascular injury leads to increased expression and processing of APP, resulting in an increase in Aβ peptide. In addition, damage to blood-brain barrier leads to decreased clearance of Aβ peptide. The accumulation of amyloid in brain (“second stroke”) amplifies neuronal dysfunction and speeds up neurodegeneration process. Both Aβ peptide accumulation and hypoperfusion lead to hyperphosphorylation of tau protein, promoting the formation of NFT [ 50 ].

Hypertension

A longitudinal study carried out by Skoog et al. (1996) demonstrated that hypertension is capable of leading to increased risk of developing AD [ 51 ]. Other studies have confirmed this association, indicating that hypertension, especially when present in middle age, negatively affects cognitive performance at more advanced ages, and this association becomes weaker with age [ 52 ]. Hypertension is capable of causing changes in the vascular walls which can lead to hypoperfusion, ischemia and cerebral hypoxia, contributing to trigger the development of AD. Studies demonstrate that cerebral ischemia is capable of leading to the accumulation of APP and Aβ, in addition to stimulating the expression of presenilin, involved in Aβ synthesis. Hypertension may also lead to dysfunction in the blood-brain barrier, an event associated with the genesis of AD by previously discussed mechanisms [ 53 ].

Type 2 diabetes

Epidemiological studies indicate a clear association between type 2 diabetes mellitus and the increased risk of developing AD. Several mechanisms for this association are suggested, including insulin resistance and insulin deficiency, impaired insulin receptor, toxicity of hyperglycemia, adverse effects due to advanced glycation end products, cerebrovascular damage, vascular inflammation and others [ 54 ].

The use of animal models was able to demonstrate that deficiency or resistance to insulin are able to stimulate the action of β and γ-secretases, besides promoting reduction of Aβ clearance, leading to its accumulation in brain tissue. Insulin resistance or deficiency are still capable of inducing hyperphosphorylation of tau protein, leading to NFT formation. Insulin and insulin-like growth factor bind to insulin receptor, leading to its autophosphorylation and activation. Activation of this receptor leads to phosphorylation of phosphoinositide 3-kinase (PI3K) enzyme, which in turn phosphorylates and inhibits glycogen synthase kinase 3β (GSK3β) enzyme, which is important for tau protein phosphorylation. Thus, insulin deficiency / resistance leads to GSK3β abnormal activation, and consequently, to an increase of p-tau formation [ 55 ].

In addition to the mechanisms discussed earlier, studies have reported that advanced glycation end products (AGEs) induce neuronal death through activation of cell death pathways, in addition to stimulating APP processing through increased expression of complexes β and γ-secretases (BACE and PSEN1), in a process involving reactive oxygen species generation [ 56 ]. In addition, Aβ peptide may undergo non-enzymatic glycation, making it an AGE more neurotoxic than its non-glycated form [ 57 ].

The role of obesity as a risk factor for AD development is still uncertain, with studies presenting rather heterogeneous results. According to a meta-analysis developed by Profenno, Porsteinsson, & Faraone (2010) [ 58 ], obesity (Body Mass Index - BMI ≥30 kg / m 2 ) is significantly and independently associated with AD developing risk. On the other hand, a meta-analysis conducted by Fitzpatrick et al. (2009) [ 59 ] indicated that obesity in middle age is a risk factor for dementia development (hazard ratio - HR: 1.39; 95% CI: 1.03–1.87), while in later stages of life, obesity is inversely correlated with the risk of dementia (HR: 0.63; 95% CI: 0.44–0.91). The same authors have also reported that below-ideal weight (BMI < 20 kg / m 2 ) is also associated with an increased risk of dementia (HR: 1.62, 95% CI: 1.02–2.64). Weight loss at more advanced ages occurs in concomitance to other comorbidities and is often indicative of poor health, and may even precede dementia onset within 10 years. Another meta-analysis conducted by Anstey et al. (2011) [ 60 ] indicated that both low weight and overweight as well as obesity in middle age are associated with a higher risk of developing AD in late life.

Dyslipidemia

Elevated cholesterol levels have been proposed as risk factors for the development of AD. Studies have already demonstrated 10% higher cholesterol levels in patients with AD, compared to healthy individuals [ 61 ]. Hypercholesterolemia is a risk factor both for atherosclerosis development and AD development as well as other neurodegenerative diseases [ 62 ].

Hypercholesterolemia increases AD risk primarily because of its effects on the blood-brain barrier. Studies have shown that elevated circulating cholesterol levels are capable of compromising integrity in blood-brain barrier [ 62 ], resulting in mechanisms previously discussed. In addition, experimental studies using animal models demonstrate that hypercholesterolemia is associated with increased Aβ peptide deposition, in addition to increased NFT formation, cognitive decline, neuroinflammation, dysfunction of cholinergic neurons and the presence of cerebral microhemorrhages compatible with AD [ 63 , 64 ].

In observational studies a beneficial effect was observed in the users of statins as the reduction in AD incidence or improvement in the disease progression [ 65 , 66 , 67 ]. However, clinical studies to date have not demonstrated benefit of statins treatment and protection against cognitive decline in AD patients at various stages of disease [ 68 , 69 , 70 , 71 , 72 ]. Contrary to meta-analysis findings conducted by Song et al. (2013) [ 73 ] who observed a lower risk of developing AD in statins users, a Cochrane meta-analysis [ 74 ] did not observe difference in disease outcome as well as alteration in mini-mental status examination (MMSE) in patients using or not statins. However, some important questions regarding the clinical studies are pointed out, i.e., whether treatment initiated in middle age prior disease onset would also have a beneficial effect in elderly, or whether in people with AD family history the treatment would be effective in comparison to those without this background.

Marital status, stress, depression and inadequate sleep

Widowhood status has been reported as an important risk factor AD. A cohort study by Håkansson et al. (2009) [ 75 ] shows that widowed individuals have an increased risk of developing AD compared to married or cohabiting individuals and that this effect is more pronounced in carriers of the APOE ε4 allele. Other studies, such as that by Fan et al. (2015) [ 76 ] demonstrated an association between the risk of all-cause dementia and widow status. A meta-analysis by Sommerlad et al. (2018) [ 77 ] reported an association between widowhood and all-cause dementia, but the same association was not found between widowhood and AD or vascular dementia.

Studies in animal models of AD have shown that stress, characterized as hyperactivation of the hypothalamic, pituitary and adrenal axis (HPA) leading to an increase in cortisol production, causes an increase in Aβ peptide deposition in regions of the brain such as hypothalamus and prefrontal cortex [ 78 , 79 , 80 ]. Carroll et al. (2011) [ 81 ] have observed that the prolonged stress caused by this hyperactivation also causes an increase in the accumulation of hyperphosphorylated tau and neurodegeneration in mice. In humans, increased levels of cortisol were observed in patients with AD compared to the control group [ 82 , 83 , 84 ]. Huang et al. (2009) [ 85 ] observed in a 2-year follow-up of patients with AD that the higher cortisol levels correlated with the faster progression of the disease, worsened in the MMSE and smaller volume of the hippocampus region when observed by resonance. The authors of this study argue that hippocampal atrophy causes a disinhibition effect on the HPA axis, which would cause elevation in cortisol levels as a consequence of the pathophysiological process of AD. Toledo et al. (2012) [ 86 ], observed in a sample of 26 patients with AD that the increase in cortisol levels is correlated with the deposition of the Aβ peptide observed by means of pittsburgh compound b-positron emission tomography (PiB-PET). Ennis et al. (2017) [ 87 ], in a 10-year longitudinal study with 1025 participants observed an increased risk of 1.31 for the development of AD and elevation in cortisol levels that were dosed in 24-h urine samples. However, this result contrasts with that observed in the Rotterdan study [ 88 ] in blood samples collected in the morning when there was no correlation between cortisol levels and AD or dementia in general.

Early adult depression is a risk factor for the development of dementia at more advanced age including AD [ 89 , 90 , 91 ]. Zverova et al. (2013) [ 83 ] observed a greater odds ratio for cognitive decline in the presence of cortisol levels and patients with AD and symptoms of depression. Wu et al. (2018) [ 92 ] observed in some patients with major depression in middle age hippocampal atrophy and Aβ peptide deposition observed by PET indicating that the protein metabolism may be altered in patients with depression.

According to a study published by Proserpio et al. (2018) [ 93 ], sleep disorders have a bidirectional relationship with AD: sleep disorders arise during the early stages of dementia and tend to worsen with the onset of dementia. Similarly, sleep disorders can lead to an increased risk of dementia. A meta-analysis by Shi et al. (2018) [ 94 ] demonstrated that individuals with sleep disorders have an increased risk of developing dementia. More specifically, individuals with insomnia are at high risk for developing AD but not for vascular dementia or other causes. Similarly, individuals with sleep disordered breathing had an increased risk of developing all-cause dementia, AD, and vascular dementia.

Smoking may affect the risk of developing AD by various mechanisms. It is known that it is able to raise the generation of free radicals, increasing oxidative stress, and to promote pro-inflammatory action in the immune system, leading to the activation of phagocytes and consequently, additional oxidative damage. In addition, smoking may lead to cerebrovascular diseases, which increase the risk of AD [ 95 , 96 ]. In a meta-analysis performed by Cataldo et al. (2010), an analysis of 8 case-control studies with affiliations with the tobacco industry suggested a protective effect of smoking in relation to AD (odds ratio (OR): 0.91, 95% CI 0.75–1, 10). In contrast, 14 cohort studies with no association with the tobacco industry demonstrated an increased relative risk for smokers (Relative Risk (RR): 1.45; 95% CI, 1.16–1.80) [ 97 ]. According to Durazzo et al. (2014), the sum of the evidence presented today in the literature is enough for the cessation of smoking to be recommended in order to reduce the incidence of dementia [ 96 ].

Protective factors

Cognitive reserve.

It has been observed in many cases a discrepancy between the degree of brain damage found in histopathological analyses and the severity of cognitive decline. To explain these findings, the theory of cognitive reserve was proposed, which postulates that the gap between brain injury and clinical manifestations is attributable to cognitive reserve capacity. This can be subdivided into two models: brain reserve model or threshold, and cognitive reserve model and / or compensation. The first is based on the amount of available neural substrate (eg, brain size, synapses density or dendritic branching), while the latter focuses on the more efficient ability to use the preexisting brain network in healthy individuals and on the recruitment of more resources to support normal functioning in presence of brain damage [ 98 ].

Several elements are associated with a greater cognitive reserve, such as educational level, occupational activities, leisure activities, physical activities and the integrity of relationships network [ 98 , 99 ]. A study conducted by Stern et al. (1994) [ 100 ] indicated that individuals with low level of schooling and low level of professional achievement had an approximately two-fold increased risk of developing dementia. Similarly, another study indicated that individuals with a higher level of leisure activities performance had a lower risk of developing dementia [ 101 ].

Physical activity

A meta-analysis developed by Hamer & Chida (2009) [ 102 ] indicated that physical activity practice is able to reduce AD risk by 45%. This protective effect is related to several mechanisms, such as reduction of blood pressure, obesity and proinflammatory activity besides the improvement in lipid profile and endothelial function. In addition, adaptations that occur in response to exercise can lead to a better cerebral blood flow and, consequently, better oxygenation of important areas for cognitive function [ 102 ]. It is also believed that physical activity is able to prevent AD by increasing neurotrophic factors such as BDNF (Brain Derived Neurotrophic Factor), IGF-1 (Insulin-Like Growth Factor), VEGF (Vascular Endothelial Growth Factor), stimulating neurogenesis and synaptic plasticity; and by the reduction of free radicals in the hippocampus, as well as increase of superoxide dismutase and eNOS (endothelial nitric oxide synthase) [ 103 ]. Studies have shown that the practice of physical activities is capable of promoting an increase in hippocampal volume, in addition to increasing plasma BDNF concentrations in healthy elderly, indicating a possible neuroprotective effect. It was also reported that in the AD elderly, practice of physical activities correlates positively with the levels of BDNF [ 104 ], which is a growth factor associated with the development and survival of neurons and synapses [ 105 ].

The relationship between the effects of diet and the risk of developing AD was based on certain patterns that were associated with lower or higher risk of developing AD [ 106 ]. As an example, Mediterranean diet is rich in unsaturated fats and antioxidants which confers a protection factor, as diets rich in saturated and trans fats and low levels of anti-oxidants are associated with higher risk of developing AD [ 106 , 107 ]. Some dietary components are essential for neurocognition protection such as dietary fatty acids, including fish oil; antioxidants, such as vitamins E and C; fruits and vegetables; vitamins B6, B12 (cobalamine) and folate, in addition to caloric restriction [ 108 ]. Antioxidants are able to prevent damage caused by reactive oxygen species in addition to stabilizing the membranes; docosahexaenoic acid (DHA) helps clear the Aβ peptide and, together with choline and uridine, aid in the synthesis of the neuronal membrane [ 106 ]. Phospholipid composition is essential in neuronal membrane function. Thus, adequate intake of DHA, eicosapentaenoic acid (EPA), uridine monophosphate, choline, folate, vitamins B6, B12, C, and E, and selenium contributes to a better synthesis of phospholipids and, consequently, to synaptic function preservation and against neurodegeneration [ 106 ]. Nerve synapses consist mainly of neuronal membranes, and neuronal and synaptic losses observed in AD have been related to degeneration and alteration in the composition of these membranes [ 109 ]. Brain aging associated with changes in lipid composition is well studied for treatment and prevention purposes with phospholipids such as phosphatidylcholine and phosphatidylserine that could favor cognitive improvement [ 110 ]. The OmegAD study (a set of double-blind, placebo-controlled clinical trials involving AD patients which evaluated the effects of omega-3 fatty acids (n − 3 FAs) daily supplementation in patients with mild to moderate AD) showed that after six months, DHA (1.7 g) and EPA (0.6 g) supplementation demonstrated benefits such as preservation of cognitive performance, increase in plasma and CSF (Cerebrospinal fluid) levels of n − 3 FAs, DHA and EPA (and negative correlation between DHA and total / phosphorylated tau levels in CSF), reduction in cytokine release pro-inflammatory by blood peripheral mononuclear cells (PBMC), modulation in the expression of genes involved in the regulation of inflammation in PBMC, elevation in transthyretin plasma levels (a protein that binds to AB and which may influence its deposition in the brain), and increase in body weight and BMI. However, the literature data do not support the benefits of 3-FA supplementation in preventing cognitive decline in elderly subjects [ 111 ].

Epidemiological studies have observed a relationship between serum levels of vitamin D reduction, especially 25-hydroxyvitamin D, and AD development [ 112 , 113 , 114 ]. Vitamin D is an important steroid hormone that acts on calcium metabolism and bone regulation, and has some functions in central nervous system, such as regulation of neurotrophic factors, calcium homeostasis, acts on oxidative stress mechanisms, immune system modulation and inflammation [ 115 ]. In the case of inflammation, vitamin D deficiency causes an increase in the amyloidogenic pathway due to elevation of BACE1 and APP cleavage and decrease of Aβ degradation [ 116 ]. Briones & Darwish (2012) [ 117 ] reported a BACE1 and Aβ peptide reduction after vitamin D supplementation in elderly rats. It has also been observed that vitamin D acts on macrophages in order to promote clearence of Aβ peptide [ 118 , 119 ]. In AD patients mutations were also observed in vitamin D receptor (VDR) gene, which would favor the onset of the disease [ 120 ]. To date, no large randomized clinical trial has been conducted on the effect of vitamin D supplementation on the cognition of AD patients. However, in smaller or cohort studies, the results of using high doses of vitamin D and cognitive improvement are divergent [ 121 , 122 , 123 , 124 ]. Vitamin D deficiency should be screened and supplemented in the elderly population due to its high prevalence, but this treatment is not specific for cognitive improvement.

Estrogen (hormone replacement therapy)

Estrogen roles in sex organs are well understood, but it has recently been observed that local production of estrogen plays specific roles in tissues in which it is produced, with or without dependence on circulating estrogen [ 125 ]. Estrogen, especially estradiol, is able to prevent mitochondrial dysfunction in nerve cells, neuroinflammation and assist in DNA repair mechanisms [ 126 ], thus presenting neuroprotective effect [ 126 , 127 ]. The results observed in epidemiological studies are inconsistent [ 128 , 129 ]. Some studies have not observed a beneficial effect of hormone replacement therapy, estrogen or combination therapy on the risk of developing AD [ 130 , 131 ]. Other studies reported a beneficial effect on cognition protection in women receiving hormone replacement therapy at different ages after the onset of menopause [ 132 , 133 , 134 , 135 ]. Inconsistent epidemiological findings, in addition to other factors such as increased risk of deep venous thrombosis, hormone replacement therapy is not recommended in order to prevent cognitive decline and AD development [ 136 ].

Other relevant factors and conclusion

The main pathophysiological mechanisms of AD are amyloidosis and tau-related neurodegeneration, and have specific topographical and chronological pathways. For instance, brain amyloidosis starts in neocortical regions and then affects subcortical structures [ 137 ]. On the other hand, neurodegeneration first appear on locus coeruleus and then spreads through transentorrinal area and neocortical regions [ 137 ]. Cognitive and behavioral features of AD are significantly correlated to the topographical distribution of neurofibrillary tangles.

There is great variability in topographical patterns of pathological findings in AD, causing great phenotypical variability [ 7 ], with atypical presentations of the disease [ 138 ]. It is not clear how risk and beneficial factors may modulate the topographical progression of amyloidosis and neurodegeneration.

The effects of modifiable risk factors on cross-sectional cognition have been the target of multiple WRAP (The Wisconsin Registry for Alzheimer’s Prevention) investigations. This study has investigated risk factors for AD in middle age, since this phase of life is less studied in relation to the later stages of aging. However, this is a critical time because it is when the Alzheimer’s pathology begins and thus, when its trajectory can be modified through pharmacological approaches and / or lifestyle changes. Within this context, the WRAP study, reported by Johnson et al. (2018), suggest that social engagement, physical and cognitive activities, glucose regulation, stress and sleep, in addition to cardiovascular and metabolic risks are interventional parameters that may improve brain health and reduce the likelihood and severity of AD pathology. These authors conclude that a good health and a salutary lifestyle are factors associated not only with better cognition and brain structure but also the lower AD pathophysiologic burden [ 139 ].

The studies of genetic risk factors are important to better elucidate the pathophysiological processes in the development of AD. However, such factors are not passible to any intervention until now. Faced to this scenario, modifiable risk factors such as diabetes, hypertension and dyslipidemia and others previously mentioned should be closely monitored to prevent complications favoring cognitive decline or even to improve the quality of life of patients with AD. In this context, it should also be emphasized that factors considered protective, such as physical exercise, diet and cognitive stimuli should be strongly and widely encouraged, so that such theoretically preventive measures can be adopted by the population contributing to reduce risk of this disease. Since no current drug intervention can modify the pathophysiological mechanisms related to the development of this devastating disease, adoption of these measures constitutes an important strategy for clinical management in order to prevent or postpone cognitive decline.

Abbreviations

• Alzheimer’s disease

Advanced glycation end products

Apolipoprotein E (ApoE)

Amyloid precursor protein

β-amyloid peptide

Brain Derived Neurotrophic Factor

Body Mass Index

Cerebrospinal fluid

Docosahexaenoic acid

Endothelial nitric oxide synthase

Eicosapentaenoic acid

Hypothalamic, pituitary and adrenal axis

Hazard Ratio

Insulin-Like Growth Factor

Omega-3 fatty acids

Neurofibrillary tangles

Peripheral blood mononuclear cells

Phosphorylated tau protein

Vitamin D receptor

Vascular Endothelial Growth Factor

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Silva, M.V.F., Loures, C.d.M.G., Alves, L.C.V. et al. Alzheimer’s disease: risk factors and potentially protective measures. J Biomed Sci 26 , 33 (2019). https://doi.org/10.1186/s12929-019-0524-y

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Home > Books > Advances in Dementia Research

Introductory Chapter: Alzheimer’s Disease—The Most Common Cause of Dementia

Submitted: 03 July 2018 Published: 29 November 2018

DOI: 10.5772/intechopen.82196

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Md. sahab uddin *.

• Department of Pharmacy, Southeast University, Bangladesh

Ghulam Md. Ashraf

• King Fahd Medical Research Center, King Abdulaziz University, Saudi Arabia

*Address all correspondence to: [email protected]

1. Introduction

Alzheimer’s disease (AD) is the utmost common form of dementia, a usual term for memory defect and other cognitive impairments that seriously affect daily life [ 1 ]. This degenerative disease is accountable for 60–80% of dementia cases. AD is not a typical part of normal aging. The supreme well-known threatening factor is aging, and the mainstreams of people with AD are 65 years and older [ 2 ]. In fact, AD is not considered as a disease of adulthood. AD and other types of dementia affect a predictable 1 in 14 persons over the 65 year of age and 1 in every 6 persons over 80 years of age. But, about 1 in every 20 cases of AD affects people with in age ranging 40–65 years, which is called early-onset AD.

AD is a progressive disease that deteriorates over time, and symptoms of dementia steadily exacerbate. In its initial stages, memory defect is mild, but over a number of years in late-stage, AD patients lose the aptitude to convey a message and reply to their surroundings [ 3 ]. AD is the sixth foremost cause of death in the USA. Patients with AD may live an average of 8 years after the symptoms are visible to others, but the survival rate is higher; it can range from 4 to 20 years, based on aging and other health situations [ 4 ].

AD is still incurable, but current treatment strategies can momentarily reduce the deterioration of the symptoms and progress of the quality of life of the patients. Today, there is a universal effort to find better ways to treat the development and progression of AD. The purpose of this chapter is to give an overview of AD.

2. Alzheimer’s and the brain

The brain has billions of nerve cells called neurons attached with each other to construct communication network. There are several groups of nerve performing specific jobs like thinking, learning, remembering, smelling, etc. [ 5 ].

To perform their job, like the receiver of supplies, generation of energy, construction of equipment, and disposal of waste, neurons operate like tiny factories. Brain cells also reserve, process information, and connect with other cells. In order to keep all of these running, they require a huge amount of fuel and oxygen as well as coordination.

Efforts of a lot of researchers are going on to untangle the complicated changes of the brain happened in the early stage and advancement of AD ( Figure 1 ). It seems feasible that brain degradation starts a decade or more before memory deficit and other cognitive dysfunctions actually appear. Throughout the early stage of AD, patients do not display any symptoms; however, cytotoxic turns do appear in the brain. Senile plaques (SPs) and neurofibrillary tangles (NFTs) are formed due to abnormal deposition of proteins that result in discontinued function of neurons, failed internetwork, and ultimately neuronal death [ 6 ].

The normal aged brain and the brain of an Alzheimer’s patient.

The hippocampus is the part of the brain having the vital role in generating memories and seems to be affected initially, and later, the damage spreads out to all other parts of the brain [ 7 ]. As a result, the brain starts to shrink. Moreover, significant widespread damage and shrunk in the brain tissues appear in the final stage of AD.

3. Causes of Alzheimer’s disease

Family history

Untreated depression

Lifestyle-related factors linked with cardiovascular events

4. Signs and symptoms of Alzheimer’s disease

With age, changes in the brain as well as rest of the body cells are obvious. Most of us in general notice such kind of changes by facing difficulties like losing the capacity of thinking and/or remembering certain things.

Difficulties in remembering newly known things and information are the most usual early feature shown in AD, because in the initial stage of Alzheimer’s changes occur in the area of the brain involved in learning [ 10 ]. In advance stage of the AD, brain changes cause generation of progressively awful symptoms, including disorientation, behavior, and mood changes; deepening skepticism about events, location, and time; baseless doubts about family, friends, and professional caregivers; serious loss of memory; and difficulties in the everyday jobs like swallowing, speaking, walking, etc. [ 11 ].

Memory deficit that interrupts daily life

Alterations in planning or problem solving ability

Trouble in doing routine works at home and work

Misperception about place and time

Trouble in the visualization and spatial dealings

Difficulty in speaking or writing

Forgetting things and reducing the capacity to repeat phases

Reduction of judgment skill

Alteration of personality and mood

Separation from social events or works

5. Pathological Hallmarks of Alzheimer’s disease

The SPs consist primarily of amyloid β (Aβ) and neurofibrillary tangles (NFTs), consist of tau proteins are the abnormal structures considered as suspects for the damage of brain cells. Aβ is derived from the amyloid precursor protein (APP), which is cleaved by beta secretase and gamma secretase, and NFTs are the aggregates of hyperphosphorylated tau protein [ 12 ].

A lot of people develop plaques and tangles along with age, as shown by autopsy studies. Patients with Alzheimer’s have the potential to spread into far more areas by plaques and tangles in a foreseeable pattern [ 5 ]. In fact, first, these pathological hallmarks appear in the area of memory before spreading to the other regions.

The impact of plaques and tangles in AD still remains unclear. Most of the researchers believe that they somehow play a complex pathogenic role in AD to block the network of brain cells and interrupts the processes required for cell survivals [ 13 ]. The destruction and death of nerve tissues are the causes of failure of the memory, personality changes, and other difficulties to carryout usual activities in everyday life and other symptoms of AD.

6. Alzheimer’s and typical age-related changes

In case of most people, the sporadic decrease in memory is measured as a typical part of the aging, which is not a threatening sign of stern mental failure or the onset of dementia ( Table 1 ).

The differences between AD and typical age-related changes [ 14 ].

Becoming easily blurred

Rarely forgetting an appointment

Entering into a room and forgetting the reason for entrance

Unable to recover info that are on the tip of the tongue

Worried to remember just read info or the details of a chat

Abruptly forgetting where things of common use (such as keys) have been kept

Fail to recall names of acquaintances or difficulty in one memory with a similar one, such as calling a grandson by his/her son’s name

7. Diagnosis of Alzheimer’s disease

The person with age group older than 80 years if diagnosed with AD can survive at least 3–4 years, whereas younger peoples can stay alive usually about more than 10 years [ 15 ].

Various methodologies and tools are deployed by the physician to identify the actual problem such as the possible AD or probable AD.

Ask the patient and the family member or close contacts about the health status, past medical history, capability to perform daily works, and alteration in behavior and personality

Conduct tests of memory, attention, language, problem-solving, and counting ability

Conduct other tests like blood and urine tests, to find other likely reasons for the problem

Perform the scans of the brain like computed tomography, positron emission tomography, magnetic resonance imaging, or other tests to detect the promising causes for symptoms

These tests are effective to identify how the person’s memory and other cognitive functions are altering over time. However, AD can be certainly diagnosed only after the death of the patient, by relating the clinical events with the autopsy of the brain.

If a person has memory problems, they must consult a physician related to their problems so as to facilitate the physician to diagnose whether it is AD or any other issues such as Parkinson’s disease, stroke, sarcoma, adverse effects of medicines, or a non-Alzheimer’s. Few of these diseases are curable and conceivably revocable.

If the disease is diagnosed in its early phase, it may be treatable and very helpful for future plans such as economic and legislative matters, becoming habituated to living measures and developing the buttress networks.

Furthermore, the participation of patients in clinical trials is also one of the advantages of early diagnosis because it makes newer researches and treatments for AD.

8. Treatment of Alzheimer’s disease

Due to the complexity of AD, its treatment by only one drug or other medication is not possible. Therefore, the pivotal strategy is to help the patient to maintain intellectual function and behavior as well as mitigate the specific concerns like reduction of memory deficits [ 7 ]. Newer therapies are expected to be establish by researchers to target the peculiar genetic, molecular and cellular mechanism which can stop the intrinsic genesis of the disease.

Psychological treatments like cognitive stimulation therapy are also helpful to improve memory, language ability as well as problem resolving talents.

9. Prevention of Alzheimer’s disease

Stopping smoking

Reducing alcohol consumption habit

Eating a balanced diet as well as maintaining weight

Staying physically and mentally fit and active

Not only AD, these events have other health aids, such as reducing the risk of numerous diseases especially cardiovascular disorders and improving the overall health status.

10. Research and progress

Nowadays, studies are focusing to detect the exact etiology of plaques deposition, tangles formation, and associated with other biological landscapes of AD [ 7 ]. The development and progress of Aβ and NFTs in the living brain, as well as the change in brain anatomy and activity, can be observed with the help of existing brain scan techniques. With the help of the results obtained by studying the alterations that take place in the brain along with body fluids, researchers evaluate the initial steps involved in the disease progress prior to the appearances of Alzheimer’s symptoms that give information about the root cause of AD as well as also facilitates its diagnosis.

The utmost enigma of AD is why it mostly attacks older is still a great obscure [ 7 ]. Research on the typical aging of the brain is making this question transparent. Researchers are learning how age-linked variations in the brain may damage neurons and contribute to AD. The alterations caused due to atrophy (i.e., shrinking) in some area of the brain, infections, release of free radicals as well as the mitochondrial defect (some deformities in the powerhouse of the cell causes unnecessary breakdown of energy molecules and results in the loss of energy). These alterations in old age people enlighten the reason why adults are susceptible to AD.

11. Conclusion

Current studies are working to elucidate copious aspects of AD and dementia. About 90% of what we know about AD has been discovered in the last 20 years. The greatest auspicious progress in AD research is how it affects the brain. There is hope that this superior understanding of the pathogenic mechanism will lead to better treatment strategy with minor adverse/side effects. At present numerous latent approaches are under study worldwide.

Conflict of interest

The authors proclaim that they have no competing interests.

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• 2. Uddin MS, Asaduzzaman M, Mamun AA, Iqbal MA, Wahid F, Rony RK. Neuroprotective activity of Asparagus racemosus Linn. against ethanol-induced cognitive impairment and oxidative stress in rats brain: Auspicious for controlling the risk of Alzheimer’s disease. Journal of Alzheimers Disease and Parkinsonism. 2016; 6 (4):1-10
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A cultural approach to dementia prevention

• An Introduction to Alzheimer’s Disease: What is it?

By: Adrianna Fusco

Introduction: Alzheimer’s disease, something we hear about online, in commercials, on news stations, and in many other parts of life. However, we are never told much about Alzheimer’s disease other than the devastating impacts it has. What is Alzheimer’s disease? What are the symptoms or signs to look out for? How does it progress? What causes it? How can it be prevented?

What is it? Alzheimer’s disease is a form of dementia, which is just an umbrella term used to describe loss of memory, language, problem solving, and other thinking abilities. More specifically, Alzheimer’s diseaseis a progressive, neurodegenerative disease that is categorized by a loss of memory, along with basic life skills like eating, bathing, talking, etc.

Symptoms: Common symptoms include: memory loss, paranoia, depression, anger, aggression, anxiety, apathy, loneliness, and psychosis. These symptoms vary from person to person.

Progress: As mentioned above, Alzheimer’s disease is a progressive disease. This means that it develops and gets worse over time. In the first stages of Alzheimer’s disease, there is usually very mild memory loss or problems with thinking abilities. The person may have a hard time remembering where they placed something or have a hard time recalling the right word to say. However, they still are independent, meaning they can still take care of themselves and do things like driving.

During the middle stages of Alzheimer’s disease, the cognitive processes get worse. Now the person may not be able to remember their personal history, like their address or phone number. They also may have a hard time recalling memories or remembering something from their past. The person is no longer able to take care of themselves because in this stage, they tend to forget where they are and often have a hard time using the bathroom or getting dressed appropriately for the day. An example of this is the person wearing shorts in the winter. Along with the cognitive changes, the person may begin to feel sad, lonely, anxious, and paranoid. The symptoms vary from person to person.

When the person hits stage 2, they will need a caregiver to assist them with their tasks and the caregiving will increase as the disease progresses. However, it’s important to help them without trying to do everything for them. They are still adults and they want to be treated as such, so it’s important to still let them have at least some control over their life. Whether that’s letting them do simply chores, like folding clothes, or doing activities, like arts and crafts. This will help provide a sense of normalcy.

The final stage of Alzheimer’s disease is when people begin to lose sense and control of the environment around them. By this point, the cognitive abilities of the individual have tremendously decreased. They can no longer speak in long formulated sentences, instead they speak in short fragments or words. They have trouble completing everyday tasks like walking, sitting, eating, and drinking. This means that they require around the clock assistance to make sure that they are remembering to eat and to help them eat. In general, the assistance is meant to make sure the person is safe and is living to their best ability. At this point, the individuals are very susceptible to infections. When the symptoms and daily conditions get really bad, usually, families turn to hospice care, so that the patient is comfortable at the end of their life. Hospice care also provides emotional support to loved ones, which is vital. Losing a loved one can cause serious emotional and mental strain, so that support is important.

The cause of Alzheimer’s disease is still being researched, but researchers have identified what they believe to be the main culprits of the disease: plaques and tangles. 

Plaques are deposits of amyloid beta that forms between nerve cells that blocks the signals and stops the right materials from being sent to the nerve for survival. In a healthy brain, amyloid beta is used to help support neural repair and growth. However, in Alzheimer’s disease, there is an overproduction of this amyloid beta protein that disturbs these cells and eventually causes the death of the cells. The death of the old cells causes the loss of old memories and information. The blocking of nerve cells can stop the production of new connections, which means short term memories are not being accurately encoded in the brain to become long term memories. 

Tangles are made up of twisted tau that builds up between cells. In a healthy brain, tau is used to help support neural strength and is important in keeping stability in the cells. However, a build up leads to the cells not being able to receive signals and the supplies it needs to function (i.e. energy). These lead to death of the cells, leading to loss of information and life skills.

There is also a biomarker known as APOE-4, that is thought to predispose people to Alzheimer’s disease. This gene along with some environmental stressors could affect whether someone gets the disease and the progression of it. However, a lot of research is still being conducted on this topic and we are constantly rerouting what we know, as new information is found.

Alzheimer’s disease is a terrible disease that claims the lives of a lot of people every year. It’s important to know the signs and to check up with your doctor when anything seems unusual. Alzheimer’s disease and dementia are not a normal part of aging, so see your doctor if you notice any issues with your memory. The earlier the disease is detected, the better it can be treated.

Stay tuned for more blog posts about Alzheimer’s disease, including a look into the mental health of caregivers, prevention, treatment, and more! We also will be writing posts about interviews with doctors, as well as posts about brain health!

Thank you for reading!

References: 

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• Published: 19 April 2024

The advent of Alzheimer treatments will change the trajectory of human aging

• Dennis J. Selkoe   ORCID: orcid.org/0000-0001-8846-9767 1  

Nature Aging volume  4 ,  pages 453–463 ( 2024 ) Cite this article

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Slowing neurodegenerative disorders of late life has lagged behind progress on other chronic diseases. But advances in two areas, biochemical pathology and human genetics, have now identified early pathogenic events, enabling molecular hypotheses and disease-modifying treatments. A salient example is the discovery that antibodies to amyloid ß-protein, long debated as a causative factor in Alzheimer’s disease (AD), clear amyloid plaques, decrease levels of abnormal tau proteins and slow cognitive decline. Approval of amyloid antibodies as the first disease-modifying treatments means a gradually rising fraction of the world’s estimated 60 million people with symptomatic disease may decline less or even stabilize. Society is entering an era in which the unchecked devastation of AD is no longer inevitable. This Perspective considers the impact of slowing AD and other neurodegenerative disorders on the trajectory of aging, allowing people to survive into late life with less functional decline. The implications of this moment for medicine and society are profound.

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Innovative microscopy demystifies metabolism of Alzheimer's

Alzheimer's disease causes significant problems with memory, thinking and behavior and is the most common form of dementia, affecting more than 50 million people around the world each year. This number is expected to triple by the year 2050.

Using their own state-of-the art imaging technologies, scientists at the University of California San Diego have now revealed how the metabolism of lipids, a class of molecule that includes fats, oils and many hormones, is changed in Alzheimer's disease. They also revealed a new strategy to target this metabolic system with new and existing drugs. The findings are published in Cell Metabolism .

"Lipids have been associated with Alzheimer's for as long as we've known about the disease," said senior and co-corresponding author Xu Chen, Ph.D., an assistant professor in the Department of Neurosciences at UC San Diego School of Medicine, referring to the original 1907 report by Alois Alzheimer that described the unusual presence of fat deposits in the brain of the first person to be diagnosed with the disease. "So much of the emphasis since then has been placed on tau and other proteins that the research community has, until the last decade or so, largely overlooked this important aspect of the disease."

"Driven by a keen interest in lipid droplet functions in aging and disease, we initiated this fruitful collaboration to harness cutting-edge SRS technology for studying lipid metabolism in tauopathy mouse brains." Said Yajuan Li, M.D., Ph.D., a postdoctoral researcher in the Shu Chien-Gene Lay Department of Bioengineering at UC San Diego Jacobs School of Engineering. SRS imaging is an approach that analyzes the way molecules in a sample interact with laser light.

In the brain, lipids come in the form of tiny droplets that control a variety of processes, such as energy storage and cellular responses to stress. These processes are tightly regulated in typical brains, but in Alzheimer's or similar diseases, lipid droplet metabolism can malfunction. While scientists understand that there is a relationship between Alzheimer's and lipid metabolism, exactly how they influence one another has remained a mystery.

To answer this question, the team looked directly at lipid droplets in the brains of mice with excess tau protein. They used a state-of-the-art SRS imaging platform developed in Lingyan Shi's lab at the Jacobs School of Engineering. The platform makes it possible to take microscopic images of lipid droplets within cells without the use chemical dyes, which can alter the delicate molecules and compromise the results.

"Intriguingly, the inert lipid droplets observed in tauopathy brains exhibit similar behavior to those found in aging brains," said co-corresponding author Lingyan Shi, Ph.D., assistant professor of bioengineering at the Jacobs School. "We are now focusing on understanding the underlying mechanisms by combing SRS imaging with other utilizing multidisciplinary techniques. Our approach is biologically neutral, so we're able to observe what's happening in the brain at the molecular level with as little interference as possible."

Shi and her team, including Li, pioneered the new approach, which uses a specially modified version of water, called heavy water, as a metabolic probe.

"Instead of using a typical chemical dye to stain lipids, we use heavy water that is naturally participating in the metabolic activities we're interested in," added Shi. "This gives us a much clearer picture of how lipids are formed spatiotemporally, which would not be possible with other approaches. Our current focus is on comprehending the underlying mechanisms of these dynamic changes of lipid metabolism in the context of aging and diseases."

The researchers discovered that in brains with tauopathy, neurons accumulate excess lipids as a result of stress or damage. This influx forces neurons to offload the excess to immune cells in the brain, called microglia. These microglia then mount an inflammatory response that causes further stress to neurons, triggering a repeating and worsening cycle.

In addition to characterizing this process, they were also able to identify a critical enzyme, called adenosine monophosphate-activated protein kinase (AMPK) that orchestrates the cycle. According to the researchers, breaking this cycle could unlock new treatment options for Alzheimer's disease. Chen is particularly optimistic about the possibility of repurposing existing drugs that modify lipid metabolism.

"We don't think this is an incidental phenomenon," said Chen. "The evidence suggests that lipid metabolism is a driving mechanism for Alzheimer's disease. There are many drugs that target lipid metabolism in other body systems, such as in the liver, so we might be able to change this system quite dramatically using tools we already have."

• Alzheimer's Research
• Healthy Aging
• Gene Therapy
• Diseases and Conditions
• Alzheimer's
• Disorders and Syndromes
• Alzheimer's disease
• Dementia with Lewy bodies
• Confocal laser scanning microscopy
• Transmission electron microscopy
• Psychotherapy
• Urinary incontinence
• Erectile dysfunction
• Biological tissue

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Materials provided by University of California - San Diego . Original written by Miles Martin. Note: Content may be edited for style and length.

Journal Reference :

• Yajuan Li, Daniel Munoz-Mayorga, Yuhang Nie, Ningxin Kang, Yuren Tao, Jessica Lagerwall, Carla Pernaci, Genevieve Curtin, Nicole G. Coufal, Jerome Mertens, Lingyan Shi, Xu Chen. Microglial lipid droplet accumulation in tauopathy brain is regulated by neuronal AMPK . Cell Metabolism , 2024; DOI: 10.1016/j.cmet.2024.03.014

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Impact of an improved outdoor space on people with dementia in a hospital unit Provisionally Accepted

• 1 Caring Futures Institute, Flinders University, Australia
• 2 Mental Health Services, Southern Adelaide Local Health Network (SALHN), Australia
• 3 Flinders Health and Medical Research Institute, Rehabilitation, Aged and Extended Care, College of Medicine and Public Health, Flinders University, Australia
• 4 Southern Adelaide Local Health Network (SALHN), Australia

The final, formatted version of the article will be published soon.

Introduction Gardens and outdoor spaces are an important part of institutional environments for people with dementia. However, evidence regarding the benefits these spaces have for people with dementia is still limited. This paper presents the evaluation of the redevelopment of an inaccessible outdoor space into a therapeutic garden on a high dependency psychogeriatric unit in an acute hospital. Method A Mixed methods evaluation was undertaken. An interrupted time series analysis investigated the impact of the garden on falls and challenging behaviours of patients using routinely collected data. Perspectives of the redeveloped garden were captured through (a) a staff survey and (b) semi-structured interviews with families of patients. Results Rates of falls and challenging behaviours dropped at the time of the garden opening but showed increasing rates each month both before and after the garden opened. Most staff believed that the garden provided benefits for patients however limited staff time and concerns over patient safety were barriers to use. Families identified four main themes related to garden use including: 1) being outside 2) occupation and identity, 3) being stimulating and 4) barriers and facilitators. Conclusion The garden was regarded positively by families and staff however, there were barriers that prevented it from being better utilised. Staff concerns over risk were not reflected in falls and challenging behaviour outcomes. Further research into how barriers to garden use may be overcome is justified.

Keywords: Alzheimer's disease, behaviour, BPSD, Dementia, fall, Garden, Hospital, Outdoor

Received: 21 Mar 2024; Accepted: 26 Apr 2024.

Copyright: © 2024 Ng, Dyer, Dawson and Laver. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Ms. Lorraine Ng, Flinders University, Caring Futures Institute, Adelaide, Australia

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Artificial intelligence technology in Alzheimer's disease research

Wenli zhang.

1 Faculty of Information Technology, Beijing University of Technology, Beijing, China;

2 Beijing Dublin International College, Beijing University of Technology, Beijing, China.

Alzheimer's disease is a neurocognitive disorder and one of the contributing factors to dementia. According to the World Health Organization, this disease has a sig-nificant impact on the global population's health, with the number of affected individuals steadily increasing each year. Amidst rapid technological development, the use of artificial intelligence has significantly expanded into the field of medical diagnostics, encompassing areas such as the analysis of medical images, drug development, design of personalized treatment plans, and disease prediction and treatment. Deep learning, which is an important branch in the field of artificial intelligence, is playing a key role in solving several medical challenges by providing important technical support for the early detection, diagnosis, and treatment of Alzheimer's disease. Given this context, this review aims to explore the differences between conventional methods and artificial intelligence techniques in Alzheimer's disease research. Additionally, it aims to summarize current non-invasive and portable techniques for detection of Alzheimer's disease, offering support and guidance for the future prediction and management of the disease.

1. Introduction

Alzheimer's disease (AD) is a progressive neurological disorder, with the highest in-cidence among individuals ages 65 and older. Current evidence suggests that the age range of the disease is gradually expanding, with middle-aged AD patients under the age of 65 years constituting the younger population affected by AD ( 1 ). Providing insight into the core mechanisms of AD, Jack et al . ( 2 ) found that the core pathological features of AD are amyloid pathology, tau protein pathology, and neurodegeneration. These three key pathological features are also key to predicting, diagnosing, and treating AD. Before the widespread adoption of artificial intelligence (AI) in healthcare, conventional testing for AD consisted of several approaches. Initially, physicians would rely on their professional expertise to evaluate whether a patient exhibited symptoms of the disease and assess its severity through in-person consultations and inquiries into the patient's medical history. Subsequently, cognitive assessment tools such as the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MOCA) were used to score the patient's cognitive abilities and determine their cognitive levels ( 3 ). Now that technology has advanced, magnetic resonance imaging (MRI), positron emission tomography (PET), diffusion tensor imaging (DTI), biomarkers, and cerebrospinal fluid (CSF) ( 4 ) are gradually being used to detect AD because they do not involve subjective intervening factors. MRI technology uses a strong magnetic field and harmless radio waves to generate high-resolution brain images, aiding physicians in observing the brain structure and detecting potential abnormalities. Biomarkers as described in ( 2 ) are used to detect AD by labeling specific markers such as amyloid and tau proteins and by ascertaining their presence and the degree of their accumulation. CSF involves the extraction of CSF samples from subjects' spinal region, which are then tested and analyzed to diagnose AD.

However, the aforementioned conventional methods for detection of AD have certain limitations. First, clinical assessment and cognitive testing methods rely to some extent on the subjective judgment of physicians. Second, due to the less distinct pathological features of AD in its early stages, brain imaging techniques such as MRI may lack the sensitivity required to predict this condition ( 5 ).

2. An overview of AI and its applications

2.1. an overview of ai.

AI is a field focused on enabling computer systems to possess cognitive capabilities akin to human thinking. Its objective is to impart machines with the capacity to per-ceive their surroundings, comprehend natural language, acquire knowledge, engage in logical reasoning, problem-solving, and demonstrate adaptability to varying tasks ( 6 ). The study of AI extends across diverse domains, predominantly encompassing machine learning (ML) and deep learning (DL).

ML is an important branch in the field of AI that uses algorithms and statistical models to learn from large amounts of data to solve specific tasks ( 7 ). The core of ML is to perform tasks such as decision-making, classification, and prediction by analyzing and learning the features of data. Common ML models include decision trees ( 8 ), random decision forests (RFs) ( 9 ), logistic regression ( 10 ), support vector machines (SVM) (11), and Bayesian classifiers ( 12 ).

DL is a subfield of ML. Driven by the proliferation of data and enhanced compu-tational capabilities, ML has evolved into DL ( 13 ). DL emulates the functioning of neuronal networks in the human brain, acquiring an understanding of data relation-ships through multi-layered neural networks and autonomously extracting data fea-tures. The core of DL is deep neural networks such as the Convolutional Neural Net-work (CNN) ( 14 ), Long Short-Term Memory Network (LSTM) ( 15 ), and Transformer ( 16 ).

2.2. Widespread use of AI in medicine

The applications of AI in medicine are divided into two main categories, physical applications and virtual applications ( 17 ). Physical applications refer to the use of AI technology to invent and create medical robots and other medical devices in order to assist in medical research and clinical practice. Virtual applications are based on ML and DL and involve algorithmic and software analysis to assist medical research. The scope of virtual applications in healthcare is extensive, including medical testing and treatment, case analysis, and analysis of the progression of chronic diseases. Addi-tionally, the use of virtual applications in the field of AD has garnered significant attention.

The subsequent discussion will focus on the use of AI in the realm of virtual medicine. Its specific applications and potential value in AD detection, diagnosis, and case analysis will be delved into.

3. ML in AD

ML has been used in the field of medical imaging for several decades, with its appli-cations found in computer-aided diagnosis and functional brain imaging ( 18 ). In the early days, the main task of ML was to assist physicians in identifying and localizing obvious signs of disease. As ML techniques developed and matured, they were gradu-ally used to handle more complex medical detection tasks. By acquiring 18-month longitudinal trajectories of 1,909 patients with mild cognitive impairment (MCI) or AD, an unsupervised ML model, the Conditional Restricted Boltzmann Machine (CRBM), was utilized to simulate the disease trajectories of patients, ultimately doing so in a way that could accurately model the progression of AD ( 19 ). A study ( 20 ) summarized multiple brain regions that are closely associated with the pathological mechanisms of AD, including the hippocampus, the internal olfactory cortex, the basal ganglia, the rectus gyrus, the precuneus, and the cerebellum, and it used ML techniques to extract these multivariate biomarkers from structural MRI brain images in order to detect AD early. Studies such as the ones mentioned that utilized ML techniques to detect latent disease markers have made some progress ( 20 , 21 , 22 ). However, ML often requires manual extraction of features, which adds to the difficulty of analyzing large amounts of data.

4. DL in AD

DL performs better and has higher accuracy when dealing with complex data com-pared to conventional ML methods. In addition, DL models are more flexible in of-fering different architectures to adapt to different data characteristics, which is particularly important in AD research.

4.1. Early prediction of AD

The focus of research on early AD is mainly on MCI, because MCI is the transition state between normal aging and AD, and therefore accurate prediction of MCI is im-portant for early prediction of AD ( 23 , 24 ). In DL, LSTM performs well in processing time-related data and can be used in prediction problem. Patients' clinical or behav-ioral data usually contain extensive time-series information, and LSTM can capture the features in these time-series and they can be used to predict the changes in pa-tients' cognitive function and disease progression over future time intervals, rather than just a simple categorization of the current patient's disease status ( 25 , 26 ). More-over, Hong et al . ( 25 ) focused on predicting AD using five quantitative biomarkers, i.e., the cortical thickness standard deviation (TS), cortical thickness average (TA), WM parcellation volume (SV), surface area (SA), and cortical parcellation volume (CV), and the results of that study showed that all five biomarkers displayed excellent ability to predict AD. TA yielded the best results in prediction. In addition, some studies have explored AD prediction using only retinal pictures, and they have achieved a fairly high accuracy ( 27 ).

4.2. Diagnosis of AD

DL can be used to build models of disease progression. Unlike early prediction of AD, detection of AD focuses more on patients who already been diagnosed, utilizing DL techniques to assess the extent of cognitive impairment. Nowadays, the diagnosis of AD mostly utilizes MRI images. In the field of processing image data, the CNN ex-cels in processing neuroimaging data, and it can mine important pathologic features from these images to help doctors detect the progression of the patient's disease ( 28 , 29 , 30 ). Other studies have used eye-tracking data to diagnose AD. They track the eye movements and visual focus of test subjects to gather cognitive information ( 31 ). The studies ( 25 , 26 , 32 ) have integrated early prediction and diagnosis of AD, forming a comprehensive process or framework for predicting AD throughout its course. Medical imaging data are used in pre-trained DL architectures to accurately identify the stage of AD and to help physicians and researchers understand the progression of the condition. In addition, Ho et al . ( 33 ) attempted to use non-invasive near-infrared spectroscopy to diagnose AD, and the highest accuracy (90.91%) was achieved using a CNN-LSTM DL model. These methods enable effective diagnosis of AD in a non-invasive manner and portable format, helping to develop personalized treatment plans and monitor disease progression.

4.3. Treatment of AD

DL plays an important role in the treatment of AD. Transformer is a DL model that can flexibly process different types and lengths of sequence data. In addition, it can capture more detailed feature information. For example, a study used graph neural networks ( 34 ) to learn and capture structural features of drug molecules, with AD-related ApoE as a target, to search for corresponding acting drugs in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and PubChem database, to create drug-target interaction (DTI) data, to extract molecular structure information from the DTI data, and to utilize the Transformer network to fuse the features of dif-ferent layers in a graph convolutional neural network to predict potential therapeutics for AD. Amyloid-beta 42 (Aβ-42) is a high-risk factor for triggering AD. In order to predict the efficacy of drugs on AD, Kaushik et al . ( 35 ) used deep neural network technology to screen the PubChem compound library, and they discovered possible Aβ-42 inhibitors and assessed the effects of drugs on AD by observing the effects of inhibitors on Aβ-42.

5. Conclusion

This paper provides an overview of the role of existing AI methods in AD research ( Table 1 ), with a focus on prediction, detection, and treatment. Historically, AD research and diagnosis usually relied on highly specialized techniques and equipment, including CSF, biomarkers, MRI, PET, and DTI. However, the rapid advancement of DL has opened new avenues. Presently, AD can be predicted using eye-tracking data, retinal images, and non-invasive near-infrared technology, offering a more accessible path to early intervention. In addition, DL technology can be used to determine drug efficacy by observing drug-inhibitor interactions, providing a convenient way to personalize treatment. The future will presumably offer more portable and advanced approaches for the prediction, detection, and treatment of AD. DL models are sure to continue playing a pivotal role in this endeavor.

Conflict of Interest

The authors have no conflicts of interest to disclose.