Current Status of the Neurobiology of Alzheimer's Disease and the Importance of Early Diagnosis

2002 ◽  
Vol 8 (4) ◽  
pp. 596-597
Author(s):  
Edith V. Sullivan
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Longitudinal Study ◽  
Early Diagnosis ◽  
Medical Treatment ◽  
Accurate Diagnosis ◽  
Current Status ◽  
Age Related ◽  
Loss Of Dignity ◽  
Scientific Rationale

Alzheimer's disease—occurring upward of 15% of individuals age 65 and older—is the most prevalent age-related dementia. Since the late 1970s, neuropsychologists have been instrumental in identifying patterns of sparing and impairment of cognitive, sensory, and motor functions and rates of declines in selective functions. Anyone who has engaged in longitudinal study of AD and anyone of that large segment of the population with relatives suffering with AD has witnessed first-hand the relentless, irreversible demise of function and ultimate loss of dignity characteristic of AD's course. The approach of Scinto and Daffner's edited book, Early Diagnosis of Alzheimer's Disease, avoids rehashing the already established descriptions of AD and provides firm, scientific rationale for the meaningfulness of early and accurate diagnosis of AD despite its current dire prognosis and lack of effective medical treatment.

scholarly journals Promise and Challenge: The Lens Model as a Biomarker for Early Diagnosis of Alzheimer's Disease

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Tian Tian ◽  
Boai Zhang ◽  
Yanjie Jia ◽  
Zhaoming Li
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Accurate Diagnosis ◽  
Lens Model ◽  
Non Invasive ◽  
Diagnosis And Prognosis ◽  
Protein Deposits ◽  
Age Related ◽  
The Brain

Alzheimer’s disease (AD) is the most common form of dementia pathologically characterized by cerebral amyloid-beta (Aβ) deposition. Early and accurate diagnosis of the disease still remains a big challenge. There is evidence that Aβaggregation starts to occur years before symptoms arise. Noninvasive monitoring of Aβplaques is critical for both the early diagnosis and prognosis of AD. Presently, there is a major effort on looking for a reasonably priced technology capable of diagnosing AD by detecting the presence of Aβ. Studies suggest that AD is systemic rather than brain-limited focus diseases and the aggregation of the disease-causing proteins also takes place in lens except the brain. There is a possible relationship between AD and a specific subtype of age-related cataract (supranuclear cataract). If similar abnormal protein deposits are present in the lens, it would facilitate non-invasive diagnosis and monitoring of disease progression. However, there are controversies on the issues related to performance and validation of Aβdeposition in lens as biomarkers for early detection of AD. Here we review the recent findings concerning Aβdeposition in the lenses of AD patients and evaluate if the ocular lens can provide a biomarker for AD.

scholarly journals Repositioning of Immunomodulators: A Ray of Hope for Alzheimer’s Disease?

2020 ◽  
Vol 14 ◽  
Author(s):  
Antonio Munafò ◽  
Chiara Burgaletto ◽  
Giulia Di Benedetto ◽  
Marco Di Mauro ◽  
Rosaria Di Mauro ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Immune System ◽  
Neurodegenerative Disorder ◽  
Drug Repositioning ◽  
Amyloid Β ◽  
Deep Understanding ◽  
Current Status ◽  
Age Related ◽  
Tnf Α

Alzheimer’s disease (AD) is the most common age-related neurodegenerative disorder characterized by cognitive decline and by the presence of amyloid β plaques and neurofibrillary tangles in the brain. Despite recent advances in understanding its pathophysiological mechanisms, to date, there are no disease-modifying therapeutic options, to slow or halt the evolution of neurodegenerative processes in AD. Current pharmacological treatments only transiently mitigate the severity of symptoms, with modest or null overall improvement. Emerging evidence supports the concept that AD is affected by the impaired ability of the immune system to restrain the brain’s pathology. Deep understanding of the relationship between the nervous and the immune system may provide a novel arena to develop effective and safe drugs for AD treatment. Considering the crucial role of inflammatory/immune pathways in AD, here we discuss the current status of the immuno-oncological, immunomodulatory and anti-TNF-α drugs which are being used in preclinical studies or in ongoing clinical trials by means of the drug-repositioning approach.

Age-Associated Memory Loss: Initial Neuropsychological and Cerebral Metabolic Findings of a Longitudinal Study

1994 ◽  
Vol 6 (1) ◽  
pp. 23-44 ◽  
Author(s):  
Gary W. Small ◽  
Anna Okonek ◽  
Mark A. Mandelkern ◽  
Asenath La Rue ◽  
Linda Chang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Longitudinal Study ◽  
Cognitive Abilities ◽  
Mood State ◽  
Familial Risk ◽  
Memory Loss ◽  
Subjective Memory ◽  
Age Related ◽  
Positron Emission

To determine the relationships between clinical and brain function in persons with a familial risk for Alzheimer's disease, the authors assessed subjective and objective cognitive abilities, mood state, and cerebral glucose metabolism (using positron emission tomography) in 43 persons with age-associated memory impairment, with and without first-degree relatives with a clinical diagnosis of Alzheimer's disease. Subjective complaints of memory loss, mood state ratings, and objective memory measures were similar in persons with a family history of Alzheimer's disease (n = 29) compared to those without such a history (n = 14). Metabolic ratios in the frontal regions correlated with a decrease in a specific type of subjective memory complaint (mnemonics usage; p < .001) and some mood state ratings. These results indicate that parietal and temporal hypometabolism is not evident in persons with mild age-related memory complaints, even when such subjects have a familial risk for Alzheimer's disease. Moreover, self-reports of mnemonics usage may be sensitive indicators of decreased frontal lobe function. Longitudinal study will determine whether such clinical and metabolic measures will predict eventual disease progression.

scholarly journals Copper Toxicity Links to Pathogenesis of Alzheimer’s Disease and Therapeutics Approaches

2020 ◽  
Vol 21 (20) ◽  
pp. 7660 ◽  
Author(s):  
Hafza Wajeeha Ejaz ◽  
Wei Wang ◽  
Minglin Lang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Oxidative Damage ◽  
Senile Plaques ◽  
Copper Toxicity ◽  
Short Review ◽  
Current Status ◽  
Age Related ◽  
Cu Ions

Alzheimer’s disease (AD) is an irreversible, age-related progressive neurological disorder, and the most common type of dementia in aged people. Neuropathological lesions of AD are neurofibrillary tangles (NFTs), and senile plaques comprise the accumulated amyloid-beta (Aβ), loaded with metal ions including Cu, Fe, or Zn. Some reports have identified metal dyshomeostasis as a neurotoxic factor of AD, among which Cu ions seem to be a central cationic metal in the formation of plaque and soluble oligomers, and have an essential role in the AD pathology. Cu-Aβ complex catalyzes the generation of reactive oxygen species (ROS) and results in oxidative damage. Several studies have indicated that oxidative stress plays a crucial role in the pathogenesis of AD. The connection of copper levels in AD is still ambiguous, as some researches indicate a Cu deficiency, while others show its higher content in AD, and therefore there is a need to increase and decrease its levels in animal models, respectively, to study which one is the cause. For more than twenty years, many in vitro studies have been devoted to identifying metals’ roles in Aβ accumulation, oxidative damage, and neurotoxicity. Towards the end, a short review of the modern therapeutic approach in chelation therapy, with the main focus on Cu ions, is discussed. Despite the lack of strong proofs of clinical advantage so far, the conjecture that using a therapeutic metal chelator is an effective strategy for AD remains popular. However, some recent reports of genetic-regulating copper transporters in AD models have shed light on treating this refractory disease. This review aims to succinctly present a better understanding of Cu ions’ current status in several AD features, and some conflicting reports are present herein.

scholarly journals Diagnosis of Alzheimer’s Disease with [18F]PET in Mild and Asymptomatic Stages

2009 ◽  
Vol 21 (1-2) ◽  
pp. 101-115 ◽  
Author(s):  
Alexander Drzezga
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Fdg Pet ◽  
Neuronal Damage ◽  
Treatment Strategies ◽  
Specific Method ◽  
Diagnostic Challenge ◽  
Age Related ◽  
18F Fdg

With longer life expectancy, dementia based on the age-related Alzheimers’ disease (AD) has turned into one of the most prevalent disorders of older age, representing a serious medical and socio-economic issue. There has been growing interest in early diagnosis of this disease, particularly regarding the initiation of new treatment strategies ahead of the onset of irreversible neuronal damage. It is accepted that the pathologic changes underlying AD appear in the brain years to decades before the symptomatic stages. Consequently, clinical measures of cognitive impairment, as used for definition of dementia, will not allow early diagnosis of AD-pathology in the mild or asymptomatic stages. Thus, a need for complementary sensitive biomarkers is apparent. Brain imaging markers are among the most promising candidates for this diagnostic challenge. Particularly, [18F]FDG PET as a marker of regional neuronal function has been demonstrated to represent a most sensitive and specific method for early identification of AD-pathology and thus for prediction of dementia of the Alzheimer type (DAT), even in the mild and asymptomatic stages. Currently, systematic data of comparable quality are hardly available for any other imaging procedure. The purpose of this article is to describe the typical findings of [18F]FDG PET in different stages of AD and to demonstrate its value for early and reliable diagnosis of Alzheimer's disease, particularly ahead of the stage of dementia of the Alzheimer’s type.

scholarly journals The PredictAD project: development of novel biomarkers and analysis software for early diagnosis of the Alzheimer's disease

2013 ◽  
Vol 3 (2) ◽  
pp. 20120072 ◽  
Author(s):  
Kari Antila ◽  
Jyrki Lötjönen ◽  
Lennart Thurfjell ◽  
Jarmo Laine ◽  
Marcello Massimini ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Developed Countries ◽  
New Drugs ◽  
Brain Images ◽  
Age Related ◽  
Number Of Patients ◽  
Irreversible Effects ◽  
The Right

Alzheimer's disease (AD) is the most common cause of dementia affecting 36 million people worldwide. As the demographic transition in the developed countries progresses towards older population, the worsening ratio of workers per retirees and the growing number of patients with age-related illnesses such as AD will challenge the current healthcare systems and national economies. For these reasons AD has been identified as a health priority, and various methods for diagnosis and many candidates for therapies are under intense research. Even though there is currently no cure for AD, its effects can be managed. Today the significance of early and precise diagnosis of AD is emphasized in order to minimize its irreversible effects on the nervous system. When new drugs and therapies enter the market it is also vital to effectively identify the right candidates to benefit from these. The main objective of the PredictAD project was to find and integrate efficient biomarkers from heterogeneous patient data to make early diagnosis and to monitor the progress of AD in a more efficient, reliable and objective manner. The project focused on discovering biomarkers from biomolecular data, electrophysiological measurements of the brain and structural, functional and molecular brain images. We also designed and built a statistical model and a framework for exploiting these biomarkers with other available patient history and background data. We were able to discover several potential novel biomarker candidates and implement the framework in software. The results are currently used in several research projects, licensed to commercial use and being tested for clinical use in several trials.

Using GANs and MLP Artificial Neural Networks to support early diagnosis of Alzheimer’s disease: a study on the potential of artificial data expansion

2021 ◽  
Author(s):  
Jonathan Bandeira ◽  
Mêuser Valença ◽  
Renan Alencar
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Computational Intelligence ◽  
Traditional Approach ◽  
Developed Countries ◽  
Classification Model ◽  
World Health ◽  
Age Related ◽  
Artificial Neural

The life expectancy of the population in the most developed countries is growing every day and, consequently, there is an increase in various age-related diseases. In Brazil, just over 1.1 million people have Alzheimer’s disease (AD). In 2019, according to the World Health Organization, Alzheimer’s disease and other dementias were the third leading cause of mortality in the Americas and Europe. Despite being a degenerative and irreversible disease, if diagnosed early, treatments can be performed to slow the progression of symptoms and ensure a better quality of life for the patient. Most papers that study Computational Intelligence solutions to support diagnosis follow an approach based on neuroimaging evidence. In addition to this, another approach that has been gaining prominence is biochemical and molecular analysis. Following this approach, Ray et al., Ravetti & Moscato and Dantas & Valença carried out studies with classifiers from statistics or Computational Intelligence to support the early diagnosis of the disease. The work was carried out from a dataset with values of 120 blood proteins. Through this, they were able to classify whether or not the patient could be diagnosed with AD. As a result, Ray et al., Ravetti & Moscato and Dantas & Valença obtained an average accuracy rate of 89%, 93% and 94.34%, respectively. Thus, this work aims to use a traditional approach with a proposed Multilayer Perceptron Artificial Neural Network model to perform the early diagnosis of a patient with or without AD and compare the results obtained with the results of the related works cited. In addition, this work has as main objective to evaluate the potential of using synthetic data generated using a Generative Adversarial Network in the training and tests of the proposed classification model.

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