scholarly journals Editorial: Designing a Protocol Adopting an Artificial Intelligence (AI)–Driven Approach for Early Diagnosis of Late-Onset Alzheimer’s Disease

2021 ◽  
Author(s):  
Victor O. K. Li ◽  
Jacqueline C. K. Lam ◽  
Yang Han ◽  
Lawrence Y. L. Cheung ◽  
Jocelyn Downey ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Late Onset

An insight into the role of Artificial Intelligence in the early diagnosis of Alzheimer’s disease

2021 ◽  
Vol 20 ◽  
Author(s):  
Rohit Kumar Verma ◽  
Manisha Pandey ◽  
Pooja Chawla ◽  
Hira Choudhury ◽  
Jayashree Mayuren ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Symptomatic Relief ◽  
Large Data ◽  
Successful Implementation ◽  
Clinical Implementation ◽  
Insight Into

Background: The complication of Alzheimer’s disease (AD) has made the development of its therapeutic a challenging task. Even after decades of research, we have achieved no more than a few years of symptomatic relief. The inability to diagnose the disease early is the foremost hurdle behind its treatment. Several studies have aimed to identify potential biomarkers that can be detected in body fluids (CSF, blood, urine, etc) or assessed by neuroimaging (i.e., PET and MRI). However, the clinical implementation of these biomarkers is incomplete as they cannot be validated. Method: To overcome the limitation, the use of artificial intelligence along with technical tools has been extensively investigated for AD diagnosis. For developing a promising artificial intelligence strategy that can diagnose AD early, it is critical to supervise neuropsychological outcomes and imaging-based readouts with a proper clinical review. Conclusion: Profound knowledge, a large data pool, and detailed investigations are required for the successful implementation of this tool. This review will enlighten various aspects of early diagnosis of AD using artificial intelligence.

scholarly journals Artificial intelligence and leukocyte epigenomics: Evaluation and prediction of late-onset Alzheimer’s disease

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248375
Author(s):  
Ray O. Bahado-Singh ◽  
Sangeetha Vishweswaraiah ◽  
Buket Aydas ◽  
Ali Yilmaz ◽  
Raghu P. Metpally ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Alzheimer’S Disease ◽  
Cardiovascular Disease ◽  
Alzheimer's Disease ◽  
Sensitivity And Specificity ◽  
Late Onset ◽  
Cns Inflammation ◽  
Peripheral Blood Leucocyte ◽  
Invasive Approach ◽  
Differentially Methylated Genes

We evaluated the utility of leucocyte epigenomic-biomarkers for Alzheimer’s Disease (AD) detection and elucidates its molecular pathogeneses. Genome-wide DNA methylation analysis was performed using the Infinium MethylationEPIC BeadChip array in 24 late-onset AD (LOAD) and 24 cognitively healthy subjects. Data were analyzed using six Artificial Intelligence (AI) methodologies including Deep Learning (DL) followed by Ingenuity Pathway Analysis (IPA) was used for AD prediction. We identified 152 significantly (FDR p<0.05) differentially methylated intragenic CpGs in 171 distinct genes in AD patients compared to controls. All AI platforms accurately predicted AD with AUCs ≥0.93 using 283,143 intragenic and 244,246 intergenic/extragenic CpGs. DL had an AUC = 0.99 using intragenic CpGs, with both sensitivity and specificity being 97%. High AD prediction was also achieved using intergenic/extragenic CpG sites (DL significance value being AUC = 0.99 with 97% sensitivity and specificity). Epigenetically altered genes included CR1L & CTSV (abnormal morphology of cerebral cortex), S1PR1 (CNS inflammation), and LTB4R (inflammatory response). These genes have been previously linked with AD and dementia. The differentially methylated genes CTSV & PRMT5 (ventricular hypertrophy and dilation) are linked to cardiovascular disease and of interest given the known association between impaired cerebral blood flow, cardiovascular disease, and AD. We report a novel, minimally invasive approach using peripheral blood leucocyte epigenomics, and AI analysis to detect AD and elucidate its pathogenesis.

scholarly journals Ethical Implications of Alzheimer’s Disease Prediction in Asymptomatic Individuals Through Artificial Intelligence

Diagnostics ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 440
Author(s):  
Frank Ursin ◽  
Cristian Timmermann ◽  
Florian Steger
Keyword(s):  
Artificial Intelligence ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Adequate Treatment ◽  
Ethical Implications ◽  
Predictive Tests ◽  
Positive Balance ◽  
Asymptomatic Individuals ◽  
The Right

Biomarker-based predictive tests for subjectively asymptomatic Alzheimer’s disease (AD) are utilized in research today. Novel applications of artificial intelligence (AI) promise to predict the onset of AD several years in advance without determining biomarker thresholds. Until now, little attention has been paid to the new ethical challenges that AI brings to the early diagnosis in asymptomatic individuals, beyond contributing to research purposes, when we still lack adequate treatment. The aim of this paper is to explore the ethical arguments put forward for AI aided AD prediction in subjectively asymptomatic individuals and their ethical implications. The ethical assessment is based on a systematic literature search. Thematic analysis was conducted inductively of 18 included publications. The ethical framework includes the principles of autonomy, beneficence, non-maleficence, and justice. Reasons for offering predictive tests to asymptomatic individuals are the right to know, a positive balance of the risk-benefit assessment, and the opportunity for future planning. Reasons against are the lack of disease modifying treatment, the accuracy and explicability of AI aided prediction, the right not to know, and threats to social rights. We conclude that there are serious ethical concerns in offering early diagnosis to asymptomatic individuals and the issues raised by the application of AI add to the already known issues. Nevertheless, pre-symptomatic testing should only be offered on request to avoid inflicted harm. We recommend developing training for physicians in communicating AI aided prediction.

Familial Patterns of Risk in Very Late-Onset Alzheimer's Disease

2003 ◽  
Author(s):  
J. M. Silverman ◽  
C. J. Smith ◽  
D. B. Marin ◽  
R. C. Mohs ◽  
C. B. Propper
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Late Onset ◽  
Familial Patterns

Exploring the Role of Aggregated Proteomes in the Pathogenesis of Alzheimer’s Disease

2020 ◽  
Vol 21 (12) ◽  
pp. 1164-1173
Author(s):  
Siju Ellickal Narayanan ◽  
Nikhila Sekhar ◽  
Rajalakshmi Ganesan Rajamma ◽  
Akash Marathakam ◽  
Abdullah Al Mamun ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Amyloid Precursor Protein ◽  
Early Onset ◽  
Late Onset ◽  
Precursor Protein ◽  
Brain Disorder ◽  
Amyloid Aβ ◽  
T Tau

: Alzheimer’s disease (AD) is a progressive brain disorder and one of the most common causes of dementia and death. AD can be of two types; early-onset and late-onset, where late-onset AD occurs sporadically while early-onset AD results from a mutation in any of the three genes that include amyloid precursor protein (APP), presenilin 1 (PSEN 1) and presenilin 2 (PSEN 2). Biologically, AD is defined by the presence of the distinct neuropathological profile that consists of the extracellular β-amyloid (Aβ) deposition in the form of diffuse neuritic plaques, intraneuronal neurofibrillary tangles (NFTs) and neuropil threads; in dystrophic neuritis, consisting of aggregated hyperphosphorylated tau protein. Elevated levels of (Aβ), total tau (t-tau) and phosphorylated tau (ptau) in cerebrospinal fluid (CSF) have become an important biomarker for the identification of this neurodegenerative disease. The aggregation of Aβ peptide derived from amyloid precursor protein initiates a series of events that involve inflammation, tau hyperphosphorylation and its deposition, in addition to synaptic dysfunction and neurodegeneration, ultimately resulting in dementia. The current review focuses on the role of proteomes in the pathogenesis of AD.

Molecular Genetics of Early- and Late-Onset Alzheimer’s Disease

2020 ◽  
Vol 20 ◽  
Author(s):  
Md. Sahab Uddin ◽  
Sharifa Hasana ◽  
Md. Farhad Hossain ◽  
Md. Siddiqul Islam ◽  
Tapan Behl ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Massively Parallel Sequencing ◽  
Late Onset ◽  
Current Knowledge ◽  
The Elderly ◽  
Apoe Ε4 ◽  
Sequencing Technologies ◽  
Genetic Components ◽  
Ε4 Allele

: Alzheimer’s disease (AD) is the most common form of dementia in the elderly and this complex disorder is associated with environmental as well as genetic components. Early-onset AD (EOAD) and late-onset AD (LOAD, more common) are major identified types of AD. The genetics of EOAD is extensively understood with three genes variants such as APP, PSEN1, and PSEN2 leading to disease. On the other hand, some common alleles including APOE are effectively associated with LOAD identified but the genetics of LOAD is not clear to date. It has been accounted that about 5% to 10% of EOAD patients can be explained through mutations in the three familiar genes of EOAD. The APOE ε4 allele augmented the severity of EOAD risk in carriers, and APOE ε4 allele was considered as a hallmark of EOAD. A great number of EOAD patients, who are not genetically explained, indicate that it is not possible to identify disease- triggering genes yet. Although several genes have been identified through using the technology of next-generation sequencing in EOAD families including SORL1, TYROBP, and NOTCH3. A number of TYROBP variants were identified through exome sequencing in EOAD patients and these TYROBP variants may increase the pathogenesis of EOAD. The existence of ε4 allele is responsible for increasing the severity of EOAD. However, several ε4 allele carriers live into their 90s that propose the presence of other LOAD genetic as well as environmental risk factors that are not identified yet. It is urgent to find out missing genetics of EOAD and LOAD etiology to discover new potential genetics facets which will assist to understand the pathological mechanism of AD. These investigations should contribute to developing a new therapeutic candidate for alleviating, reversing and preventing AD. This article based on current knowledge represents the overview of the susceptible genes of EOAD, and LOAD. Next, we represent the probable molecular mechanism which might elucidate the genetic etiology of AD and highlight the role of massively parallel sequencing technologies for novel gene discoveries.

Alzheimer’s Disease and Retinal Degeneration: A Glimpse at Essential Trace Metals in Ocular Fluids and Tissues

2020 ◽  
Vol 16 (12) ◽  
pp. 1073-1083 ◽  
Author(s):  
Alessandra Micera ◽  
Luca Bruno ◽  
Andrea Cacciamani ◽  
Mauro Rongioletti ◽  
Rosanna Squitti
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Trace Metals ◽  
Late Onset ◽  
Current Knowledge ◽  
Pathological Condition ◽  
Retinal Disease ◽  
Cellular Aging ◽  
Research Strategies ◽  
Aged People

Background: Life expectancy is increasing all over the world, although neurodegenerative disorders might drastically affect the individual activity of aged people. Of those, Alzheimer’s Disease (AD) is one of the most social-cost age-linked diseases of industrialized countries. To date, retinal diseases seem to be more common in the developing world and characterize principally aged people. Agerelated Macular Degeneration (AMD) is a late-onset, neurodegenerative retinal disease that shares several clinical and pathological features with AD, including stress stimuli such as oxidative stress, inflammation and amyloid formations. Method: In both diseases, the detrimental intra/extra-cellular deposits have many similarities. Aging, hypercholesterolemia, hypertension, obesity, arteriosclerosis and smoking are risk factors to develop both diseases. Cellular aging routes have similar organelle and signaling patterns in retina and brain. The possibility to find out new research strategies represent a step forward to disclose potential treatment for both of them. Essential trace metals play critical roles in both physiological and pathological condition of retina, optic nerve and brain, by influencing metabolic processes chiefly upon complex multifactorial pathogenesis. Conclusion: Hence, this review addresses current knowledge about some up-to-date investigated essential trace metals associated with AD and AMD. Changes in the levels of systemic and ocular fluid essential metals might reflect the early stages of AMD, possibly disclosing neurodegeneration pathways shared with AD, which might open to potential early detection.

Pharmacogenetics of Angiotensin-Converting Enzyme Inhibitors in Patients with Alzheimer's Disease Dementia

2018 ◽  
Vol 15 (4) ◽  
pp. 386-398 ◽  
Author(s):  
Fabricio Ferreira de Oliveira ◽  
Elizabeth Suchi Chen ◽  
Marilia Cardoso Smith ◽  
Paulo Henrique Ferreira Bertolucci
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Angiotensin Converting Enzyme ◽  
Cognitive Decline ◽  
Enzyme Inhibitors ◽  
Late Onset ◽  
Amyloid Β ◽  
Converting Enzyme ◽  
Converting Enzyme Inhibitors ◽  
Alzheimer’S Disease Dementia

Background: While the angiotensin-converting enzyme degrades amyloid-β, angiotensinconverting enzyme inhibitors (ACEis) may slow cognitive decline by way of cholinergic effects, by increasing brain substance P and boosting the activity of neprilysin, and by modulating glucose homeostasis and augmenting the secretion of adipokines to enhance insulin sensitivity in patients with Alzheimer’s disease dementia (AD). We aimed to investigate whether ACE gene polymorphisms rs1800764 and rs4291 are associated with cognitive and functional change in patients with AD, while also taking APOE haplotypes and anti-hypertensive treatment with ACEis into account for stratification. Methods: Consecutive late-onset AD patients were screened with cognitive tests, while their caregivers were queried for functional and caregiver burden scores. Prospective pharmacogenetic correlations were estimated for one year, considering APOE and ACE genotypes and haplotypes, and treatment with ACEis. Results: For 193 patients, minor allele frequencies were 0.497 for rs1800764 – C (44.6% heterozygotes) and 0.345 for rs4291 – T (38.9% heterozygotes), both in Hardy-Weinberg equilibrium. Almost 94% of all patients used cholinesterase inhibitors, while 155 (80.3%) had arterial hypertension, and 124 used ACEis. No functional impacts were found regarding any genotypes or pharmacological treatment. Either for carriers of ACE haplotypes that included rs1800764 – T and rs4291 – A, or for APOE4- carriers of rs1800764 – T or rs4291 – T, ACEis slowed cognitive decline independently of blood pressure variations. APOE4+ carriers were not responsive to treatment with ACEis. Conclusion: ACEis may slow cognitive decline for patients with AD, more remarkably for APOE4- carriers of specific ACE genotypes.

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