scholarly journals Association of Alzheimer’s Disease Genetic Risk Loci with Cognitive Performance and Decline: A Systematic Review

2019 ◽  
Vol 69 (4) ◽  
pp. 1109-1136
Author(s):  
Shea J. Andrews ◽  
G. Peggy McFall ◽  
Andrew Booth ◽  
Roger A. Dixon ◽  
Kaarin J. Anstey
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Performance ◽  
Genetic Risk

scholarly journals Focused ultrasound and Alzheimer’s disease A systematic review

2018 ◽  
Vol 12 (4) ◽  
pp. 353-359 ◽  
Author(s):  
Rodrigo Marmo da Costa e Souza ◽  
Inaê Carolline Silveira da Silva ◽  
Anna Beatriz Temoteo Delgado ◽  
Pedro Hugo Vieira da Silva ◽  
Victor Ribeiro Xavier Costa
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Effective Treatment ◽  
Cognitive Performance ◽  
Therapeutic Target ◽  
Focused Ultrasound ◽  
Tau Phosphorylation ◽  
Promising Therapeutic Target ◽  
Preclinical Trials

ABSTRACT Alzheimer’s disease (AD) affects millions of people, however, there is still no effective treatment. The use of focused ultrasound with microbubbles (FUS-MB) for the opening of the blood-brain barrier has been recently studied and may become a promising therapeutic target. Objective: To discuss the use of FUS-MB for the treatment of AD and to present some of the techniques used. Methods: A systematic review was performed of MEDLINE/PubMed and Biblioteca Virtual em Saúde (BVS) services, using the keywords: focused ultrasound, Alzheimer, amyloid-b. Original articles were included in the study; studies that did not focus on Alzheimer’s treatment were excluded. Results: Fifteen original studies were selected. Preclinical trials were able to reduce amyloid-b plaques and tau phosphorylation, improving cognitive performance in AD animals. Conclusion: The results are very promising, but the therapy still requires maturation. Further studies are needed to systematize all the techniques used and their effects in order to enable use in humans.

scholarly journals The Interplay of Diet Quality and Alzheimer’s Disease Genetic Risk Score in Relation to Cognitive Performance Among Urban African Americans

Nutrients ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 2181 ◽  
Author(s):  
Sharmin Hossain ◽  
May A. Beydoun ◽  
Marie F Kuczmarski ◽  
Salman Tajuddin ◽  
Michele K Evans ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Performance ◽  
Risk Score ◽  
Diet Quality ◽  
Genetic Risk ◽  
Verbal Fluency ◽  
Genetic Risk Score ◽  
Healthy Eating Index ◽  
Cognitive Test

We examined the interactive associations of poor diet quality and Alzheimer’s Disease (AD) genetic risk with cognitive performance among 304 African American adults (mean age~57 years) from the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study. In this cross-sectional study, selected participants had complete predictors and covariate data with 13 cognitive test scores as outcomes. Healthy Eating Index-2010 (HEI-2010), Dietary Approaches to Stop Hypertension (DASH), and mean adequacy ratio (MAR) were measured. A genetic risk score for AD in HANDLS (hAlzScore) was computed from 12 selected single nucleotide polymorphisms (SNPs). Our key hypotheses were tested using linear regression models. The hAlzScore was directly associated with poor performance in verbal memory (−0.4 ± 0.2, 0.01) and immediate visual memory (0.4 ± 0.2, 0.03) measured in seconds, in women only. The hAlzScore interacted synergistically with poorer diet quality to determine lower cognitive performance on a test of verbal fluency. Among numerous SNP × diet quality interactions for models of cognitive performance as outcomes, only one passed correction for multiple testing, namely verbal fluency. Our results suggest that improved diet quality can potentially modify performance on cognitive tests of verbal fluency among individuals with higher AD genetic risk.

Olfactory Function, Genetic Predisposition, and Cognitive Performance in Chinese adults

2021 ◽  
Vol 19 ◽  
Author(s):  
Xianyi Yang ◽  
Jing Si ◽  
Shuchun Lin ◽  
Xiaofeng Zhou ◽  
Hui Zhang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Performance ◽  
Genetic Predisposition ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Olfactory Function ◽  
Central China ◽  
Nucleotide Polymorphisms ◽  
Chinese Adults

Objective: The objective of this study is to examine the association of olfactory function and genetic predisposition of Alzheimer’s disease (AD) with cognitive performance in adults. Methods: A total of 2049 Chinese adults from Rugao Longevity and Ageing Study (RuLAS, n=1460, mean age 78 years) and Central China Cohort (CCC, n=589, mean age 48 years) were included in this study. A standard interview-based survey, clinical information, and blood samples were collected in both cohorts. Olfactory function in terms of olfactory identification was measured by the brief version of the Chinese Smell Identification Test consisted of 18 full points. Cognitive performance was measured by the Chinese version of the Mini-mental State Examination. A genetic risk score (GRS) was calculated from 5 single nucleotide polymorphisms, which were robustly related to Alzheimer’s disease in Caucasians and cognitive performance in our Chinese population. Results: In the pooled analyses, participants at the lowest quartile of olfactory function had significantly higher odds of cognitive impairment (adjusted odds ratio [95% CI] =1.45 [1.00 to 2.09], Ptrend =0.005), and such association was stronger among participants with a stronger genetic predisposition of Alzheimer’s disease (β coefficient±SE, -0.06±0.03 in participants with a lower GRS vs. -0.19±0.05 in those with a higher GRS, respectively, Pinteraction=0.01). Similar associations were observed in RuLAS (P-trend=0.06) and in CCC (P-trend<0.001). Conclusion: In this study, a decreased olfactory function was associated with worse cognitive performance in adults, especially among participants with a higher genetic risk of Alzheimer’s disease. Further studies are warranted to evaluate the causal relationship between olfaction and cognitive performance.

scholarly journals Deficits in emotion processing in Alzheimer’s disease: a systematic review

2021 ◽  
Vol 15 (3) ◽  
pp. 314-330
Author(s):  
Rogeria Cristina Rangel da Silva ◽  
Raquel Luíza Santos de Carvalho ◽  
Marcia Cristina Nascimento Dourado
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Performance ◽  
Systematic Reviews ◽  
Emotional Processing ◽  
Emotion Processing ◽  
Scientific Information ◽  
Emotional Perception ◽  
The Impact

ABSTRACT Emotional processing involves the ability of the individual to infer emotional information. There is no consensus about how Alzheimer’s disease (AD) affects emotional processing. Objective: Our aim is to systematically review the impact of AD on emotion processing. Methods: We conducted a search based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The literature search was performed using the electronic databases MEDLINE (PubMed) and Science Citation Index (Institute for Scientific Information [ISI]). The following descriptors were used in the review process: emotion or emotional processing, cognition or cognitive functions, and Alzheimer disease or Alzheimer’s disease. This systematic review was recorded in the International Prospective Register of Systematic Reviews (PROSPERO) under the number CRD42018115891. Results: We identified 425 articles, 19 of which met our criteria. Visual emotional stimuli were the most used among studies. Most studies used tasks of emotional naming, discrimination, identification, and correspondence. The results were contradictory. Many studies reported that individuals with AD were impaired on emotional perception tasks, while other results reported preserved skills. The relationship between emotional processing and cognition is also unclear. Some studies suggested that general cognitive performance affects performance in emotional perception tasks among people with AD, but other studies have shown deficits in recognizing emotion, regardless of cognitive performance. Conclusions: Studies are scarce, present contradictory results, and report impairment in emotional processing in relation to cognition. Moreover, the analyses of the correlation between emotion processing and cognitive functioning failed to reveal clear relationships.

Economic Evaluations of Treatment Options in Patients with Alzheimer's Disease – A Systematic Review

2011 ◽  
Vol 73 (08/09) ◽  
Author(s):  
L Pouryamout ◽  
A Neumann ◽  
J Dams ◽  
J Wasem ◽  
R Dodel
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Treatment Options ◽  
Economic Evaluations

Leveraging Technology in Detection of Alzheimer’s Disease: A Systematic Review (Preprint)

2019 ◽  
Author(s):  
Clemens Kruse ◽  
Britney Larson ◽  
Reagan Wilkinson ◽  
Roger Samson ◽  
Taylor Castillo
Keyword(s):  
Magnetic Resonance Imaging ◽  
United States ◽  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
The United States ◽  
Diagnostic Process ◽  
Resonance Imaging ◽  
Common Cause ◽  
Key Terms

BACKGROUND Incidence of AD continues to increase, making it the most common cause of dementia and the sixth-leading cause of death in the United States. 2018 numbers are expected to double by 2030. OBJECTIVE We examined the benefits of utilizing technology to identify and detect Alzheimer’s disease in the diagnostic process. METHODS We searched PubMed and CINAHL using key terms and filters to identify 30 articles for review. We analyzed these articles and reported them in accordance with the PRISMA guidelines. RESULTS We identified 11 technologies used in the detection of Alzheimer’s disease: 66% of which used some form of MIR. Functional, structural, and 7T magnetic resonance imaging were all used with structural being the most prevalent. CONCLUSIONS MRI is the best form of current technology being used in the detection of Alzheimer’s disease. MRI is a noninvasive approach that provides highly accurate results in the diagnostic process of Alzheimer’s disease.

Evaluating Thrombin Inhibition in Alzheimer’s Disease (The BEACON Trial): Protocol for a Pilot Study (Preprint)

2019 ◽  
Author(s):  
Cláudia Yang Santos ◽  
Christine Getter ◽  
John Stoukides ◽  
Brian Ott ◽  
Stephen Salloway ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Pilot Study ◽  
Cognitive Performance ◽  
Thrombin Inhibitor ◽  
Placebo Control ◽  
Open Label ◽  
Double Blind ◽  
Thrombin Inhibition ◽  
Approved Drugs

BACKGROUND The precise mechanisms whereby cardiovascular risk factors increase the risk of Alzheimer’s disease (AD) have not been delineated. We reported that microvessels isolated from AD brains overexpress a diverse array of neurotoxic and inflammatory proteins, which is consistent with the process of vascular activation. In pre-clinical studies using AD animal models we showed that a vascular activation inhibitor reduced vascular-derived neuroinflammation and improved cognitive performance. Thrombin is a key mediator of cerebrovascular activation in AD. OBJECTIVE This study aims to investigate the safety and potential efficacy of the direct thrombin inhibitor dabigatran, in patients with mild cognitive impairment (MCI) or mild AD to decrease vascular-derived neuroinflammation and improve cognitive performance. METHODS Participants will be enrolled then evaluated quarterly throughout the 24-month study. This is a 24-month randomized-control, double-blind, placebo-controlled, multicenter, delayed-start, pilot study evaluating thrombin inhibition in people with biomarker-confirmed MCI probably due to AD or mild AD. 40 - 60 participants will be recruited between 50 - 85 years old. In the initial 9-months of study, either dabigatran or placebo will be orally administered to patients at a dose of 150 mg per day. After 9 months of the placebo-control (Phase I), the placebo arm will cross-over to an active, open-label (Phase II) where all patients will be treated with a 150 mg daily dose of dabigatran orally for an additional 12 months. A 3-month non-treatment follow-up period will assess duration of effects. RESULTS Beginning in July 2019, and concluding in August 2022, this study is expected to publish final results in January 2023. CONCLUSIONS BEACON is a first-in-kind randomized clinical trial targeting thrombin activation in AD therapeutics. This trial will stimulate translational investigations of an FDA-approved drugs in a newly defined therapeutic areas. CLINICALTRIAL Clinicaltrials.gov NCT03752294

scholarly journals Machine Learning for the Classification of Alzheimer’s Disease and Its Prodromal Stage Using Brain Diffusion Tensor Imaging Data: A Systematic Review

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1071
Author(s):  
Lucia Billeci ◽  
Asia Badolato ◽  
Lorenzo Bachi ◽  
Alessandro Tonacci
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Classification Problem ◽  
Computer Algorithms ◽  
Imaging Data

Alzheimer’s disease is notoriously the most common cause of dementia in the elderly, affecting an increasing number of people. Although widespread, its causes and progression modalities are complex and still not fully understood. Through neuroimaging techniques, such as diffusion Magnetic Resonance (MR), more sophisticated and specific studies of the disease can be performed, offering a valuable tool for both its diagnosis and early detection. However, processing large quantities of medical images is not an easy task, and researchers have turned their attention towards machine learning, a set of computer algorithms that automatically adapt their output towards the intended goal. In this paper, a systematic review of recent machine learning applications on diffusion tensor imaging studies of Alzheimer’s disease is presented, highlighting the fundamental aspects of each work and reporting their performance score. A few examined studies also include mild cognitive impairment in the classification problem, while others combine diffusion data with other sources, like structural magnetic resonance imaging (MRI) (multimodal analysis). The findings of the retrieved works suggest a promising role for machine learning in evaluating effective classification features, like fractional anisotropy, and in possibly performing on different image modalities with higher accuracy.

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