scholarly journals New Insights into the Molecular Bases of Familial Alzheimer’s Disease

2020 ◽  
Vol 10 (2) ◽  
pp. 26 ◽  
Author(s):  
Valeria D’Argenio ◽  
Daniela Sarnataro
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Protein Misfolding ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
App Processing ◽  
Rare Mutations ◽  
Genome Wide ◽  
Molecular Bases ◽  
The Brain

Like several neurodegenerative disorders, such as Prion and Parkinson diseases, Alzheimer’s disease (AD) is characterized by spreading mechanism of aggregated proteins in the brain in a typical “prion-like” manner. Recent genetic studies have identified in four genes associated with inherited AD (amyloid precursor protein-APP, Presenilin-1, Presenilin-2 and Apolipoprotein E), rare mutations which cause dysregulation of APP processing and alterations of folding of the derived amyloid beta peptide (Aβ). Accumulation and aggregation of Aβ in the brain can trigger a series of intracellular events, including hyperphosphorylation of tau protein, leading to the pathological features of AD. However, mutations in these four genes account for a small of the total genetic risk for familial AD (FAD). Genome-wide association studies have recently led to the identification of additional AD candidate genes. Here, we review an update of well-established, highly penetrant FAD-causing genes with correlation to the protein misfolding pathway, and novel emerging candidate FAD genes, as well as inherited risk factors. Knowledge of these genes and of their correlated biochemical cascade will provide several potential targets for treatment of AD and aging-related disorders.

The Genetics of Alzheimer’s Disease

2013 ◽  
pp. 805-809
Author(s):  
Rudolph E. Tanzi
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Late Onset ◽  
Association Studies ◽  
Major Gene ◽  
Genome Wide Association Studies ◽  
Rare Mutations ◽  
Current State ◽  
Genome Wide ◽  
Familial Form

Risk for Alzheimer’s disease (AD) is strongly influenced by genetics. In fact, following age, the second strongest risk factor for AD is family history. To date, genetic studies have thus far demonstrated that the inheritance of AD is dichotomous. Roughly half of the cases of the rare early-onset (<60 years) familial form of AD (EO-FAD) are caused by rare mutations in APP, PSEN1, and PSEN2.These mutations usually guarantee onset and account for ~5% of AD. The major gene influencing risk for late-onset AD (LOAD) is APOE. The ε‎4 and ε‎2 variants increase and decrease risk for AD, respectively. Together, these four genes account for up to 50% of the genetic variance of AD. To find the remaining AD genes, multiple genome-wide association studies (GWAS) have resulted in the identification of eleven other AD candidate genes. In this review, I summarize the current state of our knowledge of the genetic factors influencing risk for AD and prospects for future studies.

Understanding the function of ABCA7 in Alzheimer's disease

2015 ◽  
Vol 43 (5) ◽  
pp. 920-923 ◽  
Author(s):  
Hongyun Li ◽  
Tim Karl ◽  
Brett Garner
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Association Studies ◽  
Chinese Hamster Ovary Cells ◽  
Amyloid Β ◽  
Mutant Form ◽  
Genome Wide Association Studies ◽  
App Processing ◽  
The Brain

ATP-binding cassette transporter A7 (ABCA7) is highly expressed in the brain. Recent genome-wide association studies (GWAS) identify ABCA7 single nt polymorphisms (SNPs) that increase Alzheimer's disease (AD) risk. It is now important to understand the true function of ABCA7 in the AD context. We have begun to address this using in vitro and in vivo AD models. Our initial studies showed that transient overexpression of ABCA7 in Chinese hamster ovary cells stably expressing human amyloid precursor protein (APP) resulted in an approximate 50% inhibition in the production of the AD-related amyloid-β (Aβ) peptide as compared with mock-transfected cells. This increased ABCA7 expression was also associated with alterations in other markers of APP processing and an accumulation of cellular APP. To probe for a function of ABCA7 in vivo, we crossed Abca7−/− mice with J20 mice, an amyloidogenic transgenic AD mouse model [B6.Cg-Tg(PDGFB-APPSwInd)20Lms/J] expressing a mutant form of human APP bearing both the Swedish (K670N/M671L) and Indiana (V717F) familial AD mutations. We found that ABCA7 loss doubled insoluble Aβ levels and amyloid plaques in the brain. This did not appear to be related to changes in APP processing (C-terminal fragment analysis), which led us to assess other mechanism by which ABCA7 may modulate Aβ homoeostasis. As we have shown that microglia express high levels of ABCA7, we examined a role for ABCA7 in the phagocytic clearance of Aβ. Our data indicated that the capacity for bone marrow-derived macrophages derived from Abca7−/− mice to phagocytose Aβ was reduced by 51% compared with wild-type (WT) mice. This suggests ABCA7 plays a role in the regulation of Aβ homoeostasis in the brain and that this may be related to Aβ clearance by microglia.

Alzheimer's disease genetics: lessons to improve disease modelling

2011 ◽  
Vol 39 (4) ◽  
pp. 910-916 ◽  
Author(s):  
Rita J. Guerreiro ◽  
John Hardy
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Current Knowledge ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Biological Processes ◽  
Complete Understanding ◽  
Genome Wide ◽  
History Of ◽  
Ad Alzheimer’S Disease

In the present review, we look back at the recent history of GWAS (genome-wide association studies) in AD (Alzheimer's disease) and integrate the major findings with current knowledge of biological processes and pathways. These topics are essential for the development of animal models, which will be fundamental to our complete understanding of AD.

scholarly journals Predicting late-onset Alzheimer’s disease from genomic data using deep neural networks

2019 ◽  
Author(s):  
Javier de Velasco Oriol ◽  
Edgar E. Vallejo ◽  
Karol Estrada ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Neural Networks ◽  
Alzheimer's Disease ◽  
Genetic Variants ◽  
Deep Neural Networks ◽  
Late Onset ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Clinical Markers ◽  
Genome Wide

AbstractAlzheimer’s disease (AD) is the leading form of dementia. Over 25 million cases have been estimated worldwide and this number is predicted to increase two-fold every 20 years. Even though there is a variety of clinical markers available for the diagnosis of AD, the accurate and timely diagnosis of this disease remains elusive. Recently, over a dozen of genetic variants predisposing to the disease have been identified by genome-wide association studies. However, these genetic variants only explain a small fraction of the estimated genetic component of the disease. Therefore, useful predictions of AD from genetic data could not rely on these markers exclusively as they are not sufficiently informative predictors. In this study, we propose the use of deep neural networks for the prediction of late-onset Alzheimer’s disease from a large number of genetic variants. Experimental results indicate that the proposed model holds promise to produce useful predictions for clinical diagnosis of AD.

scholarly journals Genome-Wide Meta-Analysis of Late-Onset Alzheimer's Disease Using Rare Variant Imputation in 324,809 Subjects Identifies Novel Rare Variant Locus NCK2: The International Genomics of Alzheimer's Project (IGAP)

2021 ◽  
Author(s):  
Adam C. Naj ◽  
Ganna Leonenko ◽  
Xueqiu Jian ◽  
Benjamin Grenier-Boley ◽  
Maria Carolina Dalmasso ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Rare Variant ◽  
Late Onset ◽  
Sequence Data ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
The Uk

Risk for late-onset Alzheimer's disease (LOAD) is driven by multiple loci primarily identified by genome-wide association studies, many of which are common variants with minor allele frequencies (MAF)>0.01. To identify additional common and rare LOAD risk variants, we performed a GWAS on 25,170 LOAD subjects and 41,052 cognitively normal controls in 44 datasets from the International Genomics of Alzheimer's Project (IGAP). Existing genotype data were imputed using the dense, high-resolution Haplotype Reference Consortium (HRC) r1.1 reference panel. Stage 1 associations of P<10-5 were meta-analyzed with the European Alzheimer's Disease Biobank (EADB) (n=20,301 cases; 21,839 controls) (stage 2 combined IGAP and EADB). An expanded meta-analysis was performed using a GWAS of parental AD/dementia history in the UK Biobank (UKBB) (n=35,214 cases; 180,791 controls) (stage 3 combined IGAP, EADB, and UKBB). Common variant (MAF≥0.01) associations were identified for 29 loci in stage 2, including novel genome-wide significant associations at TSPAN14 (P=2.33×10-12), SHARPIN (P=1.56×10-9), and ATF5/SIGLEC11 (P=1.03[mult]10-8), and newly significant associations without using AD proxy cases in MTSS1L/IL34 (P=1.80×10-8), APH1B (P=2.10×10-13), and CLNK (P=2.24×10-10). Rare variant (MAF<0.01) associations with genome-wide significance in stage 2 included multiple variants in APOE and TREM2, and a novel association of a rare variant (rs143080277; MAF=0.0054; P=2.69×10-9) in NCK2, further strengthened with the inclusion of UKBB data in stage 3 (P=7.17×10-13). Single-nucleus sequence data shows that NCK2 is highly expressed in amyloid-responsive microglial cells, suggesting a role in LOAD pathology.

scholarly journals Alzheimer's disease: the large gene instability hypothesis

2017 ◽  
Author(s):  
Sourena Soheili-Nezhad
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Late Onset ◽  
Association Studies ◽  
Phase Iii ◽  
Testable Hypothesis ◽  
Genome Wide Association Studies ◽  
Evolutionary Forces ◽  
Large Gene ◽  
Genome Wide

All drug trials of the Alzheimer's disease (AD) have failed to slow the progression of dementia in phase III studies, and the most effective therapeutic strategy remains controversial due to the poorly understood disease mechanisms. For AD drug design, amyloid beta (Aβ) and its cascade have been the primary focus since decades ago, but mounting evidence indicates that the underpinning molecular pathways of AD are more complex than the classical reductionist models. Several genome-wide association studies (GWAS) have recently shed light on dark aspects of AD from a hypothesis-free perspective. Here, I use this novel insight to suggest that the amyloid cascade hypothesis may be a wrong model for AD therapeutic design. I review 23 novel genetic risk loci and show that, as a common theme, they code for receptor proteins and signal transducers of cell adhesion pathways, with clear implications in synaptic development, maintenance, and function. Contrary to the Aβ-based interpretation, but further reinforcing the unbiased genome-wide insight, the classical hallmark genes of AD including the amyloid precursor protein (APP), presenilins (PSEN), and APOE also take part in similar pathways of growth cone adhesion and contact-guidance during brain development. On this basis, I propose that a disrupted synaptic adhesion signaling nexus, rather than a protein aggregation process, may be the central point of convergence in AD mechanisms. By an exploratory bioinformatics analysis, I show that synaptic adhesion proteins are encoded by largest known human genes, and these extremely large genes may be vulnerable to DNA damage accumulation in aging due to their mutational fragility. As a prototypic example and an immediately testable hypothesis based on this argument, I suggest that mutational instability of the large Lrp1b tumor suppressor gene may be the primary etiological trigger for APOE-dab1 signaling disruption in late-onset AD. In conclusion, the large gene instability hypothesis suggests that evolutionary forces of brain complexity have led to emergence of large and fragile synaptic genes, and these unstable genes are the bottleneck etiology of aging disorders including senile dementias. A paradigm shift is warranted in AD prevention and therapeutic design.

scholarly journals Genetic Insights into the Impact of Complement in Alzheimer’s Disease

Genes ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1990
Author(s):  
Megan Torvell ◽  
Sarah M. Carpanini ◽  
Nikoleta Daskoulidou ◽  
Robert A. J. Byrne ◽  
Rebecca Sims ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Complement Activation ◽  
Association Studies ◽  
Screening Tests ◽  
Diagnostic Tools ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Activation Products ◽  
The Impact

The presence of complement activation products at sites of pathology in post-mortem Alzheimer’s disease (AD) brains is well known. Recent evidence from genome-wide association studies (GWAS), combined with the demonstration that complement activation is pivotal in synapse loss in AD, strongly implicates complement in disease aetiology. Genetic variations in complement genes are widespread. While most variants individually have only minor effects on complement homeostasis, the combined effects of variants in multiple complement genes, referred to as the “complotype”, can have major effects. In some diseases, the complotype highlights specific parts of the complement pathway involved in disease, thereby pointing towards a mechanism; however, this is not the case with AD. Here we review the complement GWAS hits; CR1 encoding complement receptor 1 (CR1), CLU encoding clusterin, and a suggestive association of C1S encoding the enzyme C1s, and discuss difficulties in attributing the AD association in these genes to complement function. A better understanding of complement genetics in AD might facilitate predictive genetic screening tests and enable the development of simple diagnostic tools and guide the future use of anti-complement drugs, of which several are currently in development for central nervous system disorders.

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