scholarly journals Genomics: New Light on Alzheimer’s Disease Research

2018 ◽  
Vol 19 (12) ◽  
pp. 3771 ◽  
Author(s):  
Yeong Jung ◽  
Yoon Kim ◽  
Mridula Bhalla ◽  
Sung Lee ◽  
Jinsoo Seo

Alzheimer’s disease (AD) is a progressive neurodegenerative disease that represents a major cause of death in many countries. AD is characterized by profound memory loss, disruptions in thinking and reasoning, and changes in personality and behavior followed by malfunctions in various bodily systems. Although AD was first identified over 100 years ago, and tremendous efforts have been made to cure the disease, the precise mechanisms underlying the onset of AD remain unclear. The recent development of next-generation sequencing tools and bioinformatics has enabled us to investigate the role of genetics in the pathogenesis of AD. In this review, we discuss novel discoveries in this area, including the results of genome-wide association studies (GWAS) that have implicated a number of novel genes as risk factors, as well as the identification of epigenetic regulators strongly associated with the onset and progression of AD. We also review how genetic risk factors may interact with age-associated, progressive decreases in cognitive function in patients with AD.

Author(s):  
Zhe Wang ◽  
Lei Meng ◽  
Hong Liu ◽  
Liang Shen ◽  
Hong-Fang Ji

Abstract In view of great difficulties in the pathogenesis analysis of Alzheimer’s disease (AD) presently, profiling the modifiable risk factors is crucial for early detection and intervention of AD. However, the causal associations among them have yet to be identified, and the effective integration and application of these data also remain considerable challenges due to the lack of efficient collection and analysis procedures. To address this issue, we performed comprehensive analyses by two-sample Mendelian randomization (2SMR) and established the AlzRiskMR database (https://github.com/SDBMC/RiskFactors2AD). Four 2SMR analysis methods, including inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode, were used for the complementary calculation to test the reliability of the results. The database currently comprises 1870 sets of data of Genome-Wide Association Studies (GWAS) from the MR-Base and NHGRI-EBI GWAS Catalog database. AlzRiskMR database not only estimates causal associations between modifiable risk factors and AD but also offers a useful and timely resource for early intervention of AD development incidence.


2021 ◽  
Vol 22 (9) ◽  
pp. 4603
Author(s):  
Shiraz Dib ◽  
Jens Pahnke ◽  
Fabien Gosselet

Several studies, including genome wide association studies (GWAS), have strongly suggested a central role for the ATP-binding cassette transporter subfamily A member 7 (ABCA7) in Alzheimer’s disease (AD). This ABC transporter is now considered as an important genetic determinant for late onset Alzheimer disease (LOAD) by regulating several molecular processes such as cholesterol metabolism and amyloid processing and clearance. In this review we shed light on these new functions and their cross-talk, explaining its implication in brain functioning, and therefore in AD onset and development.


2011 ◽  
Vol 39 (4) ◽  
pp. 910-916 ◽  
Author(s):  
Rita J. Guerreiro ◽  
John Hardy

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.


2019 ◽  
Author(s):  
Javier de Velasco Oriol ◽  
Edgar E. Vallejo ◽  
Karol Estrada ◽  

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.


2021 ◽  
Author(s):  
Adam C. Naj ◽  
Ganna Leonenko ◽  
Xueqiu Jian ◽  
Benjamin Grenier-Boley ◽  
Maria Carolina Dalmasso ◽  
...  

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.


2017 ◽  
Author(s):  
Sourena Soheili-Nezhad

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.


Genes ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1990
Author(s):  
Megan Torvell ◽  
Sarah M. Carpanini ◽  
Nikoleta Daskoulidou ◽  
Robert A. J. Byrne ◽  
Rebecca Sims ◽  
...  

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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