scholarly journals The Impact of Complement Genes on the Risk of Late-Onset Alzheimer’s Disease

Genes ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 443
Author(s):  
Sarah M. Carpanini ◽  
Janet C. Harwood ◽  
Emily Baker ◽  
Megan Torvell ◽  
Rebecca Sims ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Late Onset ◽  
Association Studies ◽  
Gene List ◽  
Genome Wide Association Studies ◽  
Gene Set ◽  
Inflammatory Status ◽  
Complement Gene ◽  
The Impact

Late-onset Alzheimer’s disease (LOAD), the most common cause of dementia, and a huge global health challenge, is a neurodegenerative disease of uncertain aetiology. To deliver effective diagnostics and therapeutics, understanding the molecular basis of the disease is essential. Contemporary large genome-wide association studies (GWAS) have identified over seventy novel genetic susceptibility loci for LOAD. Most are implicated in microglial or inflammatory pathways, bringing inflammation to the fore as a candidate pathological pathway. Among the most significant GWAS hits are three complement genes: CLU, encoding the fluid-phase complement inhibitor clusterin; CR1 encoding complement receptor 1 (CR1); and recently, C1S encoding the complement enzyme C1s. Complement activation is a critical driver of inflammation; changes in complement genes may impact risk by altering the inflammatory status in the brain. To assess complement gene association with LOAD risk, we manually created a comprehensive complement gene list and tested these in gene-set analysis with LOAD summary statistics. We confirmed associations of CLU and CR1 genes with LOAD but showed no significant associations for the complement gene-set when excluding CLU and CR1. No significant association with other complement genes, including C1S, was seen in the IGAP dataset; however, these may emerge from larger datasets.

scholarly journals The clinical utility of gene testing for Alzheimer’s disease

2011 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
Emily R. Atkins ◽  
Peter K. Panegyres
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Onset ◽  
Late Onset ◽  
Association Studies ◽  
Susceptibility Gene ◽  
Genome Wide Association Studies ◽  
Apoe Ε4 ◽  
Gene Testing ◽  
A Genome

Alzheimer’s disease (AD) is the largest cause of dementia, affecting 35.6 million people in 2010. Amyloid precursor protein, presenilin 1 and presenilin 2 mutations are known to cause familial early-onset AD, whereas apolipoprotein E (APOE) ε4 is a susceptibility gene for late-onset AD. The genes for phosphatidylinositol- binding clathrin assembly protein, clusterin and complement receptor 1 have recently been described by genome-wide association studies as potential risk factors for lateonset AD. Also, a genome association study using single neucleotide polymorphisms has identified an association of neuronal sortilin related receptor and late-onset AD. Gene testing, and also predictive gene testing, may be of benefit in suspected familial early-onset AD however it adds little to the diagnosis of lateonset AD and does not alter the treatment. We do not recommend APOE ε4 genotyping.

scholarly journals Pyk2 overexpression in postsynaptic neurons blocks amyloid β1–42-induced synaptotoxicity in microfluidic co-cultures

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Devrim Kilinc ◽  
Anaïs-Camille Vreulx ◽  
Tiago Mendes ◽  
Amandine Flaig ◽  
Diego Marques-Coelho ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Amyloid Precursor Protein ◽  
Genetic Risk ◽  
Association Studies ◽  
Amyloid Β ◽  
Precursor Protein ◽  
Genome Wide Association Studies ◽  
Risk Genes ◽  
The Impact

Abstract Recent meta-analyses of genome-wide association studies identified a number of genetic risk factors of Alzheimer’s disease; however, little is known about the mechanisms by which they contribute to the pathological process. As synapse loss is observed at the earliest stage of Alzheimer’s disease, deciphering the impact of Alzheimer’s risk genes on synapse formation and maintenance is of great interest. In this article, we report a microfluidic co-culture device that physically isolates synapses from pre- and postsynaptic neurons and chronically exposes them to toxic amyloid β peptides secreted by model cell lines overexpressing wild-type or mutated (V717I) amyloid precursor protein. Co-culture with cells overexpressing mutated amyloid precursor protein exposed the synapses of primary hippocampal neurons to amyloid β1–42 molecules at nanomolar concentrations and induced a significant decrease in synaptic connectivity, as evidenced by distance-based assignment of postsynaptic puncta to presynaptic puncta. Treating the cells with antibodies that target different forms of amyloid β suggested that low molecular weight oligomers are the likely culprit. As proof of concept, we demonstrate that overexpression of protein tyrosine kinase 2 beta—an Alzheimer’s disease genetic risk factor involved in synaptic plasticity and shown to decrease in Alzheimer’s disease brains at gene expression and protein levels—selectively in postsynaptic neurons is protective against amyloid β1–42-induced synaptotoxicity. In summary, our lab-on-a-chip device provides a physiologically relevant model of Alzheimer’s disease-related synaptotoxicity, optimal for assessing the impact of risk genes in pre- and postsynaptic compartments.

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 Pyk2 Overexpression in Postsynaptic Neurons Blocks Aβ1-42-induced Synaptotoxicity in a Microfluidic Co-Culture Model

2019 ◽  
Author(s):  
Devrim Kilinc ◽  
Anaïs-Camille Vreulx ◽  
Tiago Mendes ◽  
Amandine Flaig ◽  
Diego Marques-Coelho ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Risk ◽  
Hippocampal Neurons ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Risk Genes ◽  
Tyrosine Kinase 2 ◽  
Model Of Alzheimer’S Disease ◽  
The Impact

AbstractRecent meta-analyses of genome-wide association studies identified a number of genetic risk factors of Alzheimer’s disease; however, little is known about the mechanisms by which they contribute to the pathological process. As synapse loss is observed at the earliest stage of Alzheimer’s disease, deciphering the impact of Alzheimer’s risk genes on synapse formation and maintenance is of great interest. In this paper, we report a microfluidic co-culture device that physically isolates synapses from pre- and postsynaptic neurons and chronically exposes them to toxic amyloid-beta (Aβ) peptides secreted by model cell lines overexpressing wild-type or mutated (V717I) amyloid precursor protein (APP). Co-culture with cells overexpressing mutated APP exposed the synapses of primary hippocampal neurons to Aβ1-42 molecules at nanomolar concentrations and induced a significant decrease in synaptic connectivity, as evidenced by distance-based assignment of postsynaptic puncta to presynaptic puncta. Treating the cells with antibodies that target different forms of Aβ suggested that low molecular weight oligomers are the likely culprit. As proof of concept, we demonstrate that overexpression of protein tyrosine kinase 2 beta (Pyk2) –an Alzheimer’s disease genetic risk factor involved in synaptic plasticity and shown to decrease in Alzheimer’s disease brains at gene expression and protein levels–selectively in postsynaptic neurons is protective against Aβ1-42-induced synaptotoxicity. In summary, our lab-on-a-chip device provides a physiologically-relevant model of Alzheimer’s disease-related synaptotoxicity, optimal for assessing the impact of risk genes in pre- and postsynaptic compartments.

scholarly journals Alzheimer’s disease Phospholipase C-gamma-2 (PLCG2) protective variant is a functional hypermorph

2018 ◽  
Author(s):  
Lorenza Magno ◽  
Christian B Lessard ◽  
Marta Martins ◽  
Pedro Cruz ◽  
Matilda Katan ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Phospholipase C ◽  
Cell Function ◽  
Immune Cell ◽  
Late Onset ◽  
Association Studies ◽  
Enzyme Function ◽  
Genome Wide Association Studies ◽  
Phospholipase C Gamma

ABSTRACTRecent Genome Wide Association Studies (GWAS) have identified novel rare coding variants in immune genes associated with late onset AD (LOAD). Amongst these, a polymorphism in Phospholipase C-gamma 2 (PLCG2) P522R, has been reported to be protective against LOAD. PLC enzymes are key elements in signal transmission networks and are potentially druggable targets. PLCG2 is highly expressed in the hematopoietic system. Hypermorphic mutations in PLCG2 in humans have been reported to cause autoinflammation and immune disorders, suggesting a key role for this enzyme in the regulation of immune cell function.We confirmed that PLCG2 expression is restricted primarily to microglia in both the healthy and AD brain. Functional analysis of the P522R variant in heterologous systems demonstrated a small hypermorphic effect of the mutation on enzyme function. PLCγ2 is therefore a potential target for modulating microglia function in AD, and a small molecule drug that weakly activates PLCγ2 may be one potential therapeutic approach.SUMMARYThe PLCG2 P522R variant is protective against Alzheimer’s disease (AD). We show that PLCG2 is expressed in CNS-resident myeloid cells, and the P522R polymorphism weakly activates enzyme function. These data suggest that activation of PLCG2 and not inhibition could be therapeutically beneficial in AD.

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.

scholarly journals Identifying Genetic Interactions Associated with Late-Onset Alzheimer’s Disease

2013 ◽  
Author(s):  
Charalampos S Floudas ◽  
Nara Um ◽  
M. Ilyas Kamboh ◽  
Michael M Barmada ◽  
Shyam Visweswaran
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Late Onset ◽  
Association Studies ◽  
Univariate Analysis ◽  
Genetic Interactions ◽  
Supporting Evidence ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide

Background Identifying genetic interactions in data obtained from genome-wide association studies (GWASs) can help in understanding the genetic basis of complex diseases. The large number of single nucleotide polymorphisms (SNPs) in GWASs however makes the identification of genetic interactions computationally challenging. We developed the Bayesian Combinatorial Method (BCM) that can identify pairs of SNPs that in combination have high statistical association with disease. Results We applied BCM to two late-onset Alzheimer’s disease (LOAD) GWAS datasets to identify SNP-SNP interactions between a set of known SNP associations and the dataset SNPs. For evaluation we compared our results with those from logistic regression, as implemented in PLINK. Gene Ontology analysis of genes from the top 200 dataset SNPs for both GWAS datasets showed overrepresentation of LOAD-related terms. Four genes were common to both datasets: APOE and APOC1, which have well established associations with LOAD, and CAMK1D and FBXL13, not previously linked to LOAD but having evidence of involvement in LOAD. Supporting evidence was also found for additional genes from the top 30 dataset SNPs. Conclusion BCM performed well in identifying several SNPs having evidence of involvement in the pathogenesis of LOAD that would not have been identified by univariate analysis due to small main effect. These results provide support for applying BCM to identify potential genetic variants such as SNPs from high dimensional GWAS datasets.

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