Genetically Predicted Coffee Consumption and Risk of Alzheimer’s Disease and Stroke

2021 ◽  
Vol 83 (4) ◽  
pp. 1815-1823
Author(s):  
Zhizhong Zhang ◽  
Mengmeng Wang ◽  
Shuai Yuan ◽  
Huan Cai ◽  
Shuang-Gen Zhu ◽  
...  

Background: Observational studies have reported that coffee consumption was associated with Alzheimer’s disease (AD) and stroke risk. However, the results are inconclusive. Objective: We aimed to evaluate whether genetically predicted coffee consumption is associated with AD and stroke using Mendelian randomization (MR) design. Methods: Summary-level data for AD (n = 54,162), ischemic stroke (n = 440,328), and intracerebral hemorrhage (ICH, n = 3,026) were adopted from publicly available databases. Summary-level data for coffee consumption were obtained from two genome-wide association studies, comprising up to 375,833 subjects. Results: Genetically predicted coffee consumption (cups/day) was associated with an increased risk of AD (OR = 1.26, 95%CI = 1.05–1.51). Moreover, genetically predicted 50%increase of coffee consumption was associated with an increased risk of ICH (OR: 2.27, 95%CI: 1.08–4.78) but a decreased risk of small vessel stroke (OR: 0.71, 95%CI: 0.51–0.996). Estimate for AD and ICH in FinnGen consortium is directionally consistent. Combined analysis of different databases further confirmed that genetically predicted coffee consumption was associated with an increased risk of AD and ICH. In the multivariable MR analysis, genetically predicted coffee consumption retained a stable effect with AD and ICH when adjusting for smoking (p < 0.05), while the association with AD attenuated when adjusting for alcohol use. Conclusion: Our results indicate that genetically predicted coffee consumption may be associated with an increased risk of AD and ICH. The underlying biological mechanisms warrant further study.

2021 ◽  
Vol 13 ◽  
Author(s):  
David Vogrinc ◽  
Katja Goričar ◽  
Vita Dolžan

Alzheimer's disease (AD) is a complex neurodegenerative disease, affecting a significant part of the population. The majority of AD cases occur in the elderly with a typical age of onset of the disease above 65 years. AD presents a major burden for the healthcare system and since population is rapidly aging, the burden of the disease will increase in the future. However, no effective drug treatment for a full-blown disease has been developed to date. The genetic background of AD is extensively studied; numerous genome-wide association studies (GWAS) identified significant genes associated with increased risk of AD development. This review summarizes more than 100 risk loci. Many of them may serve as biomarkers of AD progression, even in the preclinical stage of the disease. Furthermore, we used GWAS data to identify key pathways of AD pathogenesis: cellular processes, metabolic processes, biological regulation, localization, transport, regulation of cellular processes, and neurological system processes. Gene clustering into molecular pathways can provide background for identification of novel molecular targets and may support the development of tailored and personalized treatment of AD.


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.


2020 ◽  
Author(s):  
Ruru Wang ◽  
Ding Ding ◽  
Abuduaili Atibaike ◽  
Jianxiong Xi ◽  
Qianhua Zhao ◽  
...  

Abstract Background Mild cognitive impairment (MCI) is an intermediate stage between normal cognition and Alzheimer’s disease (AD). Genome-wide association studies (GWAS) have identified many AD-risk variants and indicated the important role of lipid metabolism pathway in AD progression. This study aimed to investigate the effects of triglyceride (TG) and genetic risk factors on progression from MCI to AD (MCI-AD progression).Methods The current study sample comprised of 305 MCI subjects aged 50 and over who were prospectively followed up for average 4.5 years in a sub-cohort of the Shanghai Aging Study. A consensus diagnosis of incident AD was conducted according to Diagnostic and Statistical Manual of Mental Disorders-IV and the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association criteria. Fasting blood samples were obtained at baseline for analyzing serum TG. Single nucleotide polymorphisms (SNPs) genotyping was performed using a MassARRAY system. The effect of TG, genetic variants and their interaction on MCI-AD progression were analyzed using Cox proportional hazards regression model.Results During a mean (±SD) follow-up period of 4.5±1.3 y, 58 subjects developed incident AD. The SNP, rs6859 in the Poliovirus Receptor–Related 2 (PVRL2) gene, was significantly associated with incident AD (false discovery rate (FDR)-adjusted P = 0.018). In multivariate cox model, the PVRL2 rs6859 AG, AA and AG+AA genotypes were associated with significantly increased incident AD, compared with the GG genotype (hazard ratio [HR] = 2.29, P = 0.029, and HR = 2.92, P = 0.013, and HR = 2.47, P =0.012, respectively). In PVRL2 rs6859 AG/AA carriers, higher ln TG was significantly associated with increased risk of incident AD (adjusted HR =2.64, P = 0.034). Ln TG and PVRL2 rs6859 had interactive effect on the MCI-AD progression (P Ln TG × rs6859 = 0.001). Conclusion The present study indicated that PVRL2 rs6859 modified the effect of TG on MCI-AD progression. Precision prevention in MCI population based on genetic information should be considered to avoid progression to AD.


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