scholarly journals Identification of epigenome-wide DNA methylation differences between carriers of APOE ε4 and APOE ε2 alleles

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Rosie M. Walker ◽  
Kadi Vaher ◽  
Mairead L. Bermingham ◽  
Stewart W. Morris ◽  
Andrew D. Bretherick ◽  
...  

Abstract Background The apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer’s disease, whilst the ε2 allele confers protection. Previous studies report differential DNA methylation of APOE between ε4 and ε2 carriers, but associations with epigenome-wide methylation have not previously been characterised. Methods Using the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer’s disease-free APOE ε4 (n = 2469) and ε2 (n = 1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses. Results We obtained replicated evidence for DNA methylation differences in a ~ 169 kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 × 10−100 ≤ P ≤ 2.44 × 10−8) and DMRs were identified in SREBF2 and LDLR (1.63 × 10−4 ≤ P ≤ 3.01 × 10−2). Pathway and meQTL analyses implicated lipid-related processes and high-density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24. Conclusions APOE ε4 vs. ε2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.

2019 ◽  
Author(s):  
Rosie M. Walker ◽  
Kadi Vaher ◽  
Mairead L. Bermingham ◽  
Stewart W. Morris ◽  
Andrew D. Bretherick ◽  
...  

AbstractBACKGROUNDThe Apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer’s disease, while the ε2 allele confers protection. Previous studies report differential DNA methylation of APOE between ε4 and ε2 carriers, but associations with epigenome-wide methylation have not previously been characterised.METHODSUsing the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer’s disease-free APOE ε4 (n=2469) and ε2 (n=1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses.RESULTSWe obtained replicated evidence for DNA methylation differences in a ~169kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 x 10−100≤P≤2.44 x 10−8) and DMRs were identified in SREBF2 and LDLR (1.63 x 10−4≤P≤3.01 x 10−2). Pathway and meQTL analyses implicated lipid-related processes and high density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24.CONCLUSIONSAPOE ε4 vs. ε2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.


2020 ◽  
Vol 20 ◽  
Author(s):  
Md. Sahab Uddin ◽  
Sharifa Hasana ◽  
Md. Farhad Hossain ◽  
Md. Siddiqul Islam ◽  
Tapan Behl ◽  
...  

: Alzheimer’s disease (AD) is the most common form of dementia in the elderly and this complex disorder is associated with environmental as well as genetic components. Early-onset AD (EOAD) and late-onset AD (LOAD, more common) are major identified types of AD. The genetics of EOAD is extensively understood with three genes variants such as APP, PSEN1, and PSEN2 leading to disease. On the other hand, some common alleles including APOE are effectively associated with LOAD identified but the genetics of LOAD is not clear to date. It has been accounted that about 5% to 10% of EOAD patients can be explained through mutations in the three familiar genes of EOAD. The APOE ε4 allele augmented the severity of EOAD risk in carriers, and APOE ε4 allele was considered as a hallmark of EOAD. A great number of EOAD patients, who are not genetically explained, indicate that it is not possible to identify disease- triggering genes yet. Although several genes have been identified through using the technology of next-generation sequencing in EOAD families including SORL1, TYROBP, and NOTCH3. A number of TYROBP variants were identified through exome sequencing in EOAD patients and these TYROBP variants may increase the pathogenesis of EOAD. The existence of ε4 allele is responsible for increasing the severity of EOAD. However, several ε4 allele carriers live into their 90s that propose the presence of other LOAD genetic as well as environmental risk factors that are not identified yet. It is urgent to find out missing genetics of EOAD and LOAD etiology to discover new potential genetics facets which will assist to understand the pathological mechanism of AD. These investigations should contribute to developing a new therapeutic candidate for alleviating, reversing and preventing AD. This article based on current knowledge represents the overview of the susceptible genes of EOAD, and LOAD. Next, we represent the probable molecular mechanism which might elucidate the genetic etiology of AD and highlight the role of massively parallel sequencing technologies for novel gene discoveries.


2021 ◽  
pp. 1-10
Author(s):  
Wei Qin ◽  
Wenwen Li ◽  
Qi Wang ◽  
Min Gong ◽  
Tingting Li ◽  
...  

Background: The global race-dependent association of Alzheimer’s disease (AD) and apolipoprotein E (APOE) genotype is not well understood. Transethnic analysis of APOE could clarify the role of genetics in AD risk across populations. Objective: This study aims to determine how race and APOE genotype affect the risks for AD. Methods: We performed a systematic search of PubMed, Embase, Web of Science, and the Cochrane Library since 1993 to Aug 25, 2020. A total of 10,395 reports were identified, and 133 were eligible for analysis with data on 77,402 participants. Studies contained AD clinical diagnostic and APOE genotype data. Homogeneous data sets were pooled in case-control analyses. Odds ratios and 95% confidence intervals for developing AD were calculated for populations of different races and APOE genotypes. Results: The proportion of APOE genotypes and alleles differed between populations of different races. Results showed that APOE ɛ4 was a risk factor for AD, whereas APOE ɛ2 protected against it. The effects of APOE ɛ4 and ɛ2 on AD risk were distinct in various races, they were substantially attenuated among Black people. Sub-group analysis found a higher frequency of APOE ɛ4/ɛ4 and lower frequency of APOE ɛ3/ɛ3 among early-onset AD than late-onset AD in a combined group and different races. Conclusion: Our meta-analysis suggests that the association of APOE genotypes and AD differ between races. These results enhance our understanding of APOE-related risk for AD across race backgrounds and provide new insights into precision medicine for AD.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Lanyu Zhang ◽  
Tiago C. Silva ◽  
Juan I. Young ◽  
Lissette Gomez ◽  
Michael A. Schmidt ◽  
...  

AbstractDNA methylation differences in Alzheimer’s disease (AD) have been reported. Here, we conducted a meta-analysis of more than 1000 prefrontal cortex brain samples to prioritize the most consistent methylation differences in multiple cohorts. Using a uniform analysis pipeline, we identified 3751 CpGs and 119 differentially methylated regions (DMRs) significantly associated with Braak stage. Our analysis identified differentially methylated genes such as MAMSTR, AGAP2, and AZU1. The most significant DMR identified is located on the MAMSTR gene, which encodes a cofactor that stimulates MEF2C. Notably, MEF2C cooperates with another transcription factor, PU.1, a central hub in the AD gene network. Our enrichment analysis highlighted the potential roles of the immune system and polycomb repressive complex 2 in pathological AD. These results may help facilitate future mechanistic and biomarker discovery studies in AD.


2015 ◽  
Vol 27 (10) ◽  
pp. 1687-1692 ◽  
Author(s):  
Renalice Neves Vieira ◽  
Joalce Dornelas Magalhães ◽  
Jemima Sant’Anna ◽  
Mateus Massao Moriguti ◽  
Débora Marques de Miranda ◽  
...  

ABSTRACTBackground:Evidences suggest that GAB2 and BDNF genes may be associated with Alzheimer's disease (AD). We aimed to investigate the GAB2 rs2373115 and BDNF rs6265 polymorphisms and the risk of AD in a Brazilian sample.Methods:269 AD patients and 114 controls were genotyped with Real-time PCR. Multifactor dimensionality reduction (MDR) was employed to explore the effects of gene–gene interactions.Results:GAB2 and BDNF were not associated with AD in our sample. Nevertheless BDNF Val allele (rs6265) presented a synergic association with the APOE ε4 allele. A multiple logistic regression demonstrated that the APOE ε4 allele and years of education were the best predictors for AD. In ε4 non-carriers sex, education and hypertension were independently correlated with AD, while in ε4 carriers we did not observe any association. The findings were further confirmed by bootstrapping method.Conclusions:Our data suggest that the interaction of BDNF and APOE has significant effect on AD. Moreover in absence of ε4, female sex, low level of education and hypertension are independently associated with AD. Interventions aimed to prevent AD should focus on these factors and also taking into account the APOE alleles.


2003 ◽  
Vol 162 (1) ◽  
pp. 313-319 ◽  
Author(s):  
David G. Cook ◽  
James B. Leverenz ◽  
Pamela J. McMillan ◽  
J. Jacob Kulstad ◽  
Sasha Ericksen ◽  
...  

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.


2018 ◽  
Author(s):  
Stephen A. Semick ◽  
Rahul A. Bharadwaj ◽  
Leonardo Collado-Torres ◽  
Ran Tao ◽  
Joo Heon Shin ◽  
...  

AbstractBackgroundLate-onset Alzheimer’s disease (AD) is a complex age-related neurodegenerative disorder that likely involves epigenetic factors. To better understand the epigenetic state associated with AD represented as variation in DNA methylation (DNAm), we surveyed 420,852 DNAm sites from neurotypical controls (N=49) and late-onset AD patients (N=24) across four brain regions (hippocampus, entorhinal cortex, dorsolateral prefrontal cortex and cerebellum).ResultsWe identified 858 sites with robust differential methylation, collectively annotated to 772 possible genes (FDR<5%, within 10kb). These sites were overrepresented in AD genetic risk loci (p=0.00655), and nearby genes were enriched for processes related to cell-adhesion, immunity, and calcium homeostasis (FDR<5%). We analyzed corresponding RNA-seq data to prioritize 130 genes within 10kb of the differentially methylated sites, which were differentially expressed and had expression levels associated with nearby DNAm levels (p<0.05). This validated gene set includes previously reported (e.g. ANK1, DUSP22) and novel genes involved in Alzheimer’s disease, such as ANKRD30B.ConclusionsThese results highlight DNAm changes in Alzheimer’s disease that have gene expression correlates, implicating DNAm as an epigenetic mechanism underlying pathological molecular changes associated with AD. Furthermore, our framework illustrates the value of integrating epigenetic and transcriptomic data for understanding complex disease.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hung-Hsin Chen ◽  
Lauren E. Petty ◽  
Jin Sha ◽  
Yi Zhao ◽  
Amanda Kuzma ◽  
...  

AbstractLate-onset Alzheimer disease (LOAD) is highly polygenic, with a heritability estimated between 40 and 80%, yet risk variants identified in genome-wide studies explain only ~8% of phenotypic variance. Due to its increased power and interpretability, genetically regulated expression (GReX) analysis is an emerging approach to investigate the genetic mechanisms of complex diseases. Here, we conducted GReX analysis within and across 51 tissues on 39 LOAD GWAS data sets comprising 58,713 cases and controls from the Alzheimer’s Disease Genetics Consortium (ADGC) and the International Genomics of Alzheimer’s Project (IGAP). Meta-analysis across studies identified 216 unique significant genes, including 72 with no previously reported LOAD GWAS associations. Cross-brain-tissue and cross-GTEx models revealed eight additional genes significantly associated with LOAD. Conditional analysis of previously reported loci using established LOAD-risk variants identified eight genes reaching genome-wide significance independent of known signals. Moreover, the proportion of SNP-based heritability is highly enriched in genes identified by GReX analysis. In summary, GReX-based meta-analysis in LOAD identifies 216 genes (including 72 novel genes), illuminating the role of gene regulatory models in LOAD.


2018 ◽  
Author(s):  
BW Kunkle ◽  
B Grenier-Boley ◽  
R Sims ◽  
JC Bis ◽  
AC Naj ◽  
...  

IntroductionLate-onset Alzheimer’s disease (LOAD, onset age > 60 years) is the most prevalent dementia in the elderly1, and risk is partially driven by genetics2. Many of the loci responsible for this genetic risk were identified by genome-wide association studies (GWAS)3–8. To identify additional LOAD risk loci, the we performed the largest GWAS to date (89,769 individuals), analyzing both common and rare variants. We confirm 20 previous LOAD risk loci and identify four new genome-wide loci (IQCK, ACE, ADAM10, and ADAMTS1). Pathway analysis of these data implicates the immune system and lipid metabolism, and for the first time tau binding proteins and APP metabolism. These findings show that genetic variants affecting APP and Aβ processing are not only associated with early-onset autosomal dominant AD but also with LOAD. Analysis of AD risk genes and pathways show enrichment for rare variants (P = 1.32 × 10−7) indicating that additional rare variants remain to be identified.


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