scholarly journals Peripheral blood DNA methylation differences in twin pairs discordant for Alzheimer’s disease

2018 ◽  
Author(s):  
Mikko Konki ◽  
Maia Malonzo ◽  
Ida K. Karlsson ◽  
Noora Lindgren ◽  
Bishwa Ghimire ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Peripheral Blood ◽  
Molecular Mechanisms ◽  
Bisulfite Sequencing ◽  
Disease Risk ◽  
Gene Array ◽  
Discordant Twin

ABSTRACTAlzheimer’s disease (AD) results from a neurodegenerative process that starts well before the diagnosis can be made. New prognostic or diagnostic markers enabling early intervention into the disease process would be highly valuable. As life style factors largely modulate the disease risk, we hypothesised that the disease associated DNA methylation signatures are detectable in the peripheral blood of discordant twin pairs. Reduced Representation Bisulfite Sequencing, single cell RNA-sequencing and gene array data were utilised to examine DNA methylation signatures and associated gene expression changes in blood and hippocampus, and targeted bisulfite sequencing in cross cohort validation. Our results reveal that discordant twin pairs have disease associated differences in their peripheral blood epigenomes. A subset of affected genes, e.g.ADARB2contain differentially methylated sites also in anterior hippocampus. The DNA methylation differences seem to influence gene expression in brain rather than in blood cells. The affected genes are associated with neuronal functions and pathologies. These DNA methylation signatures are valuable disease marker candidates and may provide insights into the molecular mechanisms of pathogenesis.

Muscarinic Receptors Expression in the Peripheral Blood Cells Differentiate Dementia with Lewy Bodies from Alzheimer’s Disease

2021 ◽  
pp. 1-8
Author(s):  
Marcella Reale ◽  
Claudia Carrarini ◽  
Mirella Russo ◽  
Fedele Dono ◽  
Laura Ferri ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Peripheral Blood ◽  
Dementia With Lewy Bodies ◽  
Mononuclear Cells ◽  
Lewy Bodies ◽  
Acetylcholinesterase Inhibitors ◽  
Operating Characteristics ◽  
Peripheral Blood Mononuclear

Background: Central nervous system disruption of cholinergic (ACh) signaling, which plays a major role in cognitive processes, is well documented in dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD). The expression of muscarinic ACh receptors type 1 and 4 (CHRM1 and CHRM4) has been reported to be altered in the brain of DLB patients. Objective: We aim to assess the peripheral gene expression of CHRM1 and 4 in DLB as a possible marker as compared to AD and healthy control (HC) subjects. Methods: Peripheral blood mononuclear cells were collected from 21 DLB, 13 AD, and 8 HC matched subjects. RT-PCR was performed to estimate gene expression of CHRM1 and CHRM4. Results: Peripheral CHRM1 expression was higher and CHRM4 was lower in DLB and AD compared to HC, whereas both CHRM1 and CHRM4 levels were higher in AD compared to DLB patients. Receiver operating characteristics curves, with logistic regression analysis, showed that combining peripheral CHRM1 and CHRM4 levels, DLB and AD subjects were classified with an accuracy of 76.0%. Conclusion: Alterations of peripheral CHRM1 and CHRM4 was found in both AD and DLB patients as compared to HC. CHRM1 and CHRM4 gene expression resulted to be lower in DLB patients compared to AD. In the future, peripheral CHRM expression could be studied as a possible marker of neurodegenerative conditions associated with cholinergic deficit and a possible marker of response to acetylcholinesterase inhibitors.

scholarly journals Longitudinal data in peripheral blood confirm that PM20D1 is a quantitative trait locus (QTL) for Alzheimer’s disease and implicate its dynamic role in disease progression

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Qi Wang ◽  
Yinghua Chen ◽  
Benjamin Readhead ◽  
Kewei Chen ◽  
Yi Su ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Longitudinal Data ◽  
Disease Progression ◽  
Peripheral Blood ◽  
Early Stage ◽  
Underlying Mechanism ◽  
Methylation Data ◽  
Brain Tissues

Abstract Background While Alzheimer’s disease (AD) remains one of the most challenging diseases to tackle, genome-wide genetic/epigenetic studies reveal many disease-associated risk loci, which sheds new light onto disease heritability, provides novel insights to understand its underlying mechanism and potentially offers easily measurable biomarkers for early diagnosis and intervention. Methods We analyzed whole-genome DNA methylation data collected from peripheral blood in a cohort (n = 649) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and compared the DNA methylation level at baseline among participants diagnosed with AD (n = 87), mild cognitive impairment (MCI, n = 175) and normal controls (n = 162), to identify differentially methylated regions (DMRs). We also leveraged up to 4 years of longitudinal DNA methylation data, sampled at approximately 1 year intervals to model alterations in methylation levels at DMRs to delineate methylation changes associated with aging and disease progression, by linear mixed-effects (LME) modeling for the unchanged diagnosis groups (AD, MCI and control, respectively) and U-shape testing for those with changed diagnosis (converters). Results When compared with controls, patients with MCI consistently displayed promoter hypomethylation at methylation QTL (mQTL) gene locus PM20D1. This promoter hypomethylation was even more prominent in patients with mild to moderate AD. This is in stark contrast with previously reported hypermethylation in hippocampal and frontal cortex brain tissues in patients with advanced-stage AD at this locus. From longitudinal data, we show that initial promoter hypomethylation of PM20D1 during MCI and early stage AD is reversed to eventual promoter hypermethylation in late stage AD, which helps to complete a fuller picture of methylation dynamics. We also confirm this observation in an independent cohort from the Religious Orders Study and Memory and Aging Project (ROSMAP) Study using DNA methylation and gene expression data from brain tissues as neuropathological staging (Braak score) advances. Conclusions Our results confirm that PM20D1 is an mQTL in AD and demonstrate that it plays a dynamic role at different stages of the disease. Further in-depth study is thus warranted to fully decipher its role in the evolution of AD and potentially explore its utility as a blood-based biomarker for AD.

scholarly journals Integrated DNA methylation and gene expression profiling across multiple brain regions implicate novel genes in Alzheimer’s disease

2019 ◽  
Vol 137 (4) ◽  
pp. 557-569 ◽  
Author(s):  
Stephen A. Semick ◽  
Rahul A. Bharadwaj ◽  
Leonardo Collado-Torres ◽  
Ran Tao ◽  
Joo Heon Shin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Brain Regions ◽  
Novel Genes

scholarly journals Association of MAPT haplotypes with Alzheimer’s disease risk and MAPT brain gene expression levels

2014 ◽  
Vol 6 (4) ◽  
pp. 39 ◽  
Author(s):  
Mariet Allen ◽  
Michaela Kachadoorian ◽  
Zachary Quicksall ◽  
Fanggeng Zou ◽  
High Chai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Risk ◽  
Expression Levels ◽  
Brain Gene Expression ◽  
Gene Expression Levels

Rs4878104 contributes to Alzheimer’s disease risk and regulates DAPK1 gene expression

2017 ◽  
Vol 38 (7) ◽  
pp. 1255-1262 ◽  
Author(s):  
Yang Hu ◽  
Liang Cheng ◽  
Ying Zhang ◽  
Weiyang Bai ◽  
Wenyang Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Risk

O3-04-06: GENE EXPRESSION PROFILING AND DNA METHYLATION IN ALZHEIMER'S DISEASE BRAINS

2014 ◽  
Vol 10 ◽  
pp. P216-P216
Author(s):  
Mariet Allen ◽  
Daniel Serie ◽  
Zhifu Sun ◽  
Saurabh Baheti ◽  
Mike Walsh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Gene Expression Profiling ◽  
Expression Profiling

scholarly journals Integrated DNA methylation and gene expression profiling across multiple brain regions implicate novel genes in Alzheimer’s disease

2018 ◽  
Author(s):  
Stephen A. Semick ◽  
Rahul A. Bharadwaj ◽  
Leonardo Collado-Torres ◽  
Ran Tao ◽  
Joo Heon Shin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Neurodegenerative Disorder ◽  
Late Onset ◽  
Brain Regions ◽  
Epigenetic Mechanism ◽  
Novel Genes ◽  
Age Related

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.

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