scholarly journals Association between DNA Methylation of the BDNF Promoter Region and Clinical Presentation in Alzheimer's Disease

2015 ◽  
Vol 5 (1) ◽  
pp. 64-73 ◽  
Author(s):  
Tomoyuki Nagata ◽  
Nobuyuki Kobayashi ◽  
Jumpei Ishii ◽  
Shunichiro Shinagawa ◽  
Ritsuko Nakayama ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Methylation Level ◽  
Clinical Presentation ◽  
Neuropsychological Test ◽  
Cpg Sites ◽  
The Brain ◽  
Normal Controls ◽  
Methylation Ratio

Background/Aims: In the present study, we examined whether DNA methylation of the brain-derived neurotrophic factor (BDNF) promoter is associated with the manifestation and clinical presentation of Alzheimer's disease (AD). Methods: Of 20 patients with AD and 20 age-matched normal controls (NCs), the DNA methylation of the BDNF promoter (measured using peripheral blood samples) was completely analyzed in 12 patients with AD and 6 NCs. The resulting methylation levels were compared statistically. Next, we investigated the correlation between the DNA methylation levels and the clinical presentation of AD. Results: The total methylation ratio (in %) of the 20 CpG sites was significantly higher in the AD patients (5.08 ± 5.52%) than in the NCs (2.09 ± 0.81%; p < 0.05). Of the 20 CpG sites, the methylation level at the CpG4 site was significantly higher in the AD subjects than in the NCs (p < 0.05). Moreover, the methylation level was significantly and negatively correlated with some neuropsychological test subscores (registration, recall, and prehension behavior scores; p < 0.05). Conclusion: These results suggest that the DNA methylation of the BDNF promoter may significantly influence the manifestation of AD and might be associated with its neurocognitive presentation.

Changes in methylation patterns of multiple genes from peripheral blood leucocytes of Alzheimer's disease patients

2013 ◽  
Vol 25 (2) ◽  
pp. 66-76 ◽  
Author(s):  
Yaping Hou ◽  
Huayun Chen ◽  
Qiong He ◽  
Wei Jiang ◽  
Tao Luo ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Methylation Level ◽  
Target Genes ◽  
Normal Population ◽  
Cpg Islands ◽  
Methylation Pattern ◽  
Control Group ◽  
Specific Pcr

BackgroundEfforts aiming at identifying biomarkers and corresponding methods for early diagnosis of Alzheimer's disease (AD) might be the most appropriate strategy to initiate promising new treatments and/or prevention of ADObjectiveThe aim of our study is to assess the association of DNA methylation pattern of various leucocyte genes with AD pathogenesis in order to find potential biomarkers and corresponding methods for molecular diagnosis of AD.MethodsDNA methylation level of various genes in AD patients and normal population were compared by bisulphite sequencing PCR and methylation-specific PCR (MSP). Furthermore, real-time PCR was used to explore the effects of DNA methylation on the expression of target genes.ResultsResults showed significant hypermethylation of mammalian orthologue of Sir2 (SIRT1) gene in AD patients compared with normal population. Meanwhile, changes in methylation level of SIRT1 gene between different severities of AD were also found. Specific primers were designed from the SIRT1 CpG islands to differentiate AD and control group by MSP method. Besides, significant demethylation of β-amyloid precursor protein (APP) gene was observed in AD patients, whereas no difference was observed in other AD-related genes. Moreover, significant decrease in expression of SIRT1 gene and increase in expression of APP gene were also found in AD patients. In addition, the expression level of SIRT1/APP genes was associated with the severity, but not with the age or gender, of AD patients.Conclusion:SIRT1 and APP might be the interesting candidate biomarkers and valuable for clinical diagnosis or treatment of AD.

scholarly journals DNA methylation patterns of β-globin cluster in β-thalassemia patients

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Xiuqin Bao ◽  
Yangjin Zuo ◽  
Diyu Chen ◽  
Cunyou Zhao
Keyword(s):  
Dna Methylation ◽  
Cord Blood ◽  
Methylation Level ◽  
Epigenetic Modification ◽  
Fetal Hemoglobin ◽  
Cpg Sites ◽  
Hbf Level ◽  
Globin Promoter ◽  
Methylation Patterns ◽  
Normal Controls

Abstract Background Reactivation of fetal hemoglobin (HbF, α2γ2) holds a therapeutic target for β-thalassemia and sickle cell disease. Although many HbF regulators have been identified, the methylation patterns in β-globin cluster driving the fetal-to-adult hemoglobin switch remains to be determined. Results Here, we evaluated DNA methylation patterns of the β-globin cluster from peripheral bloods of 105 β0/β0 thalassemia patients and 44 normal controls. We also recruited 15 bone marrows and 4 cord blood samples for further evaluation. We identified that the CpG sites in the locus control region (LCR) DNase I hypersensitive site 4 and 3 (HS4-3) regions, and γ- and β-globin promoters displayed hypomethylation in β0/β0-thalassemia patients, especially for the patients with high HbF level, as compared with normal controls. Furthermore, hypomethylations in most of CpG sites of the HS4-3 core regions were also observed in bone marrows (BM) of β0/β0-patients compared with normal controls; and methylation level of γ-globin promoter -50 and + 17 CpG sites showed lower methylation level in patients with high HbF level compared with those with low HbF level and a negative correlation with HbF level among β0-thalassemia patients. Finally, γ-globin promoter + 17 and + 50 CpG sites also displayed significant hypomethylation in cord blood (CB) tissues compared with BM tissues from normal controls. Conclusions Our findings revealed methylation patterns in β-globin cluster associated with β0 thalassemia disease and γ-globin expression, contributed to understand the epigenetic modification in β0 thalassemia patients and provided candidate targets for the therapies of β-hemoglobinopathies.

scholarly journals Promoter methylation and gene expression of Pin1 is associated to the risk of Alzheimer's disease in Southern Chinese

2020 ◽  
Author(s):  
Suk Ling Ma ◽  
Nelson Leung Sang Tang ◽  
Linda Chiu Wa Lam
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Protective Factor ◽  
Age At Onset ◽  
Melting Curve ◽  
Melting Curve Analysis ◽  
Southern Chinese ◽  
Normal Controls

Background: Pin1 is a propyl cis-trans isomerase and it has been associated with age-at-onset of Alzheimer's disease (AD) and other pathological characteristic of AD. DNA methylation is one of the gene regulation and it might affect the gene expression. Objectives: This study was aimed to examine the correlation between DNA methylation and gene expression of Pin1 and its effect on the risk of AD in a Chinese population. Methods: 80 AD patients and 180 normal controls were recruited in this study and their cognitive function were assessed. Pin1 gene expression and methylation were quantified by real-time RT-PCR and Melting Curve Analysis-Methylation assay (MCA-Meth) respectively. Results: Our finding revealed a positive correlation between methylation and gene expression of Pin1 (p=0.001) and increased Pin1 methylation was predisposed to the risk of AD (p<0.001). CG genotype of Pin1 SNP rs2287839 was associated with higher gene expression of Pin1 (p=0.036) and the effect was only prominent in normal controls as AD patients were already methylated at Pin1 promoter. Furthermore, methylation of Pin1 was associated with better performance in cognition (p=0.018). Conclusions: Our result further supported the involvement of Pin1 in AD and the increased level of Pin1 might be a protective factor for AD.

Promoter Methylation and Gene Expression of Pin1 Associated with the Risk of Alzheimer’s Disease in Southern Chinese

2021 ◽  
Vol 17 (13) ◽  
pp. 1232-1237
Author(s):  
Suk L. Ma ◽  
Nelson L.S. Tang ◽  
Linda C. Wa Lam
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Protective Factor ◽  
Melting Curve ◽  
Melting Curve Analysis ◽  
Southern Chinese ◽  
Methylation Assay ◽  
Normal Controls

Background: Pin1 is a propyl cis-trans isomerase and it has been associated with age-atonset of Alzheimer’s disease (AD) and other pathological characteristics of AD. DNA methylation is one of the gene regulation mechanisms and it might affect the gene expression. Objectives: This study was aimed to examine the correlation between DNA methylation and gene expression of Pin1 and its effect on the risk of AD in a Chinese population. Methods: 80 AD patients and 180 normal controls were recruited in this study and their cognitive functions were assessed. Pin1 gene expression and methylation were quantified by real-time RT-PCR and Melting Curve Analysis-Methylation assay (MCA-Meth), respectively. Results: Our finding revealed a positive correlation between methylation and gene expression of Pin1 (p=0.001) and increased Pin1 methylation was predisposed to the risk of AD (p<0.001). CG genotype of Pin1 SNP rs2287839 was associated with higher gene expression of Pin1 (p=0.036) and the effect was only prominent in normal controls as AD patients were already methylated at Pin1 promoter. Furthermore, methylation of Pin1 was associated with better performance in cognition (p=0.018). Conclusion: Our result further supported the involvement of Pin1 in AD and the increased level of Pin1 might be a protective factor for AD.

scholarly journals ANALYSES OF BRAIN CORTICAL CHANGES OF ALZHEIMER’S DISEASE

2021 ◽  
pp. 2140025
Author(s):  
YUTING LV ◽  
WENSHUO ZHAO ◽  
XUFENG YAO ◽  
SONG XU ◽  
ZHIXIAN TANG ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Brain Regions ◽  
Morphological Description ◽  
Gyrification Index ◽  
Morphological Differences ◽  
The Brain ◽  
Normal Controls

Alzheimer’s disease (AD) produces complicated cortical changes in gray matter (GM) of the human brain. However, alterations in the brain cortex have not been clearly addressed. In our study, a cohort of 236 cases MR data enrolled from the ADNI database was categorized into three groups of normal controls (NCs), mild cognitive impairment (MCI) and AD. The GM morphological differences were investigated among the three groups using the magnetic resonance (MR) GM characteristics of gray matter volume (GMV), cortical thickness (CT), cortical surface area (CSA) and local gyrification index (LGI) at the three levels of whole brain, bilateral hemispheres and critical brain regions. Totally, there were six critical brain regions for GMV, 11 for CT, 2 for CSA and 59 for LGI among the three groups for the no-division groups. Also, there were 11 critical brain regions for GMV, 15 for CT, 8 for CSA, 3 for LGI for female sub-groups and 4 critical brain regions for GMV, 11 for CT, 1 for CSA, 3 for LGI for male sub-groups. The four measured cortical characteristics showed reliable capability in the morphological description of GM changes of AD. In conclusion, the cortical characteristics of GMV, CT, CSA and LGI of critical brain regions showed valuable indications for GM changes of AD, and those characteristics could be used as imaging markers for AD prediction.

scholarly journals Argentina-Alzheimer's disease neuroimaging initiative (Arg-ADNI): neuropsychological evolution profile after one-year follow up

2018 ◽  
Vol 76 (4) ◽  
pp. 231-240 ◽  
Author(s):  
Patricio Chrem Méndez ◽  
Ismael Calandri ◽  
Federico Nahas ◽  
María Julieta Russo ◽  
Ignacio Demey ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Functional Performance ◽  
Neuropsychological Test ◽  
Neuropsychological Testing ◽  
Semantic Fluency ◽  
Dementia Patients ◽  
One Year ◽  
Normal Controls

ABSTRACT The Argentina-Alzheimer's disease neuroimaging initiative (Arg-ADNI) study is a longitudinal prospective cohort of 50 participants at a single institution in Buenos Aires, Argentina. Longitudinal assessments on a neuropsychological test battery were performed on 15 controls, 24 mild cognitive impairment (MCI) patients and 12 Alzheimer's disease (AD) dementia patients. In our study population, there was a high prevalence of positive AD biomarkers in the AD group, 92.3% (12/13); and a low prevalence in the normal controls, 20%; almost half (48%) of the patients diagnosed with MCI had positive amyloid detection. After a one year, the significant differences found at baseline on neuropsychological testing were similar at the follow-up assessment even though the AD group had significantly altered its functional performance (FAQ and CDR). The exception was semantic fluency, which showed greater impairment between the AD group and MCI and normal controls respectively. For these tests, the addition of AD biomarkers as a variable did not significantly alter the variations previously found for the established clinical group's model. Finally, the one-year conversion rate to dementia was 20% in the MCI cohort.

DNA methylation level of the neprilysin promoter in Alzheimer's disease brains

2018 ◽  
Vol 670 ◽  
pp. 8-13 ◽  
Author(s):  
Kenichi Nagata ◽  
Tatsuo Mano ◽  
Shigeo Murayama ◽  
Takaomi C. Saido ◽  
Atsushi Iwata
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Methylation Level

scholarly journals Alzheimer’s disease-associated (hydroxy)methylomic changes in the brain and blood

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Roy Lardenoije ◽  
Janou A. Y. Roubroeks ◽  
Ehsan Pishva ◽  
Markus Leber ◽  
Holger Wagner ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Dna Methylation ◽  
Late Onset ◽  
Middle Temporal Gyrus ◽  
Promising Target ◽  
Subsequent Conversion ◽  
Novel Therapeutic Strategies ◽  
Genomic Regions ◽  
The Brain

Abstract Background Late-onset Alzheimer’s disease (AD) is a complex multifactorial affliction, the pathogenesis of which is thought to involve gene-environment interactions that might be captured in the epigenome. The present study investigated epigenome-wide patterns of DNA methylation (5-methylcytosine, 5mC) and hydroxymethylation (5-hydroxymethylcytosine, 5hmC), as well as the abundance of unmodified cytosine (UC), in relation to AD. Results We identified epigenetic differences in AD patients (n = 45) as compared to age-matched controls (n = 35) in the middle temporal gyrus, pertaining to genomic regions close to or overlapping with genes such as OXT (− 3.76% 5mC, pŠidák = 1.07E−06), CHRNB1 (+ 1.46% 5hmC, pŠidák = 4.01E−04), RHBDF2 (− 3.45% UC, pŠidák = 4.85E−06), and C3 (− 1.20% UC, pŠidák = 1.57E−03). In parallel, in an independent cohort, we compared the blood methylome of converters to AD dementia (n = 54) and non-converters (n = 42), at a preclinical stage. DNA methylation in the same region of the OXT promoter as found in the brain was found to be associated with subsequent conversion to AD dementia in the blood of elderly, non-demented individuals (+ 3.43% 5mC, pŠidák = 7.14E−04). Conclusions The implication of genome-wide significant differential methylation of OXT, encoding oxytocin, in two independent cohorts indicates it is a promising target for future studies on early biomarkers and novel therapeutic strategies in AD.

scholarly journals A Tensor-Based Framework for rs-fMRI Classification and Functional Connectivity Construction

2020 ◽  
Vol 14 ◽  
Author(s):  
Ali Noroozi ◽  
Mansoor Rezghi
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Functional Connectivity ◽  
Extraction Methods ◽  
Classification Performance ◽  
Brain Diseases ◽  
Brain Disorder ◽  
Brain Images ◽  
The Brain ◽  
Normal Controls

Recently, machine learning methods have gained lots of attention from researchers seeking to analyze brain images such as Resting-State Functional Magnetic Resonance Imaging (rs-fMRI) to obtain a deeper understanding of the brain and such related diseases, for example, Alzheimer's disease. Finding the common patterns caused by a brain disorder through analysis of the functional connectivity (FC) network along with discriminating brain diseases from normal controls have long been the two principal goals in studying rs-fMRI data. The majority of FC extraction methods calculate the FC matrix for each subject and then use simple techniques to combine them and obtain a general FC matrix. In addition, the state-of-the-art classification techniques for finding subjects with brain disorders also rely on calculating an FC for each subject, vectorizing, and feeding them to the classifier. Considering these problems and based on multi-dimensional nature of the data, we have come up with a novel tensor framework in which a general FC matrix is obtained without the need to construct an FC matrix for each sample. This framework also allows us to reduce the dimensionality and create a novel discriminant function that rather than using FCs works directly with each sample, avoids vectorization in any step, and uses the test data in the training process without forcing any prior knowledge of its label into the classifier. Extensive experiments using the ADNI dataset demonstrate that our proposed framework effectively boosts the fMRI classification performance and reveals novel connectivity patterns in Alzheimer's disease at its early stages.

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