scholarly journals Comparison of Illumina 450K and EPIC arrays in placental DNA methylation

Epigenetics ◽  
2019 ◽  
Vol 14 (12) ◽  
pp. 1177-1182 ◽  
Author(s):  
Nora Fernandez-Jimenez ◽  
Catherine Allard ◽  
Luigi Bouchard ◽  
Patrice Perron ◽  
Mariona Bustamante ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Illumina 450K

scholarly journals Apolipoprotein E DNA methylation and late-life disease

2018 ◽  
Vol 47 (3) ◽  
pp. 899-907 ◽  
Author(s):  
Ida K Karlsson ◽  
Alexander Ploner ◽  
Yunzhang Wang ◽  
Margaret Gatz ◽  
Nancy L Pedersen ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Apolipoprotein E ◽  
Promoter Region ◽  
Allelic Variation ◽  
450K Array ◽  
Blood Draw ◽  
Standard Deviation Increase ◽  
Illumina 450K ◽  
Apoe Locus ◽  
Illumina 450K Array

Abstract Background This study aims to investigate if DNA methylation of the apolipoprotein E (APOE) locus affects the risks of dementia, Alzheimeŕs disease (AD) or cardiovascular disease (CVD). Methods DNA methylation across theAPOE gene has previously been categorized into three distinct regions: a hypermethylated region in the promoter, a hypomethylated region in the first two introns and exons and a hypermethylated region in the 3′exon that also harbours theAPOE ε2 and ε4 alleles. DNA methylation levels in leukocytes were measured using the Illumina 450K array in 447 Swedish twins (mean age 78.1 years). We used logistic regression to investigate whether methylation levels in those regions affect the odds of disease. Results We found that methylation levels in the promoter region were associated with dementia and AD after adjusting for sex, age at blood draw, education, smoking and relatedness among twins [odds ratio (OR) 1.32 per standard deviation increase in methylation levels, 95% confidence interval (CI) 1.08–1.62 for dementia; OR 1.38, 95% CI 1.07–1.78 for AD). We did not detect any difference in methylation levels between CVD cases and controls. Results were similar when comparing within discordant twin pairs, and did not differ as a function ofAPOE genotype. Conclusions We found that higher DNA methylation levels in the promoter region ofAPOE increase the odds of dementia and AD, but not CVD. The effect was independent ofAPOE genotype, indicating that allelic variation and methylation variation inAPOE may act independently to increase the risk of dementia.

scholarly journals Derivation of Poly-Methylomic Profile Scores for Schizophrenia

2019 ◽  
Author(s):  
Oliver J. Watkeys ◽  
Sarah Cohen-Woods ◽  
Yann Quidé ◽  
Murray J. Cairns ◽  
Bronwyn Overs ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Multiple Testing ◽  
P Value ◽  
Summary Statistics ◽  
Illumina 450K ◽  
Profile Score ◽  
Methylation Patterns ◽  
Control Association ◽  
Schizophrenia Case ◽  
450K Methylation

AbstractSchizophrenia (SZ) and bipolar disorder (BD) share numerous clinical and biological features as well as environmental risk factors that may be associated with altered DNA methylation. In this study we sought to construct a Poly-Methylomic Profile Score (PMPS) for SZ, representing the degree of epigenome-wide methylation according to previously published findings; we then examined its association with SZ and BD in an independent sample. DNA methylation for 57 SZ, 59 BD cases and 55 healthy controls (HCs) was quantified using the Illumina 450K methylation beadchip. We constructed five PMPSs for different p-value thresholds using summary statistics reported in a large epigenome-wide schizophrenia case-control association study, weighted by individual CpG effect sizes. All SZ PMPSs were significantly elevated in SZ cases relative to HCs, with the score calculated at the most stringent threshold accounting for the greatest amount of variance in SZ (compared to other PMPSs derived at more inclusivep-value thresholds). However, none of the PMPSs were associated with BD, or a combined cohort of BD and SZ cases relative to HCs. Results demonstrating elevated PMPSs in SZ relative to BD did not survive correction for multiple testing. PMPSs were also not associated with positive or negative symptom severity. That this SZ-derived PMPSs was elevated among SZ, but not BD participants, suggests that epigenome-wide methylation patterns associated with schizophrenia may represent distinct pathophysiology that is yet to be elucidated. Whether this PMPS may be associated with neuroanatomical or other biological endophenotypes relevant to SZ and/or BD remains to be determined.

scholarly journals Agreement in DNA methylation levels from the Illumina 450K array across batches, tissues, and time

Epigenetics ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. 19-32 ◽  
Author(s):  
Marie Forest ◽  
Kieran J. O'Donnell ◽  
Greg Voisin ◽  
Helene Gaudreau ◽  
Julia L. MacIsaac ◽  
...  
Keyword(s):  
Dna Methylation ◽  
450K Array ◽  
Illumina 450K ◽  
Illumina 450K Array

scholarly journals Considerations for normalization of DNA methylation data by Illumina 450K BeadChip assay in population studies

Epigenetics ◽  
2013 ◽  
Vol 8 (11) ◽  
pp. 1141-1152 ◽  
Author(s):  
Paul Yousefi ◽  
Karen Huen ◽  
Raul Aguilar Schall ◽  
Anna Decker ◽  
Emon Elboudwarej ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Population Studies ◽  
Methylation Data ◽  
Illumina 450K

scholarly journals The methylome of the human frontal cortex across development

2014 ◽  
Author(s):  
Andrew E Jaffe ◽  
Yuan Gao ◽  
Ran Tao ◽  
Thomas M Hyde ◽  
Daniel R Weinberger ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Frontal Cortex ◽  
Regulation Of Gene Expression ◽  
Epigenetic State ◽  
Illumina 450K ◽  
Human Frontal Cortex ◽  
Development And Aging ◽  
Genomic Resource ◽  
Gene Expression Levels

DNA methylation (DNAm) plays an important role in epigenetic regulation of gene expression, orchestrating tissue differentiation and development during all stages of mammalian life. This epigenetic control is especially important in the human brain, with extremely dynamic gene expression during fetal and infant life, and becomes progressively more stable at later periods of development . We characterized the epigenetic state of the developing and aging human frontal cortex in post-mortem tissue from 351 individuals across the lifespan using the Illumina 450k DNA methylation microarray. The largest changes in the methylome occur at birth at varying spatial resolutions - we identify 359,087 differentially methylated loci, which form 23,732 significant differentially methylated regions (DMRs). There were also 298 regions of long-range changes in DNAm, termed "blocks", associated with birth that strongly overlap previously published colon cancer blocks. We then identify 55,439 DMRs associated with development and aging, of which 61.9% significantly associate with nearby gene expression levels. Lastly, we find enrichment of genomic loci of risk for schizophrenia and several other common diseases among these developmental DMRs. These data, integrated with existing genetic and transcriptomic data, create a rich genomic resource across brain development.

scholarly journals Integrative analysis with expanded DNA methylation data reveals common key regulators and pathways in cancers

2018 ◽  
Author(s):  
Shicai Fan ◽  
Jianxiong Tang ◽  
Nan Li ◽  
Ying Zhao ◽  
Rizi Ai ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Human Genome ◽  
Therapeutic Targets ◽  
Integrative Analysis ◽  
Axonal Guidance ◽  
Methylation Data ◽  
450K Array ◽  
Diagnosis And Prognosis ◽  
Illumina 450K ◽  
Illumina 450K Array

AbstractThe integration of genomic and DNA methylation data has been demonstrated as a powerful strategy in understanding cancer mechanisms and identifying therapeutic targets. The TCGA consortium has mapped DNA methylation in thousands of cancer samples using Illumina Infinium Human Methylation 450K BeadChip (Illumina 450K array) that only covers about 1.5% of CpGs in the human genome. Therefore, increasing the coverage of the DNA methylome would significantly leverage the usage of the TCGA data. Here, we present a new model called EAGLING that can expand the Illumina 450K array data 18 times to cover about 30% of the CpGs in the human genome. We applied it to analyze 13 cancers in TCGA. By integrating the expanded methylation, gene expression and somatic mutation data, we identified the genes showing differential patterns in each of the 13 cancers. Many of the triple-evidenced genes identified in the majority of the cancers are biomarkers or potential biomarkers. Pan-cancer analysis also revealed the pathways in which the triple-evidenced genes are enriched, which include well known ones as well as new ones such as axonal guidance signaling pathway and pathways related to inflammatory processing or inflammation response. Triple-evidenced genes, particularly TNXB, RRM2, CELSR3, SLC16A3, FANCI, MMP9, MMP11, SIK1, TRIM59, showed superior predictive power in both tumor diagnosis and prognosis. These results have demonstrated that the integrative analysis using the expanded methylation data is powerful in identifying critical genes/pathways that may serve as new therapeutic targets.

scholarly journals shinyMethyl: interactive quality control of Illumina 450k DNA methylation arrays in R

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 175 ◽  
Author(s):  
Jean-Philippe Fortin ◽  
Elana Fertig ◽  
Kasper Hansen
Keyword(s):  
Dna Methylation ◽  
Quality Control ◽  
Large Scale ◽  
Association Studies ◽  
Principal Component ◽  
The Cancer Genome Atlas ◽  
Bioconductor Package ◽  
Interactive Interface ◽  
Illumina 450K ◽  
Cancer Genome Atlas

We present shinyMethyl, a Bioconductor package for interactive quality control of DNA methylation data from Illumina 450k arrays. The package summarizes 450k experiments into small exportable R objects from which an interactive interface is launched. Reactive plots allow fast and intuitive quality control assessment of the samples. In addition, exploration of the phenotypic associations is possible through coloring and principal component analysis. Altogether, the package makes it easy to perform quality assessment of large-scale methylation datasets, such as epigenome-wide association studies or the datasets available through The Cancer Genome Atlas portal. The shinyMethyl package is implemented in R and available via Bioconductor. Its development repository is at https://github.com/jfortin1/shinyMethyl.

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