scholarly journals Gene-methylation interactions: Discovering region-wise DNA methylation levels that modify SNP-associated disease risk

2019 ◽  
Author(s):  
Julia Romanowska ◽  
Øystein A. Haaland ◽  
Astanand Jugessur ◽  
Miriam Gjerdevik ◽  
Zongli Xu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Methylation Level ◽  
Disease Risk ◽  
Association Studies ◽  
R Package ◽  
Epigenetic Mark ◽  
Genome Wide Association Studies ◽  
Association Analyses ◽  
Cpg Dinucleotides ◽  
New Methods

AbstractThe genetic code is tightly linked to epigenetic instructions as to what genes to express, and when and where to express them. The most studied epigenetic mark is DNA methylation at CpG dinucleotides. Today’s technology enables a rapid assessment of DNA sequence and methylation levels at a single-site resolution for hundreds of thousands of sites in the human genome, in thousands of individuals at a time. Recent years have seen a rapid increase in epigenome-wide association studies (EWAS) searching for the causes of risk for genetic diseases that previous genome-wide association studies (GWAS) could not pinpoint. However, those single-omics data analyses led to even more questions and it has become clear that only by integrating data one can get closer to answers. Here, we propose two new methods within genetic association analyses that treat the level of DNA methylation at a given CpG site as environmental exposure. Our analyses search for statistical interactions between a given allele and DNA methylation (G×Me), and between a parent-of-origin effect and DNA methylation (PoO× Me). The new methods were implemented in the R package Haplin and were tested on a dataset comprising genotype data from mother-father-child triadsm with DNA methylation data from the children only. The phenotype here was orofacial clefts (OFC), a relatively common birth defect in humans, which is known to have a genetic origin and an environmental component possibly mediated by DNA methylation. We found no significant PoO×Me interactions and a few significant G×Me interactions. Our results show that the significance of these interaction effects depends on the genomic region in which the CpGs reside and on the number of strata of methylation level. We demonstrate that, by including the methylation level around the SNP in the analyses, the estimated relative risk of OFC can change significantly. We also discuss the importance of including control data in such analyses. The new methods will be of value for all the researchers who want to explore genome- and epigenome-wide datasets in an integrative manner. Moreover, thanks to the implementation in a popular R package, the methods are easily accessible and enable fast scans of the genome- and epigenome-wide datasets.

Abstract MP32: Epigenome-Wide DNA Methylation Profiling in a CVD Cohort: The ARIC Study

Circulation ◽  
2013 ◽  
Vol 127 (suppl_12) ◽  
Author(s):  
James S Pankow ◽  
Ellen W Demerath ◽  
Weihua Guan ◽  
Myriam Fornage ◽  
Thomas H Mosley ◽  
...  
Keyword(s):  
Dna Methylation ◽  
X Chromosome ◽  
Methylation Level ◽  
Association Studies ◽  
Univariate Analysis ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Stage Of Development ◽  
Average Methylation ◽  
Aric Study

DNA methylation is mitotically heritable modification in chromatin structure that impacts transcriptional control of genes and cellular function. Recent technological advances provide opportunities to systematically interrogate variation in DNA methylation across the genome in large epidemiologic studies. However, unlike inherited changes to the genetic sequence, variation in site-specific methylation varies by tissue, stage of development, disease state, and may be affected by gender, aging and exposure to environmental factors. As a result, there is likely a greater threat of confounding in epigenome-wide methylation studies compared to genome-wide association studies of SNPs. The Illumina Infinium HumanMethylation450 BeadChip was used to measure DNA methylation in peripheral blood obtained from African American participants from the Jackson, Mississippi and Forsyth County, North Carolina field centers of the Atherosclerosis Risk in Communities (ARIC) Study, a population-based cohort of middle-aged men and women. After excluding outlier samples and CpG sites using quality control filters, we analyzed 473,687 sites in 2873 subjects who were between 47-71 years of age at the time of DNA collection. We used linear regression with robust standard errors to examine cross-sectional associations of demographic factors with the beta value, an estimate of the average methylation level at each locus, and applied a Bonferroni correction to account for multiple testing. In univariate analysis, 91% of sites on the X chromosome and 10% of sites on the autosomes exhibited statistically significant gender differences in methylation level (p<1x10-7). Average methylation was higher in women than men for most of the significant sites (63% and 89% on the X chromosome and autosomes, respectively). Percent European ancestry estimated from ancestry informative markers was significantly associated with methylation level at 4% of sites. Age was also significantly associated with methylation at 4% of sites; average methylation was lower in older subjects compared to younger subjects for the majority (58%) of these sites. As we begin to implement epigenome-wide studies of DNA methylation and CVD outcomes, these results indicate that such studies will require careful consideration of adjustment techniques to avoid confounding by gender, age, and other covariates.

scholarly journals MultiMeta: an R package for meta-analysing multi-phenotype genome-wide association studies

2015 ◽  
Author(s):  
Dragana Vuckovic ◽  
Paolo Gasparini ◽  
Nicole Soranzo ◽  
Valentina Iotchkova
Keyword(s):  
Multivariate Analysis ◽  
Association Studies ◽  
Meta Analysis ◽  
R Package ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
New Methods ◽  
Genome Wide ◽  
Inverse Variance

Summary: As new methods for multivariate analysis of Genome Wide Association Studies (GWAS) become available, it is important to be able to combine results from different cohorts in a meta-analysis. The R package MultiMeta provides an implementation of the inverse-variance based method for meta-analysis, generalized to an n-dimensional setting. Availability: The R package MultiMeta can be downloaded from CRAN Contact: [email protected]

scholarly journals Common alleles of CMT2 and NRPE1 are major determinants of de novo DNA methylation variation in Arabidopsis thaliana

2019 ◽  
Author(s):  
Eriko Sasaki ◽  
Taiji Kawakatsu ◽  
Joseph Ecker ◽  
Magnus Nordborg
Keyword(s):  
Dna Methylation ◽  
Large Scale ◽  
Cytosine Methylation ◽  
De Novo ◽  
Association Studies ◽  
Published Data ◽  
Epigenetic Mark ◽  
Stabilizing Selection ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractDNA cytosine methylation is an epigenetic mark associated with silencing of transposable elements (TEs) and heterochromatin formation. In plants, it occurs in three sequence contexts: CG, CHG, and CHH (where H is A, T, or C). The latter does not allow direct inheritance of methylation during DNA replication due to lack of symmetry, and methylation must therefore be re-established every cell generation. Genome-wide association studies (GWAS) have previously shown that CMT2 and NRPE1 are major determinants of genome-wide patterns of TE CHH-methylation. Here we instead focus on CHH-methylation of individual TEs and TE-families, allowing us to identify the pathways involved in CHH-methylation simply from natural variation and confirm the associations by comparing them with mutant phenotypes. Methylation at TEs targeted by the RNA-directed DNA methylation (RdDM) pathway is unaffected by CMT2 variation, but is strongly affected by variation at NRPE1, which is largely responsible for the longitudinal cline in this phenotype. In contrast, CMT2-targeted TEs are affected by both loci, which jointly explain 7.3% of the phenotypic variation (13.2% of total genetic effects). There is no longitudinal pattern for this phenotype, however, because the geographic patterns appear to compensate for each other in a pattern suggestive of stabilizing selection.Author SummaryDNA methylation is a major component of transposon silencing, and essential for genomic integrity. Recent studies revealed large-scale geographic variation as well as the existence of major trans-acting polymorphisms that partly explained this variation. In this study, we re-analyze previously published data (The 1001 Epigenomes), focusing on de novo DNA methylation patterns of individual TEs and TE families rather than on genome-wide averages (as was done in previous studies). GWAS of the patterns reveals the underlying regulatory networks, and allowed us to comprehensively characterize trans-regulation of de novo DNA methylation and its role in the striking geographic pattern for this phenotype.

scholarly journals A Bayesian Framework for Multiple Trait Colocalization from Summary Association Statistics

2017 ◽  
Author(s):  
Claudia Giambartolomei ◽  
Jimmy Zhenli Liu ◽  
Wen Zhang ◽  
Mads Hauberg ◽  
Huwenbo Shi ◽  
...  
Keyword(s):  
Disease Risk ◽  
Association Studies ◽  
R Package ◽  
Supplementary Information ◽  
External Information ◽  
Genome Wide Association Studies ◽  
Human Brain Tissue ◽  
Multiple Trait ◽  
Trait Locus ◽  
Regulatory Effects

AbstractMotivationMost genetic variants implicated in complex diseases by genome-wide association studies (GWAS) are non-coding, making it challenging to understand the causative genes involved in disease. Integrating external information such as quantitative trait locus (QTL) mapping of molecular traits (e.g., expression, methylation) is a powerful approach to identify the subset of GWAS signals explained by regulatory effects. In particular, expression QTLs (eQTLs) help pinpoint the responsible gene among the GWAS regions that harbor many genes, while methylation QTLs (mQTLs) help identify the epigenetic mechanisms that impact gene expression which in turn affect disease risk. In this work we propose multiple-trait-coloc (moloc), a Bayesian statistical framework that integrates GWAS summary data with multiple molecular QTL data to identify regulatory effects at GWAS risk loci.ResultsWe applied moloc to schizophrenia (SCZ) and eQTL/mQTL data derived from human brain tissue and identified 52 candidate genes that influence SCZ through methylation. Our method can be applied to any GWAS and relevant functional data to help prioritize disease associated genes.Availabilitymoloc is available for download as an R package (https://github.com/clagiamba/moloc). We also developed a web site to visualize the biological findings (icahn.mssm.edu/moloc). The browser allows searches by gene, methylation probe, and scenario of [email protected] informationSupplementary data are available at Bioinformatics online.

scholarly journals Variably methylated regions in the newborn epigenome: environmental, genetic and combined influences

2018 ◽  
Author(s):  
Darina Czamara ◽  
Gökçen Eraslan ◽  
Jari Lahti ◽  
Christian M. Page ◽  
Marius Lahti-Pulkkinen ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Environmental Factors ◽  
Genetic Variants ◽  
Disease Risk ◽  
Association Studies ◽  
Information Criterion ◽  
Genome Wide Association Studies ◽  
Complex Disorders ◽  
Genetic And Environmental Factors ◽  
Genomic Regions

AbstractBackgroundEpigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. We examined the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs), defined as consecutive CpGs showing the highest variability of DNAm in 4 independent cohorts (PREDO, DCHS, UCI, MoBa, N=2,934).ResultsWe used Akaike’s information criterion to test which factors best explained variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E) including maternal demographic, psychosocial and metabolism related phenotypes, genotypes in cis (G), or their additive (G+E) or interaction (GxE) effects. G+E and GxE models consistently best explained variability in DNAm of VMRs across the cohorts, with G explaining the remaining sites best. VMRs best explained by G, GxE or G+E, as well as their associated functional genetic variants (predicted using deep learning algorithms), were located in distinct genomic regions, with different enrichments for transcription and enhancer marks. Genetic variants of not only G and G+E models, but also of variants in GxE models were significantly enriched in genome wide association studies (GWAS) for complex disorders.ConclusionGenetic and environmental factors in combination best explain DNAm at VMRs. The CpGs best explained by G, G+E or GxE are functionally distinct. The enrichment of GxE variants in GWAS for complex disorders supports their importance for disease risk.

scholarly journals Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Daniel L. McCartney ◽  
Josine L. Min ◽  
Rebecca C. Richmond ◽  
Ake T. Lu ◽  
Maria K. Sobczyk ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Biological Aging ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Biomarkers Of Aging ◽  
Genome Wide ◽  
Shared Genetic

Abstract Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

scholarly journals Comparison of DNA Methylation Profiles of Hemostatic Genes between Liver Tissue and Peripheral Blood within Individuals

2020 ◽  
Author(s):  
Annelie Angerfors ◽  
Martina Olsson Lindvall ◽  
Björn Andersson ◽  
Staffan Nilsson ◽  
Marcela Davila Lopez ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Peripheral Blood ◽  
Liver Tissue ◽  
Association Studies ◽  
Epidemiological Studies ◽  
Methylation Pattern ◽  
Cpg Dinucleotides ◽  
Phenotypic Differences ◽  
Targeted Bisulfite Sequencing ◽  
Hemostatic Genes

AbstractDNA methylation has become increasingly recognized in the etiology of complex diseases, including thrombotic disorders. Blood is often collected in epidemiological studies for genotyping and has recently also been used to examine DNA methylation in epigenome-wide association studies. DNA methylation patterns are often tissue-specific, thus, peripheral blood may not accurately reflect the methylation pattern in the tissue of relevance. Here, we collected paired liver and blood samples concurrently from 27 individuals undergoing liver surgery. We performed targeted bisulfite sequencing for a set of 35 hemostatic genes primarily expressed in liver to analyze DNA methylation levels of >10,000 cytosine-phosphate-guanine (CpG) dinucleotides. We evaluated whether DNA methylation in blood could serve as a proxy for DNA methylation in liver at individual CpGs. Approximately 30% of CpGs were nonvariable and were predominantly hypo- (<25%) or hypermethylated (>70%) in both tissues. While blood can serve as a proxy for liver at these CpGs, the low variability renders these unlikely to explain phenotypic differences. We therefore focused on CpG sites with variable methylation levels in liver. The level of blood–liver tissue correlation varied widely across these variable CpGs; moderate correlations (0.5 ≤ r < 0.75) were detected for 6% and strong correlations (r ≥ 0.75) for a further 4%. Our findings indicate that it is essential to study the concordance of DNA methylation between blood and liver at individual CpGs. This paired blood–liver dataset is intended as a resource to aid interpretation of blood-based DNA methylation results.

scholarly journals Genetics and Epigenetics in Asthma

2021 ◽  
Vol 22 (5) ◽  
pp. 2412
Author(s):  
Polyxeni Ntontsi ◽  
Andreas Photiades ◽  
Eleftherios Zervas ◽  
Georgina Xanthou ◽  
Konstantinos Samitas
Keyword(s):  
Dna Methylation ◽  
Association Studies ◽  
Airway Remodeling ◽  
Methylation Pattern ◽  
Atopic Asthma ◽  
Genome Wide Association Studies ◽  
Childhood Onset ◽  
Gene Markers ◽  
Asthmatic Patients ◽  
Asthma Susceptibility

Asthma is one of the most common respiratory disease that affects both children and adults worldwide, with diverse phenotypes and underlying pathogenetic mechanisms poorly understood. As technology in genome sequencing progressed, scientific efforts were made to explain and predict asthma’s complexity and heterogeneity, and genome-wide association studies (GWAS) quickly became the preferred study method. Several gene markers and loci associated with asthma susceptibility, atopic and childhood-onset asthma were identified during the last few decades. Markers near the ORMDL3/GSDMB genes were associated with childhood-onset asthma, interleukin (IL)33 and IL1RL1 SNPs were associated with atopic asthma, and the Thymic Stromal Lymphopoietin (TSLP) gene was identified as protective against the risk to TH2-asthma. The latest efforts and advances in identifying and decoding asthma susceptibility are focused on epigenetics, heritable characteristics that affect gene expression without altering DNA sequence, with DNA methylation being the most described mechanism. Other less studied epigenetic mechanisms include histone modifications and alterations of miR expression. Recent findings suggest that the DNA methylation pattern is tissue and cell-specific. Several studies attempt to describe DNA methylation of different types of cells and tissues of asthmatic patients that regulate airway remodeling, phagocytosis, and other lung functions in asthma. In this review, we attempt to briefly present the latest advancements in the field of genetics and mainly epigenetics concerning asthma susceptibility.

scholarly journals Children’s Greenness Exposure and IQ-Associated DNA Methylation: A Prospective Cohort Study

2021 ◽  
Vol 18 (14) ◽  
pp. 7429
Author(s):  
Kyung-Shin Lee ◽  
Yoon-Jung Choi ◽  
Jin-Woo Cho ◽  
Sung-Ji Moon ◽  
Youn-Hee Lim ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Cohort Study ◽  
Literature Review ◽  
Cognitive Ability ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Association Studies ◽  
The Body ◽  
Genome Wide Association Studies ◽  
Regulatory Pathways

Epigenetics is known to be involved in regulatory pathways through which greenness exposure influences child development and health. We aimed to investigate the associations between residential surrounding greenness and DNA methylation changes in children, and further assessed the association between DNA methylation and children’s intelligence quotient (IQ) in a prospective cohort study. We identified cytosine-guanine dinucleotide sites (CpGs) associated with cognitive abilities from epigenome- and genome-wide association studies through a systematic literature review for candidate gene analysis. We estimated the residential surrounding greenness at age 2 using a geographic information system. DNA methylation was analyzed from whole blood using the HumanMethylationEPIC array in 59 children at age 2. We analyzed the association between greenness exposure and DNA methylation at age 2 at the selected CpGs using multivariable linear regression. We further investigated the relationship between DNA methylation and children’s IQ. We identified 8743 CpGs associated with cognitive ability based on the literature review. Among these CpGs, we found that 25 CpGs were significantly associated with greenness exposure at age 2, including cg26269038 (Bonferroni-corrected p ≤ 0.05) located in the body of SLC6A3, which encodes a dopamine transporter. DNA methylation at cg26269038 at age 2 was significantly associated with children’s performance IQ at age 6. Exposure to surrounding greenness was associated with cognitive ability-related DNA methylation changes, which was also associated with children’s IQ. Further studies are warranted to clarify the epigenetic pathways linking greenness exposure and neurocognitive function.

Abstract 288: Novel Mechanisms of Non-coding Genomic Regulation Identified in Cardiac Disease-in-a-dish Models

2016 ◽  
Vol 119 (suppl_1) ◽  
Author(s):  
Aditya Kumar ◽  
Stephanie Thomas ◽  
Kirsten Wong ◽  
Kevin Tenerelli ◽  
Valentina Lo Sardo ◽  
...  
Keyword(s):  
Heart Attack ◽  
Connexin 43 ◽  
Disease Risk ◽  
Association Studies ◽  
Correlation Coefficients ◽  
Induced Pluripotent Stem Cell ◽  
Genome Wide Association Studies ◽  
Isogenic Line ◽  
Nucleotide Polymorphisms ◽  
Increased Risk

Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) at gene loci that affect cardiovascular function, and while mechanisms in protein-coding loci are obvious, those in non-coding loci are difficult to determine. 9p21 is a recently identified locus associated with increased risk of coronary artery disease (CAD) and myocardial infarction. Associations have implicated SNPs in altering smooth muscle and endothelial cell properties but have not identified adverse effects in cardiomyocytes (CMs) despite enhanced disease risk. Using induced pluripotent stem cell-derived CMs from patients that are homozygous risk/risk (R/R) and non-risk/non-risk (N/N) for 9p21 SNPs and either CAD positive or negative, we assessed CM function when cultured on hydrogels capable of mimicking the fibrotic stiffening associated with disease post-heart attack, i.e. “heart attack-in-a-dish” stiffening from 11 kiloPascals (kPa) to 50 kPa. While all CMs independent of genotype and disease beat synchronously on soft matrices, R/R CMs cultured on dynamically stiffened hydrogels exhibited asynchronous contractions and had significantly lower correlation coefficients versus N/N CMs in the same conditions. Dynamic stiffening reduced connexin 43 expression and gap junction assembly in R/R CMs but not N/N CMs. To eliminate patient-to-patient variability, we created an isogenic line by deleting the 9p21 gene locus from a R/R patient using TALEN-mediated gene editing, i.e. R/R KO. Deletion of the 9p21 locus restored synchronous contractility and organized connexin 43 junctions. As a non-coding locus, 9p21 appears to repress connexin transcription, leading to the phenotypes we observe, but only when the niche is stiffened as in disease. These data are the first to demonstrate that disease-specific niche remodeling, e.g. a “heart attack-in-a-dish” model, can differentially affect CM function depending on SNPs within a non-coding locus.

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