Exposure to air pollution is associated with DNA methylation changes in sperm.

Exposure to air pollutants has been associated with adverse health outcomes in adults and children who were prenatally exposed. In addition to reducing exposure to air pollutants, it is important to identify their biologic targets in order to mitigate the health consequences of exposure. One molecular change associated with prenatal exposure to air pollutants is DNA methylation (DNAm), which has been associated with changes in placenta and cord blood tissues at birth. However, little is known about how air pollution exposure impacts the sperm epigenome, which could provide important insights into the mechanism of transmission to offspring. In the present study, we explored whether exposure to particulate matter less than 2.5 microns in diameter, particulate matter less than 10 microns in diameter, nitrogen dioxide (NO2), or ozone (O3) was associated with DNAm in sperm contributed by participants in the Early Autism Risk Longitudinal Investigation prospective pregnancy cohort. Air pollution exposure measurements were calculated as the average exposure for each pollutant measured within 4 weeks prior to the date of sample collection. Using array-based genome-scale methylation analyses, we identified 80, 96, 35, and 67 differentially methylated regions (DMRs) significantly associated with particulate matter less than 2.5 microns in diameter, particulate matter less than 10 microns in diameter, NO2, and O3, respectively. While no DMRs were associated with exposure to all four pollutants, we found that genes overlapping exposure-related DMRs had a shared enrichment for gene ontology biological processes related to neurodevelopment. Together, these data provide compelling support for the hypothesis that paternal exposure to air pollution impacts DNAm in sperm, particularly in regions implicated in neurodevelopment.

Precision pharmacological reversal of strain-specific diet-induced metabolic syndrome in mice informed by epigenetic and transcriptional regulation.

Diet-related metabolic syndrome is the largest contributor to adverse health in the United States. However, the study of gene-environment interactions and their epigenomic and transcriptomic integration is complicated by the lack of environmental and genetic control in humans that is possible in mouse models. Here we exposed three mouse strains, C57BL/6J (BL6), A/J, and NOD/ShiLtJ (NOD), to a high-fat, high-carbohydrate diet, leading to varying degrees of metabolic syndrome. We then performed transcriptomic and genome-wide DNA methylation analyses for each strain and found overlapping but also highly divergent changes in gene expression and methylation upstream of the discordant metabolic phenotypes. Strain-specific pathway analysis of dietary effects revealed a dysregulation of cholesterol biosynthesis common to all three strains but distinct regulatory networks driving this dysregulation. This suggests a strategy for strain-specific targeted pharmacologic intervention of these upstream regulators informed by epigenetic and transcriptional regulation. As a pilot study, we administered the drug GW4064 to target one of these genotype-dependent networks, the farnesoid X receptor pathway, and found that GW4064 exerts strain-specific protection against dietary effects in BL6, as predicted by our transcriptomic analysis. Furthermore, GW4064 treatment induced inflammatory-related gene expression changes in NOD, indicating a strain-specific effect in its associated toxicities as well as its therapeutic efficacy. This pilot study demonstrates the potential efficacy of precision therapeutics for genotype-informed dietary metabolic intervention and a mouse platform for guiding this approach.

Cytoskeletal activation of NHE1 regulates cell volume and DNA methylation.

The regulation of mammalian cell volume is crucial for maintaining key cellular processes. Cells can rapidly respond to osmotic and hydrostatic pressure imbalances during environmental challenges, generating fluxes of water and ions that alter volume within minutes. While the role of ion pump and leak in cell volume regulation has been well-established, the role of the actomyosin cytoskeleton and its substantial interplay with ion transporters are still unclear. In this work, we discover a system of cell volume regulation controlled by cytoskeletal activation of ion transporters. Under hypotonic shock, NIH-3T3 and MCF-10A display a 20% secondary volume increase (SVI) following the initial regulatory volume decrease. We show that SVI is initiated by Ca 2+ influx through stretch activated channel Piezo1 and subsequent actomyosin remodeling. Rather than contracting cells, actomyosin triggers cell swelling by activating Na + -H + exchanger 1 (NHE1) through their co-binding partner ezrin. Cytoskeletal activation of NHE1 can be similarly triggered by mechanical stretch and attenuated by soft substrates. This mechanism is absent in certain cancer cell lines such as HT1080 and MDA-MB-231, where volume regulation is dominated by intrinsic response of ion transporters. Moreover, cytoskeletal activation of NHE1 during SVI induces nuclear deformation, leading to DNA demethylation and a significant, immediate transcriptomic response in 3T3 cells, a phenomenon that is absent in HT1080 cells. Overall, our findings reveal the central role of Ca 2+ and actomyosin-mediated mechanosensation in the regulation of ion transport, cell volume, DNA methylation, and transcriptomics.

Refining risk estimates for lead in drinking water based on the impact of genetics and diet on blood lead levels using the Collaborative Cross mouse population.

Blood lead (Pb) level (BLL) is a commonly used biomarker to evaluate associations with health effects. However, interventions to reduce the adverse effects of Pb require relating BLL to external exposure. Moreover, risk mitigation actions need to ensure protection of more susceptible individuals with a greater tendency to accumulate Pb. Because little data is available to quantify inter-individual variability in biokinetics of Pb, we investigated the influence of genetics and diet on BLL in the genetically diverse Collaborative Cross (CC) mouse population. Adult female mice from 49 CC strains received either a standard mouse chow or a chow mimicking the American diet while being provided water ad libitum with 1000 ppm Pb for 4 weeks. In both arms of the study, inter-strain variability was observed; however, in American diet-fed animals, the BLL was greater and more variable. Importantly, the degree of variation in BLL among strains on the American diet was greater (2.3) than the default variability estimate (1.6) used in setting the regulatory standards. Genetic analysis identified suggestive diet-associated haplotypes that were associated with variation in BLL, largely contributed by the PWK/PhJ strain. This study quantified the variation in BLL that is due to genetic background, diet, and their interactions, and observed that it may be greater than that assumed for current regulatory standards for Pb in drinking water. Moreover, this work highlights the need of characterizing inter-individual variation in BLL to ensure adequate public health interventions aimed at reducing human health risks from Pb.

Precision pharmacological reversal of genotype-specific diet-induced metabolic syndrome in mice informed by transcriptional regulation.

Diet-related metabolic syndrome is the largest contributor to adverse health in the United States. However, the study of gene-environment interactions and their epigenomic and transcriptomic integration is complicated by the lack of environmental and genetic control in humans that is possible in mouse models. Here we exposed three mouse strains, C57BL/6J (BL6), A/J, and NOD/ShiLtJ (NOD), to a high-fat high-carbohydrate diet, leading to varying degrees of metabolic syndrome. We then performed transcriptomic and genomic DNA methylation analyses and found overlapping but also highly divergent changes in gene expression and methylation upstream of the discordant metabolic phenotypes. Strain-specific pathway analysis of dietary effects reveals a dysregulation of cholesterol biosynthesis common to all three strains but distinct regulatory networks driving this dysregulation. This suggests a strategy for strain-specific targeted pharmacologic intervention of these upstream regulators informed by transcriptional regulation. As a pilot study, we administered the drug GW4064 to target one of these genotype-dependent networks, the Farnesoid X receptor pathway, and found that GW4064 exerts genotype-specific protection against dietary effects in BL6, as predicted by our transcriptomic analysis, as well as increased inflammatory-related gene expression changes in NOD. This pilot study demonstrates the potential efficacy of precision therapeutics for genotype-informed dietary metabolic intervention, and a mouse platform for guiding this approach.

Epigenetic changes in sperm are associated with paternal and child quantitative autistic traits in an autism-enriched cohort.

There is a need to consider paternal contributions to autism spectrum disorder (ASD) more strongly. Autism etiology is complex, and heritability is not explained by genetics alone. Understanding paternal gametic epigenetic contributions to autism could help fill this knowledge gap. In the present study, we explored whether paternal autistic traits, and the sperm epigenome, were associated with autistic traits in children at 36 months enrolled in the Early Autism Risk Longitudinal Investigation (EARLI) cohort. EARLI is a pregnancy cohort that recruited and enrolled pregnant women in the first half of pregnancy who already had a child with ASD. After maternal enrollment, EARLI fathers were approached and asked to provide a semen specimen. Participants were included in the present study if they had genotyping, sperm methylation data, and Social Responsiveness Scale (SRS) score data available. Using the CHARM array, we performed genome-scale methylation analyses on DNA from semen samples contributed by EARLI fathers. The SRS-a 65-item questionnaire measuring social communication deficits on a quantitative scale-was used to evaluate autistic traits in EARLI fathers (n = 45) and children (n = 31). We identified 94 significant child SRS-associated differentially methylated regions (DMRs), and 14 significant paternal SRS-associated DMRs (fwer p < 0.05). Many child SRS-associated DMRs were annotated to genes implicated in ASD and neurodevelopment. Six DMRs overlapped across the two outcomes (fwer p < 0.1), and, 16 DMRs overlapped with previous child autistic trait findings at 12 months of age (fwer p < 0.05). Child SRS-associated DMRs contained CpG sites independently found to be differentially methylated in postmortem brains of individuals with and without autism. These findings suggest paternal germline methylation is associated with autistic traits in 3-year-old offspring. These prospective results for autism-associated traits, in a cohort with a family history of ASD, highlight the potential importance of sperm epigenetic mechanisms in autism.

Comprehensive DNA Methylation Analysis Indicates That Pancreatic Intraepithelial Neoplasia Lesions Are Acinar-Derived and Epigenetically Primed for Carcinogenesis.

Pancreatic ductal adenocarcinoma (PDAC) is believed to arise from the accumulation of a series of somatic mutations and is also frequently associated with pancreatic intraepithelial neoplasia (PanIN) lesions. However, there is still debate as to whether the cell type-of-origin of PanINs and PDACs in humans is acinar or ductal. As cell type identity is maintained epigenetically, DNA methylation changes during pancreatic neoplasia can provide a compelling perspective to examine this question. Here, we performed laser-capture microdissection on surgically resected specimens from 18 patients to isolate, with high purity, DNA for whole-genome bisulfite sequencing from four relevant cell types: acini, nonneoplastic ducts, PanIN lesions, and PDAC lesions. Differentially methylated regions (DMR) were identified using two complementary analytical approaches: bsseq, which identifies any DMRs but is particularly useful for large block-like DMRs, and informME, which profiles the potential energy landscape across the genome and is particularly useful for identifying differential methylation entropy. Both global methylation profiles and block DMRs clearly implicated an acinar origin for PanINs. At the gene level, PanIN lesions exhibited an intermediate acinar-ductal phenotype resembling acinar-to-ductal metaplasia. In 97.6% of PanIN-specific DMRs, PanIN lesions had an intermediate methylation level between normal and PDAC, which suggests from an information theory perspective that PanIN lesions are epigenetically primed to progress to PDAC. Thus, epigenomic analysis complements histopathology to define molecular progression toward PDAC. The shared epigenetic lineage between PanIN and PDAC lesions could provide an opportunity for prevention by targeting aberrantly methylated progression-related genes. SIGNIFICANCE: Analysis of DNA methylation landscapes provides insights into the cell-of-origin of PanIN lesions, clarifies the role of PanIN lesions as metaplastic precursors to human PDAC, and suggests potential targets for chemoprevention.

Epigenetics as a mediator of plasticity in cancer.

The concept of an epigenetic landscape describing potential cellular fates arising from pluripotent cells, first advanced by Conrad Waddington, has evolved in light of experiments showing nondeterministic outcomes of regulatory processes and mathematical methods for quantifying stochasticity. In this Review, we discuss modern approaches to epigenetic and gene regulation landscapes and the associated ideas of entropy and attractor states, illustrating how their definitions are both more precise and relevant to understanding cancer etiology and the plasticity of cancerous states. We address the interplay between different types of regulatory landscapes and how their changes underlie cancer progression. We also consider the roles of cellular aging and intrinsic and extrinsic stimuli in modulating cellular states and how landscape alterations can be quantitatively mapped onto phenotypic outcomes and thereby used in therapy development.

DNA methylation entropy is associated with DNA sequence features and developmental epigenetic divergence.

Epigenetic information defines tissue identity and is largely inherited in development through DNA methylation. While studied mostly for mean differences, methylation also encodes stochastic change, defined as entropy in information theory. Analyzing allele-specific methylation in 49 human tissue sample datasets, we find that methylation entropy is associated with specific DNA binding motifs, regulatory DNA, and CpG density. Then applying information theory to 42 mouse embryo methylation datasets, we find that the contribution of methylation entropy to time- and tissue-specific patterns of development is comparable to the contribution of methylation mean, and methylation entropy is associated with sequence and chromatin features conserved with human. Moreover, methylation entropy is directly related to gene expression variability in development, suggesting a role for epigenetic entropy in developmental plasticity.

Effects of 6-Aminonicotinic Acid Esters on the Reprogrammed Epigenetic State of Distant Metastatic Pancreatic Carcinoma.

In the search for alternatives to 6-aminonicotinamide (6AN), a series of 6-aminonicotinic acid esters were designed and synthesized as precursors of 6-amino-NADP+, a potent inhibitor of 6-phosphogluconate dehydrogenase (6PGD). Like 6AN, some of these esters were found to reverse the loss of histone 3 lysine 9 trimethylation (H3K9me3) in patient-derived pancreatic ductal adenocarcinoma (PDAC) distant metastasis (A38-5). Among them, 1-(((cyclohexyloxy)carbonyl)oxy)ethyl 6-aminonicotinate (5i) showed more potent antiproliferative activity than 6AN. Metabolite analysis revealed that compound 5i produced a marked increase in metabolites upstream of 6PGD, indicating intracellular inhibition of 6PGD by 6-amino-NADP+ derived from compound 5i through 6-aminonicotinic acid (6ANA) via the Preiss-Handler pathway. Despite the more potent pharmacological effects shown by compound 5i in A38-5, compound 5i was found to be substantially less toxic to primary hippocampal rat neurons compared to 6AN, indicating its therapeutic potential in targeting distant metastatic cells.

Extracellular fluid viscosity enhances cell migration and cancer dissemination.

Cells respond to physical stimuli, such as stiffness1, fluid shear stress2 and hydraulic pressure3,4. Extracellular fluid viscosity is a key physical cue that varies under physiological and pathological conditions, such as cancer5. However, its influence on cancer biology and the mechanism by which cells sense and respond to changes in viscosity are unknown. Here we demonstrate that elevated viscosity counterintuitively increases the motility of various cell types on two-dimensional surfaces and in confinement, and increases cell dissemination from three-dimensional tumour spheroids. Increased mechanical loading imposed by elevated viscosity induces an actin-related protein 2/3 (ARP2/3)-complex-dependent dense actin network, which enhances Na+/H+ exchanger 1 (NHE1) polarization through its actin-binding partner ezrin. NHE1 promotes cell swelling and increased membrane tension, which, in turn, activates transient receptor potential cation vanilloid 4 (TRPV4) and mediates calcium influx, leading to increased RHOA-dependent cell contractility. The coordinated action of actin remodelling/dynamics, NHE1-mediated swelling and RHOA-based contractility facilitates enhanced motility at elevated viscosities. Breast cancer cells pre-exposed to elevated viscosity acquire TRPV4-dependent mechanical memory through transcriptional control of the Hippo pathway, leading to increased migration in zebrafish, extravasation in chick embryos and lung colonization in mice. Cumulatively, extracellular viscosity is a physical cue that regulates both short- and long-term cellular processes with pathophysiological relevance to cancer biology.

Autism-Associated DNA Methylation at Birth From Multiple Tissues Is Enriched for Autism Genes in the Early Autism Risk Longitudinal Investigation.

Background: Pregnancy measures of DNA methylation, an epigenetic mark, may be associated with autism spectrum disorder (ASD) development in children. Few ASD studies have considered prospective designs with DNA methylation measured in multiple tissues and tested overlap with ASD genetic risk loci. Objectives: To estimate associations between DNA methylation in maternal blood, cord blood, and placenta and later diagnosis of ASD, and to evaluate enrichment of ASD-associated DNA methylation for known ASD-associated genes. Methods: In the Early Autism Risk Longitudinal Investigation (EARLI), an ASD-enriched risk birth cohort, genome-scale maternal blood (early n = 140 and late n = 75 pregnancy), infant cord blood (n = 133), and placenta (maternal n = 106 and fetal n = 107 compartments) DNA methylation was assessed on the Illumina 450k HumanMethylation array and compared to ASD diagnosis at 36 months of age. Differences in site-specific and global methylation were tested with ASD, as well as enrichment of single site associations for ASD risk genes (n = 881) from the Simons Foundation Autism Research Initiative (SFARI) database. Results: No individual DNA methylation site was associated with ASD at genome-wide significance, however, individual DNA methylation sites nominally associated with ASD (P < 0.05) in each tissue were highly enriched for SFARI genes (cord blood P = 7.9 × 10-29, maternal blood early pregnancy P = 6.1 × 10-27, maternal blood late pregnancy P = 2.8 × 10-16, maternal placenta P = 5.6 × 10-15, fetal placenta P = 1.3 × 10-20). DNA methylation sites nominally associated with ASD across all five tissues overlapped at 144 (29.5%) SFARI genes. Conclusion: DNA methylation sites nominally associated with later ASD diagnosis in multiple tissues were enriched for ASD risk genes. Our multi-tissue study demonstrates the utility of examining DNA methylation prior to ASD diagnosis.

Estimating DNA methylation potential energy landscapes from nanopore sequencing data.

High-throughput third-generation nanopore sequencing devices have enormous potential for simultaneously observing epigenetic modifications in human cells over large regions of the genome. However, signals generated by these devices are subject to considerable noise that can lead to unsatisfactory detection performance and hamper downstream analysis. Here we develop a statistical method, CpelNano, for the quantification and analysis of 5mC methylation landscapes using nanopore data. CpelNano takes into account nanopore noise by means of a hidden Markov model (HMM) in which the true but unknown ("hidden") methylation state is modeled through an Ising probability distribution that is consistent with methylation means and pairwise correlations, whereas nanopore current signals constitute the observed state. It then estimates the associated methylation potential energy function by employing the expectation-maximization (EM) algorithm and performs differential methylation analysis via permutation-based hypothesis testing. Using simulations and analysis of published data obtained from three human cell lines (GM12878, MCF-10A, and MDA-MB-231), we show that CpelNano can faithfully estimate DNA methylation potential energy landscapes, substantially improving current methods and leading to a powerful tool for the modeling and analysis of epigenetic landscapes using nanopore sequencing data.

Statistical mechanics meets single-cell biology.

Single-cell omics is transforming our understanding of cell biology and disease, yet the systems-level analysis and interpretation of single-cell data faces many challenges. In this Perspective, we describe the impact that fundamental concepts from statistical mechanics, notably entropy, stochastic processes and critical phenomena, are having on single-cell data analysis. We further advocate the need for more bottom-up modelling of single-cell data and to embrace a statistical mechanics analysis paradigm to help attain a deeper understanding of single-cell systems biology.

Converging genetic and epigenetic drivers of paediatric acute lymphoblastic leukaemia identified by an information-theoretic analysis.

In cancer, linking epigenetic alterations to drivers of transformation has been difficult, in part because DNA methylation analyses must capture epigenetic variability, which is central to tumour heterogeneity and tumour plasticity. Here, by conducting a comprehensive analysis, based on information theory, of differences in methylation stochasticity in samples from patients with paediatric acute lymphoblastic leukaemia (ALL), we show that ALL epigenomes are stochastic and marked by increased methylation entropy at specific regulatory regions and genes. By integrating DNA methylation and single-cell gene-expression data, we arrived at a relationship between methylation entropy and gene-expression variability, and found that epigenetic changes in ALL converge on a shared set of genes that overlap with genetic drivers involved in chromosomal translocations across the disease spectrum. Our findings suggest that an epigenetically driven gene-regulation network, with UHRF1 (ubiquitin-like with PHD and RING finger domains 1) as a central node, links genetic drivers and epigenetic mediators in ALL.

Human brain region-specific variably methylated regions are enriched for heritability of distinct neuropsychiatric traits.

BACKGROUND: DNA methylation dynamics in the brain are associated with normal development and neuropsychiatric disease and differ across functionally distinct brain regions. Previous studies of genome-wide methylation differences among human brain regions focus on limited numbers of individuals and one to two brain regions. RESULTS: Using GTEx samples, we generate a resource of DNA methylation in purified neuronal nuclei from 8 brain regions as well as lung and thyroid tissues from 12 to 23 donors. We identify differentially methylated regions between brain regions among neuronal nuclei in both CpG (181,146) and non-CpG (264,868) contexts, few of which were unique to a single pairwise comparison. This significantly expands the knowledge of differential methylation across the brain by 10-fold. In addition, we present the first differential methylation analysis among neuronal nuclei from basal ganglia tissues and identify unique CpG differentially methylated regions, many associated with ion transport. We also identify 81,130 regions of variably CpG methylated regions, i.e., variable methylation among individuals in the same brain region, which are enriched in regulatory regions and in CpG differentially methylated regions. Many variably methylated regions are unique to a specific brain region, with only 202 common across all brain regions, as well as lung and thyroid. Variably methylated regions identified in the amygdala, anterior cingulate cortex, and hippocampus are enriched for heritability of schizophrenia. CONCLUSIONS: These data suggest that epigenetic variation in these particular human brain regions could be associated with the risk for this neuropsychiatric disorder.

A Dysregulated DNA Methylation Landscape Linked to Gene Expression in MLL-Rearranged AML.

Translocations of the KMT2A (MLL) gene define a biologically distinct and clinically aggressive subtype of acute myeloid leukaemia (AML), marked by a characteristic gene expression profile and few cooperating mutations. Although dysregulation of the epigenetic landscape in this leukaemia is particularly interesting given the low mutation frequency, its comprehensive analysis using whole genome bisulphite sequencing (WGBS) has not been previously performed. Here we investigated epigenetic dysregulation in nine MLL-rearranged (MLL-r) AML samples by comparing them to six normal myeloid controls, using a computational method that encapsulates mean DNA methylation measurements along with analyses of methylation stochasticity. We discovered a dramatically altered epigenetic profile in MLL-r AML, associated with genome-wide hypomethylation and a markedly increased DNA methylation entropy reflecting an increasingly disordered epigenome. Methylation discordance mapped to key genes and regulatory elements that included bivalent promoters and active enhancers. Genes associated with significant changes in methylation stochasticity recapitulated known MLL-r AML expression signatures, suggesting a role for the altered epigenetic landscape in the transcriptional programme initiated by MLL translocations. Accordingly, we established statistically significant associations between discordances in methylation stochasticity and gene expression in MLL-r AML, thus providing a link between the altered epigenetic landscape and the phenotype.

Independent Methylome-Wide Association Studies of Schizophrenia Detect Consistent Case-Control Differences.

Methylome-wide association studies (MWASs) are promising complements to sequence variation studies. We used existing sequencing-based methylation data, which assayed the majority of all 28 million CpGs in the human genome, to perform an MWAS for schizophrenia in blood, while controlling for cell-type heterogeneity with a recently generated platform-specific reference panel. Next, we compared the MWAS results with findings from 3 existing large-scale array-based schizophrenia methylation studies in blood that assayed up to ~450 000 CpGs. Our MWAS identified 22 highly significant loci (P < 5 × 10-8) and 852 suggestively significant loci (P < 1 × 10-5). The top finding (P = 5.62 × 10-11, q = 0.001) was located in MFN2, which encodes mitofusin-2 that regulates Ca2+ transfer from the endoplasmic reticulum to mitochondria in cooperation with DISC1. The second-most significant site (P = 1.38 × 10-9, q = 0.013) was located in ALDH1A2, which encodes an enzyme for astrocyte-derived retinoic acid-a key neuronal morphogen with relevance for schizophrenia. Although the most significant MWAS findings were not assayed on the arrays, we observed significant enrichment of overlapping findings with 2 of the 3 array datasets (P = 0.0315, 0.0045, 0.1946). Overrepresentation analysis of Gene Ontology terms for the genes in the significant overlaps suggested high similarity in the biological functions detected by the different datasets. Top terms were related to immune and/or stress responses, cell adhesion and motility, and a broad range of processes essential for neurodevelopment.

Analyzing whole genome bisulfite sequencing data from highly divergent genotypes.

In the study of DNA methylation, genetic variation between species, strains or individuals can result in CpG sites that are exclusive to a subset of samples, and insertions and deletions can rearrange the spatial distribution of CpGs. How to account for this variation in an analysis of the interplay between sequence variation and DNA methylation is not well understood, especially when the number of CpG differences between samples is large. Here, we use whole-genome bisulfite sequencing data on two highly divergent mouse strains to study this problem. We show that alignment to personal genomes is necessary for valid methylation quantification. We introduce a method for including strain-specific CpGs in differential analysis, and show that this increases power. We apply our method to a human normal-cancer dataset, and show this improves accuracy and power, illustrating the broad applicability of our approach. Our method uses smoothing to impute methylation levels at strain-specific sites, thereby allowing strain-specific CpGs to contribute to the analysis, while accounting for differences in the spatial occurrences of CpGs. Our results have implications for joint analysis of genetic variation and DNA methylation using bisulfite-converted DNA, and unlocks the use of personal genomes for addressing this question.

Blood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease.

BACKGROUND: DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts. METHODS: Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts. RESULTS: Among 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts. CONCLUSION: Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.