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1.
Nucleic Acids Res ; 47(19): e117, 2019 Nov 04.
Artigo em Inglês | MEDLINE | ID: mdl-31392989

RESUMO

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.

2.
Circulation ; 140(8): 645-657, 2019 Aug 20.
Artigo em Inglês | MEDLINE | ID: mdl-31424985

RESUMO

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.

3.
Schizophr Bull ; 2019 Jun 05.
Artigo em Inglês | MEDLINE | ID: mdl-31165892

RESUMO

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.

4.
BMC Bioinformatics ; 20(1): 175, 2019 Apr 08.
Artigo em Inglês | MEDLINE | ID: mdl-30961526

RESUMO

BACKGROUND: Establishment and maintenance of DNA methylation throughout the genome is an important epigenetic mechanism that regulates gene expression whose disruption has been implicated in human diseases like cancer. It is therefore crucial to know which genes, or other genomic features of interest, exhibit significant discordance in DNA methylation between two phenotypes. We have previously proposed an approach for ranking genes based on methylation discordance within their promoter regions, determined by centering a window of fixed size at their transcription start sites. However, we cannot use this method to identify statistically significant genomic features and handle features of variable length and with missing data. RESULTS: We present a new approach for computing the statistical significance of methylation discordance within genomic features of interest in single and multiple test/reference studies. We base the proposed method on a well-articulated hypothesis testing problem that produces p- and q-values for each genomic feature, which we then use to identify and rank features based on the statistical significance of their epigenetic dysregulation. We employ the information-theoretic concept of mutual information to derive a novel test statistic, which we can evaluate by computing Jensen-Shannon distances between the probability distributions of methylation in a test and a reference sample. We design the proposed methodology to simultaneously handle biological, statistical, and technical variability in the data, as well as variable feature lengths and missing data, thus enabling its wide-spread use on any list of genomic features. This is accomplished by estimating, from reference data, the null distribution of the test statistic as a function of feature length using generalized additive regression models. Differential assessment, using normal/cancer data from healthy fetal tissue and pediatric high-grade glioma patients, illustrates the potential of our approach to greatly facilitate the exploratory phases of clinically and biologically relevant methylation studies. CONCLUSIONS: The proposed approach provides the first computational tool for statistically testing and ranking genomic features of interest based on observed DNA methylation discordance in comparative studies that accounts, in a rigorous manner, for biological, statistical, and technical variability in methylation data, as well as for variability in feature length and for missing data.


Assuntos
Epigênese Genética , Epigenômica , Genômica , Metilação de DNA , Genoma Humano , Humanos , Neoplasias/diagnóstico , Neoplasias/genética , Probabilidade
5.
Environ Int ; 126: 363-376, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-30826615

RESUMO

BACKGROUND: Prenatal air pollution exposure has been linked to many adverse health conditions in the offspring. However, little is known about the mechanisms underlying these associations. Epigenetics may be one plausible biologic link. Here, we sought to identify site-specific and global DNA methylation (DNAm) changes, in developmentally relevant tissues, associated with prenatal exposure to nitrogen dioxide (NO2) and ozone (O3). Additionally, we assessed whether sex-specific changes in methylation exist and whether DNAm changes are consistently observed across tissues. METHODS: Genome-scale DNAm measurements were obtained using the Infinium HumanMethylation450k platform for 133 placenta and 175 cord blood specimens from Early Autism Risk Longitudinal Investigation (EARLI) neonates. Ambient NO2 and O3 exposure levels were based on prenatal address locations of EARLI mothers and the Environmental Protection Agency's AirNOW monitoring network using inverse distance weighting. We computed sample-level aggregate methylation measures for each of 5 types of genomic regions including genome-wide, open sea, shelf, shore, and island regions. Linear regression was performed for each genomic region; per-sample aggregate methylation measures were modeled as a function of quantitative exposure level with covariate adjustment. In addition, bumphunting was performed to identify differentially methylated regions (DMRs) associated with prenatal O3 and NO2 exposures in each tissue and by sex, with adjustment for technical and biological sources of variation. RESULTS: We identified global and locus-specific changes in DNA methylation related to prenatal exposure to NO2 and O3 in 2 developmentally relevant tissues. Neonates with increased prenatal O3 exposure had lower aggregate levels of DNAm at CpGs located in open sea and shelf regions of the genome. We identified 6 DMRs associated with prenatal NO2 exposure, including 3 sex-specific. An additional 3 sex-specific DMRs were associated with prenatal O3 exposure levels. DMRs initially detected in cord blood samples (n = 4) showed consistent exposure-related changes in DNAm in placenta. However, the DMRs initially detected in placenta (n = 5) did not show DNAm differences in cord blood and, thus, they appear to be tissue-specific. CONCLUSIONS: We observed global, locus, and sex-specific methylation changes associated with prenatal NO2 and O3 exposures. Our findings support DNAm is a biologic target of prenatal air pollutant exposures and highlight epigenetic involvement in sex-specific differential susceptibility to environmental exposure effects in 2 developmentally relevant tissues.


Assuntos
Poluição do Ar/análise , Metilação de DNA , Troca Materno-Fetal , Poluentes Atmosféricos/análise , Saúde da Criança , Epigenômica , Feminino , Humanos , Saúde do Lactente , Recém-Nascido , Masculino , Exposição Materna , Dióxido de Nitrogênio/análise , Ozônio/análise , Placenta/química , Gravidez
6.
Nat Neurosci ; 22(2): 307-316, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30643296

RESUMO

Epigenetic modifications confer stable transcriptional patterns in the brain, and both normal and abnormal brain function involve specialized brain regions. We examined DNA methylation by whole-genome bisulfite sequencing in neuronal and non-neuronal populations from four brain regions (anterior cingulate gyrus, hippocampus, prefrontal cortex, and nucleus accumbens) as well as chromatin accessibility in the latter two. We find pronounced differences in both CpG and non-CpG methylation (CG-DMRs and CH-DMRs) only in neuronal cells across brain regions. Neuronal CH-DMRs were highly associated with differential gene expression, whereas CG-DMRs were consistent with chromatin accessibility and enriched for regulatory regions. These CG-DMRs comprise ~12 Mb of the genome that is highly enriched for genomic regions associated with heritability of neuropsychiatric traits including addictive behavior, schizophrenia, and neuroticism, thus suggesting a mechanistic link between pathology and differential neuron-specific epigenetic regulation in distinct brain regions.


Assuntos
Comportamento Aditivo/metabolismo , Encéfalo/metabolismo , Cromatina/metabolismo , Metilação de DNA , Neurônios/metabolismo , Neuroticismo/fisiologia , Esquizofrenia/metabolismo , Comportamento Aditivo/genética , Ilhas de CpG , Epigênese Genética , Genoma , Humanos , Esquizofrenia/genética
7.
Mol Cell ; 72(1): 60-70.e3, 2018 Oct 04.
Artigo em Inglês | MEDLINE | ID: mdl-30244832

RESUMO

Epigenetic control of regulatory networks is only partially understood. Expression of Insulin-like growth factor-II (IGF2) is controlled by genomic imprinting, mediated by silencing of the maternal allele. Loss of imprinting of IGF2 (LOI) is linked to intestinal and colorectal cancers, causally in murine models and epidemiologically in humans. However, the molecular underpinnings of the LOI phenotype are not clear. Surprisingly, in LOI cells, we find a reversal of the relative activities of two canonical signaling pathways triggered by IGF2, causing further rebalancing between pro- and anti-apoptotic signaling. A predictive mathematical model shows that this network rebalancing quantitatively accounts for the effect of receptor tyrosine kinase inhibition in both WT and LOI cells. This mechanism also quantitatively explains both the stable LOI phenotype and the therapeutic window for selective killing of LOI cells, and thus prevention of epigenetically controlled cancers. These findings suggest a framework for understanding epigenetically modified cell signaling.

8.
Mol Autism ; 9: 40, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29988321

RESUMO

Background: Several reports have suggested a role for epigenetic mechanisms in ASD etiology. Epigenome-wide association studies (EWAS) in autism spectrum disorder (ASD) may shed light on particular biological mechanisms. However, studies of ASD cases versus controls have been limited by post-mortem timing and severely small sample sizes. Reports from in-life sampling of blood or saliva have also been very limited in sample size and/or genomic coverage. We present the largest case-control EWAS for ASD to date, combining data from population-based case-control and case-sibling pair studies. Methods: DNA from 968 blood samples from children in the Study to Explore Early Development (SEED 1) was used to generate epigenome-wide array DNA methylation (DNAm) data at 485,512 CpG sites for 453 cases and 515 controls, using the Illumina 450K Beadchip. The Simons Simplex Collection (SSC) provided 450K array DNAm data on an additional 343 cases and their unaffected siblings. We performed EWAS meta-analysis across results from the two data sets, with adjustment for sex and surrogate variables that reflect major sources of biological variation and technical confounding such as cell type, batch, and ancestry. We compared top EWAS results to those from a previous brain-based analysis. We also tested for enrichment of ASD EWAS CpGs for being targets of meQTL associations using available SNP genotype data in the SEED sample. Findings: In this meta-analysis of blood-based DNA from 796 cases and 858 controls, no single CpG met a Bonferroni discovery threshold of p < 1.12 × 10- 7. Seven CpGs showed differences at p < 1 × 10- 5 and 48 at 1 × 10- 4. Of the top 7, 5 showed brain-based ASD associations as well, often with larger effect sizes, and the top 48 overall showed modest concordance (r = 0.31) in direction of effect with cerebellum samples. Finally, we observed suggestive evidence for enrichment of CpG sites controlled by SNPs (meQTL targets) among the EWAS CpG hits, which was consistent across EWAS and meQTL discovery p value thresholds. Conclusions: No single CpG site showed a large enough DNAm difference between cases and controls to achieve epigenome-wide significance in this sample size. However, our results suggest the potential to observe disease associations from blood-based samples. Among the seven sites achieving suggestive statistical significance, we observed consistent, and stronger, effects at the same sites among brain samples. Discovery-oriented EWAS for ASD using blood samples will likely need even larger samples and unified genetic data to further understand DNAm differences in ASD.


Assuntos
Transtorno do Espectro Autista/genética , Metilação de DNA , Transtorno do Espectro Autista/sangue , Estudos de Casos e Controles , Pré-Escolar , Ilhas de CpG , Epigênese Genética , Feminino , Estudo de Associação Genômica Ampla , Humanos , Masculino
9.
Nat Commun ; 9(1): 2397, 2018 06 19.
Artigo em Inglês | MEDLINE | ID: mdl-29921915

RESUMO

The human leukocyte antigen (HLA) haplotype DRB1*15:01 is the major risk factor for multiple sclerosis (MS). Here, we find that DRB1*15:01 is hypomethylated and predominantly expressed in monocytes among carriers of DRB1*15:01. A differentially methylated region (DMR) encompassing HLA-DRB1 exon 2 is particularly affected and displays methylation-sensitive regulatory properties in vitro. Causal inference and Mendelian randomization provide evidence that HLA variants mediate risk for MS via changes in the HLA-DRB1 DMR that modify HLA-DRB1 expression. Meta-analysis of 14,259 cases and 171,347 controls confirms that these variants confer risk from DRB1*15:01 and also identifies a protective variant (rs9267649, p < 3.32 × 10-8, odds ratio = 0.86) after conditioning for all MS-associated variants in the region. rs9267649 is associated with increased DNA methylation at the HLA-DRB1 DMR and reduced expression of HLA-DRB1, suggesting a modulation of the DRB1*15:01 effect. Our integrative approach provides insights into the molecular mechanisms of MS susceptibility and suggests putative therapeutic strategies targeting a methylation-mediated regulation of the major risk gene.

11.
Sci Rep ; 8(1): 4340, 2018 Mar 07.
Artigo em Inglês | MEDLINE | ID: mdl-29515171

RESUMO

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

12.
Bioinformatics ; 34(15): 2673-2675, 2018 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-29554207

RESUMO

Motivation: The alignment of bisulfite-treated DNA sequences (BS-seq reads) to a large genome involves a significant computational burden beyond that required to align non-bisulfite-treated reads. In the analysis of BS-seq data, this can present an important performance bottleneck that can be mitigated by appropriate algorithmic and software-engineering improvements. One strategy is to modify the read-alignment algorithms by integrating the logic related to BS-seq alignment, with the goal of making the software implementation amenable to optimizations that lead to higher speed and greater sensitivity than might otherwise be attainable. Results: We evaluated this strategy using Arioc, a short-read aligner that uses GPU (general-purpose graphics processing unit) hardware to accelerate computationally-expensive programming logic. We integrated the BS-seq computational logic into both GPU and CPU code throughout the Arioc implementation. We then carried out a read-by-read comparison of Arioc's reported alignments with the alignments reported by well-known CPU-based BS-seq read aligners. With simulated reads, Arioc's accuracy is equal to or better than the other read aligners we evaluated. With human sequencing reads, Arioc's throughput is at least 10 times faster than existing BS-seq aligners across a wide range of sensitivity settings. Availability and implementation: The Arioc software is available for download at https://github.com/RWilton/Arioc. It is released under a BSD open-source license. Supplementary information: Supplementary data are available at Bioinformatics online.

13.
BMC Bioinformatics ; 19(1): 87, 2018 03 07.
Artigo em Inglês | MEDLINE | ID: mdl-29514626

RESUMO

BACKGROUND: DNA methylation is a stable form of epigenetic memory used by cells to control gene expression. Whole genome bisulfite sequencing (WGBS) has emerged as a gold-standard experimental technique for studying DNA methylation by producing high resolution genome-wide methylation profiles. Statistical modeling and analysis is employed to computationally extract and quantify information from these profiles in an effort to identify regions of the genome that demonstrate crucial or aberrant epigenetic behavior. However, the performance of most currently available methods for methylation analysis is hampered by their inability to directly account for statistical dependencies between neighboring methylation sites, thus ignoring significant information available in WGBS reads. RESULTS: We present a powerful information-theoretic approach for genome-wide modeling and analysis of WGBS data based on the 1D Ising model of statistical physics. This approach takes into account correlations in methylation by utilizing a joint probability model that encapsulates all information available in WGBS methylation reads and produces accurate results even when applied on single WGBS samples with low coverage. Using the Shannon entropy, our approach provides a rigorous quantification of methylation stochasticity in individual WGBS samples genome-wide. Furthermore, it utilizes the Jensen-Shannon distance to evaluate differences in methylation distributions between a test and a reference sample. Differential performance assessment using simulated and real human lung normal/cancer data demonstrate a clear superiority of our approach over DSS, a recently proposed method for WGBS data analysis. Critically, these results demonstrate that marginal methods become statistically invalid when correlations are present in the data. CONCLUSIONS: This contribution demonstrates clear benefits and the necessity of modeling joint probability distributions of methylation using the 1D Ising model of statistical physics and of quantifying methylation stochasticity using concepts from information theory. By employing this methodology, substantial improvement of DNA methylation analysis can be achieved by effectively taking into account the massive amount of statistical information available in WGBS data, which is largely ignored by existing methods.


Assuntos
Teoria da Informação , Modelos Teóricos , Estatística como Assunto , Sulfitos/química , Sequenciamento Completo do Genoma/métodos , Sequência de Bases , Simulação por Computador , Ilhas de CpG/genética , Metilação de DNA/genética , Entropia , Epigênese Genética , Ontologia Genética , Genoma Humano , Humanos , Neoplasias Pulmonares/genética , Probabilidade , Navegador
14.
Genetics ; 208(1): 399-417, 2018 01.
Artigo em Inglês | MEDLINE | ID: mdl-29158425

RESUMO

The incidence of diet-induced metabolic disease has soared over the last half-century, despite national efforts to improve health through universal dietary recommendations. Studies comparing dietary patterns of populations with health outcomes have historically provided the basis for healthy diet recommendations. However, evidence that population-level diet responses are reliable indicators of responses across individuals is lacking. This study investigated how genetic differences influence health responses to several popular diets in mice, which are similar to humans in genetic composition and the propensity to develop metabolic disease, but enable precise genetic and environmental control. We designed four human-comparable mouse diets that are representative of those eaten by historical human populations. Across four genetically distinct inbred mouse strains, we compared the American diet's impact on metabolic health to three alternative diets (Mediterranean, Japanese, and Maasai/ketogenic). Furthermore, we investigated metabolomic and epigenetic alterations associated with diet response. Health effects of the diets were highly dependent on genetic background, demonstrating that individualized diet strategies improve health outcomes in mice. If similar genetic-dependent diet responses exist in humans, then a personalized, or "precision dietetics," approach to dietary recommendations may yield better health outcomes than the traditional one-size-fits-all approach.


Assuntos
Dietética , Metabolismo Energético , Nível de Saúde , Animais , Composição Corporal , Dieta , Modelos Animais de Doenças , Glucose/metabolismo , Humanos , Fígado/metabolismo , Doenças Metabólicas/etiologia , Doenças Metabólicas/metabolismo , Camundongos , Fenótipo
15.
Sci Rep ; 7(1): 14589, 2017 Nov 06.
Artigo em Inglês | MEDLINE | ID: mdl-29109506

RESUMO

Cigarette smoking is an established environmental risk factor for Multiple Sclerosis (MS), a chronic inflammatory and neurodegenerative disease, although a mechanistic basis remains largely unknown. We aimed at investigating how smoking affects blood DNA methylation in MS patients, by assaying genome-wide DNA methylation and comparing smokers, former smokers and never smokers in two Swedish cohorts, differing for known MS risk factors. Smoking affects DNA methylation genome-wide significantly, an exposure-response relationship exists and the time since smoking cessation affects methylation levels. The results also show that the changes were larger in the cohort bearing the major genetic risk factors for MS (female sex and HLA risk haplotypes). Furthermore, CpG sites mapping to genes with known genetic or functional role in the disease are differentially methylated by smoking. Modeling of the methylation levels for a CpG site in the AHRR gene indicates that MS modifies the effect of smoking on methylation changes, by significantly interacting with the effect of smoking load. Alongside, we report that the gene expression of AHRR increased in MS patients after smoking. Our results suggest that epigenetic modifications may reveal the link between a modifiable risk factor and the pathogenetic mechanisms.

16.
Nat Commun ; 8(1): 1011, 2017 10 24.
Artigo em Inglês | MEDLINE | ID: mdl-29066808

RESUMO

Integration of emerging epigenetic information with autism spectrum disorder (ASD) genetic results may elucidate functional insights not possible via either type of information in isolation. Here we use the genotype and DNA methylation (DNAm) data from cord blood and peripheral blood to identify SNPs associated with DNA methylation (meQTL lists). Additionally, we use publicly available fetal brain and lung meQTL lists to assess enrichment of ASD GWAS results for tissue-specific meQTLs. ASD-associated SNPs are enriched for fetal brain (OR = 3.55; P < 0.001) and peripheral blood meQTLs (OR = 1.58; P < 0.001). The CpG targets of ASD meQTLs across cord, blood, and brain tissues are enriched for immune-related pathways, consistent with other expression and DNAm results in ASD, and reveal pathways not implicated by genetic findings. This joint analysis of genotype and DNAm demonstrates the potential of both brain and blood-based DNAm for insights into ASD and psychiatric phenotypes more broadly.


Assuntos
Transtorno do Espectro Autista/genética , Ilhas de CpG/genética , Metilação de DNA/genética , Epigênese Genética , Transtorno do Espectro Autista/sangue , Encéfalo/embriologia , Encéfalo/metabolismo , Estudos de Casos e Controles , Pré-Escolar , Epigenômica/métodos , Sangue Fetal/metabolismo , Seguimentos , Estudo de Associação Genômica Ampla , Genótipo , Humanos , Lactente , Recém-Nascido , Pulmão/embriologia , Pulmão/metabolismo , Fenótipo , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Cordão Umbilical/metabolismo
17.
Nat Genet ; 49(5): 719-729, 2017 May.
Artigo em Inglês | MEDLINE | ID: mdl-28346445

RESUMO

Epigenetics is the study of biochemical modifications carrying information independent of DNA sequence, which are heritable through cell division. In 1940, Waddington coined the term "epigenetic landscape" as a metaphor for pluripotency and differentiation, but methylation landscapes have not yet been rigorously computed. Using principles from statistical physics and information theory, we derive epigenetic energy landscapes from whole-genome bisulfite sequencing (WGBS) data that enable us to quantify methylation stochasticity genome-wide using Shannon's entropy, associating it with chromatin structure. Moreover, we consider the Jensen-Shannon distance between sample-specific energy landscapes as a measure of epigenetic dissimilarity and demonstrate its effectiveness for discerning epigenetic differences. By viewing methylation maintenance as a communications system, we introduce methylation channels and show that higher-order chromatin organization can be predicted from their informational properties. Our results provide a fundamental understanding of the information-theoretic nature of the epigenome that leads to a powerful approach for studying its role in disease and aging.


Assuntos
Metilação de DNA , Epigênese Genética , Epigenômica/métodos , Análise de Sequência de DNA/métodos , Envelhecimento/genética , Algoritmos , Células Cultivadas , Células-Tronco Embrionárias/metabolismo , Entropia , Regulação da Expressão Gênica , Genoma Humano/genética , Humanos , Neoplasias/genética , Neoplasias/patologia , Sulfitos/química
18.
Arthritis Res Ther ; 19(1): 71, 2017 03 29.
Artigo em Inglês | MEDLINE | ID: mdl-28356135

RESUMO

BACKGROUND: Multiple factors, including interactions between genetic and environmental risks, are important in susceptibility to rheumatoid arthritis (RA). However, the underlying mechanism is not fully understood. This study was undertaken to evaluate whether DNA methylation can mediate the interaction between genotype and smoking in the development of anti-citrullinated peptide antibody (ACPA)-positive RA. METHODS: We investigated the gene-smoking interactions in DNA methylation using 393 individuals from the Epidemiological Investigation of Rheumatoid Arthritis (EIRA). The interaction between rs6933349 and smoking in the risk of developing ACPA-positive RA was further evaluated in a larger portion of the EIRA (1119 controls and 944 ACPA-positive patients with RA), and in the Malaysian Epidemiological Investigation of Rheumatoid Arthritis (MyEIRA) (1556 controls and 792 ACPA-positive patients with RA). Finally, mediation analysis was performed to investigate whether DNA methylation of cg21325723 mediates this gene-environment interaction on the risk of developing of ACPA-positive RA. RESULTS: We identified and replicated one significant gene-environment interaction between rs6933349 and smoking in DNA methylation of cg21325723. This gene-smoking interaction is a novel interaction in the risk of developing ACPA-positive in both Caucasian (multiplicative P value = 0.056; additive P value = 0.016) and Asian populations (multiplicative P value = 0.035; additive P value = 0.00027), and it is mediated through DNA methylation of cg21325723. CONCLUSIONS: We showed that DNA methylation of cg21325723 can mediate the gene-environment interaction between rs6933349 and smoking, impacting the risk of developing ACPA-positive RA, thus being a potential regulator that integrates both internal genetic and external environmental risk factors.


Assuntos
Artrite Reumatoide/genética , Autoanticorpos/imunologia , Metilação de DNA/genética , Interação Gene-Ambiente , Fumar/efeitos adversos , Adulto , Idoso , Artrite Reumatoide/imunologia , Autoantígenos/imunologia , Feminino , Genótipo , Humanos , Complexo Principal de Histocompatibilidade/genética , Masculino , Pessoa de Meia-Idade , Análise de Sequência com Séries de Oligonucleotídeos , Peptídeos Cíclicos/imunologia , Polimorfismo de Nucleotídeo Único
19.
Nat Genet ; 49(3): 367-376, 2017 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-28092686

RESUMO

During the progression of pancreatic ductal adenocarcinoma (PDAC), heterogeneous subclonal populations emerge that drive primary tumor growth, regional spread, distant metastasis, and patient death. However, the genetics of metastases largely reflects that of the primary tumor in untreated patients, and PDAC driver mutations are shared by all subclones. This raises the possibility that an epigenetic process might operate during metastasis. Here we report large-scale reprogramming of chromatin modifications during the natural evolution of distant metastasis. Changes were targeted to thousands of large chromatin domains across the genome that collectively specified malignant traits, including euchromatin and large organized chromatin histone H3 lysine 9 (H3K9)-modified (LOCK) heterochromatin. Remarkably, distant metastases co-evolved a dependence on the oxidative branch of the pentose phosphate pathway (oxPPP), and oxPPP inhibition selectively reversed reprogrammed chromatin, malignant gene expression programs, and tumorigenesis. These findings suggest a model whereby linked metabolic-epigenetic programs are selected for enhanced tumorigenic fitness during the evolution of distant metastasis.


Assuntos
Epigênese Genética/genética , Glucose/metabolismo , Metástase Neoplásica/genética , Neoplasias Pancreáticas/genética , Carcinogênese/genética , Carcinoma Ductal Pancreático/genética , Carcinoma Ductal Pancreático/metabolismo , Cromatina/genética , Epigenômica/métodos , Expressão Gênica/genética , Heterocromatina/genética , Histonas/genética , Humanos , Neoplasias Pancreáticas/metabolismo
20.
Artigo em Inglês | MEDLINE | ID: mdl-27980682

RESUMO

BACKGROUND: The Illumina 450k array has been widely used in epigenetic association studies. Current quality-control (QC) pipelines typically remove certain sets of probes, such as those containing a SNP or with multiple mapping locations. An additional set of potentially problematic probes are those with DNA methylation distributions characterized by two or more distinct clusters separated by gaps. Data-driven identification of such probes may offer additional insights for downstream analyses. RESULTS: We developed a procedure, termed "gap hunting," to identify probes showing clustered distributions. Among 590 peripheral blood samples from the Study to Explore Early Development, we identified 11,007 "gap probes." The vast majority (9199) are likely attributed to an underlying SNP(s) or other variant in the probe, although SNP-affected probes exist that do not produce a gap signals. Specific factors predict which SNPs lead to gap signals, including type of nucleotide change, probe type, DNA strand, and overall methylation state. These expected effects are demonstrated in paired genotype and 450k data on the same samples. Gap probes can also serve as a surrogate for the local genetic sequence on a haplotype scale and can be used to adjust for population stratification. CONCLUSIONS: The characteristics of gap probes reflect potentially informative biology. QC pipelines may benefit from an efficient data-driven approach that "flags" gap probes, rather than filtering such probes, followed by careful interpretation of downstream association analyses. Our results should translate directly to the recently released Illumina EPIC array given the similar chemistry and content design.


Assuntos
Metilação de DNA , Análise de Sequência com Séries de Oligonucleotídeos/métodos , Algoritmos , Transtorno do Espectro Autista/genética , Transtorno do Espectro Autista/patologia , Estudos de Casos e Controles , Pré-Escolar , Ilhas de CpG , Bases de Dados Genéticas , Epigenômica , Genoma Humano , Estudo de Associação Genômica Ampla , Genótipo , Humanos , Polimorfismo de Nucleotídeo Único
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