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William A. Held - One of the best experts on this subject based on the ideXlab platform.

  • Tissue specific Differentially Methylated Regions (TDMR) : Changes in DNA methylation during development
    Genomics, 2008
    Co-Authors: Fei Song, Srimoyee Ghosh, Saleh Mahmood, Ping Liang, Domminic J. Smiraglia, Hiroki Nagase, William A. Held
    Abstract:

    Tissue specific Differentially Methylated Regions (TDMRs) were identified and localized in the mouse genome using second generation virtual RLGS (vRLGS). Sequenom MassARRAY quantitative methylation analysis was used to confirm and determine the fine structure of tissue specific differences in DNA methylation. TDMRs have a broad distribution of locations to intragenic and intergenic Regions including both CpG islands, and non-CpG islands Regions. Somewhat surprising, there is a strong bias for TDMR location in non-promoter intragenic Regions. Although some TDMRs are within or close to repeat sequences, overall they are less frequently associated with repetitive elements than expected from a random distribution. Many TDMRs are Methylated at early developmental stages, but unMethylated later, suggesting active or passive demethylation, or expansions of populations of cells with unMethylated TDMRs. This is notable during postnatal testis differentiation where many testis specific TDMRs become progressively "deMethylated". These results suggest that methylation changes during development are dynamic, involve demethylation and methylation, and may occur at late stages of embryonic development or even postnatally.

  • Analysis of tissue-specific Differentially Methylated Regions (TDMs) in humans.
    Genomics, 2006
    Co-Authors: Eiko Kitamura, Jun Igarashi, Aiko Morohashi, Naoko Hida, Toshinori Oinuma, Norimichi Nemoto, Fei Song, Srimoyee Ghosh, William A. Held, Chikako Yoshida-noro
    Abstract:

    Alterations in DNA methylation have been implicated in mammalian development. Hence, the identification of tissue-specific Differentially Methylated Regions (TDMs) is indispensable for understanding its role. Using restriction landmark genomic scanning of six mouse tissues, 150 putative TDMs were identified and 14 were further analyzed. The DNA sequences of the 14 mouse TDMs are analyzed in this study. Six of the human homologous Regions show TDMs to both mouse and human and genes in five of these Regions have conserved tissue-specific expression: preferential expression in testis. A TDM, DDX4, is further analyzed in nine testis tissues. An increase in methylation of the promoter region is significantly associated with a marked reduction of the gene expression and defects in spermatogenesis, suggesting that hypomethylation of the DDX4 promoter region regulates DDX4 gene expression in spermatogenic cells. Our results indicate that some genomic Regions with tissue-specific methylation and expression are conserved between mouse and human and suggest that DNA methylation may have an important role in regulating differentiation and tissue-/cell-specific gene expression of some genes.

  • association of tissue specific Differentially Methylated Regions tdms with differential gene expression
    Proceedings of the National Academy of Sciences of the United States of America, 2005
    Co-Authors: Fei Song, Hiroki Nagase, Joseph F Smith, Makoto T Kimura, Arlene D Morrow, Tomoki Matsuyama, William A. Held
    Abstract:

    Early studies proposed that DNA methylation could have a role in regulating gene expression during development [Riggs, A.D. (1975) Cytogenet. Cell Genet. 14, 9–25]. However, some studies of DNA methylation in known tissue-specific genes during development do not support a major role for DNA methylation. In the results presented here, tissue-specific Differentially Methylated Regions (TDMs) were first identified, and then expression of genes associated with these Regions correlated with methylation status. Restriction landmark genomic scanning (RLGS) was used in conjunction with virtual RLGS to identify 150 TDMs [Matsuyama, T., Kimura, M.T., Koike, K., Abe, T., Nakao, T., Asami, T., Ebisuzaki, T., Held, W.A., Yoshida, S. & Nagase, H. (2003) Nucleic Acids Res. 31, 4490–4496]. Analysis of 14 TDMs by methylation-specific PCR and by bisulfite genomic sequencing confirms that the Regions identified by RLGS are Differentially Methylated in a tissue-specific manner. The results indicate that 5% or more of the CpG islands are TDMs, disputing the general notion that all CpG islands are unMethylated. Some of the TDMs are within 5′ promoter CpG islands of genes, which exhibit a tissue-specific expression pattern that is consistent with methylation status and a role in tissue differentiation.

Lily Wang - One of the best experts on this subject based on the ideXlab platform.

  • coMethDMR: accurate identification of co-Methylated and Differentially Methylated Regions in epigenome-wide association studies with continuous phenotypes.
    Nucleic acids research, 2019
    Co-Authors: Lissette Gomez, Gabriel J. Odom, Zhen Gao, Xi Chen, Juan I. Young, Eden R. Martin, Lizhong Liu, Anthony J. Griswold, Lanyu Zhang, Lily Wang
    Abstract:

    Recent technology has made it possible to measure DNA methylation profiles in a cost-effective and comprehensive genome-wide manner using array-based technology for epigenome-wide association studies. However, identifying Differentially Methylated Regions (DMRs) remains a challenging task because of the complexities in DNA methylation data. Supervised methods typically focus on the Regions that contain consecutive highly significantly Differentially Methylated CpGs in the genome, but may lack power for detecting small but consistent changes when few CpGs pass stringent significance threshold after multiple comparison. Unsupervised methods group CpGs based on genomic annotations first and then test them against phenotype, but may lack specificity because the regional boundaries of methylation are often not well defined. We present coMethDMR, a flexible, powerful, and accurate tool for identifying DMRs. Instead of testing all CpGs within a genomic region, coMethDMR carries out an additional step that selects co-Methylated sub-Regions first. Next, coMethDMR tests association between methylation levels within the sub-region and phenotype via a random coefficient mixed effects model that models both variations between CpG sites within the region and differential methylation simultaneously. coMethDMR offers well-controlled Type I error rate, improved specificity, focused testing of targeted genomic Regions, and is available as an open-source R package.

  • coMethDMR: Accurate identification of co-Methylated and Differentially Methylated Regions in epigenome-wide association studies
    2019
    Co-Authors: Lissette Gomez, Gabriel J. Odom, Zhen Gao, Xi Chen, Juan I. Young, Eden R. Martin, Lizhong Liu, Anthony J. Griswold, Lanyu Zhang, Lily Wang
    Abstract:

    ABSTRACT Recent technology has made it possible to measure DNA methylation profiles in a cost-effective and comprehensive genome-wide manner using array-based technology for epigenome-wide association studies. However, identifying Differentially Methylated Regions (DMRs) remains a challenging task because of the complexities in DNA methylation data. Supervised methods typically focus on the Regions that contain consecutive highly significantly Differentially Methylated CpGs in the genome, but may lack power for detecting small but consistent changes when few CpGs pass stringent significance threshold after multiple comparison. Unsupervised methods group CpGs based on genomic annotations first and then test them against phenotype, but may lack specificity because the regional boundaries of methylation are often not well defined. We present coMethDMR, a flexible, powerful, and accurate tool for identifying DMRs. Instead of testing all CpGs within a genomic region, coMethDMR carries out an additional step that selects co-Methylated sub-Regions first. Next, coMethDMR tests association between methylation levels within the sub-region and phenotype via a random coefficient mixed effects model that models both variations between CpG sites within the region and differential methylation simultaneously. coMethDMR offers well-controlled Type I error rate, improved specificity, focused testing of targeted genomic Regions, and is available as an open-source R package.

  • An evaluation of supervised methods for identifying Differentially Methylated Regions in Illumina methylation arrays.
    Briefings in bioinformatics, 2018
    Co-Authors: Saurav Mallik, Gabriel J. Odom, Zhen Gao, Lissette Gomez, Xi Chen, Lily Wang
    Abstract:

    Epigenome-wide association studies (EWASs) have become increasingly popular for studying DNA methylation (DNAm) variations in complex diseases. The Illumina methylation arrays provide an economical, high-throughput and comprehensive platform for measuring methylation status in EWASs. A number of software tools have been developed for identifying disease-associated Differentially Methylated Regions (DMRs) in the epigenome. However, in practice, we found these tools typically had multiple parameter settings that needed to be specified and the performance of the software tools under different parameters was often unclear. To help users better understand and choose optimal parameter settings when using DNAm analysis tools, we conducted a comprehensive evaluation of 4 popular DMR analysis tools under 60 different parameter settings. In addition to evaluating power, precision, area under precision-recall curve, Matthews correlation coefficient, F1 score and type I error rate, we also compared several additional characteristics of the analysis results, including the size of the DMRs, overlap between the methods and execution time. The results showed that none of the software tools performed best under their default parameter settings, and power varied widely when parameters were changed. Overall, the precision of these software tools were good. In contrast, all methods lacked power when effect size was consistent but small. Across all simulation scenarios, comb-p consistently had the best sensitivity as well as good control of false-positive rate.

Lene Christiansen - One of the best experts on this subject based on the ideXlab platform.

  • Epigenome-wide exploratory study of monozygotic twins suggests Differentially Methylated Regions to associate with hand grip strength
    Biogerontology, 2019
    Co-Authors: Mette Soerensen, Weilong Li, Birgit Debrabant, Marianne Nygaard, Jonas Mengel-from, Morten Frost, Kaare Christensen, Lene Christiansen
    Abstract:

    Hand grip strength is a measure of muscular strength and is used to study age-related loss of physical capacity. In order to explore the biological mechanisms that influence hand grip strength variation, an epigenome-wide association study (EWAS) of hand grip strength in 672 middle-aged and elderly monozygotic twins (age 55–90 years) was performed, using both individual and twin pair level analyses, the latter controlling the influence of genetic variation. Moreover, as measurements of hand grip strength performed over 8 years were available in the elderly twins (age 73–90 at intake), a longitudinal EWAS was conducted for this subsample. No genome-wide significant CpG sites or pathways were found, however two of the suggestive top CpG sites were mapped to the COL6A1 and CACNA1B genes, known to be related to muscular dysfunction. By investigating genomic Regions using the comb-p algorithm, several Differentially Methylated Regions in regulatory domains were identified as significantly associated to hand grip strength, and pathway analyses of these Regions revealed significant pathways related to the immune system, autoimmune disorders, including diabetes type 1 and viral myocarditis, as well as negative regulation of cell differentiation. The genes contributing to the immunological pathways were HLA - B , HLA - C , HLA - DMA , HLA - DPB1 , MYH10 , ERAP1 and IRF8 , while the genes implicated in the negative regulation of cell differentiation were IRF8 , CEBPD , ID2 and BRCA1 . In conclusion, this exploratory study suggests hand grip strength to associate with Differentially Methylated Regions enriched in immunological and cell differentiation pathways, and hence merits further investigations.

  • Epigenome-wide exploratory study of monozygotic twins suggests Differentially Methylated Regions to associate with hand grip strength
    Biogerontology, 2019
    Co-Authors: Mette Soerensen, Birgit Debrabant, Marianne Nygaard, Jonas Mengel-from, Morten Frost, Kaare Christensen, Lene Christiansen, Qihua Tan
    Abstract:

    Hand grip strength is a measure of muscular strength and is used to study age-related loss of physical capacity. In order to explore the biological mechanisms that influence hand grip strength variation, an epigenome-wide association study (EWAS) of hand grip strength in 672 middle-aged and elderly monozygotic twins (age 55–90 years) was performed, using both individual and twin pair level analyses, the latter controlling the influence of genetic variation. Moreover, as measurements of hand grip strength performed over 8 years were available in the elderly twins (age 73–90 at intake), a longitudinal EWAS was conducted for this subsample. No genome-wide significant CpG sites or pathways were found, however two of the suggestive top CpG sites were mapped to the COL6A1 and CACNA1B genes, known to be related to muscular dysfunction. By investigating genomic Regions using the comb-p algorithm, several Differentially Methylated Regions in regulatory domains were identified as significantly associated to hand grip strength, and pathway analyses of these Regions revealed significant pathways related to the immune system, autoimmune disorders, including diabetes type 1 and viral myocarditis, as well as negative regulation of cell differentiation. The genes contributing to the immunological pathways were HLA-B, HLA-C, HLA-DMA, HLA-DPB1, MYH10, ERAP1 and IRF8, while the genes implicated in the negative regulation of cell differentiation were IRF8, CEBPD, ID2 and BRCA1. In conclusion, this exploratory study suggests hand grip strength to associate with Differentially Methylated Regions enriched in immunological and cell differentiation pathways, and hence merits further investigations. Electronic supplementary material The online version of this article (10.1007/s10522-019-09818-1) contains supplementary material, which is available to authorized users.

Tania Wang - One of the best experts on this subject based on the ideXlab platform.

  • Epigenome-wide association study of Alzheimer's disease replicates 22 Differentially Methylated positions and 30 Differentially Methylated Regions.
    Clinical epigenetics, 2020
    Co-Authors: Yu Sun, Tania Wang
    Abstract:

    BACKGROUND Growing evidence shows that epigenetic modifications play a role in Alzheimer's disease (AD). We performed an epigenome-wide association study (EWAS) to evaluate the DNA methylation differences using postmortem superior temporal gyrus (STG) and inferior frontal gyrus (IFG) samples. RESULTS Samples from 72 AD patients and 62 age-matched cognitively normal controls were assayed using Illumina© Infinium MethylationEPIC BeadChip. Five and 14 Differentially Methylated positions (DMPs) associated with pathology (i.e., Braak stage) with p value less than Bonferroni correction threshold of 6.79 × 10-8 in the STG and IFG were identified, respectively. These cytosine-phosphate-guanine (CpG) sites included promoter associated cg26263477 annotated to ABCA7 in the STG (p = 1.21 × 10-11), and cg14058329 annotated to the HOXA5/HOXA3/HOXA-AS3 gene cluster (p = 1.62 × 10-9) and cg09448088 (p = 3.95 × 10-9) annotated to MCF2L in the IFG. These genes were previously reported to harbor DMPs and/or Differentially Methylated Regions (DMRs). Previously reported DMPs annotated to RMGA, GNG7, HOXA3, GPR56, SPG7, PCNT, RP11-961A15.1, MCF2L, RHBDF2, ANK1, PCNT, TPRG1, and RASGEF1C were replicated (p 

  • epigenome wide association study of alzheimer s disease replicates 22 Differentially Methylated positions and 30 Differentially Methylated Regions
    Clinical Epigenetics, 2020
    Co-Authors: Yu Sun, Tania Wang
    Abstract:

    BACKGROUND Growing evidence shows that epigenetic modifications play a role in Alzheimer's disease (AD). We performed an epigenome-wide association study (EWAS) to evaluate the DNA methylation differences using postmortem superior temporal gyrus (STG) and inferior frontal gyrus (IFG) samples. RESULTS Samples from 72 AD patients and 62 age-matched cognitively normal controls were assayed using Illumina© Infinium MethylationEPIC BeadChip. Five and 14 Differentially Methylated positions (DMPs) associated with pathology (i.e., Braak stage) with p value less than Bonferroni correction threshold of 6.79 × 10-8 in the STG and IFG were identified, respectively. These cytosine-phosphate-guanine (CpG) sites included promoter associated cg26263477 annotated to ABCA7 in the STG (p = 1.21 × 10-11), and cg14058329 annotated to the HOXA5/HOXA3/HOXA-AS3 gene cluster (p = 1.62 × 10-9) and cg09448088 (p = 3.95 × 10-9) annotated to MCF2L in the IFG. These genes were previously reported to harbor DMPs and/or Differentially Methylated Regions (DMRs). Previously reported DMPs annotated to RMGA, GNG7, HOXA3, GPR56, SPG7, PCNT, RP11-961A15.1, MCF2L, RHBDF2, ANK1, PCNT, TPRG1, and RASGEF1C were replicated (p < 0.0001). One hundred twenty-one and 173 DMRs associated with pathology in the STG and IFG, respectively, were additionally identified. Of these, DMRs annotated to 30 unique genes were also identified as significant DMRs in the same brain region in a recent meta-analysis, while additional DMRs annotated to 12 genes were reported as DMRs in a different brain region or in a cross-cortex meta-analysis. The significant DMRs were enriched in promoters, CpG islands, and exons in the genome. Gene set enrichment analysis of DMPs and DMRs showed that gene sets involved in neuroinflammation (e.g., microglia differentiation), neurogenesis, and cognition were enriched (false discovery rate (FDR) < 0.05). CONCLUSIONS Twenty-two DMPs and 30 DMRs associated with pathology were replicated, and novel DMPs and DMRs were discovered.

Wendy P. Robinson - One of the best experts on this subject based on the ideXlab platform.

  • Genome-wide mapping of imprinted Differentially Methylated Regions by DNA methylation profiling of human placentas from triploidies.
    Epigenetics & chromatin, 2011
    Co-Authors: Ryan K. C. Yuen, Ruby Jiang, Maria S. Peñaherrera, Deborah E. Mcfadden, Wendy P. Robinson
    Abstract:

    Background Genomic imprinting is an important epigenetic process involved in regulating placental and foetal growth. Imprinted genes are typically associated with Differentially Methylated Regions (DMRs) whereby one of the two alleles is DNA Methylated depending on the parent of origin. Identifying imprinted DMRs in humans is complicated by species- and tissue-specific differences in imprinting status and the presence of multiple regulatory Regions associated with a particular gene, only some of which may be imprinted. In this study, we have taken advantage of the unbalanced parental genomic constitutions in triploidies to further characterize human DMRs associated with known imprinted genes and identify novel imprinted DMRs.

  • Genome-wide mapping of imprinted Differentially Methylated Regions by DNA methylation profiling of human placentas from triploidies
    Epigenetics & Chromatin, 2011
    Co-Authors: Ryan K. C. Yuen, Ruby Jiang, Maria S. Peñaherrera, Deborah E. Mcfadden, Wendy P. Robinson
    Abstract:

    Background Genomic imprinting is an important epigenetic process involved in regulating placental and foetal growth. Imprinted genes are typically associated with Differentially Methylated Regions (DMRs) whereby one of the two alleles is DNA Methylated depending on the parent of origin. Identifying imprinted DMRs in humans is complicated by species- and tissue-specific differences in imprinting status and the presence of multiple regulatory Regions associated with a particular gene, only some of which may be imprinted. In this study, we have taken advantage of the unbalanced parental genomic constitutions in triploidies to further characterize human DMRs associated with known imprinted genes and identify novel imprinted DMRs. Results By comparing the promoter methylation status of over 14,000 genes in human placentas from ten diandries (extra paternal haploid set) and ten digynies (extra maternal haploid set) and using 6 complete hydatidiform moles (paternal origin) and ten chromosomally normal placentas for comparison, we identified 62 genes with apparently imprinted DMRs (false discovery rate