DNA Methylation Modifications Associated with Chronic Fatigue Syndrome
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Mendeley | Further Information

{"title"=>"DNA methylation modifications associated with Chronic Fatigue Syndrome", "type"=>"journal", "authors"=>[{"first_name"=>"Wilfred C.", "last_name"=>"De Vega", "scopus_author_id"=>"55938980200"}, {"first_name"=>"Suzanne D.", "last_name"=>"Vernon", "scopus_author_id"=>"7102116134"}, {"first_name"=>"Patrick O.", "last_name"=>"McGowan", "scopus_author_id"=>"23667758100"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84905860167", "sgr"=>"84905860167", "pui"=>"373746856", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"25111603", "doi"=>"10.1371/journal.pone.0104757"}, "id"=>"d59ce365-4fd7-30e5-8d81-1b425f0322f3", "abstract"=>"Chronic Fatigue Syndrome (CFS), also known as myalgic encephalomyelitis, is a complex multifactorial disease that is characterized by the persistent presence of fatigue and other particular symptoms for a minimum of 6 months. Symptoms fail to dissipate after sufficient rest and have major effects on the daily functioning of CFS sufferers. CFS is a multi-system disease with a heterogeneous patient population showing a wide variety of functional disabilities and its biological basis remains poorly understood. Stable alterations in gene function in the immune system have been reported in several studies of CFS. Epigenetic modifications have been implicated in long-term effects on gene function, however, to our knowledge, genome-wide epigenetic modifications associated with CFS have not been explored. We examined the DNA methylome in peripheral blood mononuclear cells isolated from CFS patients and healthy controls using the Illumina HumanMethylation450 BeadChip array, controlling for invariant probes and probes overlapping polymorphic sequences. Gene ontology (GO) and network analysis of differentially methylated genes was performed to determine potential biological pathways showing changes in DNA methylation in CFS. We found an increased abundance of differentially methylated genes related to the immune response, cellular metabolism, and kinase activity. Genes associated with immune cell regulation, the largest coordinated enrichment of differentially methylated pathways, showed hypomethylation within promoters and other gene regulatory elements in CFS. These data are consistent with evidence of multisystem dysregulation in CFS and implicate the involvement of DNA modifications in CFS pathology.", "link"=>"http://www.mendeley.com/research/dna-methylation-modifications-associated-chronic-fatigue-syndrome-3", "reader_count"=>59, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Researcher"=>12, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>10, "Student > Postgraduate"=>1, "Other"=>6, "Student > Master"=>9, "Student > Bachelor"=>9, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Researcher"=>12, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>10, "Student > Postgraduate"=>1, "Other"=>6, "Student > Master"=>9, "Student > Bachelor"=>9, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Agricultural and Biological Sciences"=>16, "Philosophy"=>1, "Computer Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>10, "Nursing and Health Professions"=>1, "Medicine and Dentistry"=>12, "Neuroscience"=>4, "Sports and Recreations"=>2, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Psychology"=>4, "Social Sciences"=>2, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>12}, "Social Sciences"=>{"Social Sciences"=>2}, "Sports and Recreations"=>{"Sports and Recreations"=>2}, "Psychology"=>{"Psychology"=>4}, "Unspecified"=>{"Unspecified"=>4}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Neuroscience"=>{"Neuroscience"=>4}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>16}, "Computer Science"=>{"Computer Science"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>10}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"Canada"=>1, "Norway"=>2, "Luxembourg"=>1, "Italy"=>1, "United Kingdom"=>1}, "group_count"=>1}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1630645"], "description"=>"<p>Distribution of hyper- and hypo-methylated CpG regions in CFS patients compared to healthy control subjects according to (<b>a</b>) genic location 1500 bp and 200 bp relative to the transcription start site (TSS), in the 5′ UTR, 3′ UTR, and within gene bodies and (<b>b</b>) location relative to CpG islands, including 2 kb upstream and downstream of CpG islands (N, S Shore respectively), and 2 kb upstream and downstream of CpG shores (N, S Shelf respectively). No significant differences were found within CpG islands.</p>", "links"=>[], "tags"=>["Biochemistry", "dna", "DNA modification", "dna methylation", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "lymphocytes", "Immune cells", "Computational biology", "genome analysis", "Gene ontologies", "Gene ontology associations", "epigenomics", "genetics", "epigenetics", "genomics", "neuroscience", "differentially", "methylated", "regions"], "article_id"=>1135042, "categories"=>["Biological Sciences"], "users"=>["Wilfred C. de Vega", "Suzanne D. Vernon", "Patrick O. McGowan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104757.g001", "stats"=>{"downloads"=>3, "page_views"=>28, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_differentially_methylated_regions_in_CFS_/1135042", "title"=>"Distribution of differentially methylated regions in CFS.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-11 03:16:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1630647"], "description"=>"<p>Validation of significant methylation differences identified by microarray (450 K) by pyrosequencing (PS), showing the average methylation level of CpG sites within the following genes (probe ID, genic location): (a) LY86 (cg02212836, first exon), (b) HIPK3 (cg25600606, gene body), and (c) LCN2 (cg14615559, TSS200). * = FDR<0.05, 450 K; * = p<0.05, PS, Wilcoxon rank-sum test. Error bars represent the standard error of the mean.</p>", "links"=>[], "tags"=>["Biochemistry", "dna", "DNA modification", "dna methylation", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "lymphocytes", "Immune cells", "Computational biology", "genome analysis", "Gene ontologies", "Gene ontology associations", "epigenomics", "genetics", "epigenetics", "genomics", "neuroscience", "microarray"], "article_id"=>1135044, "categories"=>["Biological Sciences"], "users"=>["Wilfred C. de Vega", "Suzanne D. Vernon", "Patrick O. McGowan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104757.g002", "stats"=>{"downloads"=>2, "page_views"=>38, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Validation_of_microarray_data_by_pyrosequencing_/1135044", "title"=>"Validation of microarray data by pyrosequencing.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-11 03:16:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1630648"], "description"=>"<p>Network map showing the clustering of DAVID GO results as produced by the Enrichment Map plugin in Cytoscape 2.8.2. Significant GO term clusters were named according to textual attributes generated by the WordCloud plugin. Node size (red circles) corresponds to the number of genes within the GO terms. Edge thickness (green lines) represents genes in common between GO terms.</p>", "links"=>[], "tags"=>["Biochemistry", "dna", "DNA modification", "dna methylation", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "lymphocytes", "Immune cells", "Computational biology", "genome analysis", "Gene ontologies", "Gene ontology associations", "epigenomics", "genetics", "epigenetics", "genomics", "neuroscience", "david"], "article_id"=>1135045, "categories"=>["Biological Sciences"], "users"=>["Wilfred C. de Vega", "Suzanne D. Vernon", "Patrick O. McGowan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104757.g003", "stats"=>{"downloads"=>5, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Clustering_of_DAVID_GO_results_/1135045", "title"=>"Clustering of DAVID GO results.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-11 03:16:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1630650"], "description"=>"<p>Relative proportions of hyper- and hypo-methylated CpG sites between CFS patients and healthy control subjects for genes associated with the immune cell regulation cluster group (immune GO) compared to all four GO term cluster groups (all GO). Results are shown for each genic region, consisting of promoter regions within 1500 bp and 200 bp of the transcription start sites (TSS), gene regulatory elements (regulatory: TSS1500, TSS200, 5′ UTR, 3′ UTR), the coding regions of genes (gene body), as well as all regions combined (total: regulatory, gene body). * = p<0.0125, Pearson Chi-Squared Test.</p>", "links"=>[], "tags"=>["Biochemistry", "dna", "DNA modification", "dna methylation", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "lymphocytes", "Immune cells", "Computational biology", "genome analysis", "Gene ontologies", "Gene ontology associations", "epigenomics", "genetics", "epigenetics", "genomics", "neuroscience", "differentially", "methylated", "sites", "cfs", "clusters"], "article_id"=>1135047, "categories"=>["Biological Sciences"], "users"=>["Wilfred C. de Vega", "Suzanne D. Vernon", "Patrick O. McGowan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104757.g004", "stats"=>{"downloads"=>3, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_differentially_methylated_sites_in_CFS_according_to_GO_clusters_and_functional_relevance_/1135047", "title"=>"Distribution of differentially methylated sites in CFS according to GO clusters and functional relevance.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-11 03:16:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1630651"], "description"=>"<p>Demographic information and RAND-36 results for CFS patients and healthy control subjects selected for DNA methylome analysis. * = p<0.05, Student’s t-test, CFS versus healthy control subjects. Data are shown as mean ± standard error of the mean, where applicable.</p>", "links"=>[], "tags"=>["Biochemistry", "dna", "DNA modification", "dna methylation", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "lymphocytes", "Immune cells", "Computational biology", "genome analysis", "Gene ontologies", "Gene ontology associations", "epigenomics", "genetics", "epigenetics", "genomics", "neuroscience", "rand-36", "subjects"], "article_id"=>1135048, "categories"=>["Biological Sciences"], "users"=>["Wilfred C. de Vega", "Suzanne D. Vernon", "Patrick O. McGowan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104757.t001", "stats"=>{"downloads"=>4, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Demographics_and_RAND_36_results_of_subjects_selected_for_the_study_/1135048", "title"=>"Demographics and RAND-36 results of subjects selected for the study.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-08-11 03:16:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1630652"], "description"=>"<p>GO terms associated with the immune cell regulation cluster for genes differentially methylated in CFS patients compared to healthy control subjects.</p>", "links"=>[], "tags"=>["Biochemistry", "dna", "DNA modification", "dna methylation", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "lymphocytes", "Immune cells", "Computational biology", "genome analysis", "Gene ontologies", "Gene ontology associations", "epigenomics", "genetics", "epigenetics", "genomics", "neuroscience"], "article_id"=>1135049, "categories"=>["Biological Sciences"], "users"=>["Wilfred C. de Vega", "Suzanne D. Vernon", "Patrick O. McGowan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104757.t002", "stats"=>{"downloads"=>4, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Immune_cell_regulation_GO_cluster_/1135049", "title"=>"Immune cell regulation GO cluster.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-08-11 03:16:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1630653"], "description"=>"<p>Examples of genes within the immune cell regulation cluster differentially methylated at gene regulatory elements in CFS patients compared to healthy control subjects.</p>", "links"=>[], "tags"=>["Biochemistry", "dna", "DNA modification", "dna methylation", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "lymphocytes", "Immune cells", "Computational biology", "genome analysis", "Gene ontologies", "Gene ontology associations", "epigenomics", "genetics", "epigenetics", "genomics", "neuroscience"], "article_id"=>1135050, "categories"=>["Biological Sciences"], "users"=>["Wilfred C. de Vega", "Suzanne D. Vernon", "Patrick O. McGowan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0104757.t003", "stats"=>{"downloads"=>4, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Immune_cell_regulation_GO_cluster_genes_/1135050", "title"=>"Immune cell regulation GO cluster genes.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-08-11 03:16:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/1630655", "https://ndownloader.figshare.com/files/1630656", "https://ndownloader.figshare.com/files/1630657", "https://ndownloader.figshare.com/files/1630658", "https://ndownloader.figshare.com/files/1630659", "https://ndownloader.figshare.com/files/1630660", "https://ndownloader.figshare.com/files/1630661"], "description"=>"<div><p>Chronic Fatigue Syndrome (CFS), also known as myalgic encephalomyelitis, is a complex multifactorial disease that is characterized by the persistent presence of fatigue and other particular symptoms for a minimum of 6 months. Symptoms fail to dissipate after sufficient rest and have major effects on the daily functioning of CFS sufferers. CFS is a multi-system disease with a heterogeneous patient population showing a wide variety of functional disabilities and its biological basis remains poorly understood. Stable alterations in gene function in the immune system have been reported in several studies of CFS. Epigenetic modifications have been implicated in long-term effects on gene function, however, to our knowledge, genome-wide epigenetic modifications associated with CFS have not been explored. We examined the DNA methylome in peripheral blood mononuclear cells isolated from CFS patients and healthy controls using the Illumina HumanMethylation450 BeadChip array, controlling for invariant probes and probes overlapping polymorphic sequences. Gene ontology (GO) and network analysis of differentially methylated genes was performed to determine potential biological pathways showing changes in DNA methylation in CFS. We found an increased abundance of differentially methylated genes related to the immune response, cellular metabolism, and kinase activity. Genes associated with immune cell regulation, the largest coordinated enrichment of differentially methylated pathways, showed hypomethylation within promoters and other gene regulatory elements in CFS. These data are consistent with evidence of multisystem dysregulation in CFS and implicate the involvement of DNA modifications in CFS pathology.</p></div>", "links"=>[], "tags"=>["Biochemistry", "dna", "DNA modification", "dna methylation", "cell biology", "Cellular types", "Animal cells", "Blood cells", "White blood cells", "lymphocytes", "Immune cells", "Computational biology", "genome analysis", "Gene ontologies", "Gene ontology associations", "epigenomics", "genetics", "epigenetics", "genomics", "neuroscience", "methylation", "modifications"], "article_id"=>1135052, "categories"=>["Biological Sciences"], "users"=>["Wilfred C. de Vega", "Suzanne D. Vernon", "Patrick O. McGowan"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0104757.s001", "https://dx.doi.org/10.1371/journal.pone.0104757.s002", "https://dx.doi.org/10.1371/journal.pone.0104757.s003", "https://dx.doi.org/10.1371/journal.pone.0104757.s004", "https://dx.doi.org/10.1371/journal.pone.0104757.s005", "https://dx.doi.org/10.1371/journal.pone.0104757.s006", "https://dx.doi.org/10.1371/journal.pone.0104757.s007"], "stats"=>{"downloads"=>22, "page_views"=>25, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_DNA_Methylation_Modifications_Associated_with_Chronic_Fatigue_Syndrome_/1135052", "title"=>"DNA Methylation Modifications Associated with Chronic Fatigue Syndrome", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-08-11 03:16:26"}

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Relative Metric

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