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1,257 results for “METHYLATION PROFILE”
MethylDetectR - A Translational Tool for Methylation-Based Health Profiling
<p><strong>** CORRECTION (2025-05-29): Please note that the script <a href="https://zenodo.org/api/records/15548022/draft/files/Script_For_User_To_Generate_Scores.R/content" target="_blank" rel="noopener noreferrer">Script_For_User_To_Generate_Scores.R</a> had an error whereby single-CpG EpiScores were producing the same score for all samples. This has been corrected in the newest version. </strong><br><br>This dataset includes reproducible code for the two applications related to the 'MethylDetectR' software. These .R files are included as 'MethylDetectR - Calculate Your Scores.R' and 'MethylDetectR.R'. An example DNAm file and SexAgeinfo file for upload to 'MethylDetectR - Calculate Your Scores' are included. These are 'DNAm_File_Example.rds' and 'SexAgeinfo_example.csv' respectively. An example output file from this application/for upload to 'MethylDetectR' is included as 'MethylDetectR - Test For Upload.csv'. An example and optional input file for case/control data is also available as 'MethylDetectR_Case_Control_Example.csv'. </p> <p>Furthermore, a script for the user to generate their own DNAm-based estimated values for human traits is included as 'Script_For_User_To_Generate_Scores.R'. A necessary associated file as 'Predictors_Shiny_By_Groups.csv' is also present for the script to run. We have also included separate necessary files to generate the chronological age predictor from Bernabeu <em>et al.</em> in our most recent versions of MethylDetectR. </p> <p>Lastly, an additional file called 'Truncate_to_these_CpGs.csv' is available which allows users to subset their methylation file to those CpG sites used in the 'MethylDetectR - Calculate Your Scores' application. This may substantially reduce the size of the methylation file for upload as well as its upload time. </p>
Simultaneous profiling of histone modifications and DNA methylation via nanopore sequencing
<p>Datasets that contain a minimum of nanopore reads sufficient for hidden Markov model training and for evaluating the performance of our computational tool - nanoHiMe at simultaneously calling CpG and/or adenine methylation on individual nanopore reads.<em> Ecoli</em>_PCR_amplicons_100k.tgz, <em>Ecoli</em>_PCR_MSssI_100k.tar.gz and <em>Ecoli</em>_PCR_pA-Hia5_100k.tar.gz are used for training new parameters of the emission distributions of individual <em>k</em>-mers from DNA template without modification, with fully methylated CpGs, and with partially methylated adenines, respectively. nanoHiMe_H3K27me3.fast5.tgz are the nanopore sequencing reads from H3K27me3 nanoHiMe-seq experiments in GM12878 cells and used for evaluating the performance of nanoHiMe at jointly calling CpG and adenine methylation.</p>
Codeletion of 1p and 19q determines distinct gene methylation and expression profiles in IDH-mutated oligodendroglial tumors _ Dataset
<p>Overall design: Genome-wide DNA methylation profiling of oligodendroglial tumors (OTs) and five non tumoral brain tissue (NTBT) samples. The Illumina Infinium Human DNA methylation 450k Beadchip was used to obtain DNA methylation profiles across approximately 450,000 CpGs in tumoral samples. Samples included 46 OTs and 5 NTBT.</p> <p>Bisulphite converted DNA from the 51 samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip</p> <p>Extracted molecule: genomic DNA</p> <p>Platform: Illumina HumanMethylation450 BeadChip (HumanMethylation450_15017482)</p> <p>Label protocol: Standard Illumina Protocol</p> <p>Hybridization protocol: bisulphite converted DNA was amplified, fragmented and hybridised to Illumina Infinium Human Methylation 450K Beadchip using standard Illumina protocol</p> <p>Scan protocol: Arrays were imaged using BeadArray Reader using standard recommended Illumina scanner setting </p> <p>Data processing: BeadStudio software v3.2</p> <p>Data format: IDAT files</p>
Blood DNA Methylation Profiling Identifies Cathepsin Z Dysregulation in Pulmonary Arterial Hypertension
<p>Ulrich, A., Wu, Y., Draisma, H., Wharton, J., Swietlik, E. M., Cebola, I., Vasilaki, E., Balkhiyarova, Z., Jarvelin, M. R., Auvinen, J., Herzig, K. H., Coghlan, J. G., Lordan, J., Church, C., Howard, L. S., Pepke-Zaba, J., Toshner, M., Wort, S. J., Kiely, D. G., Condliffe, R., … Rhodes, C. J. (2024). <a href="https://pubmed.ncbi.nlm.nih.gov/38184627/"><strong>Blood DNA methylation profiling identifies cathepsin Z dysregulation in pulmonary arterial hypertension</strong></a>. <em>Nature communications</em>, <em>15</em>(1), 330. https://doi.org/10.1038/s41467-023-44683-0</p> <p>Maternal educational attainment (MEA) shapes offspring health through multiple potential pathways. Differential DNA methylation may provide a mechanistic understanding of these long-term associations. We aimed to quantify the associations of MEA with offspring DNA methylation levels at birth, in childhood and in adolescence. Using 37 studies from high-income countries, we performed meta-analysis of epigenome-wide association studies (EWAS) to quantify the associations of completed years of MEA at the time of pregnancy with offspring DNA methylation levels at birth (n = 9 881), in childhood (n = 2 017), and adolescence (n = 2 740), adjusting for relevant covariates. MEA was found to be associated with DNA methylation at 473 cytosine-phosphate-guanine sites at birth, one in childhood, and four in adolescence. We observed enrichment for findings from previous EWAS on maternal folate, vitamin-B12 concentrations, maternal smoking, and pre-pregnancy BMI. The associations were directionally consistent with MEA being inversely associated with behaviours including smoking and BMI. Our findings form a bridge between socio-economic factors and biology and highlight potential pathways underlying effects of maternal education. The results broaden our understanding of bio-social associations linked to differential DNA methylation in multiple early stages of life. The data generated also offers an important resource to help a more precise understanding of the social determinants of health.</p>
Genome-wide DNA methylation profiling identifies epigenetic signatures of β-lactams induced fatal anaphylactic shock
<p>Drug hypersensitivity is one of the most frequent causes of anaphylaxis in adults, of which antibiotics are the most common culprits, particularly β-lactams induced anaphylactic shock deaths. We provided the genome wide DNA methylation profiling study of PBMC from 14 individuals peripheral venous blood samples. Illumina Infinium Human Methylation EPIC BeadChip was used. Among the 14 individuals, 8 patients were died from β-lactams induced anaphylactic shock, 6 healthy individuals were controls. Inclusion criteria for the β-lactams induced anaphylactic shock as follows: ①A clear history of β-lactams transfusion or components of β-lactams detected from blood (or skin of suspicious infusion site); ②Shock symptoms occurred after infusion of β-lactams and died within a short period of time; ③The immunohistochemical results of throat, lung and gastrointestinal tissues showed that tryptase or chymase were mostly positive expression; ④ Excluding other causes (disease, poisoning) of death; ⑤ No decay occurred in the corpse.Inclusion criteria for controls as follows: ① Healthy, no previous common underlying diseases and no history of genetic disease; ② No history of allergies to drugs, food, pollen and so on; ③Skin prick test (SPT) is negative, allergen-specific IgE (sIgE)< 100IU/mL; the skin test results of β-lactam drugs were negative.</p>
Investigating the DNA methylation profile of e-cigarette use
<p>EWAS of smoking (vs. non-smoking) in SEE-Cigs study (smvsnon_mainmodel.csv)</p> <p>EWAS of e-cigarette use (vs. smoking) in SEE-Cigs study (vapevssm_mainmodel.csv)</p> <p>EWAS of e-cigarette use (vs. non-smoking) in SEE-Cigs study (vapevsnon_mainmodel.csv)</p>
Methylation profiling of Waldenstorm's Macroglobulinemia
<p><span>Currently, the role of DNA methylation in the IgM-monoclonal gammopathy disease spectrum remains poorly understood. In the present study, a multi-omics prospective analysis was conducted integrating DNA methylation, RNA-seq and WES data in 34 subjects [23 WM, 6 IgM-MGUS, 5 normal controls]. Analysis was focused on defining differences between IgM-gammopathies (WM/IgM-MGUS) compared to controls, and specifically between WM and IgM-MGUS. Between groups, genome-wide DNA methylation analysis demonstrated a significant number of differentially methylated regions which were annotated according to genomic region. Next, integration of RNA-seq data was performed to identify potentially epigenetically deregulated pathways. We found that pathways involved in cell cycle, metabolism, cytokine/immune signaling, cytoskeleton, tumor microenvironment, and intracellular signaling were differentially activated and potentially epigenetically regulated. Importantly, there was a positive enrichment of CXCR4 signaling pathway along with several interleukin (IL-6, IL-8, IL15) signaling pathways in WM compared to IgM-MGUS. Further assessment of known tumor suppressor genes and oncogenes uncovered differential promoter methylation of several targets with concordant change in gene expression, including <em>CCND1</em> and <em>CD79B</em>. Overall, this report define how aberrant DNA methylation in IgM-gammopathies may play acritical role in the epigenetic control of oncogenesis and key cellular functions. </span></p>
Analysis of DNA methylation profile of Korean chronic lymphocytic leukaemia (CLL) patients with MeDIP-Seq
<p>In this study, we performed genome-wide methylation profiling of eight CLL patients and five control subjects, in an Asian cohort. Methyl-CpG-binding domain sequencing (MBD-Seq) was used as the profiling method. Differential methylation analysis identified a number of differentially methylated regions (DMRs) and genes (DMGs). More regions were hypomethylated than were hypermethylated. Promoters contained the highest proportion of DMRs, while distal intergenic and intron regions contained the largest number of DMRs. Gene Ontology, pathway analysis, and network-based prioritization of DMGs were also performed.</p>
HG002 data for Profiling Chromatin Accessibility in Humans Using Adenine Methylation and Long-Read Sequencing
<p>This dataset includes 6mA frequency data for the HG002 native DNA (untreated) sample sequenced on nanopore r9.4.1.</p>
NA12878 and MCF7 data for Profiling Chromatin Accessibility in Humans Using Adenine Methylation and Long-Read Sequencing
<p>This dataset includes 5mC and 6mA frequency data for NA12878 and MCF7 EcoGII-treated chromatin samples sequenced on nanopore r9.4.1.</p>
DNA methylation profiling and genomic analysis in 20 children with short stature who were born small-for-gestational age
<p><b><span>Purpose:</span></b> In a significant proportion of children born small-for-gestational age (SGA) with failure of catch-up growth, the etiology of short stature remains unclear after routine diagnostic work-up. We wanted to investigate if extensive analysis of the (epi)genome can unravel the cause of growth failure in a significant portion of these children.</p> <p><b><span>Patients and Methods:</span></b><span> Twenty </span><span>SGA</span><span> children treated with growth hormone (GH) because of short stature were selected from the BELGROW database of the Belgian Society for Pediatric Endocrinology and Diabetology </span>for<span> exome sequencing, SNP array and genome-wide methylation analysis to identify the (epi)genetic cause. First year response to GH was compared to the response of SGA patients in the KIGS database.</span></p> <p><b><span>Results:</span></b><span> We identified (likely) pathogenic variants in 4 children (from 3 families) using exome sequencing and found pathogenic CNV in 2 probands using SNP array. In a child harboring a <i>NSD1</i>-containing microduplication, we identified a DNA methylation signature that is opposite to the genome-wide DNA methylation signature of Sotos syndrome. Moreover, we observed multi-locus imprinting disturbances in two children in whom no other genomic alteration could be identified. Five out of 6 children with a genetic diagnosis had an "above average" response to GH.</span></p> <p><b><span>Conclusions: </span></b><span>The study indicates that a more advanced approach with deep genotyping can unravel unexpected (epi)genomic alterations in SGA children with persistent growth failure. Most SGA children with a genetic diagnosis had a good response to GH treatment.</span></p>
Peripheral blood DNA methylation profiles predict future development of B-cell Non-Hodgkin Lymphoma
<p>Lack of accurate methods for early lymphoma detection limits the ability to cure patients. Patients with Non-Hodgkin lymphomas (NHL) who present with advanced disease have worse outcomes.</p> <p>We developed a DNA methylation-based prediction tool for NHL, based on blood samples collected prospectively from 278 apparently healthy patients who were followed for up to 16 years to monitor for NHL development. A predictive score was developed using machine learning methods in a robust training/validation framework.</p> <p>Our predictive score incorporates CpG DNA methylation at 135 genomic positions, with higher scores predicting higher risk. It was 85% and 78% accurate for identifying patients at risk of developing future NHL, in patients with high or low epigenetic mitotic clock respectively, in a validation cohort. It was also sensitive at detecting active NHL (96.3% accuracy) and healthy status (95.6% accuracy) in additional independent cohorts. Scores optimized for specific NHL subtypes showed significant but lower accuracy for predicting other subtypes. Our score incorporates hyper-methylation of Polycomb and <em>HOX</em> genes, which have roles in NHL development, as well as <em>PAX5</em> - a master transcriptional regulator of B-cell fate. Subjects with higher risk scores showed higher regulatory T-cells, memory B-cells, but lower naïve T helper lymphocytes fractions in the blood.</p> <p>A score based on DNA methylation in blood is accurate at predicting NHL development with lead time of up to 16 years. Future prospective studies will be required to confirm the utility of our signature for managing patients who are at high risk for developing future NHL.</p>
Effects of temperature treatments on cytosine-methylation profiles of diploid and tetraploid plants of the alpine species Ranunculus kuepferi (Ranunculaceae)
<p>The current dataset refers to the DNA methylation patterns of diploid and tetraploid individuals of <em>Ranunculus kuepferi</em>, obtained with the method of methylation-sensitive AFLPs (MS-AFLPs).</p> <p>The individuals of Ranunculus kuepferi were collected from several locations throughout the distribution of the species in the Alps, transferred to the old Botanical Garden of Göttingen and placed into two climate chambers MC1000E (Snijders Scientific, Tilburg, Netherlands), where the temperature treatment experiments took place. In the first chamber a cold treatment was applied (+7°C day/+2°C night; frost treatment: -1°C cold shocks for three nights per week), while in the second chamber a warm treatment was applied (+15° day/+10°C night).</p> <p>The plants were shifted from one treatment to the other one after the end of the 2016 flowering period and leaf material was collected during the flowering period of 2016 and 2017. This material went through the respective lab procedures in order to obtain the genome-wide patterns of epigenetic variation via MS-AFLPs.</p> <p>The analysis of the electropherograms was conducted with Peakscanner v.2 and fragment scoring was performed with RawGeno 2.0-1 R package. These fragment scoring binary matrices are presented here.</p>
The pan-epigenome of the symbiotic nitrogen fixing bacterium Sinorhizobium meliloti unravels unexpected variability of DNA-methylation profiles in closely related strains
<p>Supplementary Dataset S1. Genome coverage data and assignment of contigs to <em>S. meliloti</em> 1021 genome replicons. MS Excel file format (.xlsx file)</p> <p>Supplementary Dataset S2. Folder containing summary pangenome statistics, core and accessory orthologs, alignments and R script. Zip archive</p> <p>Supplementary Dataset S3. Number motifs and methylated motifs identified and their ratio. Data on number of motifs (RAW), number of methylated motifs (METH), fraction of methylated motifs (RATIO) related to functional features (CDSid, tIG and US sequences) and to replicons (CHR, chromosome; PA, pSymA; PB, pSymB and other) are reported. Red color in columns from “other” indicate missing data (i.e., absence of replicons other than chromosome, pSymA, pSymB). .xlsx file</p>
Effect of Vitamin E Supplementation in Methylation and microRNAs Profile
ClinicalTrials.gov study NCT02922491. IPD Sharing: NO. Countries: 1. Publications: 1.
A Single-center, Prospective Cohort Study on the Differentiation of Benign and Malignant Bile Duct Stenosis Based on Bile and Peripheral Blood cfDNA Methylation Profiles
ClinicalTrials.gov study NCT06115655. IPD Sharing: NO. Countries: 1. Publications: 7.
Methyl-donor Nutrient Supplementation and Methylation Profile in Lupus Patients With Obesity
ClinicalTrials.gov study NCT05097365. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Predicting Non-small Cell Lung Cancer (NSCLC) Lymph Node Metastasis: Integrating Circulating Tumor DNA (ctDNA) Mutation/ Methylation Profiling With Positron Emission Tomography-computed Tomography (PE
ClinicalTrials.gov study NCT06358222. IPD Sharing: NO. Countries: 1. Publications: 6.
Epigenome-wide DNA Methylation Profiling in Aneurysmal Subarachnoid Hemorrhage and Delayed Ischemic Neurologic Deficit
ClinicalTrials.gov study NCT06881329. IPD Sharing: YES. Countries: 1. Publications: 1.
Effects of temperature treatments on cytosine-methylation profiles of diploid and tetraploid plants of the alpine species Ranunculus kuepferi (Ranunculaceae)
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