Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Longitudinal Personal DNA Methylome Dynamics in a Human with a Chronic Condition

ABSTRACT: Epigenomics regulates gene expression and is as important as genomics in precision personal health, as it is heavily influenced by environment and lifestyle. We profiled whole genome DNA methylation and corresponding transcriptome of peripheral blood mononuclear cells collected from a human volunteer over a period of 36 months, generating 28 methylome and 57 transcriptome datasets. We found that DNA methylomic changes are associated with infrequent glucose levels alteration, whereas the transcriptome underwent dynamic changes during events such as viral infections. Most DNA meta-methylome changes occurred 80-90 days prior to clinically detectable glucose elevation. Analysis of the deep personal methylome dataset revealed an unprecedented number of allelic differentially methylated regions (aDMR) which remain stable longitudinally and are preferentially associated with allele-specific gene regulation. Our results revealed that different types of "omics" data associate with different aspects of conditions of this individual: DNA methylation with chronic disease and transcriptome with acute events.

ORGANISM(S): Homo sapiens

PROVIDER: GSE111405 | GEO | 2018/10/05

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Shared Molecules

Only show the datasets with similarity scores above: 0.5

Threshold

0.5

Similar Datasets

Longitudinal analysis of personal cfDNA methylome patterns in metastatic prostate cancer [plasma]

Project description:Disease progression and therapeutic resistance are hallmarks of advanced stage prostate cancer (PCa), which remains a major cause of cancer-related mortality around the world. Longitudinal studies, coupled with the use of liquid biopsies, offer a potentially new and minimally invasive platform to study the dynamics of tumour progression. Our study aimed to investigate the dynamics of personal methylomic profiles of metastatic PCa (mPCa) patients, during disease progression and therapy administration. 52 plasma samples from 9 patients with mPCa were collected, longitudinally, over 13-21 months. After cell-free DNA (cfDNA) isolation, DNA methylation was profiled using the Infinium MethylationEPIC BeadChip and analysed using the minfi software. The top 5% most variable probes across time, within each individual, were utilised to study dynamic methylation patterns during disease progression and therapeutic response. Statistical testing was carried out to identify and validate ctDNA differentially methylated genes (DMGs). Personal cfDNA global methylation patterns were temporally stable throughout disease course. A proportion of analysed CpG sites presented a dynamic temporal pattern that was consistent with clinical events, such as therapy administration, and were prominently associated with immune response pathways. Study of ctDNA identified >2,000 DMGs with dynamic methylation patterns. We concluded that longitudinal assessment of cfDNA methylation in mPCa patients unveiled dynamic patterns associated with the occurrence of specific clinical events, thus highlighting the potential of using liquid biopsies to study PCa progression.

2021-09-01 | GSE157273 | GEO

Longitudinal Personal DNA Methylome Dynamics in a Human with a Chronic Condition

Project description:Longitudinal Personal DNA Methylome Dynamics in a Human with a Chronic Condition

| PRJNA436956 | ENA

Personal Neoantigen Cancer Vaccines

Project description:Personal Neoantigen Cancer Vaccines

| PRJNA401959 | ENA

Personal and transgenerational cues are nonadditive at the phenotypic and molecular level

Project description:Organisms can gain information about their environment from their ancestors, their parents, or their own personal experience. “Cue integration” models often start with the simplifying assumption that information from different sources is additive. Here, we test key assumptions and predictions of cue integration theory at both the phenotypic and molecular level in threespined sticklebacks (Gasterosteus aculeatus). We show that regardless of whether cues about predation risk were provided by their father or acquired through personal experience, sticklebacks produced the same set of predator-adapted phenotypes. Moreover, there were nonadditive effects of personal and paternal experience: animals that received cues from both sources resembled animals that received cues from a single source. A similar pattern was detected at the molecular level: there was a core set of genes that were differentially expressed in the brains of offspring regardless of whether risk was experienced by their father, themselves or both. These results provide strong support for cue integration theory because they show that cues provided by parents and personal experience are comparable at both the phenotypic and molecular level, and draw attention to the importance of nonadditive responses to multiple cues.

2018-06-13 | GSE113548 | GEO

The EN-TEx Resource for Personal Functional Genomics

Project description:An overall goal of functional genomics has been to measure the impact of variants on molecular endophenotypes (e.g. gene expression levels or the degree of TF binding) and relate this to organismal traits and disease phenotypes. However, all the experiments to date have been described relative to a generic reference genome, significantly hobbling their interpretation. Here, we describe a strategy for finding significant relationships between disease variation and genomic annotation via personal functional genomics, by performing personal genome sequencing and paired functional genomics experiments, on the same individual.

2024-05-22 | PXD022787 | Pride

HumanMethylation450 data from the pilot study of the 'Personal Genome Project UK': PGP-UK10 and the first three genome donations

Project description:This study consists of 24 genome-wide methylation profiles which have been generated from blood and saliva samples collected from ten volunteers in the Personal Genome Project UK. The Personal Genome Project UK aims to create publicly available genome, health and trait data, and these ten volunteers represent the pilot study (PGP-UK10) and the first three genome donation participants. These samples were bisulphite converted using the EZ DNA methylation kit (Zymo), using the alternative incubation conditions recommended for HumanMethylation450 BeadChip (Illumina). Genome-wide DNA methylation was then profiled using the HumanMethylation450 BeadChip (Illumina).

2016-12-12 | E-MTAB-5377 | biostudies-arrayexpress

Longitudinal analysis of personal cfDNA methylome patterns in metastatic prostate cancer [plasma]

Project description:Longitudinal analysis of personal cfDNA methylome patterns in metastatic prostate cancer [plasma]

| PRJNA660746 | ENA

Individuality and variation of personal regulomes in human T cells

Project description:We surveyed the variation and dynamics of active regulatory elements genome-wide in CD4+ T cells, using Assay of Transposase Accessible Chromatin with sequencing (ATAC-seq) in longitudinal samples from healthy volunteers and during T cell activation. We created robust pipelines that enable accurate single molecule counting and allelic discrimination from clinical material. Over 4000 regulatory elements (7.2%) showed reproducible personal variation in activity. Gender was the most significant attributable source of regulome variation. ATAC-seq revealed novel elements that escape X chromosome inactivation and predicted gender-specific gene regulatory networks across autosomes, which coordinately impact genes with immune function. Noisy regulatory elements with personal variation in accessibility are significantly enriched for autoimmune disease loci. Over one third of regulome variation lacked genetic variation in cis, suggesting contributions from environmental or epigenetic factors. These results refine concepts of human individuality and provide foundational reference to compare disease-associated regulomes.

2015-06-23 | GSE60682 | GEO

Personal Omics Profiling Reveals Dynamic Molecular Phenotypes and Actionable Medical Risks

Project description:We have determined the whole genome sequence of an individual at high accuracy and performed an integrated analysis of omics profiles over a 1.5 year period that included healthy and two virally infected states. Omics profiling of transcriptomes, proteomes, cytokines, metabolomes and autoantibodyomes from blood components have revealed extensive, dynamic and broad changes in diverse molecular components and biological pathways that occurred during healthy and disease states. Many changes were associated with allele- and edit-specific expression at the RNA and protein levels, which may contribute to personalized responses. Importantly, genomic information was also used to predict medical risks, including Type II Diabetes (T2D), whose onset was observed during the course of our study using standard clinical tests and molecular profiles, and whose disease progression was monitored and subsequently partially managed. Our study demonstrates that longitudinal personal omics profiling can relate genomic information to global functional omics activity for physiological and medical interpretation of healthy and disease states.

2012-03-16 | GSE32874 | GEO

RNA-seq data from the pilot study of the 'Personal Genome Project UK': PGP-UK10

Project description:This study consists of 10 whole genome RNA-seq profiles which have been generated from blood samples collected from ten different volunteers in the Personal Genome Project UK

2018-03-04 | E-MTAB-6523 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data