Longitudinal Personal DNA Methylome Dynamics in a Human with a Chronic Condition
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ABSTRACT:
PROVIDER: PRJNA436956 | ENA |
REPOSITORIES: ENA
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Project description: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.
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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.
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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
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. We examined chromatin structure using ATAC-seq in purified human CD4+ T cells in 33 samples from 12 healthy donors and 15 samples from 3 patients with cutaneous T cell leukemia (CTCL). For T cell activation (TCA) time course, CD4+ cells from healthy donor 1 isolated as above were stimulated with ionomycin (1 ug/mL) and Phorbol Myristate Acetate (PMA; 20 ng/mL) and collected at 0, 1, 2, 4 hours in duplicate.
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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.
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