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Longitudinal prediction of DNA methylation to forecast epigenetic outcomes

ABSTRACT: Longitudinal prediction of DNA methylation to forecast epigenetic outcomes

PROVIDER: PRJNA1068624 | ENA |

REPOSITORIES: ENA

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Longitudinal prediction of DNA methylation to forecast epigenetic outcomes

Project description:We introduce a probabilistic and longitudinal machine learning framework based on multi-mean Gaussian processes (GPs), accounting for individual and gene correlations across time. This method provides future predictions of DNA methylation status at different individual ages while accounting for uncertainty.

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REMODEL: A modular framework for longitudinal ctDNA methylation profiling reveals treatment response and relapse-associated epigenetic remodeling

Project description:Circulating tumour DNA (ctDNA) methylation profiling is a promising non-invasive tool for disease monitoring, but longitudinal interpretation is limited by variable sequencing coverage and the loss of clinically relevant signals. We developed REMODEL (Recovery-based Epigenetic Monitoring of Dynamic methylation for Longitudinal analysis), an integrated framework combining coverage-aware binning, count-based longitudinal statistics, and a novel Epigenetic Recovery Score (ERS) to quantify post-treatment methylation recovery. Applied to 17 serial plasma samples from two T-cell lymphoma patients (2,025 genomic bins), REMODEL distinguished durable remission, characterized by coordinated demethylation (86.4% of bins) and sustained positive ERS, from relapse, marked by widespread hypermethylation (64.9% of bins) and persistently negative ERS despite clinical remission. By integrating dynamic methylation detection with recovery modelling, REMODEL provides an interpretable framework for longitudinal ctDNA methylation analysis and minimal residual disease monitoring.

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Prediction of neurological outcomes shortly after cardiac arrest

Project description:Prediction of neurological outcomes shortly after cardiac arrest would represent a major breakthrough. We tested the ability of gene expression profiles of blood cells to predict outcome in cardiac arrest patients. 35 consecutive cardiac arrest patients treated with therapeutic hypothermia (33Â°C for 24h) were included in this prospective monocentre study. Cerebral Performance Category (CPC) was determined at discharge and 6 months later. All patients had blood sampling at the end of hypothermia. Gene expression profiles of blood cells were determined using 25,000~gene microarray in two groups of patients: good outcome (CPC 1-2) and bad outcome (CPC 3-5).

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Developmental Dynamics of Blood DNA Methylation in Dairy Cattle from Birth to Adulthood: a longitudinal study based on enzymatic methyl-sequencing (EM-seq).

Project description:DNA methylation is a key epigenetic mechanism involved in the regulation of gene expression, development, and ageing. It is also one of the most promising biomarkers for biological age prediction, particularly through the development of epigenetic clocks. In this study, we analyzed DNA methylation dynamics in Holstein Friesian dairy cattle across three developmental stages: birth, weaning, and adulthood, using enzymatic methyl-sequencing (EM-seq) data obtained from longitudinal blood samples collected from six female individuals. The results revealed variable methylation profiles across developmental stages, particularly in promoter regions. Differential methylation analysis highlighted marked epigenetic remodeling between birth and weaning (662,571 differentially methylated CpG sites, DMCs), as well as between weaning and adulthood (190,437 DMCs), with a global trend toward hypomethylation in adulthood. Furthermore, estimation of blood cell proportions by deconvolution indicated that methylation variations were partly associated with changes in cellular composition during development, suggesting that age alone did not fully explain the observed variability. Finally, a subset of CpG sites showing consistent and unidirectional methylation changes was identified, representing potential candidates for epigenetic aging biomarkers. These results may contribute to improving epigenetic age prediction models, particularly in young animals, a developmental stage that remains underrepresented in current epigenetic clocks. Overall, this study showed that DNA methylation dynamics in cattle result from an interaction between intrinsic aging processes, immune system maturation, and changes in cellular composition, and provided new insights into epigenetic age estimation in dairy cattle.

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DNA methylation of longitudinal samples from The Swedish Adoption/Twin Study of Aging (SATSA)

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