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| Étude d'association pangénomique multi-omique de l'épigénome× | Étude d'association pangénomique épigénétique (EWAS)× | |
|---|---|---|
| Domaine | Bio-informatique | Bio-informatique |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 2011 (EWAS foundation); multi-omics integration ~2015–2020 | 2008–2011 (term and framework established c. 2011) |
| Auteur d'origine≠ | Rakyan, Down, Balding & Beck (EWAS framework); multi-omics integration extended by multiple groups (~2015–2020) | Rakyan, Down, Balding & Beck (conceptual framework); Illumina arrays enabled large-scale application |
| Type≠ | Integrative association study | Population-scale epigenomic association study |
| Source fondatrice | Rakyan, V. K., Down, T. A., Balding, D. J., & Beck, S. (2011). Epigenome-wide association studies for common human diseases. Nature Reviews Genetics, 12(8), 529–541. DOI ↗ | Rakyan, V. K., Down, T. A., Balding, D. J., & Beck, S. (2011). Epigenome-wide association studies for common human diseases. Nature Reviews Genetics, 12(8), 529–541. DOI ↗ |
| Alias | multi-omics EWAS, integrative EWAS, multi-layer epigenome-wide association, multi-omics epigenomic integration | EWAS, methylome-wide association study, epigenetic association study, DNA methylation association study |
| Apparentées≠ | 4 | 5 |
| Résumé≠ | A multi-omics epigenome-wide association study (multi-omics EWAS) systematically scans the entire epigenome — typically DNA methylation at CpG sites — for associations with a phenotype of interest, then integrates findings across additional omics layers such as transcriptomics, genomics, proteomics, or metabolomics. By linking epigenetic variation to molecular changes at multiple biological levels simultaneously, this approach identifies regulatory mechanisms and biomarkers that single-omics EWAS cannot resolve. | An epigenome-wide association study (EWAS) is a hypothesis-free, genome-scale method that systematically tests whether epigenetic marks — predominantly CpG-site DNA methylation — differ between individuals with and without a trait, disease, or exposure. By scanning hundreds of thousands of genomic positions simultaneously, EWAS identifies loci where the epigenome is reproducibly associated with a phenotype, offering a layer of biological regulation that classical GWAS does not capture. |
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