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Updated: Jan 6, 2026

Optimized Analysis of DNA Methylation and Gene Expression from Small, Anatomically-defined Areas of the Brain
Published on: July 12, 2012
Integrative DNA methylation and transcriptome analysis reveal cell-type specific patterns in response to elevated
O Emery1,2, C Carmeli3, S Gonseth-Nusslé4
1Department of Health Promotion and Prevention (DPSP), Unisanté, University Center for Primary Care and Public Health, Lausanne, Switzerland.
None:
Allostatic load (AL) is a measure of the body's multi-systemic physiological dysregulation in response to chronic stress and life events. High AL has been associated with poor long-term health outcomes such as cardiovascular disease and mortality. DNA methylation (DNAm) is an epigenetic mechanism involving both genes and environmental factors and contributes to gene expression regulation. Hence, changes in AL can possibly be reflected in DNAm and gene expression differences and leveraging epigenetic and transcriptomic data together can help elucidate the underlying biological processes involved. To assess differential DNAm and gene expression between high and low AL in a cell-type specific manner, bulk DNAm and transcriptome signals from whole blood samples of 429 individuals from the Swiss Kidney Project On Genes in Hypertension (SKIPOGH) cohort were first deconvoluted into cell-type specific signals for six blood cell types using tensor composition analysis (TCA) and the software CIBERSORTx. For each cell type, DNAm associated with gene expression changes was then determined in high (N = 126) vs low (N = 303) AL groups. A total of 263 CpG-gene pairs were identified across all cell types, corresponding to 250 unique CpGs and 138 unique differentially methylated genes (DMGs). Several immune processes were enriched among downregulated genes of CD8 T and B cells, suggesting an impairment of the immune response, which is compatible with high AL. These findings highlight the importance of using cell-specific signals in DNAm and transcriptome analyses and may contribute to identify AL biomarkers and/or potential therapeutic targets.
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