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From aging to Alzheimer’s disease: brain DNA methylation changes in late life

David Lukacsovich, Juan I. Young, Lissette Gomez, Michael A. Schmidt, Wei Zhang, Brian W. Kunkle, Xi Chen, Eden R. Martin, Lily Wang

Description

This GitHub repository includes scripts used for the analyses in the above manuscript.

Aging is a major risk factor for Alzheimer’s disease (AD), but the molecular processes linking aging to AD remain unclear. We studied brain DNA methylation (DNAm) changes in normal aging versus AD in late life. Our comprehensive meta-analysis of two large cohorts of postmortem prefrontal cortex samples from subjects over 65 years old identified numerous DNAm differences consistently associated with aging in both cohorts, highlighting key genes such as ELOVL2, ISM1, and KLF14, which are implicated in various aging processes. These DNAm differences are predominantly hypermethylated, enriched in promoter regions, and associated with genes involved in immune processes and metabolic functions. Our results also revealed significant overlaps between aging-associated DNAm differences and those involved in AD, supporting the hypothesis that aging and AD are interconnected at the molecular level. Intriguingly, nearly all DNAm differences significantly associated with both age (at death) and AD Braak stage showed concordant effect sizes in the same direction. Our study provides valuable insights into the aging-associated epigenetic landscape and its potential implications for AD. As aging and AD are intertwined, targeting age-related epigenetic modifications may offer new therapeutic strategies for AD.

1. Pre-processing DNA methylation data

File Dataset Link
code/markdown/01a_prepare_BDR_data.Rmd BDR Link to the script
code/markdown/01a_prepare_Rosmap_data.Rmd Rosmap Link to the script
code/markdown/01b_preprocess_BDR_data.Rmd BDR Link to the script
code/markdown/01b_preprocess_Rosmap_data.Rmd Rosmap Link to the script

2. Single cohort and meta-analysis

File Link
code/markdown/02a_associate_data.Rmd Link to the script
code/markdown/02b_association_meta_analysis.Rmd Link to the script
code/markdown/02c_association_signif_probes.Rmd Link to the script

3. DMR and enrichment analyses

File Link
code/markdown/03a_cometh_dmr.Rmd Link to the script
code/markdown/03b_cometh_dmr_meta_analysis.Rmd Link to the script
code/markdown/03c_Annotate_combp.Rmd Link to the script
code/markdown/03d_merge_cometh_dmr_combp.Rmd Link to the script
code/markdown/03e_enrichment_analysis.Rmd Link to the script
code/markdown/03f_enrichment_analysis_figures.Rmd Link to the script

4. Correlation of aging-associated CpGs and DMRs methylation levels in blood and brain samples

File Link
code/markdown/04a_brain_blood_correlation.Rmd Link to the script

5. Correlation between aging-associated DNAm with expressions of nearby genes

File Link
code/markdown/05a_get_DNAm_Data.Rmd Link to the script
code/markdown/05b_preprocess_DNAm_Data.Rmd Link to the script
code/markdown/05c_get_DNAm_residuals.Rmd Link to the script
code/markdown/05d_get_DMR_residuals.Rmd Link to the script
code/markdown/05e_get_RNA_residuals.Rmd Link to the script
code/markdown/05f_associate_RNA_to_DNAm.Rmd Link to the script
code/markdown/05g_sensitivity_analysis.Rmd Link to the script

6. Creating figures

File Link
code/markdown/06a_aging_vs_ad_miami.Rmd Link to the script
code/markdown/06b_venn_diagram.Rmd Link to the script
code/markdown/06c_epigenetic_association.Rmd Link to the script
code/markdown/06d_check_against_miamiad.Rmd Link to the script
code/markdown/06e_get_matched_samples.Rmd Link to the script

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