Methylation entropy landscape of Chinese long-lived individuals reveals lower epigenetic noise related to human healthy aging.
Hao-Tian WangFu-Hui XiaoZong-Liang GaoLi-Yun GuoLi-Qin YangGong-Hua LiQing-Peng KongPublished in: Aging cell (2024)
The transition from ordered to noisy is a significant epigenetic signature of aging and age-related disease. As a paradigm of healthy human aging and longevity, long-lived individuals (LLI, >90 years old) may possess characteristic strategies in coping with the disordered epigenetic regulation. In this study, we constructed high-resolution blood epigenetic noise landscapes for this cohort by a methylation entropy (ME) method using whole genome bisulfite sequencing (WGBS). Although a universal increase in global ME occurred with chronological age in general control samples, this trend was suppressed in LLIs. Importantly, we identified 38,923 genomic regions with LLI-specific lower ME (LLI-specific lower entropy regions, for short, LLI-specific LERs). These regions were overrepresented in promoters, which likely function in transcriptional noise suppression. Genes associated with LLI-specific LERs have a considerable impact on SNP-based heritability of some aging-related disorders (e.g., asthma and stroke). Furthermore, neutrophil was identified as the primary cell type sustaining LLI-specific LERs. Our results highlight the stability of epigenetic order in promoters of genes involved with aging and age-related disorders within LLI epigenomes. This unique epigenetic feature reveals a previously unknown role of epigenetic order maintenance in specific genomic regions of LLIs, which helps open a new avenue on the epigenetic regulation mechanism in human healthy aging and longevity.
Keyphrases
- dna methylation
- gene expression
- endothelial cells
- high resolution
- genome wide
- air pollution
- machine learning
- atrial fibrillation
- depressive symptoms
- oxidative stress
- chronic obstructive pulmonary disease
- copy number
- cystic fibrosis
- deep learning
- brain injury
- transcription factor
- wastewater treatment
- genetic diversity