Abstract
The impact of healthy aging on molecular programming of immune cells is poorly understood. Here we report comprehensive characterization of healthy aging in human classical monocytes, with a focus on epigenomic, transcriptomic and proteomic alterations, as well as the corresponding proteomic and metabolomic data for plasma, using healthy cohorts of 20 young and 20 older males (~27 and ~64 years old on average). For each individual, we performed enhanced reduced representation bisulfite sequencing-based DNA methylation profiling, which allowed us to identify a set of age-associated differentially methylated regions (DMRs)—a novel, cell-type-specific signature of aging in the DNA methylome. Hypermethylation events were associated with H3K27me3 in the CpG islands near promoters of lowly expressed genes, while hypomethylated DMRs were enriched in H3K4me1-marked regions and associated with age-related increase of expression of the corresponding genes, providing a link between DNA methylation and age-associated transcriptional changes in primary human cells.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 124-141 |
| Number of pages | 18 |
| Journal | Nature Aging |
| Volume | 1 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2021 |
Bibliographical note
Funding Information:The study was supported by funding from the Aging Biology Foundation to the Artyomov laboratory. The Bagaitkar lab is partially supported by GM125504 and DE28296. The Dixit lab is supported in part by NIH grants P01AG051459, AI105097, AG051459 and AR070811, the Glenn Foundation on Aging Research and Cure Alzheimer’s Fund. This publication is solely the responsibility of the authors and does not necessarily represent the official view of the National Centre for Research Resources (NCRR) or the National Institutes of Health (NIH). We thank the Genome Technology Access Centre in the Department of Genetics at Washington University School of Medicine for help with genomic analysis. The centre is partially supported by NCI Cancer Centre Support grant number P30 CA91842 to the Siteman Cancer Centre and by ICTS/CTSA grant number UL1TR000448 from the NCRR, a component of the NIH, and the NIH Roadmap for Medical Research. We also thank the Epigenomic Core of Weill Cornell Medicine for the initial analysis of the methylation data (eRRBS and raw data pre-processing). We acknowledge the ENCODE consortium and the ENCODE production laboratories that generated the datasets used in the manuscript. We thank I. Miralda for the Fig. 1 schematic.
Funding Information:
The study was supported by funding from the Aging Biology Foundation to the Artyomov laboratory. The Bagaitkar lab is partially supported by GM125504 and DE28296. The Dixit lab is supported in part by NIH grants P01AG051459, AI105097, AG051459 and AR070811, the Glenn Foundation on Aging Research and Cure Alzheimer’s Fund. This publication is solely the responsibility of the authors and does not necessarily represent the official view of the National Centre for Research Resources (NCRR) or the National Institutes of Health (NIH). We thank the Genome Technology Access Centre in the Department of Genetics at Washington University School of Medicine for help with genomic analysis. The centre is partially supported by NCI Cancer Centre Support grant number P30 CA91842 to the Siteman Cancer Centre and by ICTS/CTSA grant number UL1TR000448 from the NCRR, a component of the NIH, and the NIH Roadmap for Medical Research. We also thank the Epigenomic Core of Weill Cornell Medicine for the initial analysis of the methylation data (eRRBS and raw data pre-processing). We acknowledge the ENCODE consortium and the ENCODE production laboratories that generated the datasets used in the manuscript. We thank I. Miralda for the Fig. 1 schematic.
Publisher Copyright:
© 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.
