Several age-related methylation changes occur in neurologic and developmental pathways, says new research.

Aging is a biological process that is characterized by a gradual decline in the function of organs leading to increased vulnerability to several diseases. We can see and feel it happening, but the process also happens on a molecular level – research has highlighted epigenetic modifications such as DNA methylation, histone modification, noncoding RNAs and others play an important role in the progression of aging [1].

Longevity.Technology: Several DNA epigenetic clocks have been built with DNA methylation-based biomarkers that use sets of CpGs (sequences of nucleotides that can be methylated) and a mathematical algorithm for the prediction of the biological age of individuals, organs and cells. One of the initial clocks was developed by Horvath and Hannum, and since then, about 15 further clocks have been developed. However, since methylation in human samples involves less than 10% of the DNA examined, information is not available about all DNA methylation changes that occur in human tissues over the course of aging. Moreover, most of the DNA methylation is limited to a certain set of CpG sites and indicate changes that occur only in such sites.

A new study in Aging Cell used an unbiased whole-genome bisulfite sequencing approach using two cell types (monocytes and muscle cells) with opposite relationships to cell turnover to determine DNA methylation across most of the genome [2].

With a comparatively short lifespan, monocytes turn over fast; muscle cells, on the other hand, live relatively longer. And they are both useful from a longevity research point of view, as changes in muscle cells can help to determine sarcopenia, while changes in monocytes can help to determine the decline of immune function with aging. Three different analyses were performed to relate genome-wide methylation levels to age followed by annotation of regions and sites whose methylation pattern changes with age. Finally, those sets of genes were fitted to pathways and gene ontology to understand the pathways associated with aging.

The results reported 6780 aging-associated differentially methylated CpG positions (aDMPs) in muscle cells and 29,492 aging-associated CpGs aDMPs in monocytes. Most of the age-associated CpG sites were observed to occur within genes for both monocyte and muscle.

The pathways regulated by aging-associated methylation changes were reported to be RUNX pathways along with Notch, ROBO, and MECP2 pathways in muscle. The pathways in monocyte included ROBO, Notch, MECP2, ERBB4, and RUNX pathways. Both monocyte and muscle pathways also included several neuronal pathways [2].

Changes in aging methylation were observed to peak around 52 and 62 for muscle and 33 and 37–42 for monocyte. 2372 aging-associated differentially methylated regions (aDMRs) were reported for muscle samples comprising 20 young individuals and 22 older individuals while 2263 aDMRs were reported for monocyte samples comprising 20 young and older individuals. The majority of aDMRs were observed to be hypomethylated with an average length of 6 CpGs.

The Notch pathway was found to be highly represented in muscle while extracellular matrix remodeling and RUNX pathways were highly represented in monocyte. The primary modules reported to be overrepresented in muscle included cAMP-mediated signaling, protein translation, and muscle contraction. The modules overrepresented in monocytes included phagocytosis, nucleotide metabolism, DNA conformation regulation, cell migration, and cell–cell adhesion. Finally, 4 CpGs were observed to be common for muscle and 12 for monocytes for the three analyses [2].

Indicating that changes in methylation occur with aging at regions enriched for nerve and developmental pathways for both monocytes and muscle cells, this study adds to our understanding of changes to the epigenome that take place in human aging. However, this research is at an early stage and further development needs to take place before it can be used as an alternative for the microarray-based methylation analysis that the current aging clocks use – but it is very much a case of ‘watch this space’ as this could prove to be a very useful tool in the future.

[1] https://www.hindawi.com/journals/sci/2020/1047896/
[2] https://onlinelibrary.wiley.com/doi/full/10.1111/acel.13847