Ageing is associated with declining physical and cognitive function, and is a huge risk factor for several brain disorders, including dementia, Parkinson’s disease and other neurodegenerative diseases. Having an understanding of the biological mechanisms involved in ageing will be a vital step towards preventing, slowing or reversing age-associated characteristics and diseases. While our circadian body clock determines our preferred rhythm of sleep and wakefulness, a fairly novel concept, referred to as ‘the epigenetic clock’, could inform us about how quickly we age, and how susceptible we are to diseases of old age. Several studies have generated estimates of biological age; these include measures of physical fitness (e.g. muscle strength), characteristics of certain cells (e.g. cellular deterioration), genomic changes (e.g. length of telomeres, which are protective regions found at the end of chromosomes) and epigenetic mechanisms (e.g. DNA methylation).
Epigenetic mechanisms act to regulate gene expression developmentally, through chemical modifications to DNA and its associated proteins. There has been recent interest in one specific epigenetic modification – DNA methylation (DNAm) – which appears to be highly predictive of chronological age. DNA methylation is the addition of a methyl group, which is a functional group with the chemical formula –CH3, to the DNA molecule. Recently, a number of tissue-specific DNAm clocks have been described, including clocks designed for whole blood, muscle, bone and paediatric buccal cells (found in the mouth/cheek). Although these DNAm age estimators have increased predictive accuracy within the specific tissues in which they were built, they lose this precision when applied to other tissues, especially the central nervous system in the brain, and older samples (>60 years). A study carried out by researchers at the University of Exeter aimed to develop a novel DNAm clock that is specifically designed for application in DNA samples isolated from the human brain, is accurate across the lifespan including in tissue from older donors (aged over 60 years), and has the potential to identify characteristics associated with biological ageing in the brain.
The researchers gathered a wide-ranging dataset of human brain DNAm data spanning the life course, with 1397 participants’ brain samples varying from the ages of 1 to 108 years of age. This dataset was split into ‘training’ and ‘testing’ samples (training = 1047, testing = 350). The researchers focussed on building a DNAm clock using relevant tissue samples from donors that spanned a broad range of ages and included a large number of samples from older donors. The DNAm age estimators were derived using various statistical methods. Their approach identified a set of 347 DNAm sites which, in combination, optimally predict age in the human cortex (the human cortex being the outer layer of the human brain).
The researchers also found that the novel clock dramatically outperformed previously reported clocks in additional brain datasets. They found that existing DNAm clocks do not perform optimally in human cortex tissue, with significant differences between derived DNAm age and actual chronological age. The most striking differences were in the accuracy of the novel DNAm clock in comparison to previously developed DNAm clocks; it outperformed the three other clocks they tested across all accuracy statistics in both brain datasets.
In summary, the study showed that previous epigenetic clocks systematically underestimate age in older samples and do not perform as well in human cortex tissue. The researchers developed an accurate novel epigenetic age model specifically for human cortex. The research team is now working on using the model on brain samples of people who had Alzheimer’s disease. They hypothesise that they will find evidence for increased biological ageing in these samples.
Original Source: Shireby GL, Davies JP, Francis PT, Burrage J, Walker EM, Neilson GWA, Dahir A, Thomas AJ, Love S, Smith RG, et. al., (2020). Recalibrating the epigenetic clock: implications for assessing biological age in the human cortex, Brain.
“Epigenetics: Nature vs Nurture”. Youtube. Universitetet i Oslo (January 2016).
Featured image source: Motion Array. “How to create a double helix in adobe after effects”, Tutorials. (September 2019).