The most important question in biology is to learn why we age and how it happens. There has been significant growth in the average life expectancy of humans, ever since the mid-twentieth century. This has led to a good increase in both the amount of older people and their proportion in the total population. This change occurring in the demography is changing the dynamics of the society, where 5% of the world population in 1950 that were 65 years older to go above 17% by the end of 2050. That being said, the problem is that there hasn’t been much success in reducing the mortality rates even though the rates of chronic diseases (Christopher, et al., 2019) have gone down lately. This is why there is a massive problem faced by people who live for long but spend most of their lives in ill health, and also become a burden on the health care system. The only appropriate solution is to increase productivity and diminish the possibility of disease affliction in the latter years of life. This would prove to be extremely beneficial for the individuals and for the macro-level too. (Partridge, Deelen, &Slagboom, 2018)
The main goal is to maximize the health span instead of lifespan, and this makes gathering the exact measure of age-related pathology very important. There is a need to measure the speed, determine the changes that happen, and ultimately figure out how ageing is responsible for the disease risk factor. A lot of people are ageing and becoming impaired due to age-related family issues and related diseases. If this biological ageing is measured properly, this can allow pre-emptive targeting and health-improving interventions can be made. This can be done for a personalized way for specific diseases, for starters. This will also further help in testing and examining interventions that are responsible for modulating the ageing process.
The benchmarks set for cellular and molecular ageing have a lot of changes attached with cell senescence, stem cell exhaustion and dysregulated nutrient sensing, among many other factors. Thus, several biological measures like the p16 tissue levels, glucose levels, telomere length, circulating CRP creatinine, and others have a significant relationship with ageing.
In recent times, scientists have come across the amazing power of epigenetic alterations that are useful in estimating a person’s age (Hovarth& Raj, 2018). Epigenetics includes all the chemical changes and modifications along with the packaging of the genome that impacts the activity. This comes with strict definitions that need inheritance with the help of mitotic cell division. Scientists have been measuring and observing how age impacts this mechanism for several decades and they have suggested a role in age-related diseases. With that being said, the link between epigenetic evolutions and modifications as well as age are very vivid with the coming of the initial high-throughput arrays that measure DNA methylation. All this high-resolution data has made easy the construction and development of accurate age estimators, which are known as “epigenetic” or more commonly the “DNA methylation clocks”. Eventually, these clocks were observed to capture the key areas of biological ageing and all the associated mortality. DNA methylation is termed as the most common modification that occurs in DNA and it happens at cytosines in a CpG dinucleotide environment in differentiated mammal cells.
Several studies have discussed challenges faced in the interesting discovery of DNA methylation clocks. DNA methylation clock is said to be an estimator built from epigenetic DNA methylation marks that are heavily related with the chronological ageing. Through this, the age-related phenotype or the outcome are accurately quantified. The DNA methylation clocks are usually made with a supervised AI method or sometimes with machine learning methods like regression. The error and residual from the chronological age is utilised as an important market for the biological age of a person. all age-related phenotypes or the outcomes can be a disease, mortality, cellular phenotypes, or clinical frailty that also includes the mitotic age. Mitotic age is also referred to as the total number of lifetime cell divisions in a tissue.
References
Christopher, Robert, Peter, Andrea, Stephan, Jordana,. . . Trey. (2019). DNA methylation ageing clocks: challenges and recommendations. Genome Biology.
Hovarth, & Raj. (2018). DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat Rev Genet, 19, 371-384.
Partridge, Deelen, &Slagboom. (2018). Facing up to the global challenges of ageing. Nature, 45-56.
