What are the Biological Age Predictors?

Scientists have searched for reliable indicators for human biological age instead of chronological age for around thirty years. They have used DNA Extraction Kit and many other sophisticated technologies to identify the difference and the factors influencing the biological age.

All thanks to successive inventions in molecular biology, scientists have come across an abundance of various candidate biomarkers that could potentially serve as predictors for biological age. In the following article, we would summarise the current findings of the biological age predictors.

What does state-of-the-art research reveal?

Since the biological age predictors are revealed by painstaking research and studies, it is quite understandable that these predictors are multiple molecules.

Although researchers have declared six predictors, some predictors have more influence on biological aging than others. For instance, the epigenetic clock is a predictor that is known for being the biomarker of aging.

Why is chronological age not reliable?

Although chronological age is a significant risk factor for chronic diseases, functional impairment, and mortality, there is significant heterogeneity in the medical conditions of older people. This is why some people in their 70s  would need medical assistance 24/7, while others would remain independent. Similarly, some older people would even escape average physiological deterioration. 

By considering everything, there is a thriving urge for a much better understanding of biological aging and all the determinants that directly or indirectly influence it. Keeping this aim in sight, there is an ongoing quest for the marker that keeps track of physiological aging and produces insights into the mechanisms. 

• The Epigenetic Clock

According to several studies and extensive research using RNA Extraction Kit, a considerable amount of DNA methylation is known as the epigenetic clock, i.e. a top biological age predictor. 

There are two types of this clock, i.e. Horvath, 2013 and Hannum et al., 2013. These clocks are considered as the calculators that accurately measure chronological age. Both the clocks have a remarkable correlation. They provide very small and mean deviations from the calendar. Usually, the difference between biological and chronological is somewhere close to 3.6 to 4.9 years. 

• DNAmAge and Mortality

One of the most incredible features of Horvath and Hannum is that both of these clocks can predict all the potential causes of mortality without being dependent on general risk factors. 

A late meta-analysis showed around 13 different cohorts in a complete sample of 13,089  demonstrations. The risk factors that any efficient epigenetic can predict include body mass index (BMI), age, education, alcohol use, physical; activity, smoking, and comorbidities. 

A few exceptions were found when the scientific authors branched the samples into sex, race, BMI, follow-up time, smoking status, etc. These exceptions had a similar association with the subgroups of mortality.

• DNAmAge and Diseases related to Ageing

Series of studies have revealed the association between DNAmAge and age-related diseases. Notably, there is an increasing acceleration rate of the Horvath clock in Alzheimer’s Disease (AD). In this condition, the patients’ prefrontal cortex is linked with amyloid load, plaques, and sharply declining episodic memory, cognitive functioning, and working memory. 

However, when non-demented individuals were observed under the study, there was no association between memory and cognition. The latter findings are more aligned with the results of the recent study. 

• Correlations between telomere length and DNAmAge 

If we talk about the correlation specifically, we will find out that it is barely or present in an almost negligible amount. 

Telomere length and DNAmAge are very intricately associated with mortality and age, and they are entirely independent of each other, 

Furthermore, the cell type adjusted by the Horvath clock does not have any links with general ailment factors such as smoking, alcohol use, hypertension, diabetes, increasing or decreasing density of macromolecules like insulin, lipoproteins, triglycerides, glucose, creatinine, and C-reactive protein (CRP). 

Another intriguing feature of the epigenetic clock is its offspring of semi-supercentenarians that decrease epigenetic in several age-matched controls. To further make it clear, there is an ideal example of centenarians. These people are healthy and prosperous agers who somehow have managed to escape the onset of myriads of diseases that emerge from aging. 

Bibliography

Jylhävä, J., Pedersen, N. L., & Hägg, S. (2017, Apiril 1). Biological Age Predictors. PMC US National Library of Medicine National Institutes of medicine. https://www.ncbi.nlm.nih.gov/pmc/