Epigenetic DNA modifications are changes in gene expression that are not caused by changes in the DNA sequence itself, but instead, they are alterations to the DNA molecule or to the proteins that interact with DNA. These modifications can be passed down from one generation to another and can be influenced by various factors, such as diet, lifestyle, and environmental exposures.
There are several types of epigenetic DNA modifications, including:
- DNA methylation: This involves the addition of a methyl group to the DNA molecule, which can turn off or reduce the expression of a particular gene.
- Histone modifications: Histones are proteins that help package DNA into a compact structure called chromatin. Modifications to histones can affect how tightly the chromatin is packed, which can influence gene expression.
- Non-coding RNA molecules: These are RNA molecules that do not code for proteins but can regulate gene expression by binding to DNA or RNA molecules.
Epigenetic DNA modifications play a critical role in regulating gene expression, and abnormalities in these modifications have been linked to various diseases, including cancer, cardiovascular disease, and neurodegenerative disorders. However, epigenetic modifications are also influenced by lifestyle choices, and certain lifestyle interventions, such as exercise and a healthy diet, may help promote healthy epigenetic modifications and reduce the risk of age-related diseases.
https://doi.org/10.1186/s40035-021-00254-1
Epigenetic DNA modifications have been used to determine biological age, which refers to how old a person's body appears to be based on biological markers, rather than their chronological age.
What is Biological age and how it is determined?
Biological age refers to the biological state of an organism, which may or may not correspond with its chronological age. While chronological age is simply a person's age in years, biological age takes into account various physiological and cellular changes that occur over time and can influence an individual's health and aging process.
Some examples of factors that can contribute to biological age include:
- Epigenetic modifications: Changes in gene expression patterns that can occur as a result of lifestyle and environmental factors.
- Telomere length: Telomeres are the protective caps at the end of chromosomes that shorten with age and are associated with cellular aging.
- Inflammation: Chronic inflammation has been linked to numerous age-related diseases.
- Oxidative stress: The accumulation of oxidative damage can contribute to cellular aging and age-related diseases.
Biological age can be influenced by a variety of factors, including genetics, lifestyle, and environmental exposures. While some of these factors, such as genetics, are beyond our control, lifestyle factors such as diet, exercise, and stress management can also play a significant role in determining biological age.
Determining biological age can be useful in predicting an individual's risk of age-related diseases and mortality and can also help guide lifestyle interventions aimed at promoting healthy aging. However, measuring biological age is still an evolving field, and more research is needed to fully understand the relationship between biological age and health outcomes.
One approach to determining biological age using epigenetic DNA modifications is to measure DNA methylation patterns at specific locations on the genome, known as epigenetic clocks. These clocks are based on the idea that changes in DNA methylation patterns occur predictably over time and can be used to estimate a person's biological age.
Several epigenetic clocks have been developed, with the most well-known being the Horvath clock and the Hannum clock. These clocks use DNA methylation data from a set of CpG sites (specific DNA sequences that tend to be methylated) to estimate biological age.
Studies have shown that these epigenetic clocks can be used to predict mortality risk and age-related diseases, such as cardiovascular disease and Alzheimer's disease, independently of chronological age. Additionally, lifestyle factors such as exercise, diet, and stress have been shown to influence epigenetic clocks, suggesting that they may be modifiable with lifestyle interventions.
What is TruAge Index test? How was it developed?
As the search for interventions to delay or reverse the aging process continues, having a reliable, universal, and affordable method for measuring biological age will be essential for evaluating the effectiveness of these interventions. TruMe Labs was founded with the goal of building a unique platform for measuring biological age. The TruMe scientists have focused on several key aspects in the design of this test:
- Self-sampling protocol: The test should be easily adapted to a self-sampling protocol, which would make it more convenient for individuals to take the test from the comfort of their own homes.
- Accuracy: The TruAge test should accurately predict an individual's biological age with a small margin of error, with a mean absolute deviation (MAD) of no more than 5 years. This means that the TruAge test should be able to estimate an individual's biological age with high precision.
- Cost-effectiveness: The testing method should be cost-effective, which could make it more accessible to a wider range of individuals.
- Quick turnaround time: The testing process should have a quick turnaround time, which could make it more appealing for individuals who are interested in learning about their biological age in a timely manner.
- Low margin of error for subsequent samples: The margin of error for subsequent samples should be no more than two months, which would allow individuals to track changes in their biological age over time with high accuracy.
TruAge Index test that aims to accurately predict an individual's biological age based on DNA methylation patterns. The TruMe scientists narrowed down age-related CpG sites that are either hypermethylated or hypomethylated during the aging process in different tissue samples, and analyzed publicly available DNAm profiles derived from saliva/buccal swabs samples that can best predict donor age.
After narrowing down to 32 CpG markers that showed a high overlap between all data sets and a high correlation between DNA methylation patterns and age, the TruMe scientists used machine learning approach to combine these markers in 4 groups that individually demonstrated a high correlation between predicted and chronological age, with mean absolute deviation (MAD) from chronological age ranging from 3.4-5.5 years.
The TruMe scientists then selected 9 highly correlated CpG sites for locus-specific DNAm analysis by Sanger sequencing or pyrosequencing for the initial in-depth validation of the TruAge Index method (TruAge Index).
To validate the TruAge Index, the TruMe scientists analyzed the biological age of 105 individuals using 3 CpG models and found reasonable precision in predictions of chronological age, with a current MAD of 4.8 years and sampling variation of +/- 0.1 years. They expect their model to improve significantly with a larger number of samples or by simultaneous measurement of additional age-associated DNAm markers.
TruMe Inc. may have conducted a clinical trial of their TruAge Index epigenetic test in partnership with Ponce de Lion Health. Clinical trials are an essential step in validating the safety and efficacy of new medical interventions, including diagnostic tests such as TruAge Index. It's encouraging to hear that TruMe Inc. is pursuing this rigorous process to ensure that their test is accurate, reliable, and safe for use in a clinical setting. In addition we were able to validate our algorithm for measuring biological age has been validated on subjects who were evaluated by clinicians. This additional validation supports the idea that biological age, as measured by epigenetic age clocks or other biomarkers, is more than just a reflection of chronological age. Instead, it reflects the physiological state of the individual and can provide insights into their health and aging process.
Overall, the TruAge Index test appears to be a promising tool for predicting biological age based on DNA methylation patterns, with a high degree of precision and a relatively low margin of error. However, further validation and refinement of the method will be necessary to improve its accuracy and reliability.
Ultimately, the goal of measuring biological age is to identify interventions that can promote healthy aging and extend lifespan. By validating your algorithm on subjects who were evaluated by clinicians, you are taking an important step toward this goal and providing further evidence for the potential of epigenetic age clocks to improve our understanding of the aging process.