UCLA researchers in the Department of Human Genetics and Biostatistics have developed a tool that utilizes DNA methylation biomarkers to estimate telomere length. The technology has great potential to monitor and evaluate interventions applied to age-related conditions.
BACKGROUND:
Telomeres are repetitive nucleotide sequences at the end of chromosomes that are not replicated during DNA synthesis of somatic cells and therefore shorten after each cell division. It is proposed that since the accumulated number of cell division in a body increases with age, telomere length can be used as a convenient age-indicator. Relative leukocyte telomere length (LTL) can be an indirect indicator of the general state of health of the body and is associated with several conditions including cardiovascular disease, psychological stress, and lifespan. Another DNA based biomarker that changes with age is the level of DNA methylation; specifically of cytosine residues of cytosine-phosphate-guanine dinucleotides (CpGs). Machine learning-based analyses of these changes have generated algorithms, known as epigenetic clocks, that use specific CpG methylation levels to accurately estimate age that is referred to as DNA methylation age (DNAm age). DNAm aging assays are already highly robust and ready for biomarker development. By contrast, the measurement of telomere length continues to encounter technical challenges and can be subject to technical confounding factors. It would be ideal if the robustness inherent in DNA methylation analyses can be extended to telomere length measurement.
INNOVATION:
UCLA researchers have developed a novel DNAm-based estimator of leukocyte telomere length (DNAm LTL) which estimates LTL based on DNA methylation levels of 140 CpGs. DNAm LTL outperforms telomere restriction fragment-based LTL in predicting mortality and time-to-heart disease, as well as associating with many age-related conditions, after adjusting for age. Age-adjusted DNAm LTL also correlates with diet and other clinical biomarkers. However, unlike actual LTL, DNAm LTL can also be related to physical functioning and age-at-menopause. This technology has great potential to monitor and evaluate interventions applied to age-related conditions.
POTENTIAL APPLICATIONS:
• Evaluation of anti-aging interventions
• Determination of mortality/morbidity risk
• Cardiovascular disease and lifespan prediction
ADVANTAGES:
• Higher accuracy
• Highly robust
• Large-scale
DEVELOPMENT-TO-DATE:
Invention has been tested in human samples and was successful in determining biomarkers of age capture aspects of biological age.
RELATED PAPERS:
Hannum et al. “Genome-Wide Methylation Profiles Reveal Quantitative Views Of Human Aging Rates.” Molecular Cell. 2013; 49(2): 359-367.