Assisted by TruDiagnostic, a team of researchers has published a preprint paper in which -omics data has been used to create an epigenetic methylation clock.
Why -omics?
The researchers begin this preprint by discussing multiple biomarkers that are used to measure physical aging, including immune cell counts, telomeres, neurological imaging, and various -omics data, which are used to gain a broad biological understanding of an organism.
This team has brought up a different source of data: electronic medical records (EMRs). The point of an EMR is to give physicians a full understanding of a patient’s health in deep and ongoing detail [1], thus allowing for personalized medicine and better therapeutic choices. Therefore, they would be a logical choice for developing a clock of higher accuracy than a clock built around chronological age or mortality risk, such as GrimAge.
These researchers note the importance of integrating molecular -omics data with the physiological data that is emphasized in diagnostic-focused EMRs. They also note that just because one element of a epigenetic clock can be used as a predictor of aging, it does not mean that there is any causal relationship between that particular genetic site and any age-related process [2].
A wealth of data for an accurate clock
In order to build the biomarker clock EMRAge from plasma and clinical data, the researchers used data from roughly 30,000 people in the Massachusetts General Brigham (MGB) Biobank. More detailed -omics data from almost 3,500 people was used to build the methylation clocks DNAmEMRAge and OMICmAge. These clocks were validated by a TruDiagnostic cohort of data from almost 13,000 people, which had fewer comorbidities than the MGB Biobank cohort.
EMRAge was correlated with chronological age by over .75. It was also correlated with conditions known to increase mortality, including chronic obstructive pulmonary disease (COPD), depression, cardiovascular diseases, stroke, diabetes, and cancer.
As its name suggests, DNAmEMRAge is a methylation clock built directly from EMRAge. These clocks are correlated with one another at a rate of roughly 0.82, with an average error of more than 8 years. The methylation clock OMICmAge focuses on the thousands of metabolites and hundreds of proteins involved in -omics that are associated with EMRAge, and this clock was of slightly higher accuracy, at 0.83. The average error was also substantially less than DNAmEMRAge, at less than 5 years.
The researchers also noticed the role of epigenetic biomarker proxies (EBPs), which are connected to specific biological systems, such as the cardiovascular system and inflammation. Some diseases, such as diabetes and COPD, also had direct relationships to some EBPs.
Better than GrimAge?
GrimAge, true to its name, has long been the standard clock for predicting all-cause mortality. However, these researchers found that both DNAmEMRAge and OMICmAge were better than GrimAge at this task, as well as being more predictive of most hazardous conditions, and they used entirely different epigenetic sites.
We observed strong positive associations between OMICmAge and male sex, tobacco smoking, chronological age, and body mass index (BMI) while we observed significant negative associations with physical activity and higher education.
While no clock is perfect, the development of these -omics-based clocks clearly represents a step forward for the field. Further development of clocks that predict specific conditions may also be on the horizon.
Literature
[1] Pendergrass, S. A., & Crawford, D. C. (2019). Using electronic health records to generate phenotypes for research. Current protocols in human genetics, 100(1), e80.
[2] Wu, L., Xie, X., Liang, T., Ma, J., Yang, L., Yang, J., … & Wu, Q. (2021). Integrated multi-omics for novel aging biomarkers and antiaging targets. Biomolecules, 12(1), 39.
