An epigenetic age test that measures 10,000 methylation sites in your DNA.
Aging is the number one risk factor for chronic disease, yet it is challenging to quantify how well someone is aging before it is too late. Because aging is a dynamic process, there is a need for an accurate, accessible, and affordable method to repeatedly gauge how well we are aging throughout the course of our lives. Biological age refers to the age that someone physically or functionally embodies and can be captured by measuring epigenetic markers (reversible modifications to our genetic blueprint that control how our genes function), most commonly, DNA methylation sites. Indeed, a decade of research has shown that epigenetic age (defined as the age estimate in years resulting from a mathematical algorithm based on the methylation state of specific CpGs in the genome) is the most promising estimator of biological age out of all other potential biomarkers. Until recently, the primary method for measuring DNA methylation (and therefore, biological age) has been the use of “epigenomewide microarrays”, which miniaturize the detection of DNA methylation levels for up to 850,000 sites distributed randomly throughout the genome. However, only a small fraction of DNA methylation sites (<1%) have been found to contribute to aging and other human traits. What this means is that most testing methods are not cost-effective since ~99% of the information obtained is irrelevant and effectively discarded.
To efficiently measure biological age and other age-related traits, AgeRate has carefully curated the epigenetic research literature to select a subset of robustly associated DNA methylation sites to build a highly specialized DNA methylation microarray (“custom Illumina HD methylation array”). Effectively, the efficient selection and measurement of relevant DNA methylation sites enables cost-effective and accurate epigenetic testing to derive biological age and 20+ other exposures, including risk factors (blood pressure, weight), diseases risk (heart attack, stroke), lifestyle habits (diet quality, physical activity levels)9,10, and environmental exposures (smoke exposure, air pollution).
AgeRate uses a novel machine-learning-based algorithm for the quantification of biological age. Using one of the largest collections of epigenetic data assembled to date, we applied several machine learning algorithms to derive an optimal predictor of biological age and then arrived at an elastic net algorithm (i.e., “AgeRate prediction”) for highly accurate age
prediction. We then compared the performance of AgeRate prediction to other epigenetic predictors in an independent dataset.
