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Epigenetic Clocks as Predictors of Mortality: A New Tool for Life Insurance Risk Stratification
THE INSURANCE TIMES
|November 2025
Numerous cohort studies have validated the utility of epigenetic clocks in predicting all-cause mortality. For instance, accelerated epigenetic aging, where biological age exceeds chronological age, has been consistently associated with increased mortality risk (Marioni et al., 2015).
1. Introduction
The accurate prediction of individual mortality risk is a longstanding challenge across medicine, public health, and actuarial science. Traditional actuarial models primarily rely on demographic data, lifestyle information, and medical history to estimate life expectancy. While useful, these models often fail to capture biological variation between chronological age and biological age, limiting their precision. Advances in molecular biology, particularly in the field of epigenetics, have revealed that DNA methylation patterns can serve as robust biomarkers of aging. These insights have led to the development of epigenetic clocks as predictive tools that quantify biological age and offer strong correlations with health outcomes and mortality risk.
This emerging technology holds particular relevance for the life insurance industry, where risk stratification is essential for underwriting policies and setting premiums. By integrating epigenetic clocks into actuarial frameworks, insurers may be able to refine risk assessment, improve accuracy, and enhance long-term financial stability. However, the incorporation of such molecular data also raises significant ethical, legal, and technical challenges that must be carefully addressed.
2. Understanding Epigenetic Clocks
2.1 What is Epigenetics?
Epigenetics refers to heritable yet reversible changes in gene expression that occur without altering the underlying DNA sequence. The most studied epigenetic mechanism is DNA methylation, involving the addition of methyl groups to cytosine residues at CpG dinucleotides. These modifications regulate gene expression, developmental processes, and responses to environmental exposures. Importantly, DNA methylation patterns change predictably with age, making them suitable biomarkers for estimating biological age.
2.2 Development of Epigenetic Clocks
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