Here, researchers advocate for a greater consideration of the role of random chance at the cellular level in the variations in life span exhibited by individuals of any given species. Why do people age at different rates and why does human life span exhibit a wide range? Exploration of human genetic data increasingly suggests that very little of this variation between individuals is due to our genes. That in turn might suggest that stochastic processes of damage and dysfunction are of greater importance to variations in aging than was previously thought to be the case by the research community.
Researchers introduced the "Tripartite Phenotype of Aging" as a new conceptual model that addresses why lifespan varies so much, even among human identical twins who share the same genes. Only about 10 to 35 percent of longevity can be traced to genes inherited from our parents. Researchers propose that the limited heritability of aging patterns and longevity in humans is an outcome of gene-environment interactions, together with stochastic, or chance, variations in the body's cells. These random changes can include cellular changes that happen during development, molecular damage that occurs later in life, and more.
The new model is a natural extension of the idea of the exposome, which was first proposed in 2005 to draw attention to the need for more data on lifetime exposure to environmental carcinogens. The exposome concept illustrates how external factors, ranging from air pollution and socioeconomic status to individual diet and exercise patterns, interact with endogenous, or internal, factors such as the body's microbiome and fat deposits.
The new model illustrates that cell-by-cell variations in gene expression, variations arising during development, random mutations, and epigenetic changes - turning genes "off" or "on" - should be explicitly considered apart from traditional genetic or environmental research regarding aging. More detailed study into these chance processes has been enabled by cutting-edge research techniques, including the study of gene transcription within single cells as well as ChIP-sequencing, which can illustrate how individual proteins interact with DNA.
The researchers offer several examples of how risks of age-related disease are poorly predicted by DNA alone but are heavily influenced by environmental exposures as well as the time and duration of the exposure, including during development or over the course of decades. One well-known example of a gene that is associated with increased Alzheimer's risk is ApoE-4; however, having the ApoE-4 gene doesn't definitively mean someone will get Alzheimer's. Studies in both mice and humans revealed that ApoE-4 and clusters of related genes interact with exposures such as air pollution or cigarette smoke to influence risk, and Alzheimer's patients also show differences in their epigenetics as compared to individuals without the disease.