Fight Aging!

To what degree do genetic variants drive the observed differences in human life expectancy? The old consensus guesstimate was that environment determines 75% of life expectancy, and genetic variants the other 25%. Further, it is the common wisdom that gene variants become more important to life expectancy in later life, either by providing greater resilience to specific forms of damage and dysfunction, or slowing the pace at which that damage and dysfunction accumulates. A great deal of medical research is based on the insight that gene variants are thought to provide on disease processes.

Views on genetic variants are changing, however. Modern research that makes use of genetic databases that cover very large populations is trending in the direction of demonstrating that ever smaller contributions to life expectancy arise from genetic variants. As the importance of genetic variants diminishes, the importance of environmental factors and lifestyle choices becomes ever greater, and the value of research into genetic variations and aging becomes more questionable.

Today's research materials discuss a recent study in which the authors provide data to suggest that gene variants become less important with age, that their contribution to emergent differences in cell metabolism is outweighed by other factors. This, like the genetic studies on large populations, is an attack on the value of research programs that focus on gene variants in the context of age-related disease. There are a great many such programs, as well as ongoing searches for new variants that might be useful to investigate more deeply. If gene variants largely do not tend to usefully predict cell and tissue behavior across an aged population, then then other high-level research strategies may well prove to be more cost-effective in the long term.

Age vs. genetics: Which is more important for how you age?

In a study of the relative effects of genetics, aging, and the environment on how some 20,000 human genes are expressed, the researchers found that aging and environment are far more important than genetic variation in affecting the expression profiles of many of our genes as we get older. The level at which genes are expressed - that is, ratcheted up or down in activity - determines everything from our hormone levels and metabolism to the mobilization of enzymes that repair the body.

while our individual genetic makeup can help predict gene expression when we are younger, it is less useful in predicting which genes are ramped up or down when we're older - in this study, older than 55 years. Identical twins, for example, have the same set of genes, but as they age, their gene expression profiles diverge, meaning that twins can age much differently from each other. The findings have implications for efforts to correlate diseases of aging with genetic variation in humans. Such studies should perhaps focus less on genetic variants that impact gene expression when pursuing drug targets.

The findings are in line with Medawar's hypothesis: Genes that are turned on when we are young are more constrained by evolution because they are critical to making sure we survive to reproduce, while genes expressed after we reach reproductive age are under less evolutionary pressure. So, one would expect a lot more variation in how genes are expressed later in life. "Across all the tissues in your body, genetics matters about the same amount. It doesn't seem like it plays more of a role in one tissue or another tissue. But aging is vastly different between different tissues. In your blood, colon, arteries, esophagus, fat tissue, age plays a much stronger role than your genetics in driving your gene expression patterns."

Tissue-specific impacts of aging and genetics on gene expression patterns in humans

Overall this work has several important implications. Our results shed light on recent work on the prediction accuracy of polygenic risk scores (PRS) which found that numerous factors, including age, sex, and socioeconomic status can profoundly impact the prediction accuracy of such scores even in individuals with the same genetic ancestry. Our results highlight that genetics exhibit varied predictive power in several different tissues as a function of age, potentially playing a role in differential PRS accuracy between young and old individuals.

This also has important implications for disease association and prediction approaches that leverage expression quantitative trait loci (eQTLs) to prioritize variants. If a significant proportion of eQTLs exhibit age-associated biases in their effect size in a tissue of interest, then these approaches may be less powerful when applied to diseases for which age is a primary risk factor such as heart disease, Alzheimer's disease, cancers, and diabetes.