Researchers call for precision medicine in cognitive aging

There's no such thing as a one-size-fits-all approach to aging brain health, says Lee Ryan, PhD, professor and head of the University of Arizona Department of Psychology, in a new paper published in Frontiers in Aging Neuroscience.

Several studies have looked at individual risk factors that may contribute to cognitive decline with age, such as chronic stress and cardiovascular disease. However, those factors may affect different people in different ways depending on other variables, such as genetics and lifestyle, Ryan says.

In the paper, Ryan and her co-authors advocate for a more personalized approach, borrowing principles of precision medicine in an effort to better understand, prevent, and treat age-related cognitive decline.

"Aging is incredibly complex, and most of the research out there was focusing on one aspect of aging at a time," Ryan said in a statement. "What we're trying to do is take the basic concepts of precision medicine and apply them to understanding aging and the aging brain. Everybody is different and there are different trajectories. Everyone has different risk factors and different environmental contexts and layered on top of that are individual differences in genetics. You have to really pull all of those things together to predict who is going to age which way. There's not just one way of aging."

Many people in their 60s or older experience some cognitive impairment, Ryan said. This not only threatens older adults' quality of life, it also has socioeconomic consequences, amounting to hundreds of billions of dollars in health care and caregiving costs, as well as lost productivity in the workplace, Ryan and her co-authors write.

The researchers said they want to make it possible to maintain brain health throughout the entire adult lifespan, which today in the U.S. is a little over 78 years old on average. In the paper, Ryan and her co-authors present a precision aging model meant to be a starting point to guide future research. It focuses primarily on three areas: broad risk categories, brain drivers, and genetic variants.

An example of a risk category for age-related cognitive decline is cardiovascular health, which has been consistently linked to brain health. The broader risk category includes within it several individual risk factors, such as obesity, diabetes and hypertension, researchers said.

The model then considers brain drivers, or the biological mechanisms through which individual risk factors in a category impact the brain. This is an area where existing research is particularly limited, Ryan said.

Finally, the model looks at genetic variants, which can either increase or decrease a person's risk for age-related cognitive decline. Despite people's best efforts to live a healthy lifestyle, genes do factor into the equation and can't be ignored, Ryan said. For example, there are genes that protect against or make it more likely that a person will get diabetes, sometimes regardless of their dietary choices.

While the precision aging model is a work in progress, Ryan and her collaborators believe that considering the combination of risk categories, brain drivers, and genetic variants is key to better understanding age-related cognitive decline and how to best intervene in different patients.