Researchers have designed a brain aging model to investigate the factors that contribute to cognitive decline, borrowing principles from precision medicine.

Cognitive decline affects a person's ability to focus, remember, and make decisions. Its severity can range from mild to severe, and it may lead to dementia, in the most severe cases. People with dementia may find it diffcult to perform everyday tasks and live independently. According to the World Health Organization (WHO), "around 50 million people have dementia." In the United States, the Centers for Disease Control and Prevention (CDC) estimates that more than 5 million people aged 65 or older have Alzheimer's disease.

It is important to note that about 85% of older adults only experience a range of age-related cognitive impairments (ARCIs) and will never develop Alzheimer's disease. Nevertheless, mild cognitive decline may decrease quality of life and has socioeconomic consequences.

Age is a major factor in cognitive impairment, but family history, education level, physical inactivity, and chronic conditions such as heart disease and diabetes may contribute to cognitive decline. As these factors affect people differently, there is no one-size-fits-all approach when it comes to the aging brain.

Developing a precision model

Researchers recently developed an aging brain model, borrowing ideas from precision medicine. Their findings appear in the journal Frontiers in Aging Neuroscience.

When working with precision medicine, the question is no longer, "Does treatment X work?" but "Who does treatment X work for?"

"A number of studies have looked at individual risk factors that may contribute to cognitive decline with age, such as chronic stress and cardiovascular disease," says study co-author professor Lee Ryan, head of the University of Arizona Department of Psychology in Tucson.

"However, those factors may affect different people in different ways depending on other variables, such as genetics and lifestyle," she adds.

Precision medicine requires a clear goal to be successful. When it comes to the health of the aging brain, researchers have been working on solutions "to maintain brain health across the full extent of the adult lifespan."

The precision aging model investigated risk factors for ARCI and potential targets for prevention and therapy. It consists of three main areas:

1. Risk categories

Scientists can classify multiple factors into a single risk category because of the way they co-occur in real life. These factors include heart failure, glucose dysregulation, and chronic stress.

2. Brain drivers

Risk categories likely affect the brain via common brain drivers, such as brain inflammation and compromised brain blood flow. These conditions speed up the aging process and may accelerate the development of neurodegenerative conditions.

3. Gene variants

Gene variants may increase the influence of risk categories, but they may also protect the individual in some cases, by moderating the impact of brain drivers. Identifying the role of gene variants is essential to understanding the impact of risk categories on brain health.

"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."

—Professor Lee Ryan

She continues, "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."

A starting point for future research

Because the precision aging model allows professionals to characterize each individual based on a specific profile of risk categories and genetic variants, it may help researchers improve their understanding of ARCI. It might also shed light on the impact of risk factors on brain drivers.

The researchers consider the precision aging model a work in progress that could be a starting point to guide future research. They may add more risk categories to their list, and they believe it is crucial to further investigate the relationships between risk categories, brain drivers, and genetic variants.

Ryan hopes that in the near future, people will be able to go to their doctor and gather all of their health and lifestyle information into an app. This approach would allow doctors to guide their patients toward personalized solutions focused on maintaining brain health across the lifespan.

"Our hope is that the research community collectively stops thinking about aging as a single process and recognizes that it is complex and not one-size-fits-all. To really move the research forward, you need to take an individualized approach," Ryan concludes.