Raphael Thys
- US scientists have developed a new research model to estimate the longevity of those older than 70 years.
- Rather than focus on specific diagnoses, it evaluates 17 causal factors that can help predict whether older people are likely to live 2, 5 or 10 more years.
- These include the ability to grocery shop, cholesterol levels and whether or not a person has smoked.
- The leading factor across the study's benchmarks was found to be physical function.
The new model relies less on specific disease diagnoses and more on factors such as the ability to grocery shop, the amount of certain small cholesterol particles circulating in the blood, and whether someone never or only occasionally smoked.
The findings provide a way to predict whether a person over the age of 70 is likely to live two, five, or 10 years. The markers may be obtained during a doctor visit, so they could be a useful guide for clinical care.
“This study was designed to determine the proximal causes of longevity—the factors that portend whether someone is likely to live two more years or 10 more years,” says Virginia Byers Kraus, professor in the departments of medicine, pathology, and orthopedic surgery at Duke University School of Medicine and lead author of the study in the journal eBioMedicine.
“Properly applied, these measures could help determine the benefits and burdens of screening tests and treatment for older people,” Kraus says.
Kraus and colleagues launched their inquiry at an opportune time, having been directed to a cache of 1,500 blood samples from a 1980s longitudinal study that enrolled older people.
The banked samples had been drawn in 1992 when participants were at least 71 years old and then stored at the NIH. They were scheduled for destruction, but the researchers arrived in time to transfer them to Duke for analysis.
The blood samples had the additional fortuitous feature of being drawn at a time that preceded the widespread use of medications such as statins, which could have skewed the results. More good luck: study participants had been followed for several years and had filled out questionnaires about their health histories and habits.
Capitalizing on all the features of the older study, the researchers were able to apply current sophisticated analytical tools. Led by Constantin Aliferis and Sisi Ma at the University of Minnesota, the researchers were able to delve into health factors to identify a core set of 17 predictive variables that have a causal impact on longevity.
The analysis found that a leading factor associated with longevity across each of the study’s benchmarks—two-, five-, and 10-years after participants had their blood drawn—was physical function, which was defined as an ability to go grocery shopping or perform housecleaning chores. Surprisingly, having cancer or heart disease was not among the main predictors.
For older people living two years beyond the time their blood had been drawn, the leading factor associated with longevity was having an abundance of high-density lipoprotein (HDL) cholesterol—and not just any HDL lipids, but high volumes of very small HDL particles.
“This was especially surprising,” Kraus says. “We hypothesize that these very small HDL particles are the size that is best at scavenging and clearing endotoxin, a potent inflammation-causing molecule from gut microbes, from the circulation. The small particle may also be best able to get into the nooks and crannies of cells to remove the bad cholesterol, so having more of them could provide this protective benefit.”
At five years beyond the original blood draw, just being of a younger age was predictive of longevity, along with cognitive function. And among the longest survivors—those living 10 years—the best predictor was a person’s smoking history, with non-smokers faring best.
“These measures clarify and enrich our understanding of mechanisms underlying longevity and could point to appropriate tests and potential interventions,” Kraus says.
She says the next stage of research is to use additional analytical tools to improve the predictivity and identify potential targets for therapies.
The study had funding from the National Institute of Aging, a unit of the National Institutes of Health, and the NIH/National Center for Advancing Translational Sciences.
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