Summary: Researchers have designed a new model of life expectancy that relies less on disease diagnosis and more on other factors, including cholesterol levels and lifestyle.
Source: duke university
A new model for predicting the life expectancy of older people relies less on their specific disease diagnoses and more on factors such as the ability to shop for groceries, the amount of certain small cholesterol particles circulating in their blood and the the fact that they have never smoked or only occasionally smoked.
The results of a study by Duke Health researchers provide a way to predict whether someone over 70 is likely to live two, five or 10 years. The markers can be obtained during a visit to the doctor, so they could be a useful guide for clinical care.
“This study was designed to determine the proximal causes of longevity — the factors that predict whether someone is likely to live two or 10 years longer,” said Virginia Byers Kraus, MD, Ph.D., professor to medical departments. , Pathology and Orthopedic Surgery at Duke University School of Medicine and lead author of the study published online in the journal eBioMedicine.
“Applied properly, these measures could help determine the pros and cons of screening tests and treatments for older adults,” Kraus said.
Kraus and his colleagues launched their investigation at the opportune moment, after being directed to a cache of 1,500 blood samples from a 1980s longitudinal study of older people.
The banked samples had been taken in 1992 when the participants were at least 71 years old and then stored at the NIH. They were supposed to be destroyed, but researchers arrived in time to transfer them to Duke for analysis.
The blood samples had the additional fortuitous characteristic of having been taken at a time before the widespread use of drugs such as statins, which could have skewed the results. Good luck again: the study participants had been followed for several years and had completed questionnaires about their backgrounds and health habits.
By capitalizing on all the features of the older study, the researchers were able to apply today’s sophisticated analytical tools. Led by Constantin Aliferis and Sisi Ma of the University of Minnesota, researchers were able to drill down into health factors to identify a core set of 17 predictor variables that have a causal impact on longevity.
The analysis found that a primary factor associated with longevity at each of the study’s endpoints – two, five and 10 years after participants’ blood was drawn – was physical function, which was defined as the ability grocery shopping or cleaning. chores. Surprisingly, having cancer or heart disease were not among the top predictors.
For older people living two years after the time their blood was drawn, the primary factor associated with longevity was having an abundance of high-density lipoprotein (HDL) cholesterol — and not just any HDL lipid, but high volumes of very small HDL particles.
“It was particularly surprising,” Kraus said. “We hypothesize that these very small HDL particles are the size that best traps and removes endotoxin, a potent inflammatory molecule of gut microbes, from the circulation. [VBKMP1] .
“The small particle may also be better able to penetrate the nooks and crannies of cells to remove bad cholesterol, so having more of it could provide that protective benefit.”
At five years after the initial blood draw, simply being younger was predictive of longevity, as well as cognitive function. And among the longest survivors – those who live 10 years – the best predictor was a person’s smoking history, with non-smokers faring the best.
“These measurements clarify and enrich our understanding of the mechanisms underlying longevity and may indicate appropriate testing and potential interventions,” Kraus said.
She said the next step in the research is to use additional analytical tools to improve predictivity and identify potential targets for therapies.
About this aging and mortality research news
Author: Alexis Porter
Source: duke university
Contact: Alexis Porter – Duke University
Image: Image is in public domain
Original research: Open access.
“Causal analysis identifies small HDL particles and physical activity as key determinants of longevity in the elderly” by Virginia Byers Kraus et al. eBioMedicine
Causal analysis identifies small HDL particles and physical activity as key determinants of longevity in older adults
The hard endpoint of death is one of the most important outcomes in clinical practice and research settings. Our goal was to discover the direct causes of longevity from medically accessible data.
Using a framework that combines local causal discovery algorithms with the discovery of maximal and compact predictive feature sets (the “Markov bounds” of the response) and equivalence classes, we examined 186 variables and their relationships with 27-year survival in 1507 participants, aged ≥ 71 years, from the D-EPESE Community Longitudinal Study.
As few as 8-15 variables predicted longevity at 2, 5 and 10 years with a predictive performance (area under the receiver operator characteristic curve) of 0.76 (95% CI 0.69, 0.83 ), 0.76 (0 72, 0 81) and 0 66 (0 61, 0 71), respectively. The number of small high-density lipoprotein particles, young age, and fewer years of smoking were the main determinants of longevity at 2, 5, and 10 years, respectively. Physical function was an important predictor of longevity across all time horizons. Age and cognitive function contributed to predictions at 5 and 10 years. Age was not among the local predictors at 2 years (although significant in univariate analysis), thus establishing that age is not a direct cause of longevity at 2 years in the context of factors measured in our data that determines longevity.
The findings of this study stem from causal data science analyzes of extensive clinical and molecular phenotyping data in a community-based cohort of older adults with known lifespans.
NIH/NIA R01AG054840, R01AG12765 and P30-AG028716, NIH/NIA contract N01-AG-12102 and NCRR 1UL1TR002494-01.
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