According to biologist David Furman of Stanford University, "Every year, the calendar tells us we're a year older. But not all humans age biologically at the same rate. You see this in the clinic — some older people are extremely disease-prone, while others are the picture of health."
(Cough — Keith Richards.)
Some have suggested that our epigenome — the sum total of the chemical changes to our DNA — can determine our biological age and predict how soon we are likely to have serious age-related health issues.
Now, Stanford scientists have discovered a different way of ascertaining our future expiration dates: the "inflammatory-aging clock" (iAge). Determining someone's iAge is not only far simpler than performing epigenetic tests. It can also help individuals and their physicians anticipate and confront health issues before they happen.
Good and bad inflammation
Credit: doucefleur / Adobe Stock
One of the things that distinguishes people who remain healthy longer from others is the strength of their immune system.
One of the immune system's primary tools is acute inflammation. This is a "good" process because it is the body's localized, protective response to things like tissue damage, invasive microbes, or metabolic stress. Importantly, it is a short-term response that lasts only as long as needed for the immune system to finish its job.
On the other hand, long-term, system-wide inflammation is "bad." This form of inflammation causes organ damage and is associated with aging. It makes a person vulnerable to a whole range of conditions, including heart attacks, cancer, strokes, arthritis, cognitive decline, depression, and Alzheimer's.
Understanding inflammation as a measure of age
Furman is the director of the 1000 Immunomes Project, "the world's largest longitudinal population-based study of immunology and aging." As such, he had access to blood samples taken from 2009 to 2016 from 1,001 healthy people aged 8-96.
Artificial intelligence (AI) analysis of the samples allowed the researchers to identify protein markers in the blood that most reliably indicated a person's inflammation age. They identified a specific cytokine, CXCL9, as being especially useful. When processed by an algorithm the team devised, it produced a simple inflammation-age value. Comparing this to the patients' histories, it turned out to align with the health of their immune systems and subsequent encounters with age-related disease. CXCL9, produced by the inner lining of blood vessels, is associated with heart disease.
The researchers verified the validity of their system by measuring the iAge of people 65 and older who had had their blood drawn in 2010. When they followed up with these people in 2017, the scientists found that their 2010 iAge turned out to be a more accurate predictor of their health than their chronological age.
Finally, the researchers tested their iAge algorithm with 29 long-lived people from Bologna, Italy — only one of whom had not yet turned 100 — comparing them to 18 average 50-79-year-old individuals. The inflammatory age of all the Bolognese participants averaged about 40 years younger than their chronological age. Furman reports that one 105-year-old man had an inflammatory age of 25.
Tick tock
CXCL9 is easy to measure and may have significant clinical applications. Specifically, it highlights the value of addressing chronic inflammation as a way to increase longevity.
Most promisingly, a person's iAge could serve as an important early-warning system. Furman notes, "Our inflammatory aging clock's ability to detect subclinical accelerated cardiovascular aging hints at its potential clinical impact." He adds, "All disorders are treated best when they're treated early."
The oldest person in history – a French woman named Jeanne Calment – lived to 122. When she was born in 1875, the average life expectancy was roughly 43.
But just how long could a human actually live? It's a question people have been asking for centuries. While average life expectancy (the number of years a person can expect to live) is relatively easy to calculate, maximum lifespan estimates (the greatest age a human could possibly reach) are much harder to make. Previous studies have placed this limit close to 140 years of age. But a more recent study proposes that the limit to human lifespan is closer to 150.
Calculating lifespan
The oldest and still most widely used method for calculating life expectancy, and thus lifespan, relies on the Gompertz equation. This is the observation, first made in the 19th century, that human death rates from disease increase exponentially with time. Essentially, this means your chance of death – from cancer, heart disease and many infections, for example – roughly doubles every eight to nine years.
There are many ways the formula can be tweaked to account for how different factors (such as sex or disease) affect the lifespan within a population. Gompertz calculations are even used to calculate health insurance premiums – which is why these companies are so interested in whether you smoke, whether you are married and anything else that might allow them to more accurately judge the age at which you will die.
Another approach to figuring out how long we can live is to look at how our organs decline with age, and run that rate of decline against the age at which they stop working. For example, eye function and how much oxygen we use while exercising show a general pattern of decline with ageing, with most calculations indicating organs will only function until the average person is around 120 years old.
But these studies also unmask increasing variation between people as they grow older. For example, some peoples' kidney function declines rapidly with age while in others it hardly changes at all.
Now researchers in Singapore, Russia, and the US have taken a different approach to estimate the maximum human lifespan. Using a computer model, they estimate that the limit of human lifespan is about 150 years.
Living to 150
Intuitively, there should be a relationship between your chance of death and how rapidly and completely you recover from illness. This parameter is a measure of your ability to maintain homeostasis – your normal physiological equilibrium – and is known as resilience. In fact, ageing can be defined as the loss of ability to maintain homeostasis. Typically, the younger the person, the better they are at recovering rapidly from illness.
To conduct the modelling study, the researchers took blood samples from over 70,000 participants aged up to 85 and looked at short-term changes in their blood cell counts. The number of white blood cells a person has can indicate the level of inflammation (disease) in their body, while the volume of red blood cells can indicate a person's risk of heart disease or stroke, or cognitive impairment, such as memory loss. The researchers then simplified this data into a single parameter, which they called the dynamic organisms state indicator (Dosi).
Changes in Dosi values across the participants predicted who would get age-related diseases, how this varied from person to person, and modelled the loss of resilience with age. These calculations predicted that for everyone – regardless of their health or genetics – resilience failed completely at 150, giving a theoretical limit to human lifespan.
But estimates of this type assume that nothing new will be done to a population, such as, no new medical treatments will be found for common diseases. This is a major flaw, since significant progress occurs over a lifetime and this benefits some people more than others.
For example, a baby born today can rely on about 85 years of medical progress to enhance their life expectancy, while an 85-year-old alive now is limited by current medical technologies. As such, the calculation used by these researchers will be relatively accurate for old people but will become progressively less so the younger the person you're looking at.
The Dosi limit for maximum lifespan is about 25% longer than Jeanne Calment lived. So if you're planning to beat it (and her), you need three important things. First is good genes, which makes living to be more than a hundred unassisted a good bet. Second, an excellent diet and exercise plan, which can add up to 15 years to life expectancy. And lastly, a breakthrough in turning our knowledge of the biology of ageing into treatments and medicines that can increase healthy lifespan.
Currently, adding more than 15-20% to healthy lifespan in normal mammals is extremely difficult, partly because our understanding of the biology of ageing remains incomplete. But it's possible to increase the lifespan of much simpler organisms – such as roundworms – by up to ten times.
Even given the current pace of progress, we can confidently expect life expectancy to increase because it has been doing this since Gompertz was alive in the 1860s. In fact, if you spend half an hour reading this article average life expectancy will have increased by six minutes. Unfortunately, at that rate, the average person won't live to 150 for another three centuries.
Richard Faragher, Professor of Biogerontology, University of Brighton
This article is republished from The Conversation under a Creative Commons license. Read the original article.
An older person's cognitive health is not always obvious. Cognitive impairment and dementia manifest gradually over time, and a person may be unaware of their advance. During this subtle transition, such a person may continue living as they always have, going about their business at home and behind the wheel. But this could lead to a dangerous car accident.
So, researchers from Columbia University have announced the development of AI algorithms that can detect mild cognitive impairment and dementia in older people based on the way they drive. The authors report in the journal Geriatrics that their algorithm is 88 percent accurate.
"Driving is a complex task involving dynamic cognitive processes and requiring essential cognitive functions and perceptual motor skills," says senior author Guohua Li, professor of epidemiology. "Our study indicates that naturalistic driving behaviors can be used as comprehensive and reliable markers for mild cognitive impairment and dementia."
Random forest model
The algorithms the researchers developed were based on a common AI statistical method involving "decision trees" that form a "random forest model." The most successful algorithm, according to lead author Sharon Di, associate professor of civil engineering, was based on "variables derived from the naturalistic driving data and basic demographic characteristics, such as age, sex, race/ethnicity and education level."
Decision trees are often used in memes in which answering "yes" or "no" regarding some attribute leads you down a path to another question, which in turn ultimately leads to a final conclusion.
Credit:Big Think
Data used in the study
The algorithm was developed using data sourced by the Longitudinal Research on Aging Drivers (LongROAD) study sponsored by the AAA Foundation for Traffic Safety. It came from in-vehicle recording devices that captured the driving behaviors of 2,977 participants from August 2015 through March 2019. At the time the project began, the motorists' ages ranged from 65 to 79 years. From the raw data, the authors of the new study derived 29 behavioral variables, which they used to develop cognitive profiles of the drivers.
Credit: Zoran Zeremski/Adobe Stock
The researchers then developed a series of machine-learning models to predict cognitive issues, with differing success rates. While models based on driving variables alone were just 66 percent accurate, and demographic models less so at 29 percent, using both models together produced an accuracy rate of 88 percent.
The researchers also explored the validity of individual factors as predictors of cognitive issues. In order of most reliable to least reliable, they were: (1) age; (2) percentage of trips traveled within 15 miles of home; (3) race/ethnicity; (4) minutes per round trip; and (5) number of hard braking events.
Li is hopeful that his team's work can help keep roadways and older drivers safe. "If validated," he says, "the algorithms developed in this study could provide a novel, unobtrusive screening tool for early detection and management of mild cognitive impairment and dementia in older drivers."
