New study finds smoking speeds up
biological clock
For years, young people have used
smoking as a way to look older. As it turns out – thanks to a first-of-its-kind
study out of the University of Lethbridge using artificial intelligence (AI) to
analyze blood biochemistry – it’s true, smoking truly does make you older.
“We demonstrate for the first time
that smoking status can be predicted using blood biochemistry and cell count
results and the recent advances in AI and machine learning,” says Dr. Olga
Kovalchuk, a professor in the Department of Biological Sciences, Board of
Governors Chair in Epigenetics of Health and Disease, and Canadian Institute of
Health Research Chair in Gender and Health.
“By employing age-prediction models developed using supervised deep learning techniques, we found that smokers exhibited higher aging rates than non-smokers. In other words, we show that smoking makes people biologically older.”
“By employing age-prediction models developed using supervised deep learning techniques, we found that smokers exhibited higher aging rates than non-smokers. In other words, we show that smoking makes people biologically older.”
This realization almost sounds like
common sense but until now, through the use of AI, it has never been quantified
and illuminated to this extent.
“We all have a chronological age but
then there is also our biological age, which is an indicator of general
fitness,” says Kovalchuk. “If somebody is 35 but on a biological clock, through
specific markers, it shows them at a biological age of 50, obviously they are
doing something wrong. Smoking, specifically in younger people, those in their
20s, 30s and 40s, is truly harmful as it makes them biologically older.”
The study, Blood Biochemistry Analysis to Detect Smoking Status and Quantify
Accelerated Aging in Smokers, was recently published in the
journal Nature – Scientific Reports. It involved a team effort
by top clinicians,
AI researchers, and deep learning and aging experts led by the Canada Cancer and Aging Research Laboratories in collaboration with InSilico Medicine, the world leaders in AI and aging research, as well as several national and international institutions.
AI researchers, and deep learning and aging experts led by the Canada Cancer and Aging Research Laboratories in collaboration with InSilico Medicine, the world leaders in AI and aging research, as well as several national and international institutions.
Kovalchuk, who co-led the study with aging expert and devoted anti-smoking campaigner Dr. Alex Zhavoronkov and was assisted by her daughter, Anna Kovalchuk (BSc ’14, MSc ’15, PhD ’17), a current University of Calgary student in the Leaders in Medicine program, has a personal connection to the effects of smoking on the human body. She also understands how the warnings linking smoking to lung cancer and heart disease often ring hollow with the millennial generation.
“Fighting smoking is kind of up
close and personal for me because my dad was a smoker and even though he quit
in 2003, it still caught up with him,” says Olga of her father’s passing.
“People are somewhat tired of hearing about lung cancer and heart disease in the context of smoking prevention but this is a different story. Our study shows that smoking is definitely associated with aging and it also shows that some effects are more pronounced in females. Maybe that’s a message that could really resonate.”
“People are somewhat tired of hearing about lung cancer and heart disease in the context of smoking prevention but this is a different story. Our study shows that smoking is definitely associated with aging and it also shows that some effects are more pronounced in females. Maybe that’s a message that could really resonate.”
Kovalchuk’s research group used data
from 149,000 anonymous individual blood biochemistry records linked to smoking
status from across the province. Through the use of AI, they were able to look
at blood biochemistry markers and predict age.
What they found was both remarkable and troubling. Age predictions showed that the biological age of male smokers was 1.5 times older than their chronological age while female smokers were nearly twice as old as their actual chronological age.
What they found was both remarkable and troubling. Age predictions showed that the biological age of male smokers was 1.5 times older than their chronological age while female smokers were nearly twice as old as their actual chronological age.
“What’s beautiful about AI is that
we couldn’t run these calculations before because the human mind just can’t
deal with these large data sets. What it looks like is a bunch of numbers,
lines of numbers, and we train it what to do and then it looks for patterns,”
says Kovalchuk.
“We wanted to do this using nothing fancy, just general basic bloodwork that is done on every general checkup. But with this data, using AI, you can see major patterns and it’s just fascinating.”
“We wanted to do this using nothing fancy, just general basic bloodwork that is done on every general checkup. But with this data, using AI, you can see major patterns and it’s just fascinating.”
How people will consume this new information
is unknown. For Kovalchuk, it’s another weapon in an age-old war against
smoking. If it’s appealing to young people’s vanity, then so be it.
“Once you develop cancer, it doesn’t
really matter how it developed, now you have to treat it, so shaming or blaming
a person for smoking is not productive,” she says.
“But if we can prevent the cancers from happening with a message that will resonate, specifically with millennials and what are they concerned about, their looks, then let’s use this information.”
“But if we can prevent the cancers from happening with a message that will resonate, specifically with millennials and what are they concerned about, their looks, then let’s use this information.”