A team or researchers in China have published new research that show the temperature patterns in different regions of the face are associated with various chronic illnesses such as high blood pressure and diabetes and may soon be used to diagnose these and other metabolic diseases and diseases of aging.
While these temperature differences are not noticeable by human touch, the investigators instead identified these subtle temperature variations using a specific AI-derived spatial temperature patterns, a trained model, and a thermal camera. Their research appears in the July 2 edition of the journal Cell Metabolism.
“Aging is a natural process,” said corresponding author Jing-Dong Jackie Han, PhD, a researcher at Peking University in Beijing. “But our tool has the potential to promote healthy aging and help people live disease-free.”
The same team of investigators had previously studied the use of 3D facial structures to predict a person’s biological age as a measure of how well the body is aging. Biological aging can also be used as an indicator of diseases risk, and researchers have developed a number of different testing methods for it but are hindered by the complexity of sample collections and data acquisition.
The new research arose from seeking whether there are other methods, such as temperature variations, that can indicate a person’s rate of aging. The aim was to develop an on-the-fly test that could provide almost immediate data on a person’s rate of aging.
“Body temperature, an often overlooked but important factor in aging and longevity, is a key homeostatic parameter that affects cell function and organism survival and is closely related to metabolism, protein denaturation, membrane fluidity, ion fluxes, and enzyme properties,” the researchers wrote. “In many endothermic species, individuals with lower body temperatures live longer and age more slowly than those with higher body temperatures.”
For their work Han and her team recruited 2,811 Chinese participants between the ages of 21 and 88 to analyze their facial temperatures. Using their collected data, the team trained AI models so they could predict a person’s “thermal age.” Using these models, they discovered that specific facial regions including the eyes, nose, and cheeks, had temperature variations that were related to age and health. These findings showed that the temperature of the nose decreases with age at a rate faster than other parts of the face and that the temperature around the eyes tends to increase with age.
They also discovered that people with metabolic disorders such as fatty liver disease and diabetes showed faster thermal aging—they tended to have higher temperatures in the eye area—than those without these conditions. People with elevated blood pressure had higher cheek temperatures.
An analysis of blood samples from participants showed that the increase in temperature around the eyes and cheeks was mainly due to increased cellular activity related to inflammation, such as the immune system fighting off infections, which led to these temperature increases.
“The thermal clock is so strongly associated with metabolic diseases that previous facial imaging models were not able to predict these conditions,” Han noted.
Furthering their discoveries, the team wanted to see if a simple intervention—exercise—could influence thermal age. Twenty-three participants jumped rope daily, completing a total of 800 jumps each day. After just two weeks of this daily activity, the participants had lowered their thermal age by five years.
Next, Han and colleagues will investigate whether they can make other disease risk associations for conditions such as sleeping disorders or cardiovascular issues.
“We hope to apply thermal facial imaging in clinical settings, as it holds significant potential for early disease diagnosis and intervention,” Han concluded.
