A type of fingerprint technology called wavelet analysis can be used to diagnose whether a person could be at risk for diabetes.
Fingerprints could be the next tool to identify a person’s predisposition for diabetes, according to a study from one Ohio University professor.
Molly Morris, a professor in OU’s Department of Biological Sciences, and her team discovered that a type of fingerprint technology can be effective in diagnosing whether a person might be at risk for diabetes.
Morris said people can begin to make lifestyle changes when they learn they have prediabetes, but they still can have health problems the rest of their lives. That makes early detection so important, she said.
“I think the future idea is that people could know early on, and so much of our food habits and how we behave are developed early in life,” Morris said. “So I think that would be amazing if people could know that early on and if we could help moms know the really critical times during development.”
The researchers, primarily Bjoern Ludwar, an electrophysiologist at Longwood University in Virginia, used a process called wavelet analysis to study fingerprints to see if they were asymmetrical, which has become a known marker for Type 2 diabetes. The team also discovered that asymmetrical fingerprints can help identify Type 1 diabetes.
Morris said wavelet analysis is similar to what crime labs use to test fingerprints.
“The wavelet method takes a very global approach to comparing how similar two fingerprints are,” Ludwar, who is a former OU postdoctoral fellow, said in an OU news release. “On the downside, it is technically a lot more complicated, and it takes more computing power than simply counting ridges on fingers of the left and right hand.”
Morris said the idea for the study was unexpected and came from a research project she had been working on related to fish growth patterns.
“This seemed very novel and it seemed to be a stretch, but I feel like that we always have more to learn,” Jay Shubrook, a former professor in OU’s Heritage College of Osteopathic Medicine and current professor at Touro University California, said in an email. “I think some of our greatest discoveries come from a willingness to think outside the box. This study is outside the box.”
Morris said the researchers recruited about 350 volunteers to test their fingerprints for the study.
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Morris said she plans to take time off next spring to travel to California to work with Shubrook to examine a different group of patients. They soon will work with a new group of patients in Vallejo, California.
“The first study was largely in a Caucasian population. We need to know if this holds true to different populations,” Shubrook said in an email. “Vallejo is one of the most diverse places in the United States with a nearly equal percent of people who are Hispanic, African American, Asian (largely Filipino) and Caucasian.”
Morris also said it would be nice to have an app which would allow users to test their fingerprints to see if they could be predisposed to diabetes.
“We’re hoping that someone might be interested in developing an app, and you would know from the time you were born if you had this propensity, and you could do something about it,” she said.
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