For Zane Burris, the question was never if he would develop type 1 diabetes (T1D). It was when.

Tests Zane received as a baby revealed he had two T1D antibodies. This meant he would almost certainly develop T1D — but they had no idea when.

“Living with that uncertainty was hard,” says Zane, now 21. “There have been so many times I wished I knew exactly what would happen and how my life would change.” 

Using "Fancy Math" To Find Answers

Throughout his life, Zane’s parents and doctors told him that he would develop T1D one day — but his most vivid memory was from a trip to the doctor when he was 16. His blood sugar was above the normal range and his doctor told him he may develop T1D soon. She also said changing his diet and lifestyle might help slow the process or improve his overall health for when he did develop T1D.

 “It was a slap in the face and a wake-up call,” Zane says. “I was kind of a chunky kid and not living the healthiest lifestyle. I decided to do everything in my control to not get diabetes.”

Dr. Greenbaum’s vision for better predicting when young people like Zane might develop T1D starts with what she calls “fancy math.”

Colin O’Rourke, MS, a biostatistician who was previously part of BRI's team, developed three algorithms. Each one uses data from different diabetes-related medical tests. Doctors punch in numbers like a patient’s age, number of antibodies they have and results of certain medical tests, and the algorithm would calculate the likelihood of developing T1D over a specific time period.

These formulas still need to be validated, which means other scientists need to test them and make sure they get the same results. But the ultimate goal is to make this testing widely available to improve care for people on track to develop T1D.

“The formulas don’t tell a family exactly what to do next,” Dr. Greenbaum says. “Instead, they give them and their doctors information that helps make decisions about next steps and future screenings.”

Test results can also help doctors recommend educational resources, determine what type of test to use for future screenings and start conversations about getting involved in research.

He’d tell anyone on track to develop T1D to educate yourself about the disease, surround yourself with positive people and know that you’ll be okay.

“Research is so important, and BRI is working to prevent and cure T1D,” he says. “And if I get to be one tiny footnote in the cure for diabetes by participating in research — well, that’s pretty incredible.” 
For Dr. Greenbaum, she hopes that this algorithm becomes one more tool in the tool kit to help better predict T1D and ultimately improve care.

“I’ve been doing this work for 40-something years, making one discovery at a time and building on what we learn. We celebrate each advance then ask the next question,” she says. “The science is fascinating, but that’s not why we do it — we do it to help make life better for people with T1D.”