There are more than 35 million people in the United States with diabetes, according to Boston College Assistant Professor of Biology Emrah Altindis. While genetics contribute to the disease, Altindis said they alone cannot explain the increasing diabetes rates in the country. `
“According to the JDRF, the number of type 1 diabetes patients in the U.S. is expected to increase by 5 million by 2050, and we have no tools to prevent it because we don’t know the cause of the disease,” he said. “The goal of my research is to understand the etiology of this disease and to find a causal link between gut microbes and type 1 diabetes.”
Altindis joined forces with Postdoctoral Research Fellows Khyati Girdhar and Qian Huang, as well as undergraduates Claudia Brady, BC ’20, and Amol Raisingani, BC ’22, to write the research article “A gut microbial peptide and molecular mimicry in the pathogenesis of type 1 diabetes.” The article explores other environmental factors such as viral infections, diet, gut microbiome composition, antibiotic exposure, and medicine that may have caused an increase in diabetes.
The BC researchers identified an association between a gut microbe and type 1 diabetes in mice, which might correspond to the disease in humans.
“In this disease, your cells are attacking only insulin producing cells in your body, so immune cells are having this autoimmune effect on insulin producing beta cells and killing them,” Altindis said. “The patient’s body cannot produce insulin anymore, and the blood glucose levels go up and cause several complex problems for the patient.”
When Altindis first started this project, he based his hypothesis on a mechanism called molecular mimicry—one of the ways in which infectious diseases can induce autoimmunity by attacking the hosts on cells.
“I thought that there might be some incident like molecules in microbes and an immune response to these microbial incidents that can stimulate the molecular mimicry mechanism and cause type 1 diabetes,” Altindis said.
Altindis also said he and his team identified one peptide on a gut bacterium called parabacteroides distasonis that is very similar to one of the main targets of the immune system on insulin.
“So when we give this bacterial peptide to T cells, the main immune cells that are isolated from type 1 diabetes patients, they couldn’t distinguish between this bacterial peptide and the insulin peptide so we proved the cross reactivity,” Altindis said.
According to Altindis, the next step in their hypothesis was to colonize the bacterium in the guts of mice models with type 1 diabetes to determine the effect of the type 1 diabetes onset. Through this display, they showed that the mice had increased rates of type 1 diabetes.
According to Girdhar, parabacteroides distasonis can modulate other bacterial growth, so it is uncertain whether type 1 diabetes is a direct effect of the bacteria or the bacteria are modulating other bacteria to cause this effect.
“Right now I’m clearing out all of the bacteria from these mice using some antibiotics, and we are specifically studying data on the data science spectrum to study whether it’s causing diabetes alone itself, not with the help of other bacteria in their communities,” Girdhar said.
Girdhar is working on this part of her experiment with the help of undergraduate student Jaewon Oh, MCAS ’23. Girdhar said she suspects it will take three to four months to determine whether there is any effect of parabacteroides distasonis specifically.
After the confirmation of the bacterium using the mouse model, Altindis said he wanted to examine the effect of this bacteria exposure in the guts of humans. To address this question, he said he downloaded data from the microbiome project, “DIABIMMUNE,” which examines the microbiome of children in Finland, Russia, and Estonia.
According to Altindis, he and his team now know that parabacteroides distasonis is causing type 1 diabetes constraints in the mouse model. By analyzing the study of human data, he said they show that the bacterium might be related with human type 1 diabetes as well.
“[Next], we will be doing two different things,” Altindis said. “The first one is to make a mutation of the sequence of bacteria and to see if the effect is really caused by this peptide. [The second step is to] get this [TEDDY data] to make the same analysis to show if we can reproduce or see similar results to what we found in this study.”