Q&A: Dr. Jason Gaglia on Visualizing the Type 1 Diabetes Attack
Friday, June 10, 2011
After decades of research on type 1 diabetes, we still see huge gaps in our understanding of the autoimmune onslaught on the pancreas that triggers the disease. Jason Gaglia, M.D., a Joslin physician now opening his own lab here, and his colleagues use magnetic resonance imaging (MRI) as part of a powerful new method of visualizing the inflammation produced by the attack. Here he answers three questions about how this new technique will aid in understanding the disease.
What does your approach allow you to do in patients?
We’ve shown that soon after a diagnosis of type 1 diabetes, you can measure the inflammation in the pancreas, which destroys the insulin-producing cells, by using MRI and magnetic nanoparticles.
During this autoimmune attack, the most numerous cells in the inflammatory lesions in the pancreas are T cells. Prior efforts at imaging this inflammation in live humans have used radioactively labeled cells or proteins focusing on these T cells. Unfortunately, the images have not been optimal and such strategies must be approached with extreme caution as repeated radiation exposures are best avoided, particularly in children.
The second-most-common autoimmune cell in the type 1 diabetes lesion is the macrophage, which gets into the pancreas islets through leaky blood vessels. It just so happens that if you design small particles correctly, macrophages will love to eat them up.
Ralph Weissleder of Massachusetts General Hospital, who was developing nanoparticle probes for cancer imaging, developed an iron-based nanoparticle that generally has a long intravascular half-life except in areas where there is increased leakage from blood vessels, as in cancers or for our purposes in the inflamed pancreas lesions of type 1 diabetes. These particles can leak out and be gobbled up by macrophages in the area of inflammation. And because they are made of iron, they are detectable by MRI.
This idea was the start of a long-term collaboration between the Weissleder lab and the lab of Diane Mathis and Christophe Benoist, formerly at Joslin and now at Harvard Medical School. I was tasked with converting this technique from something that worked in animals to something that would work in people. We demonstrated success in a pilot study in a paper published in January in the Journal of Clinical Investigation.
What are the benefits of this approach?
I won’t use it for a diagnosis of clinical diabetes. I can do that with a blood glucose reading. MRI is a whole lot more expensive than a blood glucose reading.
But this MRI technique will be very useful in several areas where currently available testing falls short.
One of them is for testing drugs aimed to slow or stop the autoimmune attack, with a series of images. I could take an image, treat the patient with a drug that might reduce the inflammation and take another image several months late. Now I could see that response much more sensitively than I could by looking at blood glucose levels, because many things are integrated into that blood glucose level. But with the MRI, I’m actually looking at what I’m interested in, which is the inflammation in the pancreas.
A number of drug trials have failed recently, unfortunately. There are people making the claim that, in at least one case, the trial failed because the researchers, trying to minimize potential side effects, picked a drug dose that was too low to be effective. With this technology, we might have found a dose that still provides the decrease in inflammation (which we could directly measure) but doesn’t give the side effects.
These images also could make it much faster to see if you’re getting a response.
Another place where this technology is potentially useful is disease prediction. If I’m running a trial for disease prevention, I want to pick those people who are at highest risk for developing clinical disease, because I can decrease the number of individuals I am exposing to risk by participating in the trial that are unlikely to develop disease during the trial anyway. This could cut down the number of people I need to enroll and potentially decrease the duration of the trial. We can likely identify those people at highest risk of progression by MRI, although we still need to prove that.
Hopefully this capability will encourage more companies to invest in type 1 diabetes research. The difficulty in making measurements at the organ level, where the disease is happening, within the pancreas itself has previously made research in this area very hard and costly.
What can this approach tell us about the causes of type 1?
I don’t know what happens in someone’s pancreas when they get type 1 diabetes. In multiple sclerosis there are very different disease patterns in different people; is the same true for type 1 diabetes? Maybe the progression is different and maybe we need to treat these people differently. I don’t know, because I can’t take out people’s pancreases, look at them and put them back in. But with a non-invasive way of looking at the inflammation in the pancreas, I can look repeatedly over time, and get a much better idea of what this disease actually is doing.
The process of developing type 1 diabetes is not fully understood. We know that some people are genetically at risk to begin with. Lots of people have these genes, but only a very small minority goes on to develop disease. You need something else to happen, and it isn’t clear what that trigger point is.
It’s possible that maybe lots of people develop a little bit of pre-clinical disease, and then the immune system turns back off. Or maybe a viral infection, or something they eat, or something else that certain people see at a certain time triggers the attack and then it just rolls down a hill like a snowball. We don’t know.
In general, antibody tests indicate that most kids who are diagnosed with type 1 diabetes will show an autoimmune reaction to insulin. When we look at adults who are diagnosed with type 1 diabetes, most of them instead have an autoimmune reaction to a protein called GAD65 and not insulin. Maybe there is a difference in the disease between these two age groups.
Those are the kinds of questions that are open. It is a very complicated problem. That’s why it will be nice to use something that looks specifically at the inflammation, because that’s a process that happens to everyone with type 1 diabetes.
Now we can go ahead and leverage this technique, with its great promise for bettering our understanding of type 1 diabetes and aiding the development of therapies.
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