In the second part of a two-part interview, Nightingale sat down with Stefan Mutter and Erkka Valo — researchers from the Finnish Diabetic Nephropathy (FinnDiane) Study Group — to discuss how urine data is changing the way researchers study diabetes and helping them make novel findings.
Traditionally, researchers have used blood samples to study diabetes. However, with the availability of fully quantitative urine metabolite data, many scientists in diabetes research claim that urine analysis might be more insightful than blood, especially in the field of diabetic kidney disease.
In the second part of a two-part interview on the future of diabetes research (read part one here), we caught up with Stefan Mutter and Erkka Valo — researchers from the world-leading Finnish Diabetic Nephropathy (FinnDiane) Study Group lead by Prof. Per-Henrik Groop — to discuss how urine data is changing the way researchers study diabetes, opening new opportunities and even helping them make novel findings and associations. Excerpts:
Mutter: It's because we mainly study kidney disease as a complication of type 1 diabetes. Since urine is produced by the kidneys, analysing it gives us a better picture of the kidney function and their health. Our study’s objective is to identify the association between type 1 diabetes and kidneys’ health to better understand the mechanisms behind the development of kidney disease. The metabolites in the urine can help us reveal this.
Mutter: There are many things that you cannot see in blood or not see so well when compared to urine. It's important to look at the urine in other diseases as well because urine is not only influenced by the function of the kidneys. The kidneys filter the blood, and in the blood, there are well-established markers for cardiovascular disease (CVD). Therefore, there are also likely changes in the urine that can be associated with CVD or its early signs. So, there are clear reasons to believe that urine could provide biomarkers for CVD.
Looking at cardiovascular disease is also very important when researching type 1 diabetes.
That’s because kidney disease takes longer to develop, therefore, even if an individual starts developing kidney disease, they're more likely to die of cardiovascular disease. So, it makes sense to study the CVD risks in the FinnDiane participants.
Valo: Also, urine is not so tightly regulated by the body as blood. More specifically, urine is a waste product.
Mutter: I am sure data from the urine will be something everyone will be interested in looking at. This way, it may even become part of the routine analysis process to assess research subjects.
In FinnDiane we do urine measurements routinely. With these new data, maybe the other cohorts too will start taking urine measurements and not completely rely on blood measurements.
Further research will show that this is an important body fluid to study. I can see that this can change the way data are collected for studies. And since it is relatively easy to collect a urine sample, this will be a simple thing to implement.
Mutter: Yes, as urine sample collection is non-invasive and therefore highly suitable for children. In FinnDiane, the participants are adults or young adults. But there are cohorts with very young children who have type 1 diabetes. For them, it would be much easier to collect urine than blood.
Valo: It would be interesting to look at the relationships of metabolite levels in the blood and urine and see how you can use that information to deepen the molecular understanding of kidney function and their role in chronic diseases. Also, from the perspective of genetics, it will be exciting to see, whether some genetic variants affect the levels and ratios between the blood and the urine metabolites.
Mutter: At the beginning of any large-scale urine analysis, it's good to look at the metabolite levels in blood and urine to identify similarities and differences between them. Similarities in the metabolite levels between blood and urine are considered as reassuring, while differences can give hints about what's happening in the kidneys. For instance, the filtration process — how it's affected or if the reabsorption in the kidneys is working properly or not. It's also nice to see that there are overlaps in the metabolites between blood and urine.
Mutter: I really think so. There were already some novel findings in our first analyses. So, there's a good chance of making further novel findings because we don't know what's in there (urine metabolites data) and how it relates to diabetes or diabetic complications.
Mutter: Yes, since we have NMR metabolite data for both blood and urine, we have been able to cross-examine correlations between urine metabolites and lipoprotein subclasses in serum, for example. They look quite interesting. Also, we have already started a cardiovascular project with the data and are introducing it in other projects as well.
Mutter: For type 1 diabetes, it's more about the treatment of complications because it's an autoimmune disease that happens early in life. So, urine can help find metabolites that indicate if an individual is starting to become more vulnerable to diabetic kidney disease or cardiovascular disease.
The initial results have already shown that the urine contains different metabolites to indicate the early and later stages of kidney disease progression. This can help us intervene early and start treating individuals at an early stage in order to be able to slow the progression.
But also, hopefully for cardiovascular disease in the future. If we can identify people, who are more likely to develop cardiovascular disease, those individuals can benefit from an earlier start of statin medication. You can also detect dietary metabolites from the urine, which can be used to give advice regarding lifestyle changes.
So, this (urine analysis) isn’t limited to type 1 diabetes but applies to type 2 diabetes as well. Prevention can work for pre-diabetic people, who haven’t been diagnosed with diabetes yet but have a high risk of developing it in the future. Nutritional metabolites also provide the possibility to check whether individuals are following their intervention guidelines. How individuals then respond to intervention is a different thing. Basically, there is a multitude of ways how you can use this data for further research.