The molecular life course of a buttercream birthday cake

Birthday parties with my extended family are always loud with lots of people and lots of food; it’s full of children eating and playing. And in the midst there is a three year old boy who patiently tells my cousin what he had to eat featuring quite prominently the buttercream he impishly licked off his piece of the birthday cake. My cousin’s son has type 1 diabetes. His body cannot produce any insulin to regulate his blood glucose levels. Therefore, it is up to him and his parents to constantly check and regulate the circulating glucose. Patients with diabetes have a shorter life expectancy due to an increased risk for microvascular diseases such as kidney disease and macrovascular diseases such as atherosclerosis and stroke. Blindness and amputations are also possible diabetic related complications.

Diabetes comes in different forms. People like my cousin’s son suffer from type 1 diabetes that typically affects younger people and leads to a complete loss of insulin production. Type 2 diabetes is more common. It develops silently and gradually mainly affecting older people when their bodies become less sensitive to insulin and it is associated with a sedentary lifestyle and obesity. As Australians become less active and more obese, type 2 diabetes is on the rise. According to Diabetes Australia, 180 Australians are newly diagnosed with type 2 diabetes every day

With so many interacting risk factors and the spectrum of diabetes, how can we make sense of the complexity? Systems biology has emerged as a branch of science that aims to put the pieces together in their appropriate context. Within the Molecular Life Course Research (Molar) group, we analyse dynamic, complex interaction data with the ultimate aim to find and understand molecular patterns that are indicative, predictive or causative of cardiovascular disease, diabetes and obesity. University of Adelaide Professor Ville-Petteri Mäkinen is heading these research efforts and he is currently supported by two Post-doctoral researchers Song Gao and Stefan Mutter. His team is one of two EMBL Australia research groups hosted by SAHMRI. EMBL is the European flagship organisation for life science research and Australia is an associated member of it with research groups all over the country. This EMBL network provides opportunities for national and international co-operations in Australia and throughout Europe.

Currently, we are working together with a group of Finnish scientists led by Dr Markku Lehto (Folkhälsan Research Center, Helsinki) looking into the relationship of type 1 diabetes and high fat meals. For that purpose, type 1 diabetes patients and healthy individuals were given three consecutive high fat meals throughout the course of one day. This reflects the situation my cousin’s son and all other patients are in. Our data consists of metabolic profiles that give information on lipids and amino acids in the blood. Lipid concentrations including cholesterol particularly are important as they are closely linked to cardiovascular disease. Most of the cholesterol is carried in low-density lipoprotein (LDL) particles to the cells and a high LDL concentration is a causal risk factor for atherosclerosis.

Looking at each metabolite separately, we were surprised how similar the average diabetic and non-diabetic person reacts to three consecutive high fat meals (Figure 1), although the situation might be very different for high-carbohydrate meals that have a stronger impact on glucose metabolism. Interestingly, the individual responses vary greatly (Figure 1). For example, it is reasonable to expect that ingestion of lipids leads to increase in circulating lipids in the blood, but in both groups there are individuals whose lipid levels stay constant and others whose increase is three times the baseline fasting value.

Figure 1. Post-prandial triglycerides. (A) Average increase in triglycerides concentrations from a fasting baseline for type 1 diabetes patients and non-diabetic individuals during the course of a day while having a high fat meal at breakfast (8m), lunch (12pm) and dinner (4pm). (B) Histogram showing the maximum increase of individual triglycerides concentrations from fasting baseline during the course of day with high fat meals at breakfast (8am), lunch (12pm) and dinner (4pm).

We have just had a first look at a large epidemiological dataset of over 8000 Chinese people living in the Jiangsu province whose nutrition, health and some socio-economic factors have been monitored meticulously at baseline and at a follow-up five years later. We are also looking at the metabolomics data from large population cohorts in Europe. The fasting state is well covered by existing literature, but the great challenge is to connect small, detailed studies like the one with high fat meals and type 1 diabetes patients with population-level data and policies. Metabolomic profiling could be a solution and therefore, we are pursuing an interdisciplinary approach to understand the biology. From a scientific point of view, small and detailed datasets that follow people throughout the day are important as they contain keys to what happens while we are not at fasting.

Now, what does this all mean for my cousin’s son? At the next birthday party when my family’s traditional buttercream cake will be served and all the children just want to lick off the cream and leave the drier sponge cake underneath for their parents, it is still unhealthy to do so. But if he and his parents monitor his blood sugar levels and keep them well controlled, our first results indicate that at least he is not worse off from a metabolomics perspective than the other healthy children who just like him cannot wait for their parents to be distracted so that they can lick off the fatty buttercream.

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