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Metabolic syndrome is a complex disorder associated with obesity that can lead to a number of serious conditions including type 2 diabetes, cardiovascular disease, non-alcoholic fatty liver disease, and cancer.
With an estimated 64 million Europeans diagnosed with type 2 diabetes alone by 2030, metabolic syndrome has a major, increasing impact on lives and public health budgets. Without intervention, the cost of treating illnesses associated with metabolic syndrome will increase to an estimated EUR 100 billion per year over the next 12 years, according to the EU-funded project RESOLVE.
The fact that some people remain healthy despite living a sedentary lifestyle with a diet rich in sugars and fats suggests that there is a clinical way to prevent metabolic syndrome, says project coordinator Bert Groen of the University Medical Center Groningen in the Netherlands.
Previous efforts have been unable to paint a complete picture of how the diseases associated with metabolic syndrome progress on a molecular level. Now, a computational framework developed by RESOLVE is already providing fresh insights into how fats and sugars are processed in the body.
RESOLVE combined the expertise of biologists, clinicians and engineers from eight EU countries to unravel some of the mysteries of metabolic syndrome. The resulting computational framework is composed of multiple computer models, providing clues as to why some people develop the associated diseases and others do not.
‘We feel that production of these models is an important step in understanding the development of metabolic syndrome, offering new opportunities to identify strategies to prevent the disease and its comorbidities,’ says Groen. ‘Importantly, this approach is not unique for metabolic syndrome and can also be applied to the study of the long-term development of other complex, progressive diseases.’
Narrowing the possibilities
The project required RESOLVE researchers to develop a new type of computational modelling because conventional mathematical models cannot come close to describing a complex network of metabolic reactions, processes and physiological outcomes – such as changes in gene expression and protein activity – using only equations. There are too many unknowns.
The novel ADAPT algorithm overcomes this uncertainty with iterative learning. As the program builds more factors into its analysis, the possible influences are narrowed down. ADAPT maps the progression of metabolic disorders by making use of experimental data alongside computer simulations to identify disturbed molecular processes.
The researchers found that the ADAPT model accurately predicted the progression of metabolic syndrome and the development of associated diseases in mice.
Within the RESOLVE computational framework, a different model was developed with the purpose of predicting the effect of bariatric surgery in obese patients with metabolic syndrome.
A massive reduction in fatty liver disease in patients one year after bariatric surgery was found. This reduction occurred in the presence of enormous improvements in metabolic health, such as insulin resistance and dyslipidemia.
The model could correctly predict improvement in blood glucose levels observed in patients one year after the surgery. This model has been developed further and is now able to take data for individual patients as an input to make personalised predictions.
The computational framework is likely to improve the diagnosis and treatment of metabolic syndrome, with the ultimate aim of identifying drug targets for controlling the levels of lipid, glucose and cholesterol in patients’ bloodstreams to prevent development of metabolic diseases.
Findings from the experimental data, clinical studies and modelling included the following results:
- there are two disease subtypes in a metabolic syndrome mouse model – those with elevated lipid levels and those without;
- enriching diets with certain amino acids (serine or alanine) reduced levels of triglycerides (fats) in the blood and the liver;
- bile acids play an important role in several aspects of metabolic syndrome, and this understanding led to the development of a comprehensive computational model to describe how the human body regulates levels of bile acid;
- newly identified microRNAs in the bloodstream could be used to help prioritise patients with the highest risk of developing diabetes.
A new route to modelling and treating metabolic disorders
The work of the RESOLVE project advances the field of metabolic diagnostics, paving the way for an effective, personalised approach to predicting, monitoring and treating metabolic syndrome and its associated diseases.
‘Our work will be translated into novel avenues for the development of therapeutic interventions – in close collaboration with the European biotechnology and pharmaceutical sectors – resulting in a profound impact on the health of European citizens,’ says Groen.