'New mathematical model to unviel cause of complex diseases'

Researchers have developed a mathematical model that can be used to distinguish whether a disease has a genetic or environmental cause, an advance that may lead to better treatments for complex disorders.
Patients with complex diseases have a higher risk of developing another. Multi-morbidity represents a huge problem in everyday clinical practice, because that makes it more difficult to provide successful treatment.
After analysing data from all over Austria, researchers from Medical University of Vienna managed to develop a mathematical model that can be used to distinguish whether a disease has a genetic or environmental cause.
One of the main current objectives within medicine is to gain an exact understanding of the main causes of complex multifactorial diseases. Such diseases include diabetes, COPD and asthma, for example.

With a new set of phenotypic data of diseases in combination with molecular biological data and modern complex system mathematics, it is possible to understand the interaction between genetic and environmental disorders in the development of complex diseases.
The science of complex systems aims, amongst other things, to identify relevant information within the "big data ocean" that leads to clinically relevant knowledge and hence to better treatment options.

At MedUni Vienna, data networking is being used to develop mathematical models and network theories covering a broad spectrum, from communication pathways in cell systems to analysis of the public healthcare system.

Researchers succeeded for the first time in developing a new method that can be used to establish whether various complex diseases are caused by genetic or environmental factors.
By comparing molecular networks with networks of the common diseases that occur in the Austrian population, they were able to calculate a so-called Geneticity Index.
If a disease has a high geneticity index, there is a high probability that it is of genetic origin.
On the other hand, if this index is low, environmental influences can be further investigated in order to tell, for example, whether the disease is caused by chemical toxins or problems with molecular signalling pathways.

"The main value of the study lies in the fact that we are able to match practically all available molecular data with the data of the actual diseases so that we can see the causes of the disease. And this is possible without having genetic data for the patient," said Stefan Thurner from MedUni Vienna.
One of the main findings of the study is that diseases are usually caused by entirely genetic or entirely environmental factors. It is rare for a disease to be caused by both mechanisms at the same time.
"A better understanding of the causes of the disease provides us with a much better starting point for any treatment," said Peter Klimek from MedUni Vienna.

The study was published in the journal Scientific Reports.