There are some problems that are more complicated than others, and some problems that are more common than others. Unfortunately, when it comes to disease, complex diseases are also the most common ones.
Unlike non-complex illnesses – which are triggered by a single faulty gene – complex diseases (such as allergies, diabetes or cancer) are caused by a combination of genetic, environmental and lifestyle factors. Increased life expectancy also means more and more people suffer from old-age related complex diseases, such as osteoporosis and Alzheimer's disease.
"A large percentage of Europeans suffer from complex diseases," Dr. Mikael Benson from Linköping University said of the pressing health concern. "Yet because complex diseases depend on thousands of genes interacting in hundreds of different ways, researching them is very difficult." The Swedish paediatrician, Benson, recently coordinated MultiMod (multi-layer network modules to identify markers for personalised medication in complex diseases), a four-year European Union (EU)-funded research project that finished in 2012. MultiMod united experts from Europe and the USA to examine individualised treatments for seasonal allergic rhinitis – commonly known as hay fever.
"The principal challenge with complex diseases is that two patients who appear to have the same affliction will not always benefit from the same treatment," Benson explained. MultiMod therefore sought to identify genetic markers that predict treatment success in individual patients.
In the past, complex disease research has largely focused on individual genes. Benson compared this to "trying to understand a football game by examining one single player in isolation from everything else". Understanding a disease like hay fever, however, requires taking thousands of genes into account. "To make sense of all of these point of data we organised genes into networks or, as we call them, modules to be able to examine hay fever on a systems level." Returning to the football analogy: "this is like watching the entire team and the interaction between the players."
Studying hay fever held several advantageous for Benson and his colleagues. Firstly, the illness is seasonal, which enabled them to examine patients both with and without symptoms. Secondly, pollen is its known trigger, meaning they could cause and monitor allergic cell reactions in laboratory conditions. Thirdly, hay fever is a common disorder, meaning the team could examine data from over 5000 people – a number that would have been difficult to reach in other diseases like cancer.
Benson added: "As hay fever is one of the simplest complex diseases, it is a good starting point for tackling the difficult area of personalised treatments for complex diseases." The team did select a rather difficult approach, however. "We were among the first to analyse clinical data from a systems medical perspective," Benson said, which is to say they collected clinical data and analysed it using modern network tools. "Once we saw our method worked with hay fever, we also successfully applied it to a study of multiple sclerosis." This included analysing a multiple sclerosis database with information from 20,000 people, of whom 10,000 were affected by multiple sclerosis. The project thus successfully identified why patients respond differently to medication and predicted treatment success for the two complex diseases, hay fever and multiple sclerosis.
Unfortunately, affected persons will have to wait several years more before these treatments become broadly available. In fact, Benson believes individually tailored cancer medication will be the first to appear on the market and plans to use the MultiMod approach to study leukaemia treatments.
Delays in successfully treating complex diseases currently cause considerable suffering in patients, as well as unnecessary costs (in the USA, for instance, it is estimated that $350 billion of ineffective prescriptions go to waste every year). Benson believes personalised treatments, like those developed by the international MultiMod team, which assembled experts from Sweden, Norway, Germany, the UK and the US, are the key to moving towards faster cures. He hopes other research teams will soon apply MultiMod's methods to other diseases.