Most diseases have a polygenic background. Many different genes are involved, interacting in complicated ways with each other, and this interaction is still poorly understood. Even the smallest changes in relevant genes may increase the risk of disease. And that is precisely the point of departure for Maik Pietzner’s research project GenDrug, for which he has now received an ERC Starting Grant.
A quantum leap in methodology
“There are hundreds of common – and often chronic – diseases for which no good drugs presently exist,” explains Pietzner. “With the GenDrug project we aim to help improve the situation of affected patients.” While diseases with high mortality rates, such as cancer, are the subject of intensive research, diseases that progress in a less spectacular manner often languish in obscurity. Much less is spent on researching such neglected diseases and developing effective medicines to treat them – even though these illnesses also significantly impact patients’ quality of life of patients on a daily basis.
“We’re focusing on such neglected diseases,” says Pietzner. “Our goal is to find small disease-specific small changes in genes, thus unveiling new targets for innovative drugs. This will require us to break new ground. We’re going to link genome sequencing findings with electronic health records and use artificial intelligence to look for previously unknown connections between genetics and disease manifestation – connections that could point to new therapeutic approaches.”
The increased availability of electronic health data opens up for the first time the possibility of systematically and economically studying diseases in millions of people. “We anticipate that sifting through the huge pools of data will reveal genetic signatures that are characteristic of certain diseases,” says Pietzner. “Our computer programs are able to recognize and visualize patterns in volumes of data so enormous that they would be impossible to tackle without AI. This represents a quantum leap in terms of methodology.”
Genes contain information for producing proteins. Pietzner and his team are especially interested in these gene products. Proteins that are abundant in specific diseases or whose blueprints have been altered could provide starting points for novel, innovative therapies. Or alternatively, newly acquired knowledge about risk genes and their gene products could support existing therapeutic approaches and offer the opportunity to develop them further – which would also benefit patients.
First interesting candidates identified
In the case of Raynaud’s phenomenon, scientists in the BIH’s Computational Medicine Group have already discovered two genes that increase the risk of this relatively common but little-studied disorder by more than 20 percent. About 2 to 5 percent of the population – women more often than men – are affected by Raynaud’s phenomenon, in which small blood vessels in the fingers or toes spasm several times a day, causing numbness and pain. The newly identified genes and their gene products have been shown to play a role in the disease. Drugs that inhibit the action of these two proteins therefore appear to be suitable for significantly alleviating the distressing symptoms of Raynaud’s.
Innovation boost hoped for
But Pietzner believes this is just the beginning. “We hope to trigger a surge in innovation by leveraging the big data made available through GenDrug, thereby substantially improving the therapeutic options for a wide range of diseases.”