Statistical analysis of genetic data helps establish causes of disease and develop precise therapies

The research group led by Professor of Statistics Matti Pirinen has been involved in establishing the genetic background of dozens of diseases using computational methods. The results developed in the field can be seen in a variety of effective new therapies.

What are your research topics?

I’m a professor of statistics investigating computational methods that allow us to draw reliable conclusions from observational data. My main field of application is research in human genetics. For example, by comparing the genomic data of over 100,000 migraine patients and healthy individuals, we wish to identify which of the millions of parts of the genome make an individual susceptible to migraine. We are also exploring which genes and biological processes are associated with such diseases.

The same computational methods we apply to migraine data are applicable to genetic research on other diseases as well. Over the years, my research group has been involved in establishing the genetic background of dozens of diseases in large international collaboration projects.

Where and how does the topic of your research have an impact?

Identifying genetic risk factors helps us understand the biological mechanisms of diseases and develop new treatment methods.

In addition, genetic data can be used for individual risk estimates, which may in the future support doctors’ decision-making and the allocation of healthcare resources.

What is particularly inspiring in your field right now?

Technological advances in genomics are staggering, and effective new treatments based on genetic data and gene editing have recently been introduced. The early development of such treatments owes much to the statistical processing of extensive genetic datasets. It’s great to be working in a field in which multidisciplinary collaboration has been shown to be crucial.