On 29 June at 11:15 Viktorija Kukuškina will defend her doctoral thesis “Understanding the mechanisms of endometrial receptivity through integration of ‘omics’ data layers”.
Research Professor in Bioinformatics Reedik Mägi
Professor of Biotechnology Andres Metspalu
Professor of Reproductive Medicine Andres Salumets
Professor Stephan Beck, Cancer Institute University College London, UK
According to the World Health Organization, over 10% of females in a stable relationship are suffering from involuntary infertility/subfertility worldwide. Untangling the reasons for this is difficult because female reproduction is a sophisticated matter and can be affected by many factors such as health, accompanying diseases, genetic background, environment, and lifestyle. As a specific example, embryo implantation – its attachment to the uterine lining (endometrium) – occurs only during a relatively short period of time, called the window of implantation (WOI), when the endometrium is most receptive to an embryo. This is critical for a commonly used fertility treatment of in vitro fertilizaton (IVF) – and to make matters more complex, the WOI is not the same for everyone, but adjusted by an interlocking system of biological regulation mechanisms. Thus, to provide successful IVF, it is important to know these exact regulation mechanisms – and, since they interact with one another, to understand how they work together, not just individually. We used pairwise integration of data from different layers of genetic regulation, such as RNA, microRNA, and DNA methylation, called together the ‘omics’ layers, and showed the advantage of the data integration approach over the usage of just a single ‘omics’ layer. As a result, we obtained the lists of novel potential biomarkers that could regulate WOI, validated some previously known receptivity biomarkers, and showed that integration of different ‘omics’ layers helps to avoid false-positive results. With our work, we encourage other researchers in the female reproduction field to integrate several data layers for further studies.