Research involving 300,000 women started as a student project

This is the largest genome-wide association study meta-analysis of its kind, analysing  data on 42 female reproductive health diagnoses from the Estonian Biobank and FinnGen. 

Researchers looked at data from around 300,000 women. According to Triin Laisk, associate professor of genomics and reproductive genetics at the University of Tartu, who coordinated the study, it is one of the first to look at a wide range of women's health diagnoses systematically, using different genetic epidemiology methods to illustrate how genetic studies can help to understand the biological background of disease. Genetic epidemiology is a branch of science that studies the genetic risk factors for various diseases.   

"Women's health has been an under-researched area for quite a long time, and we are truly delighted that it is now receiving this kind of coverage in Nature Medicine," said Triin Laisk, adding that it is a good example of how something that started as a student project can become a very important piece of research in the field, published in one of the best journals in the world.   

In addition to identifying previously undescribed genetic associations, shared genetics were also described. In this way, genetic risk factors which are shared across different phenotypes, provide information about processes central to women's health, such as reproductive tract development, folliculogenesis and hormone regulation. Unique genetic associations on the other hand reflect disease-specific biological mechanisms.    

"Identifying previously undescribed associations provides information on the biological background of diseases and traits, which are a valuable input for, for example, drug development. A good example is the analysis of ovarian cysts, where we identified associations with genes whose role in human folliculogenesis has not been described previously but which are associated with ovulation and maturation of oocyte-containing follicles in mouse models. Such information could be useful, for example, in developing drugs for in vitro fertilization," said Laisk. Based on the results of the same project, the research group has previously published articles on the genetics of ectopic pregnancy and endometrial polyps. "We felt that these diagnoses deserved special attention," added Laisk.   

Genetics can also be used in disease risk prediction. The study used a disease called intrahepatic cholestasis in pregnancy (ICP), a rare liver disease of pregnancy, as an example. Symptoms of ICP include itching and skin irritation, and the disease usually manifests after the 30th week of pregnancy. "We found that a risk score summarizing all genetic risk factors is highly predictive of disease risk, setting the stage for early identification of at-risk pregnancies," explained Laisk. ICP is not preventable, but knowing the increased risk allows for an earlier diagnosis, which helps reduce potential complications.   

What makes the study special is that it looked separately at what are known as population-specific associations or genetic risk factors, which can be identified only by analysing Estonian and Finnish data. "This illustrates the unique value of Estonian Biobank in the global context," added Laisk. The project is also a good input for future research, as the summary statistics of the analyses are publicly available.   

See the study in Nature Medicine: https://www.nature.com/articles/s41591-025-03543-8