Tracking the endometrial cycle

Melbourne Bioinformatics bioinformatician and PhD student Jessica Chung is joint lead author of a Nature Communications paper which outlines an important new method for tracking endometrial cycles through gene expression.

Thanks to its key role in the menstrual cycle, the health of the endometrium is important to the quality of most women's lives. But while it has come under increasing research scrutiny in recent decades, the endometrium is still surprisingly poorly understood. In large part this is due to the difficulty in determining endometrial staging, not only because of the naturally wide differences in the length of menstrual cycles but also the rapid changes how endometrial genes are expressed, varying on a daily or even hourly basis. Together, these factors have made it difficult to replicate findings in research on topics such as endometriosis, heavy menstrual bleeding and endometrial receptivity for embryo implantation.

In research just published in Nature Communications, a team, led by Prof Peter Rogers of the Royal Women's Hospital and including Jessica Chung (joint lead author) and Clare Sloggett of Melbourne Bioinformatics, has developed a new method to accurately determine where a woman is in her menstrual cycle by analysing the activity of key endometrial genes. This molecular staging model identifies significant daily changes in the activity of over 3400 genes, with the most pronounced changes occurring during the secretory phase, in which hormonal changes prepare the endometrium for implantation. By standardising gene activity data, the study has shown that endometrial gene expression changes significantly with age. This breakthrough method offers a wealth of new information on uterine gene activity and opens the door to better understanding the endometrium’s role in reproductive health.

The code for the molecular staging model is available on Jessica's github repository as endest, an R package. The paper can be read here:

Teh, W.T., Chung, J., Holdsworth-Carson, S.J., Donoghue, J.F., Healey, M., Rees, H.C., Bittinger, S., Obers, V., Sloggett, C., Kendarsari, R., Fung, J.N., Mortlock, S., Montgomery, G.W., Girling, J.E., Rogers, P. a. W., 2023. A molecular staging model for accurately dating the endometrial biopsy. Nat Commun 14, 6222. https://doi.org/10.1038/s41467-023-41979-z