A molecular staging model for accurately dating the endometrial biopsy

W. T. Teh, J. Chung, S. J. Holdsworth-Carson, J. F. Donoghue, M. Healey, H. C. Rees, S. Bittinger, V. Obers, C. Sloggett, R. Kendarsari, J. N. Fung, S. Mortlock, G. W. Montgomery, J. E. Girling and P. A. W. Rogers ()
Additional contact information
W. T. Teh: University of Melbourne Department of Obstetrics and Gynaecology
J. Chung: University of Melbourne Department of Obstetrics and Gynaecology
S. J. Holdsworth-Carson: University of Melbourne Department of Obstetrics and Gynaecology
J. F. Donoghue: University of Melbourne Department of Obstetrics and Gynaecology
M. Healey: University of Melbourne Department of Obstetrics and Gynaecology
H. C. Rees: Royal Women’s Hospital
S. Bittinger: Royal Women’s Hospital
V. Obers: Melbourne Pathology
C. Sloggett: University of Melbourne
R. Kendarsari: University of Queensland
J. N. Fung: University of Queensland
S. Mortlock: University of Queensland
G. W. Montgomery: University of Queensland
J. E. Girling: University of Melbourne Department of Obstetrics and Gynaecology
P. A. W. Rogers: University of Melbourne Department of Obstetrics and Gynaecology

Nature Communications, 2023, vol. 14, issue 1, 1-13

Abstract: Abstract Natural variability in menstrual cycle length, coupled with rapid changes in endometrial gene expression, makes it difficult to accurately define and compare different stages of the endometrial cycle. Here we develop and validate a method for precisely determining endometrial cycle stage based on global gene expression. Our ‘molecular staging model’ reveals significant and remarkably synchronised daily changes in expression for over 3400 endometrial genes throughout the cycle, with the most dramatic changes occurring during the secretory phase. Our study significantly extends existing data on the endometrial transcriptome, and for the first time enables identification of differentially expressed endometrial genes with increasing age and different ethnicities. It also allows reinterpretation of all endometrial RNA-seq and array data that has been published to date. Our molecular staging model will significantly advance understanding of endometrial-related disorders that affect nearly all women at some stage of their lives, such as heavy menstrual bleeding, endometriosis, adenomyosis, and recurrent implantation failure.

Date: 2023
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DOI: 10.1038/s41467-023-41979-z

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