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A molecular staging model for accurately dating the endometrial biopsy

Author

Listed:
  • W. T. Teh

    (University of Melbourne Department of Obstetrics and Gynaecology
    Royal Women’s Hospital
    Melbourne IVF)

  • J. Chung

    (University of Melbourne Department of Obstetrics and Gynaecology
    University of Melbourne)

  • S. J. Holdsworth-Carson

    (University of Melbourne Department of Obstetrics and Gynaecology
    Royal Women’s Hospital
    Epworth HealthCare)

  • J. F. Donoghue

    (University of Melbourne Department of Obstetrics and Gynaecology
    Royal Women’s Hospital)

  • M. Healey

    (University of Melbourne Department of Obstetrics and Gynaecology
    Royal Women’s Hospital)

  • H. C. Rees

    (Royal Women’s Hospital
    Royal Children’s Hospital)

  • S. Bittinger

    (Royal Women’s Hospital
    Royal Children’s Hospital)

  • V. Obers

    (Melbourne Pathology)

  • C. Sloggett

    (University of Melbourne
    University of Melbourne at the Peter Doherty Institute)

  • R. Kendarsari

    (University of Queensland
    Illumina Inc. 11 Biopolis Way)

  • 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
    University of Otago)

  • P. A. W. Rogers

    (University of Melbourne Department of Obstetrics and Gynaecology
    Royal Women’s Hospital)

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.

Suggested Citation

  • 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. G, 2023. "A molecular staging model for accurately dating the endometrial biopsy," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41979-z
    DOI: 10.1038/s41467-023-41979-z
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    References listed on IDEAS

    as
    1. Josep Darbà & Alicia Marsà, 2022. "Economic Implications of Endometriosis: A Review," PharmacoEconomics, Springer, vol. 40(12), pages 1143-1158, December.
    2. Simon N. Wood & Natalya Pya & Benjamin Säfken, 2016. "Smoothing Parameter and Model Selection for General Smooth Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1548-1563, October.
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