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EBioMedicine· 2026Q1· Review

Decoding adenomyosis: integrative insights from genetics, multiomics, and advanced computational analyses

刘斌雅, Juan C. Irwin, Linda C. Giudice

Short summary

Integrative analysis of genetics, multiomics, and computational tools reveals causal genes and genomic/epigenetic mechanisms driving adenomyosis, including altered estrogen/progesterone signaling and inflammation.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Adenomyosis pathogenesis involves genetics, multiomics, and computational analyses.
  • Specific genes are causally linked to adenomyosis.
  • Genomic and epigenetic mechanisms promote altered estrogen/progesterone signaling and inflammation.
  • AI-driven platforms integrating multiomics data identify potential therapeutic candidates.

AI-generated from the title and abstract; the full text is not read.

Abstract

Adenomyosis is an oestrogen-driven, inflammatory uterine disorder characterised by endometrial glands and stroma in the myometrium resulting in abnormal bleeding, pain, and poor reproductive outcomes. Multiple contributors to its pathogenesis and pathophysiology have been identified over the years using a variety of experimental approaches and technologies, with gaps in integrating these approaches into a comprehensive paradigm of adenomyosis pathobiology. This review provides integrative insights from recent studies focused on genetics, multiomics, and advanced computational approaches. These demonstrate that select genes are causally linked to adenomyosis and that genomic and epigenetic mechanisms promote the enhanced oestrogen and diminished progesterone signalling and associated inflammation that are pathognomonic of the disorder, supported by orthogonal validation including novel 3D in vitro cell models. In addition, advanced computational tools, including AI-driven platforms that integrate multiomics data, reveal promising therapeutic candidates for mitigating disease progression and symptoms and improving fertility and pregnancy success.

The authors' abstract, as published at the source. EBioMedicine, 2026 · DOI ↗

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Field: Reproductive Medicine

Reproductive MedicineMedicine