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

Binya Liu, Liu B, 刘斌雅, Juan C. Irwin, Irwin JC, Linda C. Giudice, Giudice LC
EBioMedicine · 2026 · pp. 106482 · doi:10.1016/j.ebiom.2026.106482 · PMID:42971818 · W7225118298
Review OA: gold public-domain-us
📄 Open PDF View on OpenAlex View on PubMed View at publisher
⚙ AI-generated summary by qwen3.7-flash, 2026-11-05 ⓘ

This review integrates genetics, multiomics, and computational analyses to reveal causal genes and epigenetic mechanisms driving estrogen-progesterone imbalance in adenomyosis, identifying therapeutic candidates via AI platforms.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

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.

My notes (saved in your browser only)

Citation neighborhood (2-hop)

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. Outer rings show 2-hop neighbours — papers reached through the immediate citers/citees. [ collapse to 1-hop ]

References (74)

Cited by (3)

Source provenance

europepmc
last seen: 2026-11-06T06:14:58.568748+00:00
openalex
last seen: 2026-11-06T06:06:51.996266+00:00
pubmed
last seen: 2026-11-06T06:08:23.875495+00:00
License: public-domain-us · commercial use OK · attribution required
Courtesy of the U.S. National Library of Medicine