# Chromatin state origins of uterine leiomyoma

## TL;DR

This study explores how chromatin states in uterine tissue contribute to the development of uterine leiomyomas, using regulatory genomics and genome-wide data.

## Contribution

The study introduces chromatin annotations for myometrium and leiomyomas, linking disease-associated genetic variants to specific chromatin states.

## Key findings

- Chromatin states in myometrium and leiomyomas reveal bivalent regions important in neoplastic processes.
- Disease association loci are enriched at active chromatin, particularly enhancers.
- Risk genotypes at the SATB2 locus affect chromatin states even in normal tissue.

## Abstract

Aberrations in the regulatory genome play a pivotal role in population-level disease predisposition. Annotation of the regulatory regions using appropriate primary tissues - instead of cell lines affected by selection and other confounding factors - could shed new light into mechanisms underlying common conditions. We test this approach in uterine leiomyomas, highly prevalent benign neoplasms of the myometrium, by creating 15-state chromatin annotations for myometrium and uterine leiomyomas. Integration with RNA-seq, ATAC-seq, HiChIP and methylation data enables us to compare the epigenomes of myometrium and ULs with distinct driver mutations, highlighting the role of bivalent regions in the neoplastic process. Subsequently, a genome wide association study meta-analysis is performed, using three different cohorts. Disease association loci are enriched at active chromatin, especially at enhancers, and harbor tumor- and driver mutation-specific chromatin states. At SATB2 locus we show the effect of the risk genotype already in the normal tissue. Integration of genome-wide association studies and deep regulatory genomics data from the correct tissue type represents a powerful approach in understanding population-level disease predisposition.

The chromatin state origins of uterine leiomyoma (UL) remain to be explored. Here, the authors integrate data from genome-wide association studies and deep regulatory genomics data from myometrium and the three UL subclasses to understand population-level disease predisposition at chromatin state level.