Integrating leiomyoma genetics, epigenomics, and single-cell transcriptomics reveals causal genetic variants, genes, and cell types

Kadir Buyukcelebi, Alexander J. Duval, Fatih Abdula, Hoda Elkafas, Fidan Seker-Polat and Mazhar Adli ()
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Kadir Buyukcelebi: Feinberg School of Medicine at Northwestern University
Alexander J. Duval: Feinberg School of Medicine at Northwestern University
Fatih Abdula: Feinberg School of Medicine at Northwestern University
Hoda Elkafas: Feinberg School of Medicine at Northwestern University
Fidan Seker-Polat: Feinberg School of Medicine at Northwestern University
Mazhar Adli: Feinberg School of Medicine at Northwestern University

Nature Communications, 2024, vol. 15, issue 1, 1-14

Abstract: Abstract Uterine fibroids (UF), that can disrupt normal uterine function and cause significant physical and psychological health problems, are observed in nearly 70% of women of reproductive age. Although heritable genetics is a significant risk factor, specific genetic variations and gene targets causally associated with UF are poorly understood. Here, we performed a meta-analysis on existing fibroid genome-wide association studies (GWAS) and integrated the identified risk loci and potentially causal single nucleotide polymorphisms (SNPs) with epigenomics, transcriptomics, 3D chromatin organization from diverse cell types as well as primary UF patient’s samples. This integrative analysis identifies 24 UF-associated risk loci that potentially target 394 genes, of which 168 are differentially expressed in UF tumors. Critically, integrating this data with single-cell gene expression data from UF patients reveales the causal cell types with aberrant expression of these target genes. Lastly, CRISPR-based epigenetic repression (dCas9-KRAB) or activation (dCas9-p300) in a UF disease-relevant cell type further refines and narrows down the potential gene targets. Our findings and the methodological approach indicate the effectiveness of integrating multi-omics data with locus-specific epigenetic editing approaches for identifying gene- and celt type-targets of disease-relevant risk loci.

Date: 2024
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DOI: 10.1038/s41467-024-45382-0

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