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Expanded Chromatin Accessibility Mapping Explains Genetic Variation Associated with Complex Traits in Liver.

Brandon M Wenz¹, Max F Dudek², Shweta Ramdas³

¹Genetics and Epigenetics Program, Cell and Molecular Biology Graduate Group, Biomedical Graduate Studies, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, USA.

Medrxiv : the Preprint Server for Health Sciences

|September 26, 2025

Summary

This summary is machine-generated.

This study used ATAC-seq to map chromatin accessibility in human livers, identifying thousands of regulatory elements and chromatin accessibility quantitative trait loci (caQTLs). Integrating this with GWAS data revealed mechanisms for complex traits, though some signals remain unexplained.

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Chromatin Extraction from Frozen Chimeric Liver Tissue for Chromatin Immunoprecipitation Analysis

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Area of Science:

Genomics
Molecular Biology
Human Genetics

Background:

Genome-wide association studies (GWAS) link genetic variants to complex human traits.
Understanding gene regulation is key to interpreting GWAS findings.
Chromatin accessibility studies reveal regulatory elements influencing gene expression.

Purpose of the Study:

To investigate the role of chromatin accessibility in human liver and its relation to complex traits.
To identify chromatin accessibility quantitative trait loci (caQTLs) and their contribution to gene regulation.
To integrate multi-omic data for a comprehensive understanding of GWAS signals in blood lipid traits.

Main Methods:

Assay for transposase-accessible chromatin with sequencing (ATAC-seq) on 189 human liver samples.
Identification of accessible chromatin regions and caQTLs.
Colocalization analysis of caQTLs, expression quantitative trait loci (eQTLs), and GWAS signals for blood lipid traits.

Main Results:

Over two million accessible chromatin regions and over 14,000 caQTLs were identified.
157 loci showed colocalization between caQTLs, eQTLs, and GWAS signals for blood lipids.
Approximately 20% of blood lipid GWAS signals lacked a clear mechanistic link through current QTL data.

Conclusions:

Integrating liver chromatin accessibility data (caQTLs) with GWAS and eQTLs provides mechanistic insights into complex trait associations.
A significant portion of GWAS signals for blood lipid traits currently lack a statistically supported molecular mechanism.
Further experimental validation is needed to fully elucidate the mechanisms underlying complex trait associations.