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Liver single-nucleus multiome profiling reveals cell-type mechanisms for cardiometabolic traits

GSE296875 Homo sapiens Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing 16 samples Submitted 2025/10/01 Platform GPL24676
Summary
Genome-wide association studies (GWAS) have identified numerous genetic variants associated with cardiometabolic traits, yet their mechanisms in relevant liver cell types remain unclear. Using multiome single-nucleus RNA and ATAC sequencing on liver samples from 39 individuals, we profiled gene expression and chromatin accessibility in 68,398 nuclei across six primary liver cell types. We identified 306,706 accessible chromatin regions, including 70,884 regions undetected in bulk tissue analyses, predominantly representing less abundant cell types. By mapping quantitative trait loci (QTLs), we detected 1,885 chromatin accessibility QTLs (caQTLs) and 67 expression QTLs (eQTLs), highlighting genetic regulation in the different liver cell types. We integrated cell-type QTLs with GWAS signals and revealed cell-types, genes, and chromatin regulatory elements involved in cardiometabolic traits, such as liver enzymes and cholesterol levels. Importantly, non-hepatocyte cell-type QTL analyses elucidated previously obscured mechanisms, such as an eQTL for ADAMTS12 in liver sinusoidal endothelial cells potentially involved in liver fibrosis, demonstrating how single-nucleus approaches capture regulatory events missed in bulk analyses. Furthermore, we annotated bulk liver caQTLs colocalized with GWAS signals to liver cell types, enhancing functional interpretations and predicting cell-type of action for complex trait associations. Our findings provide a comprehensive, high-resolution map of the hepatic regulatory landscape, advancing the understanding of cellular contexts and molecular mechanisms underlying cardiometabolic diseases.
Published in
Liver single-nucleus multiome profiling reveals cell-type mechanisms for cardiometabolic traits
Alkhawaja AA, Currin KW, Perrin HJ et al. · American journal of human genetics 2026 · PMID 41338218 · doi:10.1016/j.ajhg.2025.11.009
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Also filed as BioProject PRJNA1261871 and SRA study SRP584786. Searching any of these in the dataset finder brings you back here.

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