Paired-Tag Aids the Development of a Multimodal Epigenetic Atlas of Liver Disease

Understanding the Epigenetic Underpinnings of Liver Disease to Develop Therapeutic Interventions

Metabolic dysfunction-associated steatotic liver disease (MASLD) and alcohol-associated liver disease (MetALD) represent major causes of human liver fibrosis (Gao & Bataller and Kisseleva & Brenner). Steatosis (or fatty liver), inflammation, and fibrosis characterize MASLD, which represents a spectrum ranging from metabolic dysfunction-associated steatotic liver (MASL) to metabolic dysfunction-associated steatohepatitis (MASH). Around 20% of MASL patients will develop MASH; however, the factors driving this progression remain unclear. While studies have linked liver disease to increased morbidity and mortality, we currently lack safe and effective treatment options (Pan et al.). How can we understand disease progression to a better extent and move towards the development of improved therapeutics for liver disease patients?

Single-cell transcriptomic studies have provided valuable insight into the cell-specific transcriptomic alterations that occur during liver disease progression (Ramachandran et al., Bendixen et al., Wang et al., and Gonzlez-Blas et al.). Importantly, the data generated represents a promising platform for the development of preventive or curative treatments. While subsequent single-cell epigenetic studies have begun to unpick the regulatory mechanism controlling the observed transcriptomic alterations, the advent of single-cell assays enabling multimodal epigenetic profiling now provides an enhanced means of describing the epigenome in relevant disease-associated liver cell types and, therefore, support the development of advanced therapeutics (Chang et al., Xie et al., and Zhu et al.). Additionally, single-cell studies focused on chromatin accessibility have identified cell type-specific candidate cis-regulatory elements (cCREs) in the liver; however, we lack data regarding the functional context of these cCREs, the heterogeneity of cCRE activity between individuals and liver disease states, and the annotation of the non-coding genome outside of cCREs defined from chromatin accessibility data only.

Researchers from the laboratories of Allen Wang, Tatiana Kisseleva, David Brenner, Bing Ren, and Kyle J Gaulton leveraged recent single-cell technology advances including Paired-Tag (Parallel analysis of individual cells for RNA expression and DNA from targeted tagmentation by sequencing) technology from Epigenome Technologies - to generate transcriptomic and chromatin accessibility profiles, histone modifications associated with active (H3K27ac) and repressive (H3K27me3) states, and chromatin conformation at the single cell level for nearly 2.5 million cells isolated from 86 human livers. The liver donors had been classified as normal or suffering from simple steatosis (MASL), MASH, MASH with a history of alcohol consumption (MetALD), with the MASH/MetALD donors divided into low (low-fibrosis MASH) and high (high-fibrosis MASH) levels of fibrosis. Reporting in a MedRxiv preprint, Elison, Chang, and Xie et al.), the team defined cell type-specific gene regulatory programs and chromatin states, determined transcriptional drivers of MASH progression, and annotated MASLD genetic risk loci, and characterized disease heterogeneity; overall, the novel genes, pathways and transcriptional networks identified could represent targets for therapeutic intervention for liver disease.

Paired-Tag from Epigenome Technologies generates joint epigenetic and transcriptomic profiles at single-cell resolution and detects histone modifications and RNA transcripts in individual nuclei with comparable efficiency to single-nucleus RNA-seq/ChIP-seq assays while avoiding the requirement for cell sorting. Paired-Tag technology enables researchers to make significant strides forward in understanding gene regulatory mechanisms and improving disease management.

Multimodal Epigenetic Profiling via Paired-Tag: The Key to Understanding, Preventing, and Treating Liver Disease?

The team generated joint single-nucleus accessible chromatin and gene expression profiles, applied droplet-based Paired-Tag (Xie et al.) to generate joint single-cell profiles of gene expression and H3K27ac/H3K27me3, and employed droplet-based single-cell Hi-C (Chang et al.) to assay chromatin conformation. Subsequently, they integrated these transcriptomic and epigenetic datasets to generate single-cell and spatial maps of normal and diseased human livers, providing unprecedented insight into the regulatory programs active in distinct liver cell types and the transcriptional drivers of MASH progression.

This approach supported a comprehensive description of liver cell type-specific regulation and the exploration of the regulatory programs that drive liver disease risk and pathogenesis. First, integrating chromatin accessibility and histone modification data aided the annotation of chromatin states and defined cCREs in liver cells across a larger proportion of the genome than previously described when employing chromatin accessibility alone (The ENCODE Project Consortium and Zhang et al.). Second, integrating chromatin state and conformation data provided much-needed functional context for cCRE activity, revealing distinct properties and varying levels of enrichment for disease risk across different chromatin states. Thirdly, the integrated epigenetic dataset as a whole supported the improved annotation of MASLD risk-associated loci in liver cell types, which involved variants not previously annotated in other cCRE catalogs (Zhang et al.) and distal target genes of risk variant activity.

As hepatocytes respond to metabolic injury early in disease development (acting as a trigger for alterations in cells that prompt MASH and fibrosis, such as hepatic stellate cells), understanding their role in disease progression and the transition from MASL to MASH remains crucial. The authors revealed significant step-by-step alterations in hepatocytes and identified distinct transcriptional drivers when comparing cells from MASL, low-fibrosis MASH, and high-fibrosis MASH donor livers. MASL hepatocytes displayed increased lipid metabolism, synthesis, and uptake and the increased activity of gene regulatory networks of associated transcription factors. While the lipid-related pathways and gene regulatory networks remained active in low-fibrosis MASH hepatocytes, these cells displayed the simultaneous activation of additional programs associated with epithelial remodeling and adhesion under the control of distinct transcription factors. Finally, the transition to high-fibrosis MASH hepatocytes associated with a reduction in lipid-related pathways and gene regulatory networks and a significant increase in inflammatory and fibrotic pathways regulated by associated transcription factors. Interestingly, the upregulated lipid-related networks in MASL and low-fibrosis MASH hepatocytes displayed the most enrichment for MASLD-associated variants, which links genetic risk to processes upregulated during early-stage disease. The authors suggest that the induction of a more beneficial hepatocyte response to lipid exposure may prevent the development of fibrosis and believe that this knowledge will aid in predicting progression, identifying biomarkers, and supporting therapeutic development.

Dramatic transitions in cellular subtypes of hepatocytes characterized severe liver fibrosis, which involved a loss of zonation and an increase in the number of specific fibrosis-associated cell types. Further analysis revealed the transcription factors and gene regulatory networks underlying zonation-based hepatocytic identity and general hepatocyte heterogeneity and identified the transcriptional drivers of changes within hepatocyte zones and sub-types in MASH livers. High-fibrosis MASH hepatocytes displayed alterations in H3K27me3-associated repressive chromatin domains, including increased repression at lipid metabolism gene loci but reduced repression at epithelial remodeling and fibrosis-related gene loci. The localization of a specific subset of highly fibrotic hepatocytes directly at the sites of fibrosis illustrated the impact of fibrosis on transcriptional and epigenetic changes in hepatocytes. These hepatocytes directly interacted with hepatic stellate cells (associated with the development of MASH and fibrosis), with downstream signaling triggered from these interactions perhaps driving the transition to a fibrotic state.

The combination of liver cell type-specific gene regulatory and genetic association data finally revealed the mechanisms of individual MASLD-associated risk loci; this approach described the regulatory logic of risk variant activity in hepatocytes at a significant fraction of MASLD loci and causally related specific variants, cCREs, transcriptional regulators, and genes with disease development. Quantitative trait locus mapping and sequence-based models revealed the direction of effect of variants on hepatocyte regulatory activity, which may aid the development of strategies to protect hepatocytes during disease. Analysis of chromatin looping highlighted novel candidate genes in hepatocytes (including those distal to risk variants) and revealed novel targets for MASLD, which incorporated PPP1R3B Creasy et al.),CEBPA Yan et al.), and other genes such as KRT8/18XBP1

Conclusions: Paired-Tag and Development of a Multimodal Epigenetic Liver Disease Atlas

Overall, Paired-Tag technology and other related techniques enabled the authors of this study to create a multimodal epigenetic atlas of the distinct liver cell types, comprehensively annotating gene regulatory programs in these cell types and describing cellular heterogeneity. Furthermore, this approach offered deep insight into the drivers of MASLD progression, which may support the development of novel therapeutics.

Paired-Tag from Epigenome Technologies generates joint epigenetic and transcriptomic profiles at the single-cell resolution and detects histone modifications and RNA transcripts in individual nuclei with an efficiency comparable to single-nucleus RNA-seq/ChIP-seq assays. Furthermore, Epigenome Technologies offers a range of single-cell products and services tailored to meet the majority of research requirements. As such, applying Paired-Tag technology may enable giant leaps forward in understanding gene regulation and complement the findings of this exciting study.

For more on how Paired-Tag can support the development of a multimodal epigenetic atlas of diseased tissues that may aid the development of novel preventative or curative strategies, see medRxiv, May 2025.