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Record W4414276383 · doi:10.1097/hep.0000000000001478

Decoding the PSC fibrotic niche: Hepatocyte stress and metallothioneins

2025· article· en· W4414276383 on OpenAlexaff
Diana Nakib, Sonya A. MacParland

Bibliographic record

VenueHepatology · 2025
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsPrimary sclerosing cholangitisPrimary biliary cirrhosisCirrhosisLiver diseaseAlcoholic liver diseaseFibrosisHepatocytePathologicalDisease

Abstract

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Recent advances in multi-omic technologies, such as single-cell and spatial transcriptomics, proteomics, and epigenomics, have critically advanced our understanding of the human liver in both health and disease. In pathologically “patchy” and heterogeneous diseases such as primary sclerosing cholangitis (PSC), a rare progressive cholestatic liver disease with no approved medical therapies other than liver transplantation, the ability to link pathological features to cellular signatures provides an opportunity for informing specific targets of disease pathways. Leveraging these approaches to investigate the hepatic and biliary niches of PSC has revealed immune-rich fibrotic lesions lined with transitioning hepatocytes,1 the biliary enrichment of a recruited neutrophil–T cell axis,2 and the hepatic presence of naive-like CD4+ T cells.3 However, due to the rarity of PSC, the difficulty accessing fresh patient tissues, and the numerous challenges associated with omics technologies, comprehensive and statistically powered multi-omic investigations of the PSC liver remain challenging. To examine hepatocyte cellular signatures that are associated with PSC-associated fibrosis at the time of explant, Chung et al4 performed a multi-omic examination, including spatial transcriptomics (ST) (Visium with 55 µm spots) (n=23) and single-nucleus RNA sequencing (snRNA-seq) (n=16), of explanted PSC liver tissue, using snRNA-seq data to deconvolve spatial signatures as previously employed by this team to investigate the immune landscape of human liver fibrosis5 (Figure 1). This newly generated dataset separately interrogates central venous and periportal regions of explanted PSC liver samples from patients with a range of transplant indications, including recurrent cholangitis (termed non-cirrhotic) and cirrhosis (termed cirrhotic), in addition to disease controls, such as alcoholic liver disease (ALD) and metabolic dysfunction–associated steatohepatitis (MASH).FIGURE 1: Multi-omic investigation of explanted PSC liver tissue reveals metallothionein–high hepatocytes at the parenchyma–fibrosis interface. Abbreviations: DDC, 3,5-diethoxycarbonyl-1,4-dihydrocollidine; PSC, primary sclerosing cholangitis.Using Visium ST to investigate peribiliary and central venous regions of the PSC liver, Chung and colleagues build on previous efforts to understand the pathological niche at the parenchyma–fibrosis interface and uncover the presence of hepatocytes enriched in metallothionein-encoding genes (MT1G, MT1H) in this niche. Previous work has demonstrated hepatic and plasma enrichment of metallothioneins, a class of proteins that bind metals to protect against oxidative stress and metal toxicity, in cholestatic and autoimmune liver disease,6 including PSC and primary biliary cholangitis (PBC),7 as well as in the context of inflammatory bowel disease (IBD).8,9 However, the microanatomical assessment of the PSC liver by Chung et al revealed specific metallothionein pathway enrichment in hepatocytes lining the edge of fibrotic lesions, which also express genes relating to acute phase inflammation (SAA1, SAA2, and SAA4) and drug detoxification (CYP2A6, CYP2C8, and CYP3A5). This pathological region residing at the perimeter of fibrotic lesions has previously been described in the PSC liver, as well as in chronic liver disease,1,10 wherein transdifferentiating cholangiocyte-like hepatocytes were identified at the periphery of peribiliary fibrotic lesions.1 With snRNA-seq, the authors show 2-fold greater proportions of mononuclear phagocytes (MPs) in the PSC liver compared with disease controls, as well as their enriched colocalization with metallothionein–high fibrotic regions at the parenchyma–fibrosis interface. The expression of acute phase proteins by injured cholangiocytes has previously been described to directly reprogram macrophages to a pathogenic phenotype involved in cholangiocyte and mesenchymal activation.11 Myeloid cells, both liver-resident Kupffer cells and recruited monocytes, are suggested to play a central role in PSC pathogenesis due to fibrosis-stage–associated hepatic recruitment of macrophages,12 evidence of hepatic myeloid dysfunction in response to stimulation, and distinct lesional recruitment of monocytic myeloid cells with maintained exclusion of Kupffer cells.1 Furthermore, while recruited macrophages have been implicated in PSC lesion progression through their localization and association with progressive fibrosis, their precise functional contributions to inflammation, cholangiocyte activation, and tissue remodeling remain to be fully elucidated. In addition, upon comparing cirrhotic and non-cirrhotic PSC liver samples by ST and snRNA-seq, the authors show that cirrhotic PSC livers and disease controls retain enriched expression of cholangiocyte-associated genes and solute transport pathways throughout the parenchyma and fibrotic regions, while the non-cirrhotic PSC liver is marked by a loss of cholangiocyte-associated gene signatures, as well as increased activation of pathways associated with hepatocyte stress, inflammation, and metallothioneins. These results highlight metallothionein expression and mononuclear phagocyte accumulation in the context of progressive ductopenia, which may define a distinct, non-fibrotic pathogenic trajectory in PSC that precedes or occurs independently of advanced cirrhosis. Together, this work suggests a scenario in which hepatocytes at the parenchyma–fibrosis interface are not only responding to local injury and inflammatory cues but may actively participate in promoting fibrogenesis through sustained acute phase response activation, stress signaling, and cross-talk with stromal and immune cells, including myeloid reprogramming. However, the mechanism of action and the underlying drivers of this persistent and multifocal hepatocyte activation remain unclear, although potential initiating and driving mechanisms for future investigations could include bile acid accumulation, microbial translocation, and viral infection. These findings raise important questions about the divergent trajectories of PSC progression, particularly the relationship between recurrent cholangitis and cirrhotic disease development. To fully delineate distinct hepatic signatures of non-fibrotic PSC, it will be essential to study liver tissue from patients at earlier, pre-transplant time points. Longitudinal and early-stage sampling could clarify the molecular underpinnings of PSC pathogenesis and identify potential biomarkers predictive of disease progression. To explore the clinical relevance of enriched hepatic metallothionein expression in PSC, Chung and colleagues investigated the relationship between hepatic MT1G expression and key serological markers in PSC patients. This revealed a significant correlation between MT1G+ spots in Visium spatial transcriptomics data of the PSC liver and key serum liver biochemistry markers, such as AST, ALP, ALT, and bilirubin. The authors further demonstrate the relationship between metallothionein expression and PSC pathogenesis by employing the 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) mouse model for biliary inflammation, which demonstrated a significant enrichment of hepatic Mt1 counts, as measured by bulk RNA-sequencing. Future work will need to validate the nature of the relationship between metallothionein expression and biliary inflammation in PSC, determining whether this expression is protective or pathogenic. This further underscores the need for disease models that are specifically tailored to PSC to accurately capture these dynamics. In addition, the authors define distinct immune-fibrotic periportal niches, fibro1 and fibro2, that share fibroblast (IGFBP, LUM, and MYL9) and endothelial cell (MGP and CCL21) markers but differ due to the high immunoglobulin gene enrichment of fibro2. The preferential localization of B cells and plasma cells to the regions of liver fibrosis suggests antigen-mediated activation of the adaptive immune response, as well as progressive development of tertiary lymphoid structures, as described in the PBC liver.13 Despite the lack of distinct diagnostic circulating autoantibodies for PSC, recent work has increasingly suggested a key role for plasma B cells in the pathogenesis of PSC, given their localization and enrichment in PSC fibrotic lesions,1 the presence of EBV-specific B cells in the PSC liver,14 and cholangiocyte-binding antibodies,15 as well as shared BCR clonotypes across the liver and gut of PSC patients.16 However, it remains unclear whether plasma B cells actively contribute to PSC progression or represent a secondary response to sustained chronic cholestatic injury. Where does this study bring us? This study takes on the challenge of identifying disease-promoting cellular pathways in liver diseases that exhibit heterogeneous pathology. The identification of hepatocyte stress responses, metallothionein expression, and plasma cell-rich fibrotic zones offers new avenues for biomarker development and therapeutic targeting. This work reinforces the importance of translational clinical and basic science teams that focus on obtaining and characterizing human tissues in an open-science, accessible, and patient-partnered manner in an effort to fully describe this rare disease, in which fresh samples are infrequent, necessitating data sharing across institutes for robust results. This work further emphasizes the need for pathologically-informed sampling of diseased regions and suggests that future approaches that simultaneously capture pathological features and cell-level transcriptional and protein expression will allow for more precise identification of new therapeutic targets for PSC. In the future, combining the data obtained through these high-resolution approaches, across multiple platforms and institutes, with sampling and profiling of the PSC liver at earlier pre-transplantation time points, will further differentiate targetable PSC-specific pathways from those of end-stage cholestatic disease. These targets will require validation both in human-derived 3D liver models (organ-on-a-chip, precision cut liver slices, and patient-derived organoids) and appropriate animal models. Looking ahead, defining the temporal dynamics of immune infiltration, the role of extrahepatic biliary compartments, and the nature and contribution of lesion-associated immune cells to parenchymal cell activation will be key to understanding PSC progression, clarifying the link between PSC and IBD, and guiding future intervention strategies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.315
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2025
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