Single-cell, single-nucleus, and spatial transcriptomics characterization of the immunological landscape in the healthy and PSC human liver
Bibliographic record
Abstract
Background Primary sclerosing cholangitis (PSC) is an immune-mediated cholestatic liver disease characterized by bile retention, biliary tree destruction, and progressive fibrosis leading to end stage liver disease and transplantation. There is an unmet need to understand the cellular composition of the PSC liver and how it underlies disease pathogenesis. We generated a comprehensive atlas of the PSC liver in comparison to a primary biliary cholangitis (PBC) and reference healthy liver dataset using multiple multi-omic modalities and functional validation. Methods We employed single-cell (sc) RNA-seq (47,156 cells), single-nucleus (sn) RNA-seq (23,000 nuclei) and spatial transcriptomics (1 sample by 10x Visium and 5 samples with multi-region profiling by Nanostring GeoMx Digital Spatial Profiler) to profile the cellular ecosystem in 10 patients with PSC. Transcriptomic profiles were compared to 24 neurologically deceased donor livers (107,542 cells) and spatial transcriptomics controls, 18,240 cells and 20,202 nuclei from 3 patients with PBC, and publicly available scRNA-seq data from 5 uninjured, 2 NAFLD, 2 ALD, and 1 PBC liver samples. Flow cytometry and intracellular cytokine staining was performed to validate PSC-specific differences in immune cell phenotype and function. Results PSC explants with cirrhosis of the liver parenchyma and prominent periductal fibrosis contained a population of hepatocytes expressing a cholangiocyte-like phenotype. These hepatocytes were surrounded by diverse immune cell populations, including monocyte-like macrophages, liver-resident and circulating natural killer cells. PSC-associated cholangiocytes, hepatic stellate cells, and endothelial cells expressed chemokine and cytokine transcripts typically involved in immune cell recruitment. As well, expanded CD4 + T cells, dendritic cells and neutrophils in the PSC liver expressed the corresponding receptors to these chemokines and cytokines, suggesting potential recruitment. Tissue-resident macrophages, by contrast, were reduced in number and exhibited a dysfunctional and downregulated inflammatory response to LPS and IFN-Ɣ stimulation. Conclusions We present a comprehensive atlas of the PSC liver and demonstrate hyper-activation and exhaustion-like phenotypes of myeloid cells and markers of chronic cytokine expression in late-stage PSC lesions. This atlas has the potential to expand our understanding of the cellular complexity of PSC and to inform novel treatment development. Impact and Implications Primary sclerosing cholangitis (PSC) is a rare liver disease characterized by chronic inflammation and irreparable damage to the bile ducts resulting in liver failure. Due to a limited understanding of the underlying pathogenesis of disease, there remains a paucity of treatment options. We sequenced healthy and diseased livers to compare the activity, interactions, and localization of immune and non-immune cells. This revealed that hepatocytes lining PSC scar regions are transforming into cholangiocytes, whereas immune cells are accumulating within the scars. Of these cells, macrophages, which typically contribute to tissue repair, were enriched in immunoregulatory genes and demonstrated a lack of responsiveness to stimulation. These cells may be involved in maintaining hepatic inflammation and could be targeted in novel therapeutic drug development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".