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Record W4385454150 · doi:10.1101/2023.07.28.550550

Single-cell and spatial transcriptomics reveals the human liver immunological landscape and myeloid dysfunction in PSC

2023· preprint· en· W4385454150 on OpenAlexafffund
Tallulah Andrews, Diana Nakib, Cátia T. Perciani, Xue Zhong, Lewis Liu, Erin Winter, Damra Camat, Sai Chung, Justin Manuel, Shantel Mangroo, Bettina E. Hansen, Bal Arpinder, Cornelia Thoeni, Blayne A. Sayed, Jordan J. Feld, Adam J. Gehring, Aliya Gulamhusein, Gideon M. Hirschfield, Amanda Riciutto, Gary D. Bader, Ian D. McGilvray, Sonya A. MacParland

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsToronto Liver CentreHospital for Sick ChildrenUniversity of TorontoUniversity Health NetworkWestern University
FundersCanadian Institutes of Health ResearchUniversity Health Network FoundationUniversity of TorontoPublic Health AgencyChan Zuckerberg InitiativeNational Institutes of HealthPublic Health Agency of CanadaCanada First Research Excellence FundGovernment of OntarioPSC Partners Seeking a CureSilicon Valley Community Foundation
KeywordsHepatic stellate cellBiologyImmune systemPrimary sclerosing cholangitisPrimary biliary cirrhosisTranscriptomePopulationCholangiocyteFibrosisPathologyLiver diseaseImmunologyMedicineGene expressionDisease

Abstract

fetched live from OpenAlex

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. As such, we generated a comprehensive atlas of the PSC liver and a reference healthy liver dataset using multiple multi-omic modalities and functional validation. Methods In this work, we employed single-cell (12,000 cells), single-nuclei (23,000 nuclei), and spatial transcriptomics (1 sample by 10x Visium and 3 samples with multi-region profiling by Nanostring GeoMx DSP) to profile the cellular ecosystem in 5 patients with PSC. Transcriptomic profiles were compared to 100k single cell transcriptomes and spatial transcriptomics controls from 24 healthy neurologically deceased donor (NDD) livers. Flow cytometry and intracellular cytokine staining was performed to validate PSC-specific differences in immune phenotype and function. Results PSC explants with cirrhosis of the liver parenchyma and prominent periductal fibrosis were associated with a unique population of hepatocytes which transformed to a cholangiocyte-like phenotype. These hepatocytes were surrounded by diverse immune cell populations, including monocyte-like macrophages, liver-resident and circulating natural killer (NK) cells. Inflamed cholangiocytes, fibrosis-resident hepatic stellate cells, and endothelial cells released cytokines that recruited CD4+T-cells, dendritic cells, and neutrophils to the PSC liver. Tissue-resident macrophages, by contrast, were reduced in number and exhibited a dysfunctional inflammatory response to LPS and IFN-Ɣ stimulation. Conclusions We present the first 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. Lay Summary Primary sclerosing cholangitis (PSC) is a rare liver disease characterized by chronic inflammation and irreparable damage to the bile ducts. Due to a limited understanding of the underlying pathogenesis of disease, there remains a paucity of treatment options. As such, we sequenced healthy and diseased livers to compare the activity, interactions, and localization of immune and non-immune cells. This revealed that outside PSC scar regions, hepatocytes are transitioning to bile duct cells, whereas within the scars, there is an accumulation of immune cells. Of these cells, macrophages that typically contribute to tissue repair were enriched in immunoregulatory genes and were less responsive to stimulation. These cells are likely involved in maintaining hepatic inflammation and could be targeted in novel therapeutic development.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.222
Teacher spread0.194 · 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 designObservational
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".

Quick stats

Citations2
Published2023
Admission routes2
Has abstractyes

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