Evidence map›Paper›PMID 38380322›Full record

ArticleFrontiers in immunology2024

Comparison of the single-cell and single-nucleus hepatic myeloid landscape within decompensated cirrhosis patients.

Lukas Van Melkebeke, Jef Verbeek, Dora Bihary, Markus Boesch, Bram Boeckx, Rita Feio-Azevedo, Lena Smets, Marie Wallays, Eveline Claus, Lawrence Bonne and 5 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.8field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 2 institutions in 1 country.

Lukas Van MelkebekeLaboratory of Hepatology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium.
Jef VerbeekLaboratory of Hepatology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium.
Dora BiharyLaboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium.
Markus BoeschLaboratory of Hepatology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium.
Bram BoeckxLaboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium.
Rita Feio-AzevedoLaboratory of Hepatology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium.
Lena SmetsLaboratory of Hepatology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium.
Marie WallaysLaboratory of Hepatology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium.
Eveline ClausDepartment of Interventional Radiology, University Hospitals Leuven, Leuven, Belgium.
Lawrence BonneDepartment of Interventional Radiology, University Hospitals Leuven, Leuven, Belgium.
Geert MaleuxDepartment of Interventional Radiology, University Hospitals Leuven, Leuven, Belgium.
Olivier GovaereDepartment of Imaging and Pathology, Translational Cell and Tissue Research, KU Leuven and University Hospitals Leuven, Leuven, Belgium.
Hannelie KorfLaboratory of Hepatology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium.
Diether LambrechtsLaboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium.
Schalk van der MerweLaboratory of Hepatology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium.
KU Leuven · BEVIB-KU Leuven Center for Cancer Biology · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and aims: A complete understanding of disease pathophysiology in advanced liver disease is hampered by the challenges posed by clinical specimen collection. Notably, in these patients, a transjugular liver biopsy (TJB) is the only safe way to obtain liver tissue. However, it remains unclear whether successful sequencing of this extremely small and fragile tissue can be achieved for downstream characterization of the hepatic landscape. Methods: Here we leveraged in-house available single-cell RNA-sequencing (scRNA-seq) and single-nucleus (snRNA-seq) technologies and accompanying tissue processing protocols and performed an in-patient comparison on TJB's from decompensated cirrhosis patients (n = 3). Results: We confirmed a high concordance between nuclear and whole cell transcriptomes and captured 31,410 single nuclei and 6,152 single cells, respectively. The two platforms revealed similar diversity since all 8 major cell types could be identified, albeit with different cellular proportions thereof. Most importantly, hepatocytes were most abundant in snRNA-seq, while lymphocyte frequencies were elevated in scRNA-seq. We next focused our attention on hepatic myeloid cells due to their key role in injury and repair during chronic liver disease. Comparison of their transcriptional signatures indicated that these were largely overlapping between the two platforms. However, the scRNA-seq platform failed to recover sufficient Kupffer cell numbers, and other monocytes/macrophages featured elevated expression of stress-related parameters. Conclusion: Our results indicate that single-nucleus transcriptome sequencing provides an effective means to overcome complications associated with clinical specimen collection and could sufficiently profile all major hepatic cell types including all myeloid cell subsets.

Indexed as

Gene Expression ProfilingLiver DiseasesHigh-Throughput Nucleotide SequencingHumansLiver CirrhosisRNA, Small NuclearSequence Analysis, RNARNA, Small Nuclearcirrhosisdecompensatedsingle cell sequence (scRNA-seq)single nucleus RNA sequencingtransjugular biopsy

Identifiers

PMID38380322
PMCPMC10878168
OpenAlexW4391576890

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.