Evidence map›Paper›PMID 41048656›Full record

ArticleLiver international communications2025

Cell-Type Deconvolution Reveals Dynamic Changes in MASLD.

Jeff J H Kim, Yang Dai

Abstract read
In one paragraph

Article in Liver international communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Jeff J H KimDepartment of Biomedical Engineering, University of Illinois Chicago, Chicago IL USA.
Yang DaiDepartment of Biomedical Engineering, University of Illinois Chicago, Chicago IL USA.

Funding

Synergistic effects of ECM and heterotypic crosstalk on cellular responses in non-alcoholic fatty liver diseaseR01DK115747 · NIDDK · UNIVERSITY OF ILLINOIS AT CHICAGO · PI Salman R Khetani, Gregory H Underhill · 2018 to 2026
$3.7M
NIDDK NIH HHS R01 DK115747
6 · The paper itself

Abstract

Background & Aims: Metabolic-associated steatotic liver disease (MASLD) is among the most prevalent liver disorders worldwide, with many patients progressing to metabolic-associated steatohepatitis (MASH) characterized by fibrosis and inflammation. The current lack of effective treatments for MASH highlights the urgent need to deepen our understanding of its underlying mechanisms. Examining cellular dynamics - specifically, changes in cell type proportions across disease stages - offers a promising avenue for gaining such insights. However, previous deconvolution analyses have been limited to a few cell types, and a comprehensive analysis encompassing diverse cell populations and their unique subtypes has yet to be conducted. Methods: In this study, we employed MuSiC deconvolution to analyze two bulk RNA sequencing datasets spanning the MASL to MASH spectrum across both fibrosis staging and Non-Alcoholic Fatty Liver Disease Activity Score (NAS) staging. Results: Our analysis reveals distinct proportional trends in 10 different cell types, including hepatocytes, cholangiocytes, two subpopulations of hepatic stellate cells, endothelial cells, and immune cells such as kupffer cells, TREM2+ macrophages, and plasma B cells. In addition to deconvolution analysis, we integrated cell type proportion data with transcriptomic profiles, significantly enhancing the performance of random forest models in classifying fibrosis stages compared to using transcriptomic data alone. Conclusions: The study's findings highlight critical cellular dynamic changes across MASLD progression, advancing our understanding of the disease mechanisms and potentially informing the development of more effective therapeutic strategies.

Indexed as

Cell-Type DeconvolutionDisease ProgressionFibrosis StagingMASHMASLD

Identifiers

PMID41048656
PMCPMC12490751

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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.