Evidence mapPaperPMID 42522643Full record

ArticleLiver international : official journal of the International Association for the Study of the Liver2026

Gene-Based Clustering Identifies QSOX1 and IL1RAP as Biomarkers of Metabolic Dysfunction-Associated Steatotic Liver Disease.

Wenfeng Ma, Jinrong Huang, Benqiang Cai, Mumin Shao, Xuewen Yu, Mikkel Breinholt Kjær, Minling Lv, Xin Zhong, Shaomin Xu, Bolin Zhan and 8 more

Abstract read
In one paragraph

Article in Liver international : official journal of the International Association for the Study of the Liver, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
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

1 citing paper in PubMed.

  1. Gene-Based Clustering Identifies QSOX1 and IL1RAP as Biomarkers of Metabolic Dysfunction-Associated Steatotic Liver Disease.Liver international : official journal of the International Association for the Study of the Liver · 2026
    Article
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

18 authors.

Wenfeng MaDepartment of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0003-1185-1065
Jinrong HuangDepartment of Biomedicine, Aarhus University, Aarhus, Denmark.ORCID https://orcid.org/0000-0001-8085-9939
Benqiang CaiDepartment of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China.
Mumin ShaoDepartment of Pathology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0001-9327-1261
Xuewen YuDepartment of Pathology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China.
Mikkel Breinholt KjærDepartment of Clinical Medicine, Aarhus University, Aarhus, Denmark.ORCID https://orcid.org/0000-0002-6385-5108
Minling LvDepartment of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China.
Xin ZhongDepartment of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China.
Shaomin XuDepartment of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China.
Bolin ZhanDepartment of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China.
Qun LiDepartment of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China.
Qi HuangDepartment of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China.
Mengqing MaDepartment of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China.
Lei ChengDepartment of Biomedicine, Aarhus University, Aarhus, Denmark.ORCID https://orcid.org/0000-0003-1122-2648
Yonglun LuoDepartment of Biomedicine, Aarhus University, Aarhus, Denmark.ORCID https://orcid.org/0000-0002-0007-7759
Henning GrønbækDepartment of Hepatology and Gastroenterology, Aarhus University Hospital, Aarhus, Denmark.ORCID https://orcid.org/0000-0001-8998-7910
Xiaozhou ZhouDepartment of Liver Disease, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, Guangdong, China.ORCID https://orcid.org/0000-0002-4758-0060
Lin LinDepartment of Biomedicine, Aarhus University, Aarhus, Denmark.ORCID https://orcid.org/0000-0002-7546-4948

Funding

Sanming Project of Medicine in Shenzen Municipality JCYJ20210324120405015Shenzhen Science and Technology Project SZSM201612074
6 · The paper itself

Abstract

BACKGROUND AND

aimsMetabolic dysfunction-associated steatotic liver disease (MASLD) is a progressive liver disease that ranges from simple steatosis to inflammation, fibrosis and cirrhosis. To address the unmet need for new MASLD biomarkers, we aimed to identify candidate biomarkers using publicly available RNA sequencing (RNA-seq) and proteomics data.

methodsAn approach involving unsupervised gene clustering was performed using homogeneously processed and integrated RNA-seq data of 625 liver specimens to screen for MASLD biomarkers, in combination with public proteomics data from healthy controls and MASLD patients. Additionally, we validated the results in the MASLD and healthy cohorts using enzyme-linked immunosorbent assay (ELISA) of plasma and immunohistochemical staining (IHC) of liver samples.

resultsWe generated a database (https://dreamapp.biomed.au.dk/NAFLD/) for exploring gene expression changes along MASLD progression to facilitate the identification of genes and pathways involved in the disease's progression. Through cross-analysis of the gene and protein clusters, we identified 38 genes as potential biomarkers for MASLD severity. Up-regulation of Quiescin sulfhydryl oxidase 1 (QSOX1) and down-regulation of Interleukin-1 receptor accessory protein (IL1RAP) were associated with increasing MASLD severity in RNA-seq and proteomics data. Particularly, the QSOX1/IL1RAP ratio in plasma demonstrated effectiveness in diagnosing MASLD, with an area under the receiver operating characteristic (AUROC) of up to 0.95 as quantified by proteomics profiling and an AUROC of 0.82 with ELISA.

conclusionsWe discovered a significant association between the levels of QSOX1 and IL1RAP and MASLD severity. Furthermore, the QSOX1/IL1RAP ratio shows promise as a non-invasive biomarker for diagnosing MASLD and assessing its severity.

Indexed as

Interleukin-1 Receptor Accessory ProteinNon-alcoholic Fatty Liver DiseaseOxidoreductases Acting on Sulfur Group DonorsBiomarkersCluster AnalysisDisease ProgressionHumansLiverProteomicsBiomarkersIL1RAP protein, humanInterleukin-1 Receptor Accessory ProteinOxidoreductases Acting on Sulfur Group Donorsinterleukin‐1 receptor accessory proteinmetabolic dysfunction‐associated steatotic liver diseasenon‐invasive biomarkerquiescin sulfhydryl oxidase 1RNA sequencing data integration

Identifiers

PMID42522643
PMCPMC13417051

What Socratic holds

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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 Socratic graph.