Evidence map›Paper›PMID 40640848›Full record

ArticleJournal of translational medicine2025

Novel subtypes of metabolic associated steatotic liver disease linked to clinical outcomes: implications for precision medicine.

Chang Hong, Sheng-Xing Liang, Ze-Yang Li, Rui-Ning Li, Hong-Bo Zhu, Mingfei He, Hao Cui, Jing-Zhe He, Yan Li, Jia-Ren Wang and 5 more

Abstract read
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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.

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

15 authors.

Chang Hong *Department of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Sheng-Xing Liang *School of Public Health, Southern Medical University, Guangzhou, 510515, China.
Ze-Yang Li *Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Rui-Ning Li *Department of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Hong-Bo Zhu *Department of Oncology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
Mingfei HeDepartment of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Hao CuiDepartment of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Jing-Zhe HeDepartment of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Yan LiDepartment of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Jia-Ren WangDepartment of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Xue-Jing ZouDepartment of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Wen-Yuan LiSchool of Public Health, Southern Medical University, Guangzhou, 510515, China. liwy666@163.com.
Lin ZengDepartment of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China. lin_zeng1126@163.com.
Li LiuDepartment of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China. liuli@i.smu.edu.cn.ORCID 0000-0002-5265-4159
Lu-Shan XiaoDepartment of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China. 15622178423@163.com.

Funding

Guangdong Natural Science Foundation No.2022A1515110656Guangzhou Science and Technology Project No.202201011183National Key R&D Program of China No.2021YFF1201304National Key R&D Program of China No.2023YFC2308500the National Nature Science Foundation of China No.82172751the National Nature Science Foundation of China No.82373301the National Nature Science Foundation of China No.82400664the National Nature Science Foundation of China No.82404077the Postdoctoral Fellowship Program of CPSF No.GZC20240663
6 · The paper itself

Abstract

BACKGROUND &

aimsAlthough metabolic dysfunction-associated steatotic liver disease (MASLD) is associated with high multimorbidity and mortality, existing classification systems and risk prediction models largely ignore the heterogeneity of MASLD. Improved subtype definition could improve prediction of outcomes and inform new precision treatment strategies.

methodsWe analyzed individuals with MASLD from population-based electronic health record resource from UK Biobank (n = 125,197) and Health examinee dataset of Nanfang Hospital (n = 995). We identified subtypes with K-means clustering method. The Cox proportional hazard regression model analyzed the relationship between variables and MASLD-related complications.

resultsAfter identifying five clusters across seven clinical indicators which were age, body mass index, monocyte/lymphocyte ratio, aspartate aminotransferase, waist-hip ratio, low-density lipoprotein-cholesterol, and cholesterol, we labelled MASLD subtypes: (1) Metabolic-Dyslipidemia, (2) Younger, (3) Obesity, (4) Inflammatory, and (5) Hepatotoxic. Metabolic outcomes differed across these five subtypes. Hepatotoxic MASLD showed an increased risk of severe liver diseases compared to Metabolic-Dyslipidemia MASLD [HR = 13.9, 95% CI 10.7-18.1]. The extrahepatic complications were highest in Inflammatory MASLD. These two groups were defined as the high-risk group with higher health burden than other three groups, which classified as low-risk group. Differential single-nucleotide polymorphisms were concentrated on chromosomes 1 and 19 when comparing the high- and low-risk groups, and the annotated genes enrichment pathways were primarily related to lipid metabolism and transport.

conclusionsPatient subtypes derived by clinical indicators are a valuable addition to existing MASLD classification systems, which could provide a valuable tool to aid in selecting specific treatment approaches.

Indexed as

Fatty LiverMetabolic DiseasesPrecision MedicineAdultAge FactorsAspartate AminotransferasesBody Mass IndexChinaCholesterolCluster AnalysisDatasets as TopicFemaleGenome-Wide Association StudyHumansLymphocyte CountMaleAspartate AminotransferasesCholesterolClinical indicatorClusterComplicationsGenome-wide association study (GWAS)MASLD

Identifiers

PMID40640848
PMCPMC12247398

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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.