Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Molecular Clustering of Metabolic Dysfunction-Associated Steatotic Liver Disease Based on Transcriptome Analysis

Full metadata record
DC Field Value Language
dc.contributor.authorRyu, Gina-
dc.contributor.authorYoon, Eileen Laurel-
dc.contributor.authorKim, Wankyu-
dc.contributor.authorJun, Dae Won-
dc.date.accessioned2025-03-12T00:30:14Z-
dc.date.available2025-03-12T00:30:14Z-
dc.date.issued2025-02-
dc.identifier.issn2075-4418-
dc.identifier.issn2075-4418-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/206748-
dc.description.abstractBackground: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a complex metabolic disorder with a diverse spectrum. This study aimed to classify patients with MASLD into molecular subtypes based on the underlying pathophysiology. Methods: We performed high-throughput RNA sequencing on 164 liver tissue samples from healthy controls and patients with MASLD. The clustering was based on individual genes or pathways that showed high variation across the samples. Second, the clustering was based on single-sample gene set enrichment analysis. Results: Optimal homogeneity was achieved by dividing the samples into four clusters (one healthy control and three MASLD clusters I-III) based on the top genes or pathways with differences across the samples. No significant differences were observed in waist circumference, blood pressure, glucose, alanine transaminase (ALT), or aspartate transferase (AST) levels between cluster I patients with MASLD and the healthy controls. Cluster I showed the clinical features of lean MASLD. Cluster III of MASLD demonstrated hypertension and a T2DM prevalence of 57.1% and 50.0%, respectively, with a significantly higher fibrosis burden (stage of fibrosis, liver stiffness, and FIB-4 value) than clusters I and II. Cluster III was associated with severe fibrosis and abnormal glucose homeostasis. In MASLD cluster I, the sphingolipid and GPCR pathways were upregulated, whereas the complement and phagocytosis pathways were downregulated. In MASLD cluster II, the cell cycle and NOTCH3 pathways increased, whereas the PI3K and insulin-related pathways decreased. In MASLD cluster III, increased activity occurred in the interleukin-2 and -4 and extracellular matrix pathways, coupled with decreased activity in the serotonin 2A and B pathways. Conclusions: MASLD can be divided into three distinct molecular phenotypes, wherein each is characterized by a specific molecular pathway.-
dc.format.extent14-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI AG-
dc.titleMolecular Clustering of Metabolic Dysfunction-Associated Steatotic Liver Disease Based on Transcriptome Analysis-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/diagnostics15030342-
dc.identifier.scopusid2-s2.0-85217541439-
dc.identifier.wosid001419499800001-
dc.identifier.bibliographicCitationDiagnostics, v.15, no.3, pp 1 - 14-
dc.citation.titleDiagnostics-
dc.citation.volume15-
dc.citation.number3-
dc.citation.startPage1-
dc.citation.endPage14-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaGeneral & Internal Medicine-
dc.relation.journalWebOfScienceCategoryMedicine, General & Internal-
dc.subject.keywordPlusadult-
dc.subject.keywordPlusalanine aminotransferase blood level-
dc.subject.keywordPlusArticle-
dc.subject.keywordPlusaspartate aminotransferase blood level-
dc.subject.keywordPlusblood pressure-
dc.subject.keywordPluscardiometabolic risk factor-
dc.subject.keywordPluscell cycle-
dc.subject.keywordPlusclinical feature-
dc.subject.keywordPlusclinical practice-
dc.subject.keywordPluscontrolled study-
dc.subject.keywordPlusdown regulation-
dc.subject.keywordPlusextracellular matrix-
dc.subject.keywordPlusgene set enrichment analysis-
dc.subject.keywordPlusglucose blood level-
dc.subject.keywordPlusglucose homeostasis-
dc.subject.keywordPlushigh throughput sequencing-
dc.subject.keywordPlushuman-
dc.subject.keywordPlushuman tissue-
dc.subject.keywordPlushypertension-
dc.subject.keywordPlusinsulin resistance-
dc.subject.keywordPlusliver biopsy-
dc.subject.keywordPlusliver fibrosis-
dc.subject.keywordPlusmetabolic fatty liver-
dc.subject.keywordPlusnon insulin dependent diabetes mellitus-
dc.subject.keywordPlusnon-negative matrix factorization-
dc.subject.keywordPluspathophysiology-
dc.subject.keywordPlusphenotype-
dc.subject.keywordPlusprospective study-
dc.subject.keywordPlusRNA sequencing-
dc.subject.keywordPlustranscriptomics-
dc.subject.keywordPlusupregulation-
dc.subject.keywordPluswaist circumference-
dc.subject.keywordAuthorMASLD-
dc.subject.keywordAuthorphenotype-
dc.subject.keywordAuthorcluster-
dc.subject.keywordAuthormolecular-
dc.identifier.urlhttps://www.mdpi.com/2075-4418/15/3/342-
Files in This Item
Go to Link
Appears in
Collections
서울 의과대학 > 서울 내과학교실 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Jun, Dae Won photo

Jun, Dae Won
서울 의과대학 (DEPARTMENT OF INTERNAL MEDICINE)
Read more

Altmetrics

Total Views & Downloads

BROWSE