Identification of hub gene for the pathogenic mechanism and diagnosis of MASLD by enhanced bioinformatics analysis and machine learning

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a heterogeneous disease caused by multiple etiologies. It is characterized by excessive fat accumulation in the liver. Without intervention, MASLD can progress from steatosis to metabolic dysfunction-associated steatohepatitis (MASH...

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Vydané v:	PloS one Ročník 20; číslo 5; s. e0324972
Hlavní autori:	Lu, Hong, Mao, Ziyong, Zheng, Mengyao, Zhang, Min, Huang, Heqing, Chen, Yiling, Lv, Long, Chen, Zutao
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Public Library of Science 28.05.2025 Public Library of Science (PLoS)
Predmet:	Bioinformatics Biology and Life Sciences Biopsy Cirrhosis Computational biology Computational Biology - methods Diagnosis Fatty liver Fatty Liver - diagnosis Fatty Liver - genetics Fatty Liver - pathology Fibrosis Gene expression Gene Expression Profiling Genes Genetic aspects Hepatocellular carcinoma Humans Inflammation Lipid metabolism Lipid Metabolism - genetics Lipids Liver Liver Cirrhosis - diagnosis Liver Cirrhosis - genetics Liver diseases Machine Learning Medical genetics Medicine and Health Sciences Metabolism Pathogenesis Proteins Ribonucleic acid RNA Software Steatosis Variables China
ISSN:	1932-6203, 1932-6203
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Shrnutí:	Metabolic dysfunction-associated steatotic liver disease (MASLD) is a heterogeneous disease caused by multiple etiologies. It is characterized by excessive fat accumulation in the liver. Without intervention, MASLD can progress from steatosis to metabolic dysfunction-associated steatohepatitis (MASH), fibrosis and even to cirrhosis and hepatocellular carcinoma. However, the pathogenesis of MASH and the mechanism underlying the development of fibrosis remain poorly understood, posing challenges for accurate diagnosis of MASH and fibrosis. In this study, we analyzed tissue RNA-seq data and clinical information of healthy individuals and MASLD patients from multiple datasets, the key genes and pathways involved in the occurrence and progression of MASLD, MASH, and fibrosis were screened respectively. Our findings reveal that the development of MASLD, MASH and fibrosis is associated with lipid metabolism processes. Based on the RNA expression profiles of identified hub genes, we established three alternative diagnostic models for MASLD, MASH, and fibrosis. These models demonstrated excellent performance in the diagnosis of MASLD, MASH, and fibrosis, with AUC values exceeding 0.9, implicating its potential clinical values in disease diagnosis.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have declared that no competing interests exist. co-first authors.
ISSN:	1932-6203 1932-6203
DOI:	10.1371/journal.pone.0324972