Reply to correspondence on “Long-term gastrointestinal and hepatobiliary outcomes of COVID-19: A multinational population-based cohort study from South Korea, Japan, and the UK” Yang-Hyun Baek Clinical and Molecular Hepatology.2025; 31(1): e123. CrossRef
Correspondence to editorial on “Long-term gastrointestinal and hepatobiliary outcomes of COVID-19: a multinational population-based cohort study from South Korea, Japan, and the UK” Kwanjoo Lee, Jaeyu Park, Jinseok Lee, Hayeon Lee, Yeonjung Ha, Dong Keon Yon Clinical and Molecular Hepatology.2025; 31(1): e87. CrossRef
Background/Aims Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression.
Methods Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD.
Results After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort.
Conclusions We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.
Citations
Citations to this article as recorded by
Opportunities and challenges of artificial intelligence in hepatology Sarah M. G. Morel, Shuyang Wu, Timothy J. Kendall, Indra N. Guha, Jonathan A. Fallowfield npj Gut and Liver.2026;[Epub] CrossRef
The application of artificial intelligence in the intersection of metabolic dysfunction-associated steatotic liver disease and cardiovascular diseases Yu Kong, Hualei Chen, Yun Chen, Chengji Wang Frontiers in Immunology.2026;[Epub] CrossRef
Association between advanced fibrosis and epigenetic age acceleration among individuals with MASLD Haili Wang, Zhenqiu Liu, Hong Fan, Chengnan Guo, Xin Zhang, Yi Li, Suzhen Zhao, Luojia Dai, Ming Zhao, Tiejun Zhang Journal of Gastroenterology.2025; 60(3): 306. CrossRef
Correspondence to editorial on “DNA methylome analysis reveals epigenetic alteration of complement genes in advanced metabolic dysfunction-associated steatotic liver disease” Amal Magdy, Hee-Jin Kim, Won Kim, Mirang Kim Clinical and Molecular Hepatology.2025; 31(1): e70. CrossRef
PNPLA3 is one of the bridges between TM6SF2 E167K variant and MASLD: Correspondence to editorial on “TM6SF2 E167K variant decreases PNPLA3-mediated PUFA transfer to promote hepatic steatosis and injury in MASLD” Baokai Sun, Likun Zhuang Clinical and Molecular Hepatology.2025; 31(1): e67. CrossRef
Early portal hypertension in metabolic dysfunction-associated steatotic liver disease: a concise review Iván López-Méndez, Eva Juárez-Hernández, Juan Pablo Soriano-Márquez, Misael Uribe, Graciela Castro-Narro Expert Review of Gastroenterology & Hepatology.2025; 19(7): 755. CrossRef
A Perfect MASH Comparing Resmetirom and GLP-1 Agonists for Metabolic-Associated Steatohepatitis Joanne Lin, Victoria Green, Aalam Sohal, Marina Roytman Journal of Clinical Gastroenterology.2025; 59(10): 923. CrossRef
Developmental programming: Differing impact of prenatal testosterone and prenatal bisphenol-A -treatment on hepatic methylome in female sheep John Dou, Soundara Viveka Thangaraj, Yiran Zhou, Vasantha Padmanabhan, Kelly Bakulski Molecular and Cellular Endocrinology.2025; 609: 112655. CrossRef
The gene expression signature of metabolic dysfunction- associated steatotic liver disease from a multiomics perspective Carlos Jose Pirola, Silvia Sookoian Clinical and Molecular Hepatology.2024; 30(2): 174. CrossRef
Correspondence on Editorial regarding “Identification of signature gene set as highly accurate determination of MASLD progression” Sungju Jung, Sumin Yoon, Jong Hoon Park, Yeon-Su Lee, Kyung Hyun Yoo Clinical and Molecular Hepatology.2024; 30(2): 287. CrossRef
Correspondence to editorial on “Multiomics profiling of buffy coat and plasma unveils etiology-specific signatures in hepatocellular carcinoma” Su Bin Lim, Hyo Jung Cho Clinical and Molecular Hepatology.2024; 30(4): 1009. CrossRef
Chitinase 1: a novel therapeutic target in metabolic dysfunction-associated steatohepatitis Jung Hoon Cha, Na Ri Park, Sung Woo Cho, Heechul Nam, Hyun Yang, Eun Sun Jung, Jeong Won Jang, Jong Young Choi, Seung Kew Yoon, Pil Soo Sung, Si Hyun Bae Frontiers in Immunology.2024;[Epub] CrossRef
Metabolic dysfunction-associated steatotic liver disease: a key factor in hepatocellular carcinoma therapy response Camilo Julio Llamoza-Torres, María Fuentes-Pardo, Bruno Ramos-Molina Metabolism and Target Organ Damage.2024;[Epub] CrossRef
Biological and clinical role of TREM2 in liver diseases Ke Ma, Shouliang Guo, Jin Li, Tao Wei, Tingbo Liang Hepatology Communications.2024;[Epub] CrossRef
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