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Oh S, Baek YH, Jung S, Yoon S, Kang B, Han SH, Park G, Ko JY, Han SY, Jeong JS, Cho JH, Roh YH, Lee SW, Choi GB, Lee YS, Kim W, Seong RH, Park JH, Lee YS, Yoo KH. Identification of signature gene set as highly accurate determination of metabolic dysfunction-associated steatotic liver disease progression. Clin Mol Hepatol 2024; 30:247-262. [PMID: 38281815 PMCID: PMC11016492 DOI: 10.3350/cmh.2023.0449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 01/09/2024] [Accepted: 01/26/2024] [Indexed: 01/30/2024] Open
Abstract
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. CONCLUSION 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.
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Affiliation(s)
- Sumin Oh
- Laboratory of Biomedical Genomics, Department of Biological Sciences, Sookmyung Women’s University, Seoul, Korea
- Research Institute of Women’s Health, Sookmyung Women’s University, Seoul, Korea
| | - Yang-Hyun Baek
- Liver Center, Department of Internal Medicine, Dong-A University College of Medicine, Busan, Korea
| | - Sungju Jung
- Laboratory of Biomedical Genomics, Department of Biological Sciences, Sookmyung Women’s University, Seoul, Korea
| | - Sumin Yoon
- Laboratory of Biomedical Genomics, Department of Biological Sciences, Sookmyung Women’s University, Seoul, Korea
| | - Byeonggeun Kang
- Department of Biological Sciences and Institute of Molecular Biology and Genetics, Seoul National University, Seoul, Korea
- Bio-MAX Institute, Seoul National University, Seoul, Korea
| | - Su-hyang Han
- Laboratory of Biomedical Genomics, Department of Biological Sciences, Sookmyung Women’s University, Seoul, Korea
| | - Gaeul Park
- Division of Rare Cancer, Research Institute, National Cancer Center, Goyang, Korea
| | - Je Yeong Ko
- Department of Biological Sciences, Sookmyung Women’s University, Seoul, Korea
| | | | - Jin-Sook Jeong
- Department of Pathology, Dong-A University Medical Center, Busan, Korea
| | - Jin-Han Cho
- Department of Diagnostic Radiology, Dong-A University Medical Center, Busan, Korea
| | - Young-Hoon Roh
- Department of Surgery, Dong-A University Medical Center, Busan, Korea
| | - Sung-Wook Lee
- Liver Center, Department of Internal Medicine, Dong-A University Medical Center, Busan, Korea
| | - Gi-Bok Choi
- Department of Radiology, On Hospital, Busan, Korea
| | - Yong Sun Lee
- Division of Rare Cancer, Research Institute, National Cancer Center, Goyang, Korea
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea
| | - Won Kim
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul Metropolitan Government Boramae Medical Center, Seoul, Korea
| | - Rho Hyun Seong
- Department of Biological Sciences and Institute of Molecular Biology and Genetics, Seoul National University, Seoul, Korea
| | - Jong Hoon Park
- Department of Biological Sciences, Sookmyung Women’s University, Seoul, Korea
| | - Yeon-Su Lee
- Division of Rare Cancer, Research Institute, National Cancer Center, Goyang, Korea
| | - Kyung Hyun Yoo
- Laboratory of Biomedical Genomics, Department of Biological Sciences, Sookmyung Women’s University, Seoul, Korea
- Research Institute of Women’s Health, Sookmyung Women’s University, Seoul, Korea
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