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The Chromatin Accessibility Landscape of Nonalcoholic Fatty Liver Disease Progression
Byeonggeun Kang,강병희,노태영,Rho Hyun Seong,김원 한국분자세포생물학회 2022 Molecules and cells Vol.45 No.5
The advent of the assay for transposase-accessible chromatin using sequencing (ATAC-seq) has shown great potential as a leading method for analyzing the genome-wide profiling of chromatin accessibility. A comprehensive reference to the ATAC-seq dataset for disease progression is important for understanding the regulatory specificity caused by genetic or epigenetic changes. In this study, we present a genome-wide chromatin accessibility profile of 44 liver samples spanning the full histological spectrum of nonalcoholic fatty liver disease (NAFLD). We analyzed the ATAC-seq signal enrichment, fragment size distribution, and correlation coefficients according to the histological severity of NAFLD (healthy control vs steatosis vs fibrotic nonalcoholic steatohepatitis), demonstrating the high quality of the dataset. Consequently, 112,303 merged regions (genomic regions containing one or multiple overlapping peak regions) were identified. Additionally, we found differentially accessible regions (DARs) and performed transcription factor binding motif enrichment analysis and de novo motif analysis to determine new biomarker candidates. These data revealed the generegulatory interactions and noncoding factors that can affect NAFLD progression. In summary, our study provides a valuable resource for the human epigenome by applying an advanced approach to facilitate diagnosis and treatment by understanding the non-coding genome of NAFLD.
Sumin Oh,Yang-Hyun Baek,Sungju Jung,Sumin Yoon,Byeonggeun Kang,Su-hyang Han,Gaeul Park,Je Yeong Ko,Sang-Young Han,Jin-Sook Jeong,Jin-Han Cho,Young-Hoon Roh,Sung-Wook Lee,Gi-Bok Choi,Yong Sun Lee,Won K 대한간학회 2024 Clinical and Molecular Hepatology(대한간학회지) Vol.30 No.2
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.