Transcriptional and Epigenetic Alterations in the Progression of Non-Alcoholic Fatty Liver Disease and Biomarkers Helping to Diagnose Non-Alcoholic Steatohepatitis
Non-alcoholic fatty liver disease (NAFLD) encompasses a broad spectrum of conditions from simple steatosis (non-alcoholic fatty liver (NAFL)) to non-alcoholic steatohepatitis (NASH), and its global prevalence continues to rise. NASH, the progressive form of NAFLD, has higher risks of liver and non-l...
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MDPI AG
2023-03-01
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author | Yalan Zhu He Zhang Pengjun Jiang Chengxia Xie Yao Luo Jie Chen |
author_facet | Yalan Zhu He Zhang Pengjun Jiang Chengxia Xie Yao Luo Jie Chen |
author_sort | Yalan Zhu |
collection | DOAJ |
description | Non-alcoholic fatty liver disease (NAFLD) encompasses a broad spectrum of conditions from simple steatosis (non-alcoholic fatty liver (NAFL)) to non-alcoholic steatohepatitis (NASH), and its global prevalence continues to rise. NASH, the progressive form of NAFLD, has higher risks of liver and non-liver related adverse outcomes compared with those patients with NAFL alone. Therefore, the present study aimed to explore the mechanisms in the progression of NAFLD and to develop a model to diagnose NASH based on the transcriptome and epigenome. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) among the three groups (normal, NAFL, and NASH) were identified, and the functional analysis revealed that the development of NAFLD was primarily related to the oxidoreductase-related activity, PPAR signaling pathway, tight junction, and pathogenic <i>Escherichia coli</i> infection. The logistic regression (LR) model, consisting of <i>ApoF</i>, <i>THOP1</i>, and <i>BICC1</i>, outperformed the other five models. With the highest AUC (0.8819, 95%CI: 0.8128–0.9511) and a sensitivity of 97.87%, as well as a specificity of 64.71%, the LR model was determined as the diagnostic model, which can differentiate NASH from NAFL. In conclusion, several potential mechanisms were screened out based on the transcriptome and epigenome, and a diagnostic model was built to help patient stratification for NAFLD populations. |
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spelling | doaj.art-5ccfd87b763b40ae912e2befcf7f116c2023-11-17T09:48:18ZengMDPI AGBiomedicines2227-90592023-03-0111397010.3390/biomedicines11030970Transcriptional and Epigenetic Alterations in the Progression of Non-Alcoholic Fatty Liver Disease and Biomarkers Helping to Diagnose Non-Alcoholic SteatohepatitisYalan Zhu0He Zhang1Pengjun Jiang2Chengxia Xie3Yao Luo4Jie Chen5Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, ChinaDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, ChinaDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, ChinaDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, ChinaDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, ChinaDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, ChinaNon-alcoholic fatty liver disease (NAFLD) encompasses a broad spectrum of conditions from simple steatosis (non-alcoholic fatty liver (NAFL)) to non-alcoholic steatohepatitis (NASH), and its global prevalence continues to rise. NASH, the progressive form of NAFLD, has higher risks of liver and non-liver related adverse outcomes compared with those patients with NAFL alone. Therefore, the present study aimed to explore the mechanisms in the progression of NAFLD and to develop a model to diagnose NASH based on the transcriptome and epigenome. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) among the three groups (normal, NAFL, and NASH) were identified, and the functional analysis revealed that the development of NAFLD was primarily related to the oxidoreductase-related activity, PPAR signaling pathway, tight junction, and pathogenic <i>Escherichia coli</i> infection. The logistic regression (LR) model, consisting of <i>ApoF</i>, <i>THOP1</i>, and <i>BICC1</i>, outperformed the other five models. With the highest AUC (0.8819, 95%CI: 0.8128–0.9511) and a sensitivity of 97.87%, as well as a specificity of 64.71%, the LR model was determined as the diagnostic model, which can differentiate NASH from NAFL. In conclusion, several potential mechanisms were screened out based on the transcriptome and epigenome, and a diagnostic model was built to help patient stratification for NAFLD populations.https://www.mdpi.com/2227-9059/11/3/970non-alcoholic fatty liver diseasenon-alcoholic steatohepatitisDNA methylationlogistic regressionmachine learning |
spellingShingle | Yalan Zhu He Zhang Pengjun Jiang Chengxia Xie Yao Luo Jie Chen Transcriptional and Epigenetic Alterations in the Progression of Non-Alcoholic Fatty Liver Disease and Biomarkers Helping to Diagnose Non-Alcoholic Steatohepatitis Biomedicines non-alcoholic fatty liver disease non-alcoholic steatohepatitis DNA methylation logistic regression machine learning |
title | Transcriptional and Epigenetic Alterations in the Progression of Non-Alcoholic Fatty Liver Disease and Biomarkers Helping to Diagnose Non-Alcoholic Steatohepatitis |
title_full | Transcriptional and Epigenetic Alterations in the Progression of Non-Alcoholic Fatty Liver Disease and Biomarkers Helping to Diagnose Non-Alcoholic Steatohepatitis |
title_fullStr | Transcriptional and Epigenetic Alterations in the Progression of Non-Alcoholic Fatty Liver Disease and Biomarkers Helping to Diagnose Non-Alcoholic Steatohepatitis |
title_full_unstemmed | Transcriptional and Epigenetic Alterations in the Progression of Non-Alcoholic Fatty Liver Disease and Biomarkers Helping to Diagnose Non-Alcoholic Steatohepatitis |
title_short | Transcriptional and Epigenetic Alterations in the Progression of Non-Alcoholic Fatty Liver Disease and Biomarkers Helping to Diagnose Non-Alcoholic Steatohepatitis |
title_sort | transcriptional and epigenetic alterations in the progression of non alcoholic fatty liver disease and biomarkers helping to diagnose non alcoholic steatohepatitis |
topic | non-alcoholic fatty liver disease non-alcoholic steatohepatitis DNA methylation logistic regression machine learning |
url | https://www.mdpi.com/2227-9059/11/3/970 |
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