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通过分子谱分析和致纤维增生性巨噬细胞的参与来识别 NAFLD 的独特纤维化亚群。

Identifying a distinct fibrosis subset of NAFLD via molecular profiling and the involvement of profibrotic macrophages.

机构信息

Department of Endocrinology and Diabetes, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xaimen, China.

Xiamen Diabetes Institute, The First Affiliated Hospital of Xiamen University, Xiamen, China.

出版信息

J Transl Med. 2023 Jul 6;21(1):448. doi: 10.1186/s12967-023-04300-6.

Abstract

BACKGROUND

There are emerging studies suggesting that non-alcoholic fatty liver disease (NAFLD) is a heterogeneous disease with multiple etiologies and molecular phenotypes. Fibrosis is the key process in NAFLD progression. In this study, we aimed to explore molecular phenotypes of NAFLD with a particular focus on the fibrosis phenotype and also aimed to explore the changes of macrophage subsets in the fibrosis subset of NAFLD.

METHODS

To assess the transcriptomic alterations of key factors in NAFLD and fibrosis progression, we included 14 different transcriptomic datasets of liver tissues. In addition, two single-cell RNA sequencing (scRNA-seq) datasets were included to construct transcriptomic signatures that could represent specific cells. To explore the molecular subsets of fibrosis in NAFLD based on the transcriptomic features, we used a high-quality RNA-sequencing (RNA-seq) dataset of liver tissues from patients with NAFLD. Non-negative matrix factorization (NMF) was used to analyze the molecular subsets of NAFLD based on the gene set variation analysis (GSVA) enrichment scores of key molecule features in liver tissues.

RESULTS

The key transcriptomic signatures on NAFLD including non-alcoholic steatohepatitis (NASH) signature, fibrosis signature, non-alcoholic fatty liver (NAFL) signature, liver aging signature and TGF-β signature were constructed by liver transcriptome datasets. We analyzed two liver scRNA-seq datasets and constructed cell type-specific transcriptomic signatures based on the genes that were highly expressed in each cell subset. We analyzed the molecular subsets of NAFLD by NMF and categorized four main subsets of NAFLD. Cluster 4 subset is mainly characterized by liver fibrosis. Patients with Cluster 4 subset have more advanced liver fibrosis than patients with other subsets, or may have a high risk of liver fibrosis progression. Furthermore, we identified two key monocyte-macrophage subsets which were both significantly correlated with the progression of liver fibrosis in NAFLD patients.

CONCLUSION

Our study revealed the molecular subtypes of NAFLD by integrating key information from transcriptomic expression profiling and liver microenvironment, and identified a novel and distinct fibrosis subset of NAFLD. The fibrosis subset is significantly correlated with the profibrotic macrophages and M2 macrophage subset. These two liver macrophage subsets may be important players in the progression of liver fibrosis of NAFLD patients.

摘要

背景

越来越多的研究表明,非酒精性脂肪性肝病(NAFLD)是一种具有多种病因和分子表型的异质性疾病。纤维化是 NAFLD 进展的关键过程。在本研究中,我们旨在探索 NAFLD 的分子表型,特别是纤维化表型,并探讨 NAFLD 纤维化亚组中巨噬细胞亚群的变化。

方法

为了评估 NAFLD 和纤维化进展中关键因素的转录组改变,我们纳入了 14 个不同的肝组织转录组数据集。此外,还纳入了两个单细胞 RNA 测序(scRNA-seq)数据集,以构建能够代表特定细胞的转录组特征。为了基于转录组特征探索 NAFLD 纤维化的分子亚群,我们使用了来自 NAFLD 患者的高质量肝组织 RNA-seq 数据集。非负矩阵分解(NMF)用于基于肝组织中关键分子特征的基因集变异分析(GSVA)富集分数分析 NAFLD 的分子亚群。

结果

通过肝转录组数据集构建了包括非酒精性脂肪性肝炎(NASH)特征、纤维化特征、非酒精性脂肪肝(NAFL)特征、肝老化特征和 TGF-β 特征在内的关键 NAFLD 转录组特征。我们分析了两个肝 scRNA-seq 数据集,并基于每个细胞亚群中高表达的基因构建了细胞类型特异性转录组特征。我们通过 NMF 分析了 NAFLD 的分子亚群,并将 NAFLD 分为四个主要亚群。第 4 亚群主要特征为肝纤维化。与其他亚群相比,第 4 亚群的患者肝纤维化更为严重,或者可能有较高的肝纤维化进展风险。此外,我们鉴定了两个关键的单核细胞-巨噬细胞亚群,这两个亚群在 NAFLD 患者的肝纤维化进展中均显著相关。

结论

我们通过整合转录组表达谱和肝微环境的关键信息,揭示了 NAFLD 的分子亚型,并确定了一种新的、独特的 NAFLD 纤维化亚群。纤维化亚群与促纤维化巨噬细胞和 M2 巨噬细胞亚群显著相关。这两个肝巨噬细胞亚群可能是 NAFLD 患者肝纤维化进展的重要参与者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73a2/10326954/b9d9b0a756ae/12967_2023_4300_Fig1_HTML.jpg

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