LUM is the hub gene of advanced fibrosis in nonalcoholic fatty liver disease patients

Integrative proteomics and metabolomics explore the effect and mechanism of Qiyin granules on improving nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) has emerged as a prominent global health concern, representing a substantial burden within the spectrum of chronic liver diseases. Despite its escalating prevalence, a definitive therapeutic strategy or efficacious pharmacological intervention for NAFLD has yet to receive official approval to date. While Fu Fang Qiyin granules have exhibited efficacy in addressing NAFLD, the intricacies of their underlying mechanism of action remain inadequately elucidated. In this study, we substantiated the ameliorative impact of Qiyin on highfat diet (HFD)induced NAFLD in rat models. The results of metabonomics showed that 108 potential biomarkers in serum and urine related to amino acid metabolism, energy metabolism, and pyrimidine metabolism, have returned to normal levels compared to the model group. Hepatic transcriptomics further indicated that Qiyin potentially confers protective effects against NAFLD by mediating liver inflammation and fibrosis through lumican (LUM) and decorin (DCN). In summation, our investigation provides compelling evidence affirming the therapeutic promise of Qiyin for NAFLD. It elucidates the underlying mechanistic pathways, furnishing a compelling rationale for its prospective clinical application.

Microarray-based Detection of Critical Overexpressed Genes in the Progression of Hepatic Fibrosis in Non-alcoholic Fatty Liver Disease: A Protein-protein Interaction Network Analysis

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is a prevalent cause of chronic liver disease and encompasses a broad spectrum of disorders, including simple steatosis, steatohepatitis, fibrosis, cirrhosis, and liver cancer. However, due to the global epidemic of NAFLD, where invasive liver biopsy is the gold standard for diagnosis, it is necessary to identify a more practical method for early NAFLD diagnosis with useful therapeutic targets; as such, molecular biomarkers could most readily serve these aims. To this end, we explored the hub genes and biological pathways in fibrosis progression in NAFLD patients.

METHODS

Raw data from microarray chips with GEO accession GSE49541 were downloaded from the Gene Expression Omnibus database, and the R package (Affy and Limma) was applied to investigate differentially expressed genes (DEGs) involved in the progress of low- (mild 0-1 fibrosis score) to high- (severe 3-4 fibrosis score) fibrosis stage NAFLD patients. Subsequently, significant DEGs with pathway enrichment were analyzed, including gene ontology (GO), KEGG and Wikipathway. In order to then explore critical genes, the protein-protein interaction network (PPI) was established and visualized using the STRING database, with further analysis undertaken using Cytoscape and Gephi software. Survival analysis was undertaken to determine the overall survival of the hub genes in the progression of NAFLD to hepatocellular carcinoma.

RESULTS

A total of 311 significant genes were identified, with an expression of 278 being upregulated and 33 downregulated in the high vs. low group. Gene functional enrichment analysis of these significant genes demonstrated major involvement in extracellular matrix (ECM)-receptor interaction, protein digestion and absorption, and the AGE-RAGE signaling pathway. The PPI network was constructed with 196 nodes and 572 edges with PPI enrichment using a p-value < 1.0 e-16. Based on this cut-off, we identified 12 genes with the highest score in four centralities: Degree, Betweenness, Closeness, and Eigenvector. Those twelve hub genes were CD34, THY1, CFTR, COL3A1, COL1A1, COL1A2, SPP1, THBS1, THBS2, LUM, VCAN, and VWF. Four of these hub genes, namely CD34, VWF, SPP1, and VCAN, showed significant association with the development of hepatocellular carcinoma.

CONCLUSION

This PPI network analysis of DEGs identified critical hub genes involved in the progression of fibrosis and the biological pathways through which they exert their effects in NAFLD patients. Those 12 genes offer an excellent opportunity for further focused research to determine potential targets for therapeutic applications.

Identification of key genes and functional enrichment analysis of liver fibrosis in nonalcoholic fatty liver disease through weighted gene co-expression network analysis

Nonalcoholic fatty liver disease (NAFLD) is a common type of chronic liver disease, with severity levels ranging from nonalcoholic fatty liver to nonalcoholic steatohepatitis (NASH). The extent of liver fibrosis indicates the severity of NASH and the risk of liver cancer. However, the mechanism underlying NASH development, which is important for early screening and intervention, remains unclear. Weighted gene co-expression network analysis (WGCNA) is a useful method for identifying hub genes and screening specific targets for diseases. In this study, we utilized an mRNA dataset of the liver tissues of patients with NASH and conducted WGCNA for various stages of liver fibrosis. Subsequently, we employed two additional mRNA datasets for validation purposes. Gene set enrichment analysis (GSEA) was conducted to analyze gene function enrichment. Through WGCNA and subsequent analyses, complemented by validation using two additional datasets, we identified five genes (BICC1, C7, EFEMP1, LUM, and STMN2) as hub genes. GSEA analysis indicated that gene sets associated with liver metabolism and cholesterol homeostasis were uniformly downregulated. BICC1, C7, EFEMP1, LUM, and STMN2 were identified as hub genes of NASH, and were all related to liver metabolism, NAFLD, NASH, and related diseases. These hub genes might serve as potential targets for the early screening and treatment of NASH.

Identification and Evaluation of Hub Long Noncoding RNAs and mRNAs in High Fat Diet Induced Liver Steatosis

Nonalcoholic fatty liver disease (NAFLD) is considered the most prevalent chronic liver disease, but the understanding of the mechanism of NAFLD is still limited. The aim of our study was to explore hub lncRNAs and mRNAs and pathological processes in high-fat diet (HFD)-induced and lycopene-intervened liver steatosis. We analyzed the gene profiles in the GSE146627 dataset from the Gene Expression Omnibus (GEO) database to identify differentially expressed lncRNAs and mRNAs, and we constructed coexpression networks based on weighted gene coexpression network analysis (WGCNA). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were utilized for functional enrichment analysis. We found that the turquoise, blue, brown, yellow, green, and black modules were significantly correlated with NAFLD. Functional enrichment analysis revealed that some hub lncRNAs (Smarca2, Tacc1, Flywch1, and Mef2c) might be involved in the regulation of the inflammatory and metabolic pathways (such as TNF signaling, metabolic, mTOR signaling, MAPK signaling, and p53 signaling pathways) in NAFLD. The establishment of an NAFLD mouse model confirmed that lycopene supply attenuated hepatic steatosis in HFD-induced NAFLD. Our analysis revealed that the inflammatory and metabolic pathways may be crucially involved in the pathogenesis of NAFLD, and hub lncRNAs provide novel biomarkers, therapeutic ideas, and targets for NAFLD. Moreover, lycopene has the potential to be a phytochemical for the prevention of HFD-induced liver steatosis.

Identification of biomarkers co-associated with M1 macrophages, ferroptosis and cuproptosis in alcoholic hepatitis by bioinformatics and experimental verification

Backgrounds

Alcoholic hepatitis (AH) is a major health problem worldwide. There is increasing evidence that immune cells, iron metabolism and copper metabolism play important roles in the development of AH. We aimed to explore biomarkers that are co-associated with M1 macrophages, ferroptosis and cuproptosis in AH patients.

Methods

GSE28619 and GSE103580 datasets were integrated, CIBERSORT algorithm was used to analyze the infiltration of 22 types of immune cells and GSVA algorithm was used to calculate ferroptosis and cuproptosis scores. Using the "WGCNA" R package, we established a gene co-expression network and analyzed the correlation between M1 macrophages, ferroptosis and cuproptosis scores and module characteristic genes. Subsequently, candidate genes were screened by WGCNA and differential expression gene analysis. The LASSO-SVM analysis was used to identify biomarkers co-associated with M1 macrophages, ferroptosis and cuproptosis. Finally, we validated these potential biomarkers using GEO datasets (GSE155907, GSE142530 and GSE97234) and a mouse model of AH.

Results

The infiltration level of M1 macrophages was significantly increased in AH patients. Ferroptosis and cuproptosis scores were also increased in AH patients. In addition, M1 macrophages, ferroptosis and cuproptosis were positively correlated with each other. Combining bioinformatics analysis with a mouse model of AH, we found that ALDOA, COL3A1, LUM, THBS2 and TIMP1 may be potential biomarkers co-associated with M1 macrophages, ferroptosis and cuproptosis in AH patients.

Conclusion

We identified 5 potential biomarkers that are promising new targets for the treatment and diagnosis of AH patients.

Whole-transcriptome sequencing revealed differentially expressed mRNAs and non-coding RNAs played crucial roles in NiONPs-induced liver fibrosis

Nickel oxide nanoparticles (NiONPs) induced liver fibrosis, while its mechanisms associated with transcriptome remained unclear. This study aimed to investigate the roles of differentially expressed (DE) messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs) in NiONPs-induced liver fibrosis, and further confirm whether JNK/c-Jun pathway enriched by the DE RNAs was involved in the regulation of the disease. A liver fibrosis rat model was established by intratracheal perfusion of NiONPs twice a week for 9 weeks. Whole-transcriptome sequencing was applied to obtain expression profiles of mRNAs, long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs) in the model rat and control liver tissues. Comparing the RNA expression profiles of the model and control liver tissues, we identified 324 DE mRNAs, 129 DE lncRNAs, 24 DE miRNAs and 33 DE circRNAs, and the potential interactions among them were revealed by constructing two co-expression networks, including lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA networks. Using RT-qPCR, we verified the sequencing results of some RNAs in the networks and obtained similar expression profiles, indicating our sequencing results were reliable and referable. Through Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, we predicted the biological functions and signaling pathways potentially related to NiONPs-induced liver fibrosis, such as "positive regulation of JNK cascade", "inflammatory response", "transcription factor binding", and MAPK, Wnt, PI3K-Akt signaling pathways. JNK/c-Jun pathway, a subclass of MAPK signal, was selected for further investigation because it was significantly enriched by fibrosis-related DE genes and activated in animal models. In vitro, we detected the cytotoxicity of NiONPs on LX-2 cells and treated the cells with 5 μg/ml NiONPs for 12 h. The results showed NiONPs induced the up-regulated protein expression of fibrotic factors collagen-1a1 (Col-1a1) and matrix metalloproteinas2 (MMP2) and JNK/c-Jun pathway activation. While these effects were reversed after JNK/c-Jun pathway was blocked by SP600125 (JNK pathway inhibitor), indicating the pathway was involved in NiONPs-induced excessive collagen formation. In conclusion, our results revealed the DE mRNAs and ncRNAs played crucial roles in NiONPs-induced liver fibrosis, and JNK/c-Jun pathway mediated the development of the disease.

Identification of key pathways and genes in the progression of silicosis based on WGCNA

Silicosis, induced by inhaling silica particles in workplaces, is one of the most common occupational diseases. The prognosis of silicosis and its consequent fibrosis is extremely poor due to limited treatment modalities and lack of understanding of the disease mechanisms. In this study, a Wistar rat model for silicosis fibrosis was established by intratracheal instillation of silica (0, 50, 100 and 200 mg/mL, 1 mL) with the evidence of Hematoxylin and Eosin (HE) and Masson staining and the expressions of inflammatory and fibrotic proteins of rats' lung tissues. RNA of lung tissues of rats exposed to 200 mg/mL silica particles and normal saline for 14 d and 28 d was extracted and sequenced to detect differentially expressed genes (DEGs) and to identify silicosis fibrosis-associated modules and hub genes by Weighted gene co-expression network analysis (WGCNA). Predictions of gene functions and signaling pathways were conducted using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. In this study, it has been demonstrated the promising role of the Hippo signaling pathway in silicosis fibrosis, which will be conducive to elucidating the specific mechanism of pulmonary fibrosis induced by silica and to determining molecular initiating event (MIE) and adverse outcome pathway (AOP) of silicosis fibrosis.

A New Murine Liver Fibrosis Model Induced by Polyhexamethylene Guanidine-Phosphate

Liver fibrosis is part of the wound healing process to help the liver recover from the injuries caused by various liver-damaging insults. However, liver fibrosis often progresses to life-threatening cirrhosis and hepatocellular carcinoma. To overcome the limitations of current in vivo liver fibrosis models for studying the pathophysiology of liver fibrosis and establishing effective treatment strategies, we developed a new mouse model of liver fibrosis using polyhexamethylene guanidine phosphate (PHMG-p), a humidifier sterilizer known to induce lung fibrosis in humans. Male C57/BL6 mice were intraperitoneally injected with PHMG-p (0.03% and 0.1%) twice a week for 5 weeks. Subsequently, liver tissues were examined histologically and RNA-sequencing was performed to evaluate the expression of key genes and pathways affected by PHMG-p. PHMG-p injection resulted in body weight loss of ~15% and worsening of physical condition. Necropsy revealed diffuse fibrotic lesions in the liver with no effect on the lungs. Histology, collagen staining, immunohistochemistry for smooth muscle actin and collagen, and polymerase chain reaction analysis of fibrotic genes revealed that PHMG-p induced liver fibrosis in the peri-central, peri-portal, and capsule regions. RNA-sequencing revealed that PHMG-p affected several pathways associated with human liver fibrosis, especially with upregulation of lumican and IRAK3, and downregulation of GSTp1 and GSTp2, which are closely involved in liver fibrosis pathogenesis. Collectively we demonstrated that the PHMG-p-induced liver fibrosis model can be employed to study human liver fibrosis.