Transcriptomic profiling of hepatic tissues for drug metabolism genes in nonalcoholic fatty liver disease: A study of human and animals

Chen, Li; Chen, Lu; Li, Xu; Qi, Lin; Zhu, Yan; Zhang, Qianru; Tan, Daopeng; He, Yuqi; Yuhe, Wang

doi:10.3389/fendo.2022.1034494

Cited by 2 publications

(2 citation statements)

References 50 publications

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“…Nonetheless, previous studies have shown that the level of gene expression involved in drug metabolism changes in NAFLD patients, affecting pharmacokinetics. [66,67] Therefore, there is much potential for our future research on targeted drugs. To conclude, CD37 and CXCL9 could serve as diagnostic markers for NAFLD, this finding may further provide strong support for comprehensive research on precision therapy of NAFLD.…”

Section: Discussionmentioning

confidence: 99%

Diagnostic value of sphingolipid metabolism-related genes CD37 and CXCL9 in nonalcoholic fatty liver disease

Zhang,

Wang,

Jiang

2024

Medicine

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The development of nonalcoholic fatty liver disease (NAFLD) has been reported to be caused by sphingolipid family inducing insulin resistance, mitochondrial dysfunction, and inflammation, which can be regulated by multiple sphingolipid metabolic pathways. This study aimed to explore the molecular mechanism of crucial sphingolipid metabolism related genes (SMRGs) in NAFLD. Firstly, the datasets (GSE48452, GSE126848, and GSE63067) from the Gene Expression Omnibus database and sphingolipid metabolism genes (SMGs) from previous research were collected for this study. The differentially expressed genes (DEGs) between different NAFLD and controls were acquired through “limma,” and the SMRGs were authenticated via weighted gene co-expression network analysis (WGCNA). After overlapping the DEGs and SMRGs, the causality between the intersection genes (DE-SMRGs) and NAFLD was explored to sort out the candidate biomarkers by Mendelian randomization (MR) study. The receiver operating characteristic (ROC) curves of candidate biomarkers in GSE48452 and GSE126848 were yielded to determine the biomarkers, followed by the nomogram construction and enrichment analysis. Finally, the immune infiltration analysis, the prediction of transcription factors (TFs) and drugs targeting biomarkers were put into effect. A total of 23 DE-SMRGs were acquired based on the differential analysis and weighted gene co-expression network analysis (WGCNA), of which 3 DE-SMRGs (CD37, CXCL9 and IL7R) were picked out for follow-up analysis through univariate and multivariate MR analysis. The values of area under ROC curve of CD37 and CXCL9 were >0.7 in GSE48452 and GSE126848, thereby being regarded as biomarkers, which were mainly enriched in amino acid metabolism. With respect to the Spearman analysis between immune cells and biomarkers, CD37 and CXCL9 were significantly positively associated with M1 macrophages (P < .001), whose proportion was observably higher in NAFLD patients compared with controls. At last, TFs (ZNF460 and ZNF384) of CD37 and CXCL9 and a total of 79 chemical drugs targeting CD37 and CXCL9 were predicted. This study mined the pivotal SMRGs, CD37 and CXCL9, and systematically explored the mechanism of action of both biomarkers based on the public databases, which could tender a fresh reference for the clinical diagnosis and therapy of NAFLD.

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Section: Discussionmentioning

confidence: 99%

Diagnostic value of sphingolipid metabolism-related genes CD37 and CXCL9 in nonalcoholic fatty liver disease

Zhang,

Wang,

Jiang

2024

Medicine

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“…GSE89632 is a representative dataset for investigation of NAFLD and we used it to obtain the most relevant modular genes for NAFLD (23)(24)(25).First, WGCNA was used for the identification of the most relevant modular genes for NAFLD.b = 26 (scale-free R 2 = 0.85) was selected as the "soft" threshold based on the scale independence and average connectivity (Figure 2A). Then, different colors are chosen to represent 9 gene co-expression ).…”

Section: Key Module Genes In Nafld Samples Were Identified By Wgcnamentioning

confidence: 99%

Identification of biomarkers for the diagnosis of chronic kidney disease (CKD) with non-alcoholic fatty liver disease (NAFLD) by bioinformatics analysis and machine learning

Cao

Du²,

Jia³

et al. 2023

Front. Endocrinol.

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BackgroundChronic kidney disease (CKD) and non-alcoholic fatty liver disease (NAFLD) are closely related to immune and inflammatory pathways. This study aimed to explore the diagnostic markers for CKD patients with NAFLD.MethodsCKD and NAFLD microarray data sets were screened from the GEO database and analyzed the differentially expressed genes (DEGs) in GSE10495 of CKD date set. Weighted Gene Co-Expression Network Analysis (WGCNA) method was used to construct gene coexpression networks and identify functional modules of NAFLD in GSE89632 date set. Then obtaining NAFLD-related share genes by intersecting DEGs of CKD and modular genes of NAFLD. Then functional enrichment analysis of NAFLD-related share genes was performed. The NAFLD-related hub genes come from intersection of cytoscape software and machine learning. ROC curves were used to examine the diagnostic value of NAFLD related hub genes in the CKD data sets and GSE89632 date set of NAFLD. CIBERSORTx was also used to explore the immune landscape in GSE104954, and the correlation between immune infiltration and hub genes expression was investigated.ResultsA total of 45 NAFLD-related share genes were obtained, and 4 were NAFLD-related hub genes. Enrichment analysis showed that the NAFLD-related share genes were significantly enriched in immune-related pathways, programmed cell death, and inflammatory response. ROC curve confirmed 4 NAFLD-related hub genes in CKD training set GSE104954 and other validation sets. Then they were used as diagnostic markers for CKD. Interestingly, these 4 diagnostic markers of CKD also showed good diagnostic value in the NAFLD date set GSE89632, so these genes may be important targets of NAFLD in the development of CKD. The expression levels of the 4 diagnostic markers for CKD were significantly correlated with the infiltration of immune cells.Conclusion4 NAFLD-related genes (DUSP1, NR4A1, FOSB, ZFP36) were identified as diagnostic markers in CKD patients with NAFLD. Our study may provide diagnostic markers and therapeutic targets for CKD patients with NAFLD.

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Transcriptomic profiling of hepatic tissues for drug metabolism genes in nonalcoholic fatty liver disease: A study of human and animals

Cited by 2 publications

References 50 publications

Diagnostic value of sphingolipid metabolism-related genes CD37 and CXCL9 in nonalcoholic fatty liver disease

Diagnostic value of sphingolipid metabolism-related genes CD37 and CXCL9 in nonalcoholic fatty liver disease

Identification of biomarkers for the diagnosis of chronic kidney disease (CKD) with non-alcoholic fatty liver disease (NAFLD) by bioinformatics analysis and machine learning

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