Exploring the role of genetic variations in NAFLD: implications for disease pathogenesis and precision medicine approaches.

Non-alcoholic fatty liver disease (NAFLD) is one of the leading causes of chronic liver diseases, affecting more than one-quarter of people worldwide. Hepatic steatosis can progress to more severe forms of NAFLD, including NASH and cirrhosis. It also may develop secondary diseases such as diabetes and cardiovascular disease. Genetic and environmental factors regulate NAFLD incidence and progression, making it a complex disease. The contribution of various environmental risk factors, such as type 2 diabetes, obesity, hyperlipidemia, diet, and sedentary lifestyle, to the exacerbation of liver injury is highly understood. Nevertheless, the underlying mechanisms of genetic variations in the NAFLD occurrence or its deterioration still need to be clarified. Hence, understanding the genetic susceptibility to NAFLD is essential for controlling the course of the disease. The current review discusses genetics' role in the pathological pathways of NAFLD, including lipid and glucose metabolism, insulin resistance, cellular stresses, and immune responses. Additionally, it explains the role of the genetic components in the induction and progression of NAFLD in lean individuals. Finally, it highlights the utility of genetic knowledge in precision medicine for the early diagnosis and treatment of NAFLD patients.

Diagnostic potential and pathogenic performance of circulating miR-146b, miR-194, and miR-214 in liver fibrosis.

Liver fibrosis is the excessive accumulation of extracellular matrix proteins. Due to the lack of an accurate test for an early diagnosis of liver fibrosis and the invasiveness of the liver biopsy procedure, there is an urgent need for effective non-invasive biomarkers for screening the patients. we aimed to evaluate the diagnostic performance of circulating miRNAs (miR-146b, -194, -214) and their related mechanisms in the pathogenesis of liver fibrosis. The expression levels of miR-146b, -194, and -214 were quantified in whole blood samples from NAFLD patients using real-time PCR. The competing endogenous RNA (ceRNA) network was constructed and a gene set enrichment analysis (GSEA) was performed for HSC activation-related genes. Also, the transcription factor (TF)-miR co-regulatory network and the survival plot for three miRNAs and core genes were illustrated. The qPCR results showed that the relative expression of miR-146b and miR-214 significantly increased in NAFLD patients, while miR-194 showed significant down-regulation. The ceRNA network analysis implicated NEAT1 and XIST as sponge candidates for these miRNAs. The GSEA results identified 15 core genes involved in HSC activation, primarily enriched in NF-κB activation and autophagy pathways. STAT3, TCF3, RELA, and RUNX1 were considered potential transcription factors connected to miRNAs in the TF-miR network. Our study elucidated three candidate circulating miRNAs differentially expressed in NAFLD that could serve as a promising non-invasive diagnostic tool for early detection strategies. Also, NF-κB activation, autophagy, and negative regulation of the apoptotic process are the main potential underlying mechanisms regulated by these miRNAs in liver fibrosis pathogenesis.

Bioinformatics analysis reveals molecular connections between non-alcoholic fatty liver disease (NAFLD) and COVID-19.

The ongoing coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 has devastatingly impacted people's lives. Non-alcoholic fatty liver disease (NAFLD) is fatal comorbidity of COVID-19 seen with potential risk factors to develop severe symptoms. This research focuses on determining and elucidating the molecular factors and connections that might contribute to the severity of SARS-CoV-2 infection in NAFLD patients. Here, we comprehensively inspected the genes involved in NAFLD and SARS-CoV-2 entry factors (SCEFs) found by searching through the DisGeNet database and literature review, respectively. Further, we identified the SCEFs-related proteins through protein-protein interaction (PPI) network construction, MCODE, and Cytohubba. Next, the shared genes involved in NAFLD and SARS-CoV-2 entry, and hub gene were determined, followed by the GO and KEGG pathways analysis. X2K database was used to construct the upstream regulatory network of hub genes, as well as to identify the top ten candidates of transcription factors (TFs) and protein kinases (PKs). PPI analysis identified connections between 4 top SCEFs, including ACE, ADAM17, DPP4, and TMPRSS2 and NAFLD-related genes such as ACE, DPP4, IL-10, TNF, and AKT1. GO and KEGG analysis revealed the top ten biological processes and pathways, including cytokine-mediated signaling, PI3K-Akt, AMPK, and mTOR signaling pathways. The upstream regulatory network revealed that AKT1 and MAPK14 as important PKs and HIF1A and SP1 as important TFs associated with AKT1, IL-10, and TNF. The molecular connections identified between COVID-19 and NAFLD may shed light on discovering the causes of the severity of SARS-CoV-2 infected NAFLD patients.

Identification of potential key genes and miRNAs involved in Hepatoblastoma pathogenesis and prognosis.

Hepatoblastoma (HB) is one of the most common liver malignancies in children, while the molecular basis of the disease is largely unknown. Therefore, this study aims to explore the key genes and molecular mechanisms of the pathogenesis of HB using a bioinformatics approach. The gene expression dataset GSE131329 was used to find differentially expressed genes (DEGs). Functional and enrichment analyses of the DEGs were performed by the EnrichR. Then, the protein-protein interaction (PPI) network of the up-regulated genes was constructed and visualized using STRING database and Cytoscape software, respectively. MCODE was used to detect the significant modules of the PPI network, and cytoHubba was utilized to rank the important nodes (genes) of the PPI modules. Overall, six ranking methods were employed and the results were validated by the Oncopression database. Moreover, the upstream regulatory network and the miRNA-target interactions of the up-regulated DEGs were analyzed by the X2K web and the miRTarBase respectively. A total of 594 DEGs, including 221 up- and 373 down-regulated genes, were obtained, which were enriched in different cellular and metabolic processes, human diseases, and cancer. Furthermore, 15 hub genes were screened, out of which, 11 were validated. Top 10 transcription factors, kinases, and miRNAs were also determined. To the best of our knowledge, the association of RACGAP1, MKI67, FOXM1, SIN3A, miR-193b, and miR-760 with HB was reported for the first time. Our findings may be used to shed light on the underlying mechanisms of HB and provide new insights for better prognosis and therapeutic strategies.