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Identification of human long noncoding RNAs associated with nonalcoholic fatty liver disease and metabolic homeostasis.

ABSTRACT: A growing number of long noncoding RNAs (lncRNAs) have emerged as vital metabolic regulators. However, most human lncRNAs are nonconserved and highly tissue specific, vastly limiting our ability to identify human lncRNA metabolic regulators (hLMRs). In this study, we established a pipeline to identify putative hLMRs that are metabolically sensitive, disease relevant, and population applicable. We first progressively processed multilevel human transcriptome data to select liver lncRNAs that exhibit highly dynamic expression in the general population, show differential expression in a nonalcoholic fatty liver disease (NAFLD) population, and respond to dietary intervention in a small NAFLD cohort. We then experimentally demonstrated the responsiveness of selected hepatic lncRNAs to defined metabolic milieus in a liver-specific humanized mouse model. Furthermore, by extracting a concise list of protein-coding genes that are persistently correlated with lncRNAs in general and NAFLD populations, we predicted the specific function for each hLMR. Using gain- and loss-of-function approaches in humanized mice as well as ectopic expression in conventional mice, we validated the regulatory role of one nonconserved hLMR in cholesterol metabolism by coordinating with an RNA-binding protein, PTBP1, to modulate the transcription of cholesterol synthesis genes. Our work overcame the heterogeneity intrinsic to human data to enable the efficient identification and functional definition of disease-relevant human lncRNAs in metabolic homeostasis.

SUBMITTER: Ruan X

PROVIDER: S-EPMC7773374 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundNonalcoholic fatty liver disease (NAFLD) is the most common liver disease. Metabolism-related genes significantly influence the onset and progression of the disease. Hence, it is necessary to screen metabolism-related biomarkers for the diagnosis and treatment of NAFLD patients.MethodsGSE48452, GSE63067, and GSE89632 datasets including nonalcoholic steatohepatitis (NASH) and healthy controls (HC) analyzed in this study were retrieved from the Gene Expression Omnibus (GEO) database. First, differentially expressed genes (DEGs) between NASH and HC samples were obtained. Next, metabolism-related DEGs (MR-DEGs) were identified by overlapping DEGs and metabolism-related genes (MRG). Further, a protein-protein interaction (PPI) network was developed to show the interaction among MR-DEGs. Subsequently, the "Least absolute shrinkage and selection operator regression" and "Random Forest" algorithms were used to screen metabolism-related genes (MRGs) in patients with NAFLD. Next, immune cell infiltration and gene set enrichment analyses (GSEA) were performed on these metabolism-related genes. Finally, the expression of metabolism-related gene was determined at the transcription level.ResultsFirst, 129 DEGs related to NAFLD development were identified among patients with nonalcoholic steatohepatitis (NASH) and healthy control. Next, 18 MR-DEGs were identified using the Venn diagram. Subsequently, four genes, including AMDHD1, FMO1, LPL, and P4HA1, were identified using machine learning algorithms. Moreover, a regulatory network consisting of four genes, 25 microRNAs (miRNAs), and 41 transcription factors (TFs) was constructed. Finally, a significant increase in FMO1 and LPL expression levels and a decrease in AMDHD1 and P4HA1 expression levels were observed in patients in the NASH group compared to the HC group.ConclusionMetabolism-related genes associated with NAFLD were identified, containing AMDHD1, FMO1, LPL, and P4HA1, which provide insights into diagnosing and treating patients with NAFLD.

Project description:ObjectiveTo investigate the differential expression profile of lncRNAs in the nonalcoholic fatty liver disease (NAFLD) model induced by oleic acid (OA) and to further explore the role of LINC01260 (ENST00000255183) in NAFLD, providing theoretical support for the clinical value of lncRNAs in NAFLD.MethodsOA (50 μg/mL) was used to induce steatosis in normal human LO2 hepatocytes for 48 h and was verified by Oil red O staining. Differential expression profiles of lncRNAs were obtained by eukaryotic circular sequencing (RNA/lncRNA/circRNA-seq) techniques. A gain-of-function (GOF) strategy for LINC01260 was adopted, Oil red O staining and semiquantitative analysis were combined to explore whether the GOF of LINC01260 affects LO2 cell steatosis. CeRNA-based bioinformatics analysis of lncRNAs was performed, and the enriched mRNAs were further verified. RXRB siRNAs were applied and verify its role in LINC01260 regulated OA-induced hepatocytes steatosis.ResultsLipid droplets of different sizes were observed in the cells of the OA group. Absorbance in the OA group was significantly increased after isopropanol decolorization (P < 0.05). Compared with those in the control group, there were 648 lncRNAs with differential expression greater than 1 time in the OA group, of which 351 were upregulated and 297 were downregulated. Fluorescence quantitative PCR showed that the expression of LINC01260 in the OA group was downregulated by 0.35 ± 0.07-fold (P < 0.05). The formation of lipid droplets in LO2 cells of the LINC01260 GOF group decreased significantly (P < 0.05). CeRNA analysis indicated that the mRNA levels of RXRB, RNPEPL1, CD82, MADD and KLC2 were changed to different degrees. Overexpression of LINC01260 significantly induced RXRB transcription (P < 0.05) and translation, and RXRB silence attenuated the lipids decrease induced by LINC01260 overexpression.ConclusionThe OA-induced NAFLD cell model has a wide range of lncRNA differential expression profiles. LINC01260 participates in the regulation of the lipid droplet formation process of NAFLD, and its overexpression can significantly inhibit the steatosis process of LO2 cells. Mechanistically, LINC01260 may act as a ceRNA to regulate the expression of RXRB, thereby affecting the adipocytokine signaling pathway.

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Identification of human long noncoding RNAs associated with nonalcoholic fatty liver disease and metabolic homeostasis.

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