Coffee Restores Expression of lncRNAs Involved in Steatosis and Fibrosis in a Mouse Model of NAFLD

Long non-coding RNAs as modulators and therapeutic targets in non-alcoholic fatty liver disease (NAFLD)

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease in the world, with epidemiological studies indicating a 25% prevalence. NAFLD is considered to be a progressive disease that progresses from simple hepatic steatosis to non-alcoholic steatohepatitis (NASH), then to liver fibrosis, and finally to cirrhosis or hepatocellular carcinoma (HCC). Existing research has mostly elucidated the etiology of NAFLD, yet its particular molecular processes remain uncertain. Long non-coding RNAs (LncRNAs) have been linked in a wide range of biological processes in recent years, with the introduction of microarray and high-throughput sequencing technologies, and previous studies have established their tight relationship with several stages of NAFLD development. Existing studies have shown that lncRNAs can regulate the signaling pathways related to hepatic lipid metabolism, NASH, NASH-related fibrosis and HCC. This review aims to provide a basic overview of NAFLD and lncRNAs, summarize and describe the mechanisms of lncRNAs action involved in the development of NAFLD, and provide an outlook on the future of lncRNAs-based therapy for NAFLD.

A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection

Single-cell RNA sequencing (scRNA-seq) technology is famous for providing a microscopic view to help capture cellular heterogeneity. This characteristic has advanced the field of genomics by enabling the delicate differentiation of cell types. However, the properties of single-cell datasets, such as high dropout events, noise, and high dimensionality, are still a research challenge in the single-cell field. To utilize single-cell data more efficiently and to better explore the heterogeneity among cells, a new graph autoencoder (GAE)-based consensus-guided model (scGAC) is proposed in this article. The data are preprocessed into multiple top-level feature datasets. Then, feature learning is performed by using GAEs to generate new feature matrices, followed by similarity learning based on distance fusion methods. The learned similarity matrices are fed back to the GAEs to guide their feature learning process. Finally, the abovementioned steps are iterated continuously to integrate the final consistent similarity matrix and perform other related downstream analyses. The scGAC model can accurately identify critical features and effectively preserve the internal structure of the data. This can further improve the accuracy of cell type identification.

Different Associations of Coffee Consumption with the Risk of Incident Metabolic Dysfunction-Associated Steatotic Liver Disease and Advanced Liver Fibrosis

Although coffee has a potential hepatoprotective effect, evidence of the relationship between coffee consumption and metabolic dysfunction-associated steatotic liver disease (MASLD) remains conflicting. There is limited evidence regarding the most appropriate coffee intake to prevent advanced liver fibrosis (ALF) in patients with MASLD. We investigated the effect of coffee consumption on MASLD and ALF among 5266 participants without MASLD and 1326 with MASLD but without ALF. Participants were grouped by coffee intake: non-consumers, >0 and <1 cups/day, ≥1 and <2 cups/day, and ≥2 cups/day. Over a median follow-up of 11.6 years for MASLD and 15.7 years for ALF, coffee consumption did not significantly affect the incidence of MASLD, with 2298 new cases observed. However, a notable inverse association was found with ALF risk in patients with MASLD among those consuming coffee ≥2 cups/day (adjusted HR 0.57, 95% CI: 0.37-0.90, p = 0.014), especially among those consuming coffee ≥2 and <3 cups/day (adjusted HR 0.51, 95% CI: 0.30-0.89, p = 0.018). This suggests a potential hepatoprotective effect of coffee, especially in preventing the progression of liver fibrosis in patients with MASLD. These findings propose that coffee consumption could be a simple and effective approach to mitigate the risk of ALF in individuals with MASLD.

An Uncharacterised lncRNA Coded by the ASAP1 Locus Is Downregulated in Serum of Type 2 Diabetes Mellitus Patients

Diabetes mellitus (DM) is a complex and multifactorial disease characterised by high blood glucose. Type 2 Diabetes (T2D), the most frequent clinical condition accounting for about 90% of all DM cases worldwide, is a chronic disease with slow development usually affecting middle-aged or elderly individuals. T2D represents a significant problem of public health today because its incidence is constantly growing among both children and adults. It is also estimated that underdiagnosis prevalence would strongly further increase the real incidence of the disease, with about half of T2D patients being undiagnosed. Therefore, it is important to increase diagnosis accuracy. The current interest in RNA molecules (both protein- and non-protein-coding) as potential biomarkers for diagnosis, prognosis, and treatment lies in the ease and low cost of isolation and quantification with basic molecular biology techniques. In the present study, we analysed the transcriptome in serum samples collected from T2D patients and unaffected individuals to identify potential RNA-based biomarkers. Microarray-based profiling and subsequent validation using Real-Time PCR identified an uncharacterised long non-coding RNA (lncRNA) transcribed from the ASAP1 locus as a potential diagnostic biomarker. ROC curve analysis showed that a molecular signature including the lncRNA and the clinicopathological parameters of T2D patients as well as unaffected individuals showed a better diagnostic performance compared with the glycated haemoglobin test (HbA1c). This result suggests that the application of this biomarker in clinical practice would help to improve the diagnosis, and therefore the clinical management, of T2D patients. The proposed biomarker would be useful in the context of predictive, preventive, and personalised medicine (3PM/PPPM).

The impact and role of identified long noncoding RNAs in nonalcoholic fatty liver disease: A narrative review

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease worldwide, but its mechanism and pathophysiology remain unclear. Long noncoding RNAs (lncRNAs) may exert a vital influence on regulating various biological functions in NAFLD.

METHODS

The databases such as Google Scholar, PubMed, and Medline were searched using the following keywords: nonalcoholic fatty liver disease, nonalcoholic fatty liver disease, NAFLD, nonalcoholic steatohepatitis, nonalcoholic steatohepatitis, NASH, long noncoding RNAs, and lncRNAs. Considering the titles and abstracts, unrelated studies were excluded. The authors evaluated the full texts of the remaining studies.

RESULTS

We summarized the current knowledge of lncRNAs and the main signaling pathways of lncRNAs involved in NAFLD explored in recent years. As a heterogeneous group of noncoding RNAs (ncRNAs), lncRNAs play crucial roles in biological processes underlying the pathophysiology of NAFLD. The mechanisms, particularly those associated with the regulation of the expression and activities of lncRNAs, play important roles in NAFLD.

CONCLUSION

A better comprehension of the mechanism controlled by lncRNAs in NAFLD is necessary for the identification of novel therapeutic targets for drug development and improved, noninvasive methods for diagnosis.

Identification of a New RNA and Protein Integrated Biomarker Panel Associated with Kidney Function Impairment in DKD: Translational Implications

Diabetic kidney disease (DKD) is a complication that strongly increases the risk of end-stage kidney disease and cardiovascular events. The identification of novel, highly sensitive, and specific early biomarkers to identify DKD patients and predict kidney function decline is a pivotal aim of translational medicine. In a previous study, after a high-throughput approach, we identified in 69 diabetic patients 5 serum mitochondrial RNAs (MT-ATP6, MT-ATP8, MT-COX3, MT-ND1, and MT-RNR1) progressively downregulated with increasing eGFR stages. Here, we analyzed the protein serum concentrations of three well-validated biomarkers: TNFRI, TNFRII, and KIM-1. The protein biomarkers were gradually upregulated from G1 to G2 and G3 patients. All protein biomarkers correlated with creatinine, eGFR, and BUN. Performing multilogistic analyses, we found that, with respect to single protein biomarkers, the combination between (I) TNFRI or KIM-1 with each RNA transcript and (II) TNFRII with MT-ATP8, MT-ATP6, MT-COX-3, and MT-ND1 determined an outstanding improvement of the diagnostic performance of G3 versus G2 patient identification, reaching values in most cases above 0.9 or even equal to 1. The improvement of AUC values was also evaluated in normoalbuminuric or microalbuminuric patients considered separately. This study proposes a novel, promising multikind marker panel associated with kidney impairment in DKD.

Identification of ribosomal protein family as immune-cell-related biomarkers of NAFLD by bioinformatics and experimental analyses

Background

Immune cells play an integral role in the development and progression of non-alcoholic fatty liver disease (NAFLD). This study was to identify immune-cell-related biomarkers for the diagnosis and treatment of NAFLD.

Methods and findings

First, we introduced human liver transcriptome data from the GEO database (GSE48452 and GSE126848) and performed a weighted gene co-expression network analysis (WGCNA) to screen out the modules related to immune cell infiltration and to identify immune-cell-related differentially expressed genes (ICR-DEGs) associated with NAFLD progression. Further, the protein-protein interaction (PPI) network of ICR-DEGs was established to obtain hub genes and subsequently, the expression trend analysis was conducted to identify immune-cell-related biomarkers of NAFLD. Finally, the mRNA expression of biomarkers was validated in a NAFLD mouse model induced by high-fat diet (HFD) feeding. In total, we identified 66 ICR-DEGs and 13 hub genes associated with NAFLD. Among them, 9 hub genes (CD247, CD74, FCGR2B, IL2RB, INPP5D, MRPL16, RPL35, RPS3A, RPS8) were correlated with the infiltrating immune cells by the Pearson correlation analysis. Subsequently, 4 immune-cell-related biomarkers (RPL35, RPS3A, RPS8, and MRPL16) with the same expression trends in GSE48452 and GSE126848 datasets were identified. These biomarkers were enriched in immune-related pathways and had a good ability to distinguish between NASH and healthy samples. Moreover, we constructed a competing endogenous RNA (ceRNA) network of biomarkers and predicted twenty potential therapeutic drugs targeting RPS3A such as taxifolin and sitagliptin. Finally, experimental validation indicated that the hepatic mRNA expression of Rpl35, Rps3A, and Rps8 was significantly decreased in NAFLD mice.

Conclusions

This study identified four ribosomal protein genes (RPL35, RPS3A, RPS8, and MRPL16) as immune-cell-related biomarkers of NAFLD, which may actively participate in the immune processes during NAFLD progression and could serve as potential targets for the diagnosis and treatment of NAFLD.

The function of long non-coding RNA in non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease is a disease that is currently prevalent in the world, increasingly becoming the mainstay of liver diseases. And its prevalence is rapidly increasing, but its pathogenesis is not entirely understood. Long non-coding RNAs have increasingly gained attention as science has progressed in recent years. Studies have shown that long non-coding RNAs are involved in a variety of biological processes in vivo, such as proliferation, differentiation, and apoptosis, and can affect disease by regulating gene expression. This review explores the biological processes involving long non-coding RNAs, including lipid metabolism, glucose metabolism, liver fibrosis, and apoptosis. In addition, we summarize how the different long non-coding RNAs involved in each process function. Finally, the shortcomings of long non-coding RNAs as potential therapeutic targets are briefly described. In conclusion, this article provides a clear visualization of the link that exists between long non-coding RNAs and non-alcoholic fatty liver disease.

The Effects of Nutrition on Chronic Conditions

The effects of nutrition on chronic conditions, such as diabetes, obesity, heart disease, and stroke, continue to generate interest among researchers [...].

Molecular hallmarks of long non-coding RNAs in aging and its significant effect on aging-associated diseases

Aging is linked to the deterioration of many physical and cognitive abilities and is the leading risk factor for Alzheimer's disease. The growing aging population is a significant healthcare problem globally that researchers must investigate to better understand the underlying aging processes. Advances in microarrays and sequencing techniques have resulted in deeper analyses of diverse essential genomes (e.g., mouse, human, and rat) and their corresponding cell types, their organ-specific transcriptomes, and the tissue involved in aging. Traditional gene controllers such as DNA- and RNA-binding proteins significantly influence such programs, causing the need to sort out long non-coding RNAs, a new class of powerful gene regulatory elements. However, their functional significance in the aging process and senescence has yet to be investigated and identified. Several recent researchers have associated the initiation and development of senescence and aging in mammals with several well-reported and novel long non-coding RNAs. In this review article, we identified and analyzed the evolving functions of long non-coding RNAs in cellular processes, including cellular senescence, aging, and age-related pathogenesis, which are the major hallmarks of long non-coding RNAs in aging.

Mitochondrial RNAs as Potential Biomarkers of Functional Impairment in Diabetic Kidney Disease

Type 2 diabetes and renal damage are strictly linked. The progressive increase in T2D incidence has stimulated the interest in novel biomarkers to improve the diagnostic performance of the commonly utilized markers such as albuminuria and eGFR. Through microarray method, we analyzed the entire transcriptome expressed in 12 serum samples of diabetic patients, six without DKD and six with DKD; the downregulation of the most dysregulated transcripts was validated in a wider cohort of 69 patients by qPCRs. We identified a total of 33 downregulated transcripts. The downregulation of four mitochondrial messenger RNAs (MT-ATP6, MT-ATP8, MT-COX3, MT-ND1) and other two transcripts (seysnoy, skerdo) was validated in patients with eGFR stage G3 versus G2 and G1. The four messenger RNAs correlated with creatinine and eGFR stages, while seysnoy and skerdo were associated with white blood cell values. All transcripts correlated also with Blood Urea Nitrogen. The four mitochondrial messenger RNAs had a high diagnostic performance in G3 versus G2 discrimination, with AUC values above 0.8. The most performant transcript was MT-ATP6, with an AUC of 0.846; sensitivity = 90%, specificity = 76%, p-value = 7.8 × 10⁻⁵. This study led to the identification of a specific molecular signature of DKD, proposing the dosage of RNAs, especially mitochondrial RNAs, as noninvasive biomarkers of diabetes complication.

Molecular Effects of Chronic Exposure to Palmitate in Intestinal Organoids: A New Model to Study Obesity and Diabetes

Intestinal cell dysfunctions involved in obesity and associated diabetes could be correlated with impaired intestinal cell development. To date, the molecular mechanisms underlying these dysfunctions have been poorly investigated because of the lack of a good model for studying obesity. The main aim of this study was to investigate the effects of lipotoxicity on intestinal cell differentiation in small intestinal organoid platforms, which are used to analyze the regulation of cell differentiation. Mouse intestinal organoids were grown in the presence/absence of high palmitate concentrations (0.5 mM) for 48 h to simulate lipotoxicity. Palmitate treatment altered the expression of markers involved in the differentiation of enterocytes and goblet cells in the early (Hes1) and late (Muc2) phases of their development, respectively, and it modified enterocytes and goblet cell numbers. Furthermore, the expression of enteroendocrine cell progenitors (Ngn3) and I cells (CCK) markers was also impaired, as well as CCK-positive cell numbers and CCK secretion. Our data indicate, for the first time, that lipotoxicity simultaneously influences the differentiation of specific intestinal cell types in the gut: enterocytes, goblet cells and CCK cells. Through this study, we identified novel targets associated with molecular mechanisms affected by lipotoxicity that could be important for obesity and diabetes therapy.

Identifying Autophagy-Related lncRNAs and Potential ceRNA Networks in NAFLD

Nonalcoholic fatty liver disease (NAFLD) is a common chronic disease with complex pathogenesis, which brings economic burden to the society, and there is still no effective therapy. Impaired autophagy has been implicated in the development of NAFLD. Long noncoding RNAs (lncRNAs) are also reported to play a role in the pathogenesis of NAFLD. However, the role of autophagy-related lncRNAs in NAFLD disease has not been elucidated. Here, we mined GSE135251, GSE160016, GSE130970 and GSE185062 datasets from the Gene Expression Omnibus database (GEO) and obtained the human autophagy-related gene list from the Human Autophagy Database (HADb) for in-depth bioinformatic analysis. Following differential expression analysis and intersection of the datasets, Pearson correlation analysis was performed on DElncRNAs and autophagy-related DEmRNAs to obtain autophagy-related lncRNAs, and then Starbase3.0 and TargetScan7.2 were used to construct competing endogenous RNAs (ceRNA) regulatory networks. We constructed four lncRNA-dominated ceRNA regulatory networks (PSMG3-AS1, MIRLET7BHG, RP11-136K7.2, LINC00925), and visualized with Cytoscape. Then we performed co-expression analysis of the ceRNA networks and autophagy-related genes, and functionally annotated them with Metascape. Finally, we performed receiver operating characteristic curve (ROC) analysis on lncRNAs and mRNAs within the ceRNA networks. Conclusively, our project is the first to study autophagy-related lncRNAs in NAFLD and finally mined four autophagy-related lncRNAs (PSMG3-AS1, MIRLET7BHG, RP11-136K7.2, LINC00925). We suggested that the four autophagy-related lncRNAs may be closely associated with the occurrence and development of NAFLD through the corresponding ceRNA regulatory networks. This research brings new horizons to the study of NAFLD.

LncNONMMUG027912 alleviates lipid accumulation through AMPKα/mTOR/SREBP1C axis in nonalcoholic fatty liver

Various metabolic diseases are closely related to lipid metabolism disorders, but the regulatory effect of long noncoding RNAs (lncRNAs) on the function of lipids has been poorly elucidated. Previous our work has found that lncNONMMUG027912 (abbreviated as lnc027912) involved in cholesterol metabolism. Here, we further explored the novel function of lipid metabolism-associated lnc027912. We found that upregulated lnc027912 in AML12 cells treated with oleic acid (OA) and palmitic acid (PA) showed a significant decrease in lipid accumulation, triglyceride (TG) levels, and lipid biosynthesis genes. In terms of regulatory mechanisms, lnc027912 increased the expression of p-AMPKα, inhibited p-mTOR levels, decreased the expression of SREBP1C in nuclei, decreased the promoter activity of SREBP1C, and inhibited the expression of lipid synthesis genes. Most importantly, lnc027912 could reduce lipid accumulation and liver inflammation through AMPKα/mTOR signal axis in nonalcoholic fatty liver disease (NAFLD) mice model. Altogether, our study revealed a novel molecular mechanism of lnc027912 in lipid metabolism through the AMPKα/mTOR/SREBP1C signaling axis and highlights the potential of lnc027912 as a new treatment target for lipid disorder diseases (such as NAFLD).

Clinical and Molecular Biomarkers for Diagnosis and Staging of NAFLD

Non-alcoholic fatty liver disease (NAFLD) is the most common hepatic pathology in industrialized countries, affecting about 25% of the general population. NAFLD is a benign condition, however, it could evolve toward more serious diseases, including non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis, and finally, hepatocellular carcinoma (HCC). Liver biopsy is still the gold standard for NAFLD diagnosis. Due to the risks associated with liver biopsy and the impossibility to apply it on a large scale, it is now necessary to identify non-invasive biomarkers, which may reliably identify patients at higher risk of progression. Therefore, several lines of research have tried to address this issue by identifying novel biomarkers using omics approaches, including lipidomics, metabolomics and RNA molecules' profiling. Thus, in this review, we firstly report the conventional biomarkers used in clinical practice for NAFL and NASH diagnosis as well as fibrosis staging, and secondly, we pay attention to novel biomarkers discovered through omics approaches with a particular focus on RNA biomarkers (microRNAs, long-noncoding RNAs), showing promising diagnostic performance for NAFL/NASH diagnosis and fibrosis staging.

Transcriptomic Analysis Reveals the Protective Effects of Empagliflozin on Lipid Metabolism in Nonalcoholic Fatty Liver Disease

Empagliflozin is a novel type of sodium-glucose cotransporter two inhibitor with diverse beneficial effects in the treatment of nonalcoholic fatty liver disease (NAFLD). Although empagliflozin impacts NAFLD by regulating lipid metabolism, the underlying mechanism has not been fully elucidated. In this study, we investigated transcriptional regulation pathways affected by empagliflozin in a mouse model of NAFLD. In this study, NAFLD was established in male C57BL/6J mice by administration of a high-fat diet; it was then treated with empagliflozin and whole transcriptome analysis was conducted. Gene expression levels detected by transcriptome analysis were then verified by quantitative real-time polymerase chain reaction, protein levels detected by Western Blot. Differential expression genes screened from RNA-Seq data were enriched in lipid metabolism and synthesis. The Gene Set Enrichment Analysis (GSEA) results showed decreased lipid synthesis and improved lipid metabolism. Empagliflozin improved NAFLD through enhanced triglyceride transfer, triglyceride lipolysis and microsomal mitochondrial β-oxidation. This study provides new insights concerning the mechanisms by which sodium-glucose cotransporter two inhibitors impact NAFLD, particularly in terms of liver lipid metabolism. The lipid metabolism-related genes identified in this experiment provide robust evidence for further analyses of the mechanism by which empagliflozin impacts NAFLD.