Upregulated lncRNA HCG18 in Patients with Non-Alcoholic Fatty Liver Disease and Its Regulatory Effect on Insulin Resistance

Xia, Yu; Zhang, Yanxia; Wang, Huiyun

doi:10.2147/dmso.s333431

Cited by 17 publications

(7 citation statements)

References 45 publications

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“…Zhang et al reported that increased serum PVT1 has good predictive value for distinguishing NAFLD patients from healthy individuals, with an AUC of 0.895, a sensitivity of 84.0%, and a specificity of 84.6% [ 25 ]. Another lncRNA, HCG18, was identified as a promising candidate biomarker in differentiating NAFLD patients from healthy individuals (AUC = 0.934, sensitivity: 82.8%, and specificity: 89.1%) [ 35 ]. Furthermore, three other studies collectively focused on lncRNA MEG3 expression in NAFLD.…”

Section: Resultsmentioning

confidence: 99%

LncRNA and circRNA in Patients with Non-Alcoholic Fatty Liver Disease: A Systematic Review

Zeng

Liu

et al. 2023

Biomolecules

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Non-alcoholic fatty liver disease (NAFLD) is currently the most common cause of chronic liver disease worldwide. Early identification and prompt treatment are critical to optimize patient management and improve long-term prognosis. Long non-coding RNA (lncRNA) and circular RNA (circRNA) are recently emerging non-coding RNAs, and are highly stable and easily detected in the circulation, representing a promising non-invasive approach for predicting NAFLD. A literature search of the Pubmed, Embase, Web of Science, and Cochrane Library databases was performed and 36 eligible studies were retrieved, including 18 on NAFLD, 13 on nonalcoholic steatohepatitis (NASH), and 11 on fibrosis and/or cirrhosis. Dynamic changes in lncRNA expression were associated with the occurrence and progression of NAFLD, among which lncRNA NEAT1, MEG3, and MALAT1 exhibited great potential as biomarkers for NAFLD. Moreover, mitochondria-located circRNA SCAR can drive metaflammation and its inhibition might be a promising therapeutic target for NASH. In this systematic review, we highlight the great potential of lncRNA/circRNA for early diagnosis and progression assessment of NAFLD. To further verify their clinical value, large-cohort studies incorporating lncRNA and circRNA expression both in liver tissue and blood should be conducted. Additionally, detailed studies on the functional mechanisms of NEAT1, MEG3, and MALAT1 will be essential for elucidating their roles in diagnosing and treating NAFLD, NASH, and fibrosis.

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Section: Resultsmentioning

confidence: 99%

LncRNA and circRNA in Patients with Non-Alcoholic Fatty Liver Disease: A Systematic Review

Zeng

Liu

et al. 2023

Biomolecules

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“…Abdulle et al also demonstrated the significance of MALAT1 as a target in diabetic-related diseases 40 . Additionally, HCG18 and BPLN3P are upregulated, which increases the risk of insulin resistance and type 1 diabetes, respectively 41 , 42 . The remaining obtained lncRNAs are novel in this cross-talk which are proposed in this study for future experimental analysis.…”

Section: Resultsmentioning

confidence: 99%

Identification of repurposed drugs targeting significant long non-coding RNAs in the cross-talk between diabetes mellitus and Alzheimer’s disease

Ghiam

Eslahchi

Shahpasand

et al. 2022

Sci Rep

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The relationship between diabetes mellitus (DM) and Alzheimer’s disease (AD) is so strong that scientists called it “brain diabetes”. According to several studies, the critical factor in this relationship is brain insulin resistance. Due to the rapid global spread of both diseases, overcoming this cross-talk has a significant impact on societies. Long non-coding RNAs (lncRNAs), on the other hand, have a substantial impact on complex diseases due to their ability to influence gene expression via a variety of mechanisms. Consequently, the regulation of lncRNA expression in chronic diseases permits the development of innovative therapeutic techniques. However, developing a new drug requires considerable time and money. Recently repurposing existing drugs has gained popularity due to the use of low-risk compounds, which may result in cost and time savings. in this study, we identified drug repurposing candidates capable of controlling the expression of common lncRNAs in the cross-talk between DM and AD. We also utilized drugs that interfered with this cross-talk. To do this, high degree common lncRNAs were extracted from microRNA-lncRNA bipartite network. The drugs that interact with the specified lncRNAs were then collected from multiple data sources. These drugs, referred to as set D, were classified in to positive (D+) and negative (D−) groups based on their effects on the expression of the interacting lncRNAs. A feature selection algorithm was used to select six important features for D. Using a random forest classifier, these features were capable of classifying D+ and D− with an accuracy of 82.5%. Finally, the same six features were extracted for the most recently Food and Drug Administration (FDA) approved drugs in order to identify those with the highest likelihood of belonging to D+ or D−. The most significant FDA-approved positive drugs, chromium nicotinate and tapentadol, were presented as repurposing candidates, while cefepime and dihydro-alpha-ergocryptine were recommended as significant adverse drugs. Moreover, two natural compounds, curcumin and quercetin, were recommended to prevent this cross-talk. According to the previous studies, less attention has been paid to the role of lncRNAs in this cross-talk. Our research not only did identify important lncRNAs, but it also suggested potential repurposed drugs to control them.

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“…From our interaction network, we found that circ_0000946 may have an interaction relationship with miR-412-3p, miR-197-3p, miR-26b-5p, miR-26a-5p, miR-3432-5p, miR-16b-3p, miR-34c -3p and miR-34b-3p. Among them, miR-197-3p [ 48 ], miR-26b-5p [ 49 ] and miR-26a-5p [ 50 ] have showed their correlation with adipocyte differentiation. For circ_0005870, we found it can have an interaction with miR-1249, miR-532-3p, miR-487a-5p, miR-140-3p, miR-216b, miR-423-5p, miR-502a, miR-500-3p, miR-504, miR-128-5p, miR-671-5p and miR-2331.…”

Section: Discussionmentioning

confidence: 99%

Key circRNAs from goat: discovery, integrated regulatory network and their putative roles in the differentiation of intramuscular adipocytes

et al. 2023

BMC Genomics

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Background The procession of preadipocytes differentiation into mature adipocytes involves multiple cellular and signal transduction pathways. Recently. a seirces of noncoding RNAs (ncRNAs), including circular RNAs (circRNAs) were proved to play important roles in regulating differentiation of adipocytes. Result In this study, we aimed to identificate the potential circRNAs in the early and late stages of goat intramuscular adipocytes differentiation. Using bioinformatics methods to predict their biological functions and map the circRNA-miRNA interaction network. Over 104 million clean reads in goat intramuscular preadipocytes and adipocytes were mapped, of which16 circRNAs were differentially expressed (DE-circRNAs). Furthermore, we used real-time fluorescent quantitative PCR (qRT-PCR) technology to randomly detect the expression levels of 8 circRNAs among the DE-circRNAs, and our result verifies the accuracy of the RNA-seq data. From the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the DE-circRNAs, two circRNAs, circ_0005870 and circ_0000946, were found in Focal adhesion and PI3K-Akt signaling pathway. Then we draw the circRNA-miRNA interaction network and obtained the miRNAs that possibly interact with circ_0005870 and circ_0000946. Using TargetScan, miRTarBase and miR-TCDS online databases, we further obtained the mRNAs that may interact with the miRNAs, and generated the final circRNA-miRNA-mRNA interaction network. Combined with the following GO (Gene Ontology) and KEGG enrichment analysis, we obtained 5 key mRNAs related to adipocyte differentiation in our interaction network, which are FOXO3(forkhead box O3), PPP2CA (protein phosphatase 2 catalytic subunit alpha), EEIF4E (eukaryotic translation initiation factor 4), CDK6 (cyclin dependent kinase 6) and ACVR1 (activin A receptor type 1). Conclusions By using Illumina HiSeq and online databases, we generated the final circRNA-miRNA-mRNA interaction network that have valuable functions in adipocyte differentiation. Our work serves as a valuable genomic resource for in-depth exploration of the molecular mechanism of ncRNAs interaction network regulating adipocyte differentiation.

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Upregulated lncRNA HCG18 in Patients with Non-Alcoholic Fatty Liver Disease and Its Regulatory Effect on Insulin Resistance

Cited by 17 publications

References 45 publications

LncRNA and circRNA in Patients with Non-Alcoholic Fatty Liver Disease: A Systematic Review

LncRNA and circRNA in Patients with Non-Alcoholic Fatty Liver Disease: A Systematic Review

Identification of repurposed drugs targeting significant long non-coding RNAs in the cross-talk between diabetes mellitus and Alzheimer’s disease

Key circRNAs from goat: discovery, integrated regulatory network and their putative roles in the differentiation of intramuscular adipocytes

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