Cracking the code: lncRNA-miRNA-mRNA integrated network analysis unveiling lncRNAs as promising non-invasive NAFLD biomarkers toward precision diagnosis

IF 2.6 4区 生物学 Q2 BIOLOGY Computational Biology and Chemistry Pub Date : 2025-01-09 DOI:10.1016/j.compbiolchem.2024.108325
Nouran Yonis , Ahmed Mousa , Mohamed H. Yousef , Ahmed M. Ghouneimy , Areeg M. Dabbish , Hana Abdelzaher , Mohamed Ali Hussein , Shahd Ezzeldin , Abdelmoneim A. Adel , Yosra H. Mahmoud , Nashwa El-Khazragy , Anwar Abdelnaser
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Abstract

Background

Non-alcoholic fatty liver disease (NAFLD) involves abnormal fat accumulation in the liver, mainly as triglycerides. It ranges from steatosis to non-alcoholic steatohepatitis (NASH), which can lead to inflammation, cellular damage, liver fibrosis, cirrhosis, or hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) are crucial for regulating gene expression across various conditions. LncRNAs are emerging as potential putative diagnostic markers for NAFLD-associated HCC.

Methods

We used two human and two mouse datasets from the Gene Expression Omnibus to analyze the expression profiles of mRNAs and lncRNAs. We created a network linking lncRNAs, miRNAs, and mRNAs to investigate the relationships among these RNA types. Additionally, we identified NAFLD-related lncRNAs from existing literature. We then quantified the expression levels of four specific lncRNAs, including PVT1, DUBR, SNHG17, and SNHG14, in the serum of 92 Egyptian participants using qPCR. Finally, we performed a Receiver Operating Characteristic analysis to evaluate the diagnostic potential of the candidate lncRNAs.

Results

Our data suggests that maternally expressed gene 3 (MEG3), H19, and DPPA2 Upstream Binding RNA (DUBR) were significantly upregulated, and plasmacytoma variant translocation 1 (PVT1) was markedly downregulated. PVT1 showed the highest diagnostic accuracy for both NAFLD and NASH. The combined panels of PVT1 +H19 for NAFLD and PVT1 +H19 +DUBR for NASH demonstrated high diagnostic potential. Uniquely, PVT1 can distinguish between NAFLD and NASH. PVT1 exhibited strong diagnostic potential for NAFLD and NASH, individually and in combination with other lncRNAs.

Conclusion

Our study identifies four lncRNAs as putative biomarkers with high specificity and accuracy, individually or combined, for differentiating between NAFLD and NASH. Healthy volunteers with PVT1 possess the highest diagnostic accuracy and significantly discriminate between NAFLD and NASH.

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破解密码:lncRNA-miRNA-mRNA集成网络分析揭示lncrna作为有前途的非侵入性NAFLD生物标志物的精确诊断。
背景:非酒精性脂肪性肝病(NAFLD)涉及肝脏异常脂肪积聚,主要是甘油三酯。它的范围从脂肪变性到非酒精性脂肪性肝炎(NASH),可导致炎症、细胞损伤、肝纤维化、肝硬化或肝细胞癌(HCC)。长链非编码rna (lncRNAs)在各种情况下调控基因表达至关重要。lncrna正在成为nafld相关HCC的潜在推定诊断标志物。方法:利用来自基因表达总汇(Gene Expression Omnibus)的两个人和两个小鼠数据集,分析mrna和lncrna的表达谱。我们创建了一个连接lncrna、mirna和mrna的网络,以研究这些RNA类型之间的关系。此外,我们从现有文献中鉴定出与nafld相关的lncrna。然后,我们使用qPCR方法量化了92名埃及参与者血清中四种特异性lncrna的表达水平,包括PVT1、DUBR、SNHG17和SNHG14。最后,我们进行了接受者操作特征分析,以评估候选lncrna的诊断潜力。结果:我们的数据显示母系表达基因3 (MEG3)、H19和DPPA2上游结合RNA (DUBR)显著上调,浆细胞瘤变异易位1 (PVT1)显著下调。PVT1对NAFLD和NASH的诊断准确率最高。PVT1 +H19联合检测NAFLD和PVT1 +H19 +DUBR联合检测NASH显示出很高的诊断潜力。独特的是,PVT1可以区分NAFLD和NASH。无论是单独还是与其他lncrna联合,PVT1都显示出对NAFLD和NASH的强大诊断潜力。结论:我们的研究确定了四种lncrna作为区分NAFLD和NASH的高特异性和准确性的推定生物标志物,单独或联合使用。患有PVT1的健康志愿者具有最高的诊断准确性,并能显著区分NAFLD和NASH。
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来源期刊
Computational Biology and Chemistry
Computational Biology and Chemistry 生物-计算机:跨学科应用
CiteScore
6.10
自引率
3.20%
发文量
142
审稿时长
24 days
期刊介绍: Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.
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