Long non-coding RNAs in biomarking COVID-19: a machine learning-based approach.

BACKGROUND: The coronavirus pandemic that started in 2019 has caused the highest mortality and morbidity rates worldwide. Data on the role of long non-coding RNAs (lncRNAs) in coronavirus disease 2019 (COVID-19) is scarce. We aimed to elucidate the relationship of three important lncRNAs in the inflammatory states, H19, taurine upregulated gene 1 (TUG1), and colorectal neoplasia differentially expressed (CRNDE) with key factors in inflammation and fibrosis induction including signal transducer and activator of transcription3 (STAT3), alpha smooth muscle actin (α-SMA), tumor necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6) in COVID-19 patients with moderate to severe symptoms. METHODS: Peripheral blood mononuclear cells from 28 COVID-19 patients and 17 healthy controls were collected. The real-time quantitative polymerase chain reaction (RT-qPCR) was performed to evaluate the expression of RNAs and lncRNAs. Western blotting analysis was also performed to determine the expression levels of STAT3 and α-SMA proteins. Machine learning and receiver operating characteristic (ROC) curve analysis were carried out to evaluate the distinguishing ability of lncRNAs. RESULTS: The expression levels of H19, TUG1, and CRNDE were significantly overexpressed in COVID-19 patients compared to healthy controls. Moreover, STAT3 and α-SMA expression levels were remarkedly increased at both transcript and protein levels in patients with COVID-19 compared to healthy subjects and were correlated with Three lncRNAs. Likewise, IL-6 and TNF-α were considerably upregulated in COVID-19 patients. Machine learning and ROC curve analysis showed that CRNDE-H19 panel has the proper ability to distinguish COVID-19 patients from healthy individuals (area under the curve (AUC) = 0.86). CONCLUSION: The overexpression of three lncRNAs in COVID-19 patients observed in this study may align with significant manifestations of COVID-19. Furthermore, their co-expression with STAT3 and α-SMA, two critical factors implicated in inflammation and fibrosis induction, underscores their potential involvement in exacerbating cardiovascular, pulmonary and common symptoms and complications associated with COVID-19. The combination of CRNDE and H19 lncRNAs seems to be an impressive host-based biomarker panel for screening and diagnosis of COVID-19 patients from healthy controls. Research into lncRNAs can provide a robust platform to find new viral infection-related mediators and propose novel therapeutic strategies for viral infections and immune disorders.

Predictive three-biomarker panel in peripheral blood mononuclear cells for detecting hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) ranks among the most prevalent cancers and accounts for a significant proportion of cancer-associated deaths worldwide. This disease, marked by multifaceted etiology, often poses diagnostic challenges. Finding a reliable and non-invasive diagnostic method seems to be necessary. In this study, we analyzed the gene expression profiles of 20 HCC patients, 12 individuals with chronic hepatitis, and 15 healthy controls. Enrichment analysis revealed that platelet aggregation, secretory granule lumen, and G-protein-coupled purinergic nucleotide receptor activity were common biological processes, cellular components, and molecular function in HCC and chronic hepatitis B (CHB) compared to healthy controls, respectively. Furthermore, pathway analysis demonstrated that "estrogen response" was involved in the pathogenesis of HCC and CHB conditions, while, "apoptosis" and "coagulation" pathways were specific for HCC. Employing computational feature selection and logistic regression classification, we identified candidate genes pivotal for diagnostic panel development and evaluated the performance of these panels. Subsequent machine learning evaluations assessed these panels' performance in an independent cohort. Remarkably, a 3-marker panel, comprising RANSE2, TNF-α, and MAP3K7, demonstrated the best performance in qRT-PCR-validated experimental data, achieving 98.4% accuracy and an area under the curve of 1. Our findings highlight this panel's promising potential as a non-invasive approach not only for detecting HCC but also for distinguishing HCC from CHB patients.

Plasma Extracellular Vesicle LncRNA H19 as a Potential Diagnostic Biomarker for Inflammatory Bowel Diseases.

BACKGROUND: Inflammatory bowel disease (IBD) is a complex gastrointestinal disease with 2 main subtypes of Crohn's disease (CD) and ulcerative colitis (UC), whose diagnosis mainly depends on the medical history, clinical symptoms, endoscopic, histologic, radiological, and serological findings. Extracellular vesicles (EVs) are now considered an additional mechanism for intercellular communication, allowing cells to exchange biomolecules. Long noncoding RNAs (lncRNAs) that are enriched in EVs have been defined as an ideal diagnostic biomarker for diseases. In this study, we investigated the expression differences of 5 lncRNAs in tissue and plasma EVs of active IBD patients compared with patients in the remission phase and healthy controls to introduce an EV-lncRNA as a noninvasive IBD diagnostic biomarker. METHODS: Twenty-two active IBD patients, 14 patients in the remission phase, 10 active rheumatoid arthritis (RA) patients, 14 irritable bowel syndrome (IBS) patients, and 22 healthy individuals were recruited in the discovery cohort. In addition, 16 patients with active IBD, 16 healthy controls, 10 inactive IBD patients, 12 active RA patients, and 14 IBS patients were also included in the validation cohort. The expression levels of 5 lncRNAs in tissue and EV-plasma were evaluated by quantitative real-time polymerase chain reaction (qRT-PCR) . Machine learning and receiver operating characteristic (ROC) curve analysis were performed to investigate the distinguishing ability of the candidate biomarkers. RESULTS: While the expression levels of lncRNAs CDKN2B-AS1, GAS5, and TUG1 were significantly downregulated, lncRNAs H19 and CRNDE were overexpressed in active IBD lesions. Expression of H19 was detected in plasma EVs whose isolation had been confirmed via dynamic light scattering, microscopy images, and western blotting. The classification results demonstrated the excellent ability of H19 in distinguishing IBD/active from IBD/remission, healthy control, RA, and IBS (area under the ROC curve = 0.95, 0.97,1, and 0.97 respectively). CONCLUSIONS: Our study suggests that circulating EV-lncRNA H19 exhibited promising potential for the diagnosis of active IBD.

The upregulation of lncRNA H19 in active IBD tissues and plasma extracellular vesicles indicated the possible association of H19 with the disease activity. In addition, the high sensitivity and specificity of this marker proposed it as a potential biomarker for the diagnosis of IBD patients.

TGF-ß receptor I inhibitor may restrict the induction of EMT in inflamed intestinal epithelial cells.

Despite the extensive body of research, understanding the exact molecular mechanisms governing inflammatory bowel diseases (IBDs) still demands further investigation. Transforming growth factor-ß1 (TGF-ß1) signaling possesses a multifacial effect on a broad range of context-dependent cellular responses. However, long-term TGF-ß1 activity may trigger epithelial-mesenchymal transition (EMT), followed by fibrosis. This study aimed to determine the role of epithelial TGF-ß1 signaling in inflammatory bowel disease (IBD) pathogenesis. The expression of TGF-ß1 signaling components and EMT-related and epithelial tight junction markers was examined in IBD patients (n = 60) as well as LPS-induced Caco-2/RAW264.7 co-culture model using quantitative real-time polymerase chain reaction (qRT-PCR), Western blotting, and immunofluorescence staining. Furthermore, the effect of A83-01, as a TGF-ß receptor I (TßRI) inhibitor, on the inflamed epithelial cells was evaluated in vitro. To evaluate the cytotoxic effects of the TßRI inhibitor, a cell viability assay was performed by the MTS method. Considering the activation of canonical and non-canonical TGF-ß1 signaling pathways in IBD patients, expression results indicated that administering A83-01 in inflamed Caco-2 cells substantially blocked the expression level of TGF-ß1, SMAD4, and PI3K and the phosphorylation of p-SMAD2/3, p-AKT, and p-RPS6 as well as prevented downregulation of LncGAS5 and LncCDKN2B. Further analysis revealed that the inhibition of TGF-ß1 signaling in inflamed epithelial cells by the small molecule could suppress the EMT-related markers as well as improve the expression of epithelial adherens and tight junctions. Collectively, these findings indicated that the inhibition of the TGF-ß1 signaling could suppress the induction of EMT in inflamed epithelial cells as well as exert a protective effect on preserving tight junction integrity. There is a pressing need to determine the exact cellular mechanisms by which TGF-ß1 exerts its effect on IBD pathogenesis.

New insights into extracellular and intracellular redox status in COVID-19 patients.

BACKGROUND: The imbalance of redox homeostasis induces hyper-inflammation in viral infections. In this study, we explored the redox system signature in response to SARS-COV-2 infection and examined the status of these extracellular and intracellular signatures in COVID-19 patients. METHOD: The multi-level network was constructed using multi-level data of oxidative stress-related biological processes, protein-protein interactions, transcription factors, and co-expression coefficients obtained from GSE164805, which included gene expression profiles of peripheral blood mononuclear cells (PBMCs) from COVID-19 patients and healthy controls. Top genes were designated based on the degree and closeness centralities. The expression of high-ranked genes was evaluated in PBMCs and nasopharyngeal (NP) samples of 30 COVID-19 patients and 30 healthy controls. The intracellular levels of GSH and ROS/O2• - and extracellular oxidative stress markers were assayed in PBMCs and plasma samples by flow cytometry and ELISA. ELISA results were applied to construct a classification model using logistic regression to differentiate COVID-19 patients from healthy controls. RESULTS: CAT, NFE2L2, SOD1, SOD2 and CYBB were 5 top genes in the network analysis. The expression of these genes and intracellular levels of ROS/O2• - were increased in PBMCs of COVID-19 patients while the GSH level decreased. The expression of high-ranked genes was lower in NP samples of COVID-19 patients compared to control group. The activity of extracellular enzymes CAT and SOD, and the total oxidant status (TOS) level were increased in plasma samples of COVID-19 patients. Also, the 2-marker panel of CAT and TOS and 3-marker panel showed the best performance. CONCLUSION: SARS-COV-2 disrupts the redox equilibrium in immune cells and the upper respiratory tract, leading to exacerbated inflammation and increased replication and entrance of SARS-COV-2 into host cells. Furthermore, utilizing markers of oxidative stress as a complementary validation to discriminate COVID-19 from healthy controls, seems promising.