Identifying novel host-based diagnostic biomarker panels for COVID-19: a whole-blood/nasopharyngeal transcriptome meta-analysis.

BACKGROUND: Regardless of improvements in controlling the COVID-19 pandemic, the lack of comprehensive insight into SARS-COV-2 pathogenesis is still a sophisticated challenge. In order to deal with this challenge, we utilized advanced bioinformatics and machine learning algorithms to reveal more characteristics of SARS-COV-2 pathogenesis and introduce novel host response-based diagnostic biomarker panels. METHODS: In the present study, eight published RNA-Seq datasets related to whole-blood (WB) and nasopharyngeal (NP) swab samples of patients with COVID-19, other viral and non-viral acute respiratory illnesses (ARIs), and healthy controls (HCs) were integrated. To define COVID-19 meta-signatures, Gene Ontology and pathway enrichment analyses were applied to compare COVID-19 with other similar diseases. Additionally, CIBERSORTx was executed in WB samples to detect the immune cell landscape. Furthermore, the optimum WB- and NP-based diagnostic biomarkers were identified via all the combinations of 3 to 9 selected features and the 2-phases machine learning (ML) method which implemented k-fold cross validation and independent test set validation. RESULTS: The host gene meta-signatures obtained for SARS-COV-2 infection were different in the WB and NP samples. The gene ontology and enrichment results of the WB dataset represented the enhancement in inflammatory host response, cell cycle, and interferon signature in COVID-19 patients. Furthermore, NP samples of COVID-19 in comparison with HC and non-viral ARIs showed the significant upregulation of genes associated with cytokine production and defense response to the virus. In contrast, these pathways in COVID-19 compared to other viral ARIs were strikingly attenuated. Notably, immune cell proportions of WB samples altered in COVID-19 versus HC. Moreover, the optimum WB- and NP-based diagnostic panels after two phases of ML-based validation included 6 and 8 markers with an accuracy of 97% and 88%, respectively. CONCLUSIONS: Based on the distinct gene expression profiles of WB and NP, our results indicated that SARS-COV-2 function is body-site-specific, although according to the common signature in WB and NP COVID-19 samples versus controls, this virus also induces a global and systematic host response to some extent. We also introduced and validated WB- and NP-based diagnostic biomarkers using ML methods which can be applied as a complementary tool to diagnose the COVID-19 infection from non-COVID cases.

Revealing transcriptional and post-transcriptional regulatory mechanisms of γ-glutamyl transferase and keratin isoforms as novel cooperative biomarkers in low-grade glioma and glioblastoma multiforme.

Gamma-glutamyltransferase (GGT) and keratins (KRT) are key factors in regulating tumor progression rely on emerging evidence. However, the prognostic values of GGT and KRT isoforms and their regulation patterns at transcriptional and post-transcriptional levels have been rarely studied. In this study, we aimed to identify cooperative prognostic biomarker signature conducted by GGT and KRT genes for overall survival prediction and discrimination in patients with low-grade glioma (LGG) and glioblastoma multiforme (GBM). To this end, we employed a differential expression network analysis on LGG-NORMAL, GBM-NORMAL, and LGG-GBM datasets. Then, all the differentially expressed genes related to a GO term "GGT activity" were excluded. After that, for obtained potential biomarkers genes, differentially expressed lncRNAs were used to detect cis-regulatory elements (CREs) and trans-regulatory elements (TREs). To scrutinize the regulation on the cytoplasm, potential interactions between these biomarker genes and DElncRNAs were predicted. Our analysis, for the first time, revealed that GGT6, KRT33B, and KRT75 in LGG, GGT2, and KRT75 in GBM and KRT75 for LGG to GBM transformation tumors can be novel cooperative prognostic biomarkers that may be applicable for early detection of LGG, GBM, and LGG to GBM transformation tumors. Consequently, KRT75 was the most important gene being regulated at both transcriptional and post-transcriptional levels significantly. Furthermore, CREs and their relative genes were coordinative up-regulated or down-regulated suggesting CREs as regulation points of these genes. In the end, up-regulation of most DElncRNAs that had physical interaction with target genes pints out that the transcripted genes may have obstacles for translation process.

Efficacy of a multiple-indication antiviral herbal drug (Saliravira®) for COVID-19 outpatients: A pre-clinical and randomized clinical trial study.

BACKGROUND: The scientific researches on COVID-19 pandemic topics are headed to an explosion of scientific literature. Despite these global efforts, the efficient treatment of patients is an in-progress challenge. Based on a meta-study of published shreds of evidence about compounds and their botanic sources in the last six decades, a novel multiple-indication herbal compound (Saliravira®) has been developed. Based on the antiviral, anti-inflammatory, and immune-enhancing properties of its ingredients, we hypothesized that Saliravira® has the potential to act as an antiviral agent, accelerate treatment, and reduce undesirable effects of COVID-19. METHODS: In this randomized, controlled, open-label clinical trial, COVID-19 outpatients were included by RT-PCR test or diagnosis of physicians according to the symptoms. Participants were randomly divided into intervention and control groups to receive Saliravira® package plus routine treatments of COVID-19 or routine treatments of COVID-19 alone, respectively. Saliravira® package includes tablets, nasal-sinuses spray, oral-pharynx spray, and inhaler drops. The treatment was for 10 days and followed up till 23 days after admission. RESULTS: On the 8th day, the "mean reduction rates" of viral load of the patients in the intervention group was 50% lower compared to the control group with a p-value < 0.05. The improvement of 10 out of 14 COVID-19 symptoms in the intervention group was significantly accelerated. The mean treatment duration of patients in the intervention group was 4.9 days less than the control group. In addition, no patients in the intervention group were hospitalized compared to 28% of the control group needed to be hospitalized.