Smoking induced salivary microbiome dysbiosis and is correlated with lipid biomarkers.

BACKGROUND: The oral microbiome plays an essential role in maintaining oral homeostasis and health; smoking significantly affects it, leading to microbial dysbiosis. The study aims to investigate changes in the oral microbiome composition of smokers in the Qatari population and establish a correlation with lipid biomarkers. METHODS: The oral microbiota was profiled from saliva samples of 200 smokers and 100 non-smokers in the Qatari population, and 16s rRNA V3-V4 region were sequenced using the Illumina MiSeq platform. The operational taxonomic units (OTUs) were clustered using QIIME and the statistical analysis was performed by R. RESULTS: Non-smokers exhibited a more diverse microbiome, with significant alpha and beta diversity differences between the non-smoker and smoker groups. Smokers had a higher abundance of Firmicutes, Bacteroidota, Actinobacteriota, Patescibacteria, and Proteobacteria at the phylum level and of Streptococcus, Prevotella, Veillonella, TM7x, and Porphyromonas at the genus level. In contrast, non-smokers had more Bacteroidota, Firmicutes, Proteobacteria, Fusobacteriota, and Patescibacteria at the phylum level, and Prevotella, Streptococcus, Veillonella, Porphromonas, and Neisseria at the genus level. Notably, Streptococcus was significantly positively correlated with LDL and negatively correlated with HDL. Additionally, Streptococcus salivarius, within the genus Streptococcus, was substantially more abundant in smokers. CONCLUSION: This study highlights the significant influence of smoking on the composition of the oral microbiome by enriching anaerobic microbes and depleting aerobic microbes. Moreover, the observed correlation between Streptococcus abundance and the lipid biomarkers suggests a potential link between smokers-induced salivary microbiome dysbiosis and lipid metabolism. Understanding the impact of smoking on altering the oral microbiome composition and its correlation with chemistry tests is essential for developing targeted interventions and strategies to improve oral health and reduce the risk of diseases.

Metabolic predictors of COVID-19 mortality and severity: a survival analysis.

Introduction: The global healthcare burden of COVID-19 pandemic has been unprecedented with a high mortality. Metabolomics, a powerful technique, has been increasingly utilized to study the host response to infections and to understand the progression of multi-system disorders such as COVID-19. Analysis of the host metabolites in response to SARS-CoV-2 infection can provide a snapshot of the endogenous metabolic landscape of the host and its role in shaping the interaction with SARS-CoV-2. Disease severity and consequently the clinical outcomes may be associated with a metabolic imbalance related to amino acids, lipids, and energy-generating pathways. Hence, the host metabolome can help predict potential clinical risks and outcomes. Methods: In this prospective study, using a targeted metabolomics approach, we studied the metabolic signature in 154 COVID-19 patients (males=138, age range 48-69 yrs) and related it to disease severity and mortality. Blood plasma concentrations of metabolites were quantified through LC-MS using MxP Quant 500 kit, which has a coverage of 630 metabolites from 26 biochemical classes including distinct classes of lipids and small organic molecules. We then employed Kaplan-Meier survival analysis to investigate the correlation between various metabolic markers, disease severity and patient outcomes. Results: A comparison of survival outcomes between individuals with high levels of various metabolites (amino acids, tryptophan, kynurenine, serotonin, creatine, SDMA, ADMA, 1-MH and carnitine palmitoyltransferase 1 and 2 enzymes) and those with low levels revealed statistically significant differences in survival outcomes. We further used four key metabolic markers (tryptophan, kynurenine, asymmetric dimethylarginine, and 1-Methylhistidine) to develop a COVID-19 mortality risk model through the application of multiple machine-learning methods. Conclusions: Metabolomics analysis revealed distinct metabolic signatures among different severity groups, reflecting discernible alterations in amino acid levels and perturbations in tryptophan metabolism. Notably, critical patients exhibited higher levels of short chain acylcarnitines, concomitant with higher concentrations of SDMA, ADMA, and 1-MH in severe cases and non-survivors. Conversely, levels of 3-methylhistidine were lower in this context.

Targeting HER2-positive breast cancer cells by a combination of dasatinib and BMS-202: Insight into the molecular pathways.

BACKGROUND: Recent investigations have reported the benefits of using a tyrosine kinase inhibitor, dasatinib (DA), as well as programmed death-ligand 1 (PD-L1) inhibitors in the management of several solid tumors, including breast cancer. Nevertheless, the outcome of the combination of these inhibitors on HER2-positive breast cancer is not explored yet. METHODS: Herein, we investigated the impact of DA and PD-L1 inhibitor (BMS-202) combination on HER2-positive breast cancer cell lines, SKBR3 and ZR75. RESULTS: Our data reveal that the combination significantly inhibits cell viability of both cancer cell lines as compared to monotreatment. Moreover, the combination inhibits epithelial-mesenchymal transition (EMT) progression and reduces cancer cell invasion by restoring E-cadherin and ß-catenin expressions and loss of vimentin, major biomarkers of EMT. Additionally, the combination reduces the colony formation of both cell lines in comparison with their matched control. Also, the combination considerably inhibits the angiogenesis of the chorioallantoic membrane model compared with monotreatment. Molecular pathway analysis of treated cells shows that this combination blocks HER2, AKT, ß-catenin, and JNK1/2/3 activities. CONCLUSION: Our findings implicate that a combination of DA and BMS-202 could have a significant impact on the management of HER2-positive breast cancer.

Inflammatory protein signatures in individuals with obesity and metabolic syndrome.

There is variability in the metabolic health status among individuals presenting with obesity; some may be metabolically healthy, while others may have developed the metabolic syndrome, a cluster including insulin resistance, hypertension, dyslipidemia, and increased risk of cardiovascular disease and type 2 diabetes. The mechanisms contributing to this metabolic heterogeneity are not fully understood. To address this question, plasma samples from 48 individuals with BMI ≥ 35 kg/m2 were examined (27 with and 21 without metabolic syndrome). Fasting plasma samples were subjected to Olink proteomics analysis for 184 cardiometabolic and inflammation-enriched proteins. Data analysis showed a clear differentiation between the two groups with distinct plasma protein expression profiles. Twenty-four proteins were differentially expressed (DEPs) between the two groups. Pathways related to immune cell migration, leukocyte chemotaxis, chemokine signaling, mucosal inflammatory response, tissue repair and remodeling were enriched in the group with metabolic syndrome. Functional analysis of DEPs revealed upregulation of 15 immunological pathways. The study identifies some of the pathways that are altered and reflect metabolic health in individuals with obesity. This provides valuable insights into some of the underlying mechanisms and can lead to identification of therapeutic targets to improve metabolic health in individuals with obesity.

The retrospective study of the metabolic patterns of BCG-vaccination in type-2 diabetic individuals in COVID-19 infection.

Background: The cross-protective nature of Bacillus Calmette-Guerin (BCG) vaccine against SARS-CoV-2 virus was previously suggested, however its effect in COVID-19 patients with type 2 diabetes (T2D) and the underlying metabolic pathways has not been addressed. This study aims to investigate the difference in the metabolomic patterns of type 2 diabetic patients with BCG vaccination showing different severity levels of COVID-19 infection. Methods: Sixty-seven COVID-19 patients were categorized into diabetic and non-diabetic individuals who had been previously vaccinated or not with BCG vaccination. Targeted metabolomics were performed from serum samples from all patients using tandem mass spectrometry. Statistical analysis included multivariate and univariate models. Results: Data suggested that while BCG vaccination may provide protection for individuals who do not have diabetes, it appears to be linked to more severe COVID-19 symptoms in T2D patients (p = 0.02). Comparing the metabolic signature of BCG vaccinated T2D individuals to non-vaccinated counterparts revealed that amino acid (sarcosine), cholesterol esters (CE 20:0, 20:1, 22:2), carboxylic acid (Aconitic acid) were enriched in BCG vaccinated T2D patients, whereas spermidine, glycosylceramides (Hex3Cer(d18:1_22:0), Hex2Cer(d18:1/22:0), HexCer(d18:1/26:1), Hex2Cer(d18:1/24:0), HexCer(d18:1/22:0) were higher in BCG vaccinated non- T2D patients. Furthermore, data indicated a decrease in sarcosine synthesis from glycine and choline and increase in spermidine synthesis in the BCG vaccinated cohort in T2D and non-T2D groups, respectively. Conclusion: This pilot study suggests increased severity of COVID-19 in BCG vaccinated T2D patients, which was marked by decreased sarcosine synthesis, perhaps via lower sarcosine-mediated removal of viral antigens.

An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case-control study.

OBJECTIVES: To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways. METHODS: We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched to 18 without metabolic complications. We measured in whole blood samples 754 human microRNAs (miRNAs), 704 metabolites using unbiased mass spectrometry metabolomics, and 25,682 transcripts, which include both protein coding genes (PCGs) as well as non-coding transcripts. We then identified differentially expressed miRNAs, PCGs, and metabolites and integrated them using databases such as mirDIP (mapping between miRNA-PCG network), Human Metabolome Database (mapping between metabolite-PCG network) and tools like MetaboAnalyst (mapping between metabolite-metabolic pathway network) to determine dysregulated metabolic pathways in obesity with metabolic complications. RESULTS: We identified 8 significantly enriched metabolic pathways comprising 8 metabolites, 25 protein coding genes and 9 microRNAs which are each differentially expressed between the subjects with obesity and those with obesity and metabolic syndrome. By performing unsupervised hierarchical clustering on the enrichment matrix of the 8 metabolic pathways, we could approximately segregate the uncomplicated obesity strata from that of obesity with metabolic syndrome. CONCLUSIONS: The data suggest that at least 8 metabolic pathways, along with their various dysregulated elements, identified via our integrative bioinformatics pipeline, can potentially differentiate those with obesity from those with obesity and metabolic complications.

Dynamics of Anti-S IgG Antibodies Titers after the Second Dose of COVID-19 Vaccines in the Manual and Craft Worker Population of Qatar.

There is limited seroepidemiological evidence on the magnitude and long-term durability of antibody titers of mRNA and non-mRNA vaccines in the Qatari population. This study was conducted to generate evidence on long-term anti-S IgG antibody titers and their dynamics in individuals who have completed a primary COVID-19 vaccination schedule. A total of 300 male participants who received any of the following vaccines BNT162b2/Comirnaty, mRNA-1273, ChAdOx1-S/Covishield, COVID-19 Vaccine Janssen/Johnson, or BBIBP-CorV or Covaxin were enrolled in our study. All sera samples were tested by chemiluminescent microparticle immunoassay (CMIA) for the quantitative determination of IgG antibodies to SARS-CoV-2, receptor-binding domain (RBD) of the S1 subunit of the spike protein of SARS-CoV-2. Antibodies against SARS-CoV-2 nucleocapsid (SARS-CoV-2 N-protein IgG) were also determined. Kaplan-Meier survival curves were used to compare the time from the last dose of the primary vaccination schedule to the time by which anti-S IgG antibody titers fell into the lowest quartile (range of values collected) for the mRNA and non-mRNA vaccines. Participants vaccinated with mRNA vaccines had higher median anti-S IgG antibody titers. Participants vaccinated with the mRNA-1273 vaccine had the highest median anti-S-antibody level of 13,720.9 AU/mL (IQR 6426.5 to 30,185.6 AU/mL) followed by BNT162b2 (median, 7570.9 AU/mL; IQR, 3757.9 to 16,577.4 AU/mL); while the median anti-S antibody titer for non-mRNA vaccinated participants was 3759.7 AU/mL (IQR, 2059.7-5693.5 AU/mL). The median time to reach the lowest quartile was 3.53 months (IQR, 2.2-4.5 months) and 7.63 months (IQR, 6.3-8.4 months) for the non-mRNA vaccine recipients and Pfizer vaccine recipients, respectively. However, more than 50% of the Moderna vaccine recipients did not reach the lowest quartile by the end of the follow-up period. This evidence on anti-S IgG antibody titers should be considered for informing decisions on the durability of the neutralizing activity and thus protection against infection after the full course of primary vaccination in individuals receiving different type (mRNA verus non-mRNA) vaccines and those with natural infection.

Antibody-Dependent Enhancement (ADE) and the role of complement system in disease pathogenesis.

Antibody-dependent enhancement (ADE) has been associated with severe disease outcomes in several viral infections, including respiratory infections. In vitro and in vivo studies showed that antibody-response to SARS-CoV and MERS-CoV could exacerbate infection via ADE. Recently in SARS CoV-2, the in vitro studies and structural analysis shows a risk of disease severity via ADE. This phenomenon is partially attributed to non-neutralizing antibodies or antibodies at sub-neutralizing levels. These antibodies result in antigen-antibody complexes' deposition and propagation of a chronic inflammatory process that destroys affected tissues. Further, antigen-antibody complexes may enhance the internalization of the virus into cells through the Fc gamma receptor (FcγR) and lead to further virus replication. Thus, ADE occur via two mechanisms; 1. Antibody mediated replication and 2. Enhanced immune activation. Antibody-mediated effector functions are mainly driven by complement activation, and the first complement in the cascade is complement 1q (C1q) which binds to the virus-antibody complex. Reports say that deficiency in circulating plasma levels of C1q, an independent predictor of mortality in high-risk patients, including diabetes, is associated with severe viral infections. Complement mediated ADE is reported in several viral infections such as dengue, West Nile virus, measles, RSV, Human immunodeficiency virus (HIV), and Ebola virus. This review discusses ADE in viral infections and the in vitro evidence of ADE in coronaviruses. We outline the mechanisms of ADE, emphasizing the role of complements, especially C1q in the outcome of the enhanced disease.

Detection of Antinuclear Antibodies Targeting Intracellular Signal Transduction, Metabolism, Apoptotic Processes and Cell Death in Critical COVID-19 Patients.

Background and Objectives: The heterogeneity of the coronavirus disease of 2019 (COVID-19) lies within its diverse symptoms and severity, ranging from mild to lethal. Acute respiratory distress syndrome (ARDS) is a leading cause of mortality in COVID-19 patients, characterized by a hyper cytokine storm. Autoimmunity is proposed to occur as a result of COVID-19, given the high similarity of the immune responses observed in COVID-19 and autoimmune diseases. Here, we investigate the level of autoimmune antibodies in COVID-19 patients with different severities. Results: Initial screening for antinuclear antibodies (ANA) IgG using ELISA revealed that 1.58% (2/126) and 4% (5/126) of intensive care unit (ICU) COVID-19 cases expressed strong and moderate ANA levels, respectively. An additional sample was positive with immunofluorescence assays (IFA) screening. However, all the non-ICU cases (n=273) were ANA negative using both assays. Samples positive for ANA were further confirmed with large-scale autoantibody screening by phage immunoprecipitation-sequencing (PhIP-Seq). The majority of the ANA-positive samples showed "speckled" ANA pattern by microscopy and revealed autoantibody specificities that targeted proteins involved in intracellular signal transduction, metabolism, apoptotic processes, and cell death by PhIP-Seq; further denoting reactivity to nuclear and cytoplasmic antigens. Conclusion: Our results further support the notion of routine screening for autoimmune responses in COVID-19 patients, which might help improve disease prognosis and patient management. Further, results provide compelling evidence that ANA-positive individuals should be excluded from being donors for convalescent plasma therapy in the context of COVID-19.

Dysregulated Metabolic Pathways in Subjects with Obesity and Metabolic Syndrome.

Background: Obesity coexists with variable features of metabolic syndrome, which is associated with dysregulated metabolic pathways. We assessed potential associations between serum metabolites and features of metabolic syndrome in Arabic subjects with obesity. Methods: We analyzed a dataset of 39 subjects with obesity only (OBO, n = 18) age-matched to subjects with obesity and metabolic syndrome (OBM, n = 21). We measured 1069 serum metabolites and correlated them to clinical features. Results: A total of 83 metabolites, mostly lipids, were significantly different (p < 0.05) between the two groups. Among lipids, 22 sphingomyelins were decreased in OBM compared to OBO. Among non-lipids, quinolinate, kynurenine, and tryptophan were also decreased in OBM compared to OBO. Sphingomyelin is negatively correlated with glucose, HbA1C, insulin, and triglycerides but positively correlated with HDL, LDL, and cholesterol. Differentially enriched pathways include lysine degradation, amino sugar and nucleotide sugar metabolism, arginine and proline metabolism, fructose and mannose metabolism, and galactose metabolism. Conclusions: Metabolites and pathways associated with chronic inflammation are differentially expressed in subjects with obesity and metabolic syndrome compared to subjects with obesity but without the clinical features of metabolic syndrome.

Identification of Prognostic Metabolomic Biomarkers at the Interface of Mortality and Morbidity in Pre-Existing TB Cases Infected With SARS-CoV-2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection currently remains one of the biggest global challenges that can lead to acute respiratory distress syndrome (CARDS) in severe cases. In line with this, prior pulmonary tuberculosis (TB) is a risk factor for long-term respiratory impairment. Post-TB lung dysfunction often goes unrecognized, despite its relatively high prevalence and its association with reduced quality of life. In this study, we used a metabolomics analysis to identify potential biomarkers that aid in the prognosis of COVID-19 morbidity and mortality in post-TB infected patients. This analysis involved blood samples from 155 SARS-CoV-2 infected adults, of which 23 had a previous diagnosis of TB (post-TB), while 132 did not have a prior or current TB infection. Our analysis indicated that the vast majority (~92%) of post-TB individuals showed severe SARS-CoV-2 infection, required intensive oxygen support with a significantly high mortality rate (52.2%). Amongst individuals with severe COVID-19 symptoms, we report a significant decline in the levels of amino acids, notably the branched chains amino acids (BCAAs), more so in the post-TB cohort (FDR <= 0.05) in comparison to mild and asymptomatic cases. Indeed, we identified betaine and BCAAs as potential prognostic metabolic biomarkers of severity and mortality, respectively, in COVID-19 patients who have been exposed to TB. Moreover, we identified serum alanine as an important metabolite at the interface of severity and mortality. Hence, our data associated COVID-19 mortality and morbidity with a long-term metabolically driven consequence of TB infection. In summary, our study provides evidence for a higher mortality rate among COVID-19 infection patients who have history of prior TB infection diagnosis, which mandates validation in larger population cohorts.

Characteristic MicroRNAs Linked to Dysregulated Metabolic Pathways in Qatari Adult Subjects With Obesity and Metabolic Syndrome.

Background: Obesity-associated dysglycemia is associated with metabolic disorders. MicroRNAs (miRNAs) are known regulators of metabolic homeostasis. We aimed to assess the relationship of circulating miRNAs with clinical features in obese Qatari individuals. Methods: We analyzed a dataset of 39 age-matched patients that includes 18 subjects with obesity only (OBO) and 21 subjects with obesity and metabolic syndrome (OBM). We measured 754 well-characterized human microRNAs (miRNAs) and identified differentially expressed miRNAs along with their significant associations with clinical markers in these patients. Results: A total of 64 miRNAs were differentially expressed between metabolically healthy obese (OBO) versus metabolically unhealthy obese (OBM) patients. Thirteen out of 64 miRNAs significantly correlated with at least one clinical trait of the metabolic syndrome. Six out of the thirteen demonstrated significant association with HbA1c levels; miR-331-3p, miR-452-3p, and miR-485-5p were over-expressed, whereas miR-153-3p, miR-182-5p, and miR-433-3p were under-expressed in the OBM patients with elevated HbA1c levels. We also identified, miR-106b-3p, miR-652-3p, and miR-93-5p that showed a significant association with creatinine; miR-130b-5p, miR-363-3p, and miR-636 were significantly associated with cholesterol, whereas miR-130a-3p was significantly associated with LDL. Additionally, miR-652-3p's differential expression correlated significantly with HDL and creatinine. Conclusions: MicroRNAs associated with metabolic syndrome in obese subjects may have a pathophysiologic role and can serve as markers for obese individuals predisposed to various metabolic diseases like diabetes.

Duration of COVID-19 mRNA Vaccine Effectiveness against Severe Disease.

Waning immunity following administration of mRNA-based COVID-19 vaccines remains a concern for many health systems. We undertook a study to determine if recent reports of waning for severe disease could have been attributed to design-related bias by conducting a study only among those detected with a first SARS-CoV-2 infection. We used a matched case-control study design with the study base being all individuals with first infection with SARS-CoV-2 reported in the State of Qatar between 1 January 2021 and 20 February 2022. Cases were those detected with first SARS-CoV-2 infection requiring intensive care (hard outcome), while controls were those detected with first SARS-CoV-2 infection who recovered without the need for intensive care. Cases and controls were matched in a 1:30 ratio for the calendar month of infection and the comorbidity category. Duration and magnitude of conditional vaccine effectiveness against requiring intensive care and the number needed to vaccinate (NNV) to prevent one more case of COVID-19 requiring intensive care was estimated for the mRNA (BNT162b2/mRNA-1273) vaccines. Conditional vaccine effectiveness against requiring intensive care was 59% (95% confidence interval (CI), 50 to 76) between the first and second dose, and strengthened to 89% (95% CI, 85 to 92) between the second dose and 4 months post the second dose in persons who received a primary course of the vaccine. There was no waning of vaccine effectiveness in the period from 4 to 6, 6 to 9, and 9 to 12 months after the second dose. This study demonstrates that, contrary to mainstream reports using hierarchical measures of effectiveness, conditional vaccine effectiveness against requiring intensive care remains robust till at least 12 months after the second dose of mRNA-based vaccines.

The prevalence of adaptive immunity to COVID-19 and reinfection after recovery - a comprehensive systematic review and meta-analysis.

This study aims to estimate the prevalence and longevity of detectable SARS-CoV-2 antibodies and T and B memory cells after recovery. In addition, the prevalence of COVID-19 reinfection and the preventive efficacy of previous infection with SARS-CoV-2 were investigated. A synthesis of existing research was conducted. The Cochrane Library, the China Academic Journals Full Text Database, PubMed, and Scopus, and preprint servers were searched for studies conducted between 1 January 2020 to 1 April 2021. Included studies were assessed for methodological quality and pooled estimates of relevant outcomes were obtained in a meta-analysis using a bias adjusted synthesis method. Proportions were synthesized with the Freeman-Tukey double arcsine transformation and binary outcomes using the odds ratio (OR). Heterogeneity was assessed using the I2 and Cochran's Q statistics and publication bias was assessed using Doi plots. Fifty-four studies from 18 countries, with around 12,000,000 individuals, followed up to 8 months after recovery, were included. At 6-8 months after recovery, the prevalence of SARS-CoV-2 specific immunological memory remained high; IgG - 90.4% (95%CI 72.2-99.9, I2 = 89.0%), CD4+ - 91.7% (95%CI 78.2-97.1y), and memory B cells 80.6% (95%CI 65.0-90.2) and the pooled prevalence of reinfection was 0.2% (95%CI 0.0-0.7, I2 = 98.8). Individuals previously infected with SARS-CoV-2 had an 81% reduction in odds of a reinfection (OR 0.19, 95% CI 0.1-0.3, I2 = 90.5%). Around 90% of recovered individuals had evidence of immunological memory to SARS-CoV-2, at 6-8 months after recovery and had a low risk of reinfection.RegistrationPROSPERO: CRD42020201234.

Complement C5a and Clinical Markers as Predictors of COVID-19 Disease Severity and Mortality in a Multi-Ethnic Population.

Coronavirus disease-2019 (COVID-19) was declared as a pandemic by WHO in March 2020. SARS-CoV-2 causes a wide range of illness from asymptomatic to life-threatening. There is an essential need to identify biomarkers to predict disease severity and mortality during the earlier stages of the disease, aiding treatment and allocation of resources to improve survival. The aim of this study was to identify at the time of SARS-COV-2 infection patients at high risk of developing severe disease associated with low survival using blood parameters, including inflammation and coagulation mediators, vital signs, and pre-existing comorbidities. This cohort included 89 multi-ethnic COVID-19 patients recruited between July 14th and October 20th 2020 in Doha, Qatar. According to clinical severity, patients were grouped into severe (n=33), mild (n=33) and asymptomatic (n=23). Common routine tests such as complete blood count (CBC), glucose, electrolytes, liver and kidney function parameters and markers of inflammation, thrombosis and endothelial dysfunction including complement component split product C5a, Interleukin-6, ferritin and C-reactive protein were measured at the time COVID-19 infection was confirmed. Correlation tests suggest that C5a is a predictive marker of disease severity and mortality, in addition to 40 biological and physiological parameters that were found statistically significant between survivors and non-survivors. Survival analysis showed that high C5a levels, hypoalbuminemia, lymphopenia, elevated procalcitonin, neutrophilic leukocytosis, acute anemia along with increased acute kidney and hepatocellular injury markers were associated with a higher risk of death in COVID-19 patients. Altogether, we created a prognostic classification model, the CAL model (C5a, Albumin, and Lymphocyte count) to predict severity with significant accuracy. Stratification of patients using the CAL model could help in the identification of patients likely to develop severe symptoms in advance so that treatments can be targeted accordingly.

SnoRNAs and miRNAs Networks Underlying COVID-19 Disease Severity.

There is a lack of predictive markers for early and rapid identification of disease progression in COVID-19 patients. Our study aims at identifying microRNAs (miRNAs)/small nucleolar RNAs (snoRNAs) as potential biomarkers of COVID-19 severity. Using differential expression analysis of microarray data (n = 29), we identified hsa-miR-1246, ACA40, hsa-miR-4532, hsa-miR-145-5p, and ACA18 as the top five differentially expressed transcripts in severe versus asymptomatic, and ACA40, hsa-miR-3609, ENSG00000212378 (SNORD78), hsa-miR-1231, hsa-miR-885-3p as the most significant five in severe versus mild cases. Moreover, we found that white blood cell (WBC) count, absolute neutrophil count (ANC), neutrophil (%), lymphocyte (%), red blood cell (RBC) count, hemoglobin, hematocrit, D-Dimer, and albumin are significantly correlated with the identified differentially expressed miRNAs and snoRNAs. We report a unique miRNA and snoRNA profile that is associated with a higher risk of severity in a cohort of SARS-CoV-2 infected patients. Altogether, we present a differential expression analysis of COVID-19-associated microRNA (miRNA)/small nucleolar RNA (snoRNA) signature, highlighting their importance in SARS-CoV-2 infection.

Substantial cell apoptosis provoked by naked PAMAM dendrimers in HER2-positive human breast cancer via JNK and ERK1/ERK2 signalling pathways.

HER2-positive breast cancer is one of its most challenging subtypes, forming around 15-25% of the total cases. It is characterized by aggressive behavior and treatment resistance. On the other hand, poly (amidoamine) (PAMAM) dendrimers are widely used in drug delivery systems and gene transfection as carriers. PAMAMs can modulate gene expression and interfere with transactivation of the human epidermal growth factor receptor family members (HER1-4). Nevertheless, the outcome of PAMAMs on HER2-positive breast cancer remains unknown. Thus, in this study, we investigated the anti-cancer effects of different generations of PAMAM dendrimers (G4 and G6) and the outcome of their surface chemistries (cationic, neutral, and anionic) on HER2-positive breast cancer cell lines, SKBR3 and ZR75. Our data showed that PAMAM dendrimers, mainly cationic types, significantly reduce cell viability in a dose-dependent manner. More significantly, PAMAMs induce substantial cell apoptosis, accompanied by the up-regulation of apoptotic markers (Bax, Caspases-3, 8 and 9) in addition to down-regulation of Bcl-2. Moreover, our data pointed out that cationic PAMAMs inhibit colony formation compared to controls and other types of PAMAMs. The molecular pathway analysis of PAMAM exposed cells revealed that PAMAMs enhance JNK1/2/3 expression while blocking ERK1/2, in addition to EGFR1 (HER1) and HER2 activities, which could be the major molecular pathway behind these events. These observed effects were comparable to lapatinib treatment, a clinically used inhibitor of HER1 and 2 receptors phosphorylation. Our findings implicate that PAMAMs may possess important therapeutic effects against HER2-positive breast cancer via JNK1/2/3, ERK1/2, and HER1/2 signalling pathways.

Metabolic reprogramming of T regulatory cells in the hypoxic tumor microenvironment.

Metabolic dysregulation in the hypoxic tumor microenvironment (TME) is considered as a hallmark of solid tumors, leading to changes in biosynthetic pathways favoring onset, survival and proliferation of malignant cells. Within the TME, hypoxic milieu favors metabolic reprogramming of tumor cells, which subsequently affects biological properties of tumor-infiltrating immune cells. T regulatory cells (Tregs), including both circulating and tissue-resident cells, are particularly susceptible to hypoxic metabolic signaling that can reprogram their biological and physicochemical properties. Furthermore, metabolic reprogramming modifies Tregs to utilize alternative substrates and undergo a plethora of metabolic events to meet their energy demands. Major impact of this metabolic reprogramming can result in differentiation, survival, excessive secretion of immunosuppressive cytokines and proliferation of Tregs within the TME, which in turn dampen anti-tumor immune responses. Studies on fine-tuning of Treg metabolism are challenging due to heterogenicity of tissue-resident Tregs and their dynamic functions. In this review, we highlight tumor intrinsic and extrinsic factors, which can influence Treg metabolism in the hypoxic TME. Moreover, we focus on metabolic reprogramming of Tregs that could unveil potential regulatory networks favoring tumorigenesis/progression, and provide novel insights, including inhibitors against acetyl-coA carboxylase 1 and transforming growth factor beta into targeting Treg metabolism for therapeutic benefits.

SARS-CoV-2 and immune-microbiome interactions: Lessons from respiratory viral infections.

By the beginning of 2020, infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had rapidly evolved into an emergent worldwide pandemic, an outbreak whose unprecedented consequences highlighted many existing flaws within public healthcare systems across the world. While coronavirus disease 2019 (COVID-19) is bestowed with a broad spectrum of clinical manifestations, involving the vital organs, the respiratory system transpires as the main route of entry for SARS-CoV-2, with the lungs being its primary target. Of those infected, up to 20% require hospitalization on account of severity, while the majority of patients are either asymptomatic or exhibit mild symptoms. Exacerbation in the disease severity and complications of COVID-19 infection have been associated with multiple comorbidities, including hypertension, diabetes mellitus, cardiovascular disorders, cancer, and chronic lung disease. Interestingly, a recent body of evidence indicated the pulmonary and gut microbiomes as potential modulators for altering the course of COVID-19, potentially via the microbiome-immune system axis. While the relative concordance between microbes and immunity has yet to be fully elucidated with regards to COVID-19, we present an overview of our current understanding of COVID-19-microbiome-immune cross talk and discuss the potential contributions of microbiome-related immunity to SARS-CoV-2 pathogenesis and COVID-19 disease progression.