ABSTRACT
INTRO: Viruses, including SARS-CoV-2, which causes COVID-19, are constantly changing. These genetic changes (aka mutations) occur over time and can lead to the emergence of new variants that may have different characteristics. After the first SARS-CoV-2 genome was published in early 2020, scientists all over the world soon realized the immediate need to obtain as much genetic information from as many strains as possible. However, understanding the functional significance of the mutations harbored by a variant is important to assess its impact on transmissibility, disease severity, immune escape, and the effectiveness of vaccines and therapeutics. METHODS: Here in Canada, we have developed an interactive framework for visualizing and reporting mutations in SARS-CoV-2 variants. This framework is composed of three stand-alone yet connected components;an interactive visualization (COVID-MVP), a manually curated functional annotation database (pokay), and a genomic analysis workflow (nf-ncov-voc). Findings: COVID-MVP provides (i) an interactive heatmap to visualize and compare mutations in SARS-CoV-2 lineages classified across different VOCs, VOIs, and VUMs;(ii) mutation profiles including the type, impact, and contextual information;(iii) annotation of biological impacts for mutations where functional data is available in the literature;(iv) summarized information for each variant and/or lineage in the form of a surveillance report;and (v) the ability to upload raw genomic sequence(s) for rapid processing and annotating for real-time classification. DISCUSSION: This comprehensive comparison allows microbiologists and public health practitioners to better predict how the mutations in emerging variants will impact factors such as infection severity, vaccine resistance, hospitalization rates, etc. CONCLUSION: This framework is cloud-compatible & standalone, which makes it easier to integrate into other genomic surveillance tools as well. COVID-MVP is integrated into the Canadian VirusSeq data portal (https://virusseqdataportal.ca) - a national data hub for SARS-COV-2 genomic data. COVID-MVP is also used by the CanCOGeN and CoVaRR networks in national COVID-19 genomic surveillance.
ABSTRACT
Background: Although a full course of vaccine against Sars- Cov-2 is effective in most patients with MS (PwMS), the duration of the protection and the efficacy of a booster dose remain poorly explored, especially across different disease modifying treatments (DMTs). Aim(s): To characterize humoral and T-cell immune response along time and following third dose of COVID-19 vaccination in PwMS. Method(s): From an established cohort evaluated at baseline (T0), PwMS were recruited after 24 weeks (T1) from the first cycle of mRNA vaccine and 4 weeks after third dose (T2). At each timepoint we evaluated the serological response by measuring the anti- Region-Binding-Domain (RBD). Cell-mediated response was analyzed by computing interferon (IFN)-gamma in response to spike peptides. Result(s): The baseline cohort consisted of 134 PwMS [mean age 46.6+/-10.8 years;F:92;mean disease duration 15.1+/-9.4 years;26.9% ocrelizumab (OCR) 30.6% fingolimod (FTY), 16.4% cladribine (CLA), 26.1%IFN-s-1a (IFNB)]. Of them, 109 were reassessed at T1, 78 at T2 and 64 completed all evaluations. In the whole cohort there was a significant reduction (p<0.0001) in anti- RBD rate from T0 [76% positive, median 52.8 BAU/ml Interquartile Range (IQR) 1150.9] to T1 (57.8% positive, median 13.2 BAU/ml IQR 95.98] and a significant 20- and 5-fold increase in median titer at T2 (75% positive, median 272.3 BAU/ml IQR 4212.3) from T1 and T0 respectively (p<0.0001). Median IFN-gamma level at T2 was significantly higher than those evaluated at T1 (p<0.0001) and T0 (p=0.009). These latter results were consistent across all DMTs. At T1 the highest detectable anti-RBD response was found in CLA (100%, median 87.7 BAU/ml IQR 22) and IFNB (93.5%;median 126.3 BAU/ml IQR 149.2) cohort, while PwMS treated with FTY and OCR showed 60% (median 8.25 BAU/ml IQR 34.3) and 21% (median 0.8 BAU/ml IQR 6) rate of anti-RBD response respectively. At T2 100% PwMS showed positive anti-RBD response except those treated with OCR (23.8% positive, median 0.6 BAU/ml IQR 4.1). IFN-gamma-S-specific T-cell response was reduced in FTY cohort at both T1 and T2 (3.3 % positive, median 0.8 pg/ml IQR 3.1 and 0.6 pg/ml IQR 2.4 respectively). Conclusion(s): A third dose of COVID-19 vaccine reinforces both humoral and cell-mediated immune response in PwMS on DMTs. Despite vaccination, PwMS treated with OCR and FTY show lower humoral and T-cell specific immune response respectively, suggesting the need of specific treatment to halt COVID-19 in case of infection.
ABSTRACT
Evidence is accumulating on the interaction between tuberculosis (TB) and COVID-19. The aim of the present review is to report the available evidence on the interaction between these two infections. Differences and similarities of TB and COVID-19, their immunological features, diagnostics, epidemiological and clinical characteristics and public health implications are discussed. The key published documents and guidelines on the topic have been reviewed. Based on the immunological mechanism involved, a shared dysregulation of immune responses in COVID-19 and TB has been found, suggesting a dual risk posed by co-infection worsening COVID-19 severity and favouring TB disease progression. The available evidence on clinical aspects suggests that COVID-19 happens regardless of TB occurrence either before, during or after an active TB diagnosis. More evidence is required to determine if COVID-19 may reactivate or worsen active TB disease. The role of sequeale and the need for further rehabilitation must be further studied Similarly, the potential role of drugs prescribed during the initial phase to treat COVID-19 and their interaction with anti-TB drugs require caution. Regarding risk of morbidity and mortality, several risk scores for COVID-19 and independent risk factors for TB have been identified: including, among others, age, poverty, malnutrition and co-morbidities (HIV co-infection, diabetes, etc.). Additional evidence is expected to be provided by the ongoing global TB/COVID-19 study.