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Background: The COVID-19 pandemic has been striking for three years and, despite the regular arise of new variants, populations are now widely immune and protected from severe symptoms. However, immunocompromised patients still have worse clinical outcomes, higher mortality and rarely develop effective immunity through vaccination or infection. Here, we studied the temporal distribution of infections, viral loads (VL) as well as the viral genetic diversity among an immunocompromised patient cohort, between January 2021 and September 2022. Method(s): Overall, 478 immunocompromised patients (solid organ transplant, HIV positive, cancer, autoimmune disease) and 234 controls (healthcare workers) from Pitie-Salpetriere and Bichat Claude-Bernard University hospitals (Paris, FRANCE) were diagnosed with SARS-CoV-2 infection by RT-qPCR. Whole genome sequencing was performed according to ARTIC protocol on Oxford Nanopore platform. All 712 full viral genomes were used to determine lineages and mapped to Wuhan-Hu-1 reference to produce a maximum likelihood phylogenetic tree (IQTree, 1000 bootstraps). Differences in temporal distributions of infections and VL were assessed using nonparametric statistical tests. Result(s): According to phylogenetic analysis, genomes from SARS-CoV- 2 infecting immunocompromised patients and those infecting healthy individuals are distributed in a similar way. No significant genetic differences can be observed between viral genomes from patients and controls within the different lineages. Temporal distribution of COVID-19 infections were also similar between immunocompromised patients and controls, with the exception of BA.2 variant for which controls were infected earlier (p< 0.001). VL were significantly lower in immunocompromised patients infected with Omicron variants (p=0.04). No differences in VL were observed for Alpha and Delta variants. Conclusion(s): At diagnosis, no intrinsic genetic divergence was observed in virus infecting immunocompromised patients compared to those circulating in the general population. Similarities in temporal distribution of infections between controls and patients suggest that these different groups become infected concomitantly. VL appeared to be lower for Omicron variants in immunocompromised patients. An earlier VL peak of Omicron and a testing of immunocompromised patients hospitalized once severe symptoms have appeared could indicate a delayed testing in these patients, once the replicative phase over. (Figure Presented).
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Background: Immunocompromised hosts with prolonged SARS-CoV-2 infections have been associated with the emergence of novel mutations, especially in the Spike protein, a key target for vaccines and therapeutics. Here, we conducted a case-control study to measure the genetic diversity of SARSCoV- 2 and to search for immunocompromised-specific minority variants. Method(s): SARS-CoV-2-positive patients with lung/cardiac/kidney transplant, HIV-positive, or treated with high doses of corticosteroids for auto-immune diseases were considered as immunocompromised hosts. SARS-CoV-2-positive healthcare workers with no auto-immune disease were used as controls. Samples were analyzed by RT-qPCR at Pitie-Salpetriere and Bichat Claude-Bernard university hospitals (Paris, France). Samples with Cycle threshold < 30 were selected for SARSCoV- 2 whole-genome sequencing using Oxford Nanopore protocol. Raw sequence data were mapped onto the Wuhan-Hu-1 reference genome, and consensus sequences were produced to determine the lineage. Only sequences covering at least 95% at >=50X depth of the Spike gene were investigated. In-house algorithms were developed to identify all majority and minority mutations in Spike. We defined a minority variant when it was present in >=6% and < 50% of the reads;and a majority variant when it was present in >50%. Result(s): We sequenced SARS-CoV-2 genome from 478 COVID-19- positive immunocompromised patients and 234 controls. More minority non-synonymous mutations in Spike were detected in viruses from immunocompromised hosts, compared to viral genomes from controls, in both Delta (p=0.001) and Omicron (p< 0.001) lineages, but not in Alpha (p=0.66) (Figure 1). Interestingly, among the 52 patients infected with the Delta variant, we concomitantly detected at low frequencies the mutations H655Y, N764K, D796Y, in three patients (associated with different auto-immune disease), that are part of Omicron variants signature mutations. Similarly, some patients (n=7) infected by Omicron BA.1 lineage had R346T at low-frequency, later fixed in Omicron BA.4.6 and BQ.1.1 lineages. None of these mutations were observed in the viral genomes from controls. Conclusion(s): Here, we report a higher genetic diversity in Spike gene among SARS-CoV-2 sequences from immunocompromised hosts for Delta and Omicron lineages. These results suggest that immunocompromised patients are more likely to allow viral genetic diversification and are associated with a risk of emergence of novel SARS-CoV-2 variants. (Figure Presented).
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Background: In 2020, France reported 2.7 million cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), making it the second most affected European country by the COVID-19 pandemic after the United Kingdom. However, dynamics of SARS-CoV-2 transmissions within France or between France and other countries remains partially characterized. We propose an analysis of these dynamics on multiple scales, from the continents to the French administrative regions. Methods: We produced 736 SARS-CoV-2 sequences from Ile-de-France (Paris area, France) and analyzed them concomitantly with GISAID deposited sequences to elucidate the origins and spread of the virus from January 2020 to December 2020. A total of 4,571 worldwide sequences, including 1,652 French sequences, constituted the final dataset. All sequences were selected to be representative of each country temporal distribution of SARS-CoV-2 to the week resolution. We used a maximum likelihood phylogenetic framework to estimate the most probable temporal and geographic spread of SARS-CoV-2 within France and worldwide. Depending on the geographical focus (France, Europe or worldwide), we pruned the tree accordingly in 1,000 independent replicates. Results: Phylogenetic analysis revealed that, during the 1st French epidemic wave (from March to May), the majority of viruses introduced to France came from North America (USA) and Europe (Spain, Italy, ?). France regularly transmitted to neighboring European countries: Belgium, Germany, Italy and United Kingdom. Contrary to the 1st wave, inter-country transmission events were limited to neighboring countries and intercontinental transmission were almost absent during the French 2nd wave (from September to November). At the French regions-scale, we observed that Ile-de-France (IDF) was the main source of infections for all other French regions during the 1st epidemic wave, with a minor participation of Provence-Alpes-Côte d'Azur (PACA). For the 2nd epidemic wave, PACA was the main source of infections for all other French regions, with a lower participation of IDF and other regions. Conclusion: Overall, our findings allow a more comprehensive representation of SARS-CoV-2 transmission chains related to and within France and the global temporal distribution of those events, in link with control measures applied during the whole 2020 period. IDF and PACA were the main hubs of transmissions in France for the 1st and the 2nd epidemic waves, respectively.
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Introduction En France, une Autorisation d’Utilisation Temporaire de cohorte (ATUc) a été délivrée le 27/02/2021 pour l’utilisation du bamlanivimab en monothérapie dans le traitement précoce (<5jours du début des symptômes) de patients adultes avec un COVID-19 léger à modéré confirmé par PCR et à haut risque d’évolution vers une forme sévère. Les patients concernés étaient les patients de >80 ans ou les patients de <80 ans immunodéprimés (transplantation, chimiothérapie, traitement immunosuppresseur). Le risque d’émergence de variants potentiellement résistants à un monothérapie par anticorps monoclonal anti-Spike, en particulier les variants E484K, avait été pris en compte lors de l’ATUc. Cependant, le bénéfice potentiel de ces traitements chez les patients à haut risque a été considéré comme supérieur au risque. Ici nous décrivons 6 patients ayant reçu de ce traitement, leur évolution et l’émergence de mutations de résistance sous pression de sélection. Matériels et méthodes Il s’agit d’une étude unicentrique en centre hospitalier universitaire. Le bamlanivimab a été administré à une dose unique de 700mg en injection IV d’une heure chez 6 patients qui ont accepté d’utiliser le traitement dans le cadre de l’ATUc. Le suivi virologique des patients a consisté en un test RT-qPCR itératif réalisé le jour de la perfusion ou la veille, à J3±1, à J5±1, à J7±1 puis tous les 3jours jusqu’à ce que la PCR soit négative. La sélection de mutation de résistance a été vérifiée par séquençage du génome complet du SARS-CoV-2 chez tous les patients. Résultats Les six hommes traités avaient un âge médian de 65 ans (extrêmes 35-97), plus de 3 comorbidités à haut risque d’évolution vers une forme sévère et 5 étaient infectés par un variant UK (N501Y.V1, B.1.1.7). Le traitement a été administré dans les 4jours suivant l’apparition des symptômes (médiane 2jours). Les 6 patients ont eu une évolution clinique favorable, deux ont eu besoin d’oxygène au débit maximal de 4 L/min. Aucun patient n’a eu besoin d’oxygénothérapie haut débit, d’une ventilation non invasive ou d’une ventilation invasive. À J20 après l’administration, un seul présentait une PCR nasopharyngée négative et 5 présentaient l’apparition d’une mutation E484K à différents moments après l’administration (J6, J7, J12, J14 et J26). Conclusion Chez ces patients à très haut risque d’évolution vers une forme sévère, la sélection de la mutation E484K après administration de bamlanivimab en monothérapie était très fréquente et bien plus importante qu’observée dans les premiers essais cliniques. Ceci peut être expliqué en partie par l’infection par un variant UK pour 5/6 patients décrits ici. L’émergence de résistance lors des bithérapies devra être suivi attentivement, notamment avec l’émergence des nouveaux variants.