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      Lung tropism in hospitalized patients following infection with SARS-CoV-2 variants from D614G to Omicron BA.2

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          Abstract

          Background

          The genetic and pathogenic characteristics of SARS-CoV-2 have evolved from the original isolated strains; however, the changes in viral virulence have not been fully defined. In this study, we analyzed the association between the severity of the pathogenesis of pneumonia in humans and SARS-CoV-2 variants that have been prevalent to date.

          Methods

          We examined changes in the variants and tropism of SARS-CoV-2. A total of 514 patients admitted between February 2020 and August 2022 were included and evaluated for pneumonia by computed tomography (CT) as a surrogate of viral tropism.

          Results

          The prevalence of pneumonia for each variant was as follows: D614G (57%, 65/114), Alpha (67%, 41/61), Delta (49%, 41/84), Omicron BA.1.1 (26%, 43/163), and Omicron BA.2 (11%, 10/92). The pneumonia prevalence in unvaccinated patients progressively declined from 70% to 11% as the variants changed: D614G (56%, 61/108), Alpha (70%, 26/37), Delta (60%, 38/63), BA.1.1 (52%, 15/29), and BA.2 (11%, 2/19). The presence of pneumonia in vaccinated patients was as follows: Delta (16%, 3/19), BA.1.1 (21%, 27/129), and BA.2 (11%, 8/73). Compared with D614G, the areas of lung involvement were also significantly reduced in BA.1.1 and BA.2 variants.

          Conclusions

          Compared with previous variants, there was a marked decrease in pneumonia prevalence and lung involvement in patients infected with Omicron owing to decreased tropism in the lungs that hindered viral proliferation in the alveolar epithelial tissue. Nevertheless, older, high-risk patients with comorbidities who are infected with an Omicron variant can still develop pneumonia and require early treatment.

          Plain language summary

          The SARS-CoV-2 virus changes over time with the differing viruses described as variants. The different variants of SARS-CoV-2 have an impact on how easily they infect people and the effects they have on infected individuals. Here, we examined images of the lungs of patients hospitalized with COVID-19 to investigate whether they had pneumonia, a type of swelling in the lung. Compared with the variant found early in the pandemic, the more recent Omicron variant led to a decreased rate of pneumonia in infected individuals. Our findings emphasize the need for early treatment, as pneumonia may progress in older patients or those with other illnesses.

          Abstract

          Hirotsu, Kakizaki et al. assess the presence of pneumonia and pathogenesis during infection with different SARS-CoV-2 variants. The prevalence of pneumonia differs depending on the infectious variant, with the lowest prevalence and mild lung pathogenesis following infection with BA.2.

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          Most cited references45

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          Time Course of Lung Changes On Chest CT During Recovery From 2019 Novel Coronavirus (COVID-19) Pneumonia

          Background Chest CT is used to assess the severity of lung involvement in COVID-19 pneumonia. Purpose To determine the change in chest CT findings associated with COVID-19 pneumonia from initial diagnosis until patient recovery. Materials and Methods This retrospective review included patients with RT-PCR confirmed COVID-19 infection presenting between 12 January 2020 to 6 February 2020. Patients with severe respiratory distress and/ or oxygen requirement at any time during the disease course were excluded. Repeat Chest CT was obtained at approximately 4 day intervals. The total CT score was the sum of lung involvement (5 lobes, score 1-5 for each lobe, range, 0 none, 25 maximum) was determined. Results Twenty one patients (6 males and 15 females, age 25-63 years) with confirmed COVID-19 pneumonia were evaluated. These patients under went a total of 82 pulmonary CT scans with a mean interval of 4±1 days (range: 1-8 days). All patients were discharged after a mean hospitalized period of 17±4 days (range: 11-26 days). Maximum lung involved peaked at approximately 10 days (with the calculated total CT score of 6) from the onset of initial symptoms (R2=0.25), p<0.001). Based on quartiles of patients from day 0 to day 26 involvement, 4 stages of lung CT were defined: Stage 1 (0-4 days): ground glass opacities (GGO) in 18/24 (75%) patients with the total CT score of 2±2; (2)Stage-2 (5-8d days): increased crazy-paving pattern 9/17 patients (53%) with a increase in total CT score (6±4, p=0.002); (3) Stage-3 (9-13days): consolidation 19/21 (91%) patients with the peak of total CT score (7±4); (4) Stage-4 (≥14 days): gradual resolution of consolidation 15/20 (75%) patients with a decreased total CT score (6±4) without crazy-paving pattern. Conclusion In patients recovering from COVID-19 pneumonia (without severe respiratory distress during the disease course), lung abnormalities on chest CT showed greatest severity approximately 10 days after initial onset of symptoms.
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            Nextstrain: real-time tracking of pathogen evolution

            Abstract Summary Understanding the spread and evolution of pathogens is important for effective public health measures and surveillance. Nextstrain consists of a database of viral genomes, a bioinformatics pipeline for phylodynamics analysis, and an interactive visualization platform. Together these present a real-time view into the evolution and spread of a range of viral pathogens of high public health importance. The visualization integrates sequence data with other data types such as geographic information, serology, or host species. Nextstrain compiles our current understanding into a single accessible location, open to health professionals, epidemiologists, virologists and the public alike. Availability and implementation All code (predominantly JavaScript and Python) is freely available from github.com/nextstrain and the web-application is available at nextstrain.org.
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              A dynamic nomenclature proposal for SARS-CoV-2 lineages to assist genomic epidemiology

              The ongoing pandemic spread of a novel human coronavirus, SARS-COV-2, associated with severe pneumonia disease (COVID-19), has resulted in the generation of tens of thousands of virus genome sequences. The rate of genome generation is unprecedented, yet there is currently no coherent nor accepted scheme for naming the expanding phylogenetic diversity of SARS-CoV-2. We present a rational and dynamic virus nomenclature that uses a phylogenetic framework to identify those lineages that contribute most to active spread. Our system is made tractable by constraining the number and depth of hierarchical lineage labels and by flagging and de-labelling virus lineages that become unobserved and hence are likely inactive. By focusing on active virus lineages and those spreading to new locations this nomenclature will assist in tracking and understanding the patterns and determinants of the global spread of SARS-CoV-2.
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                Author and article information

                Contributors
                hirotsu-bdyu@ych.pref.yamanashi.jp
                Journal
                Commun Med (Lond)
                Commun Med (Lond)
                Communications Medicine
                Nature Publishing Group UK (London )
                2730-664X
                25 February 2023
                25 February 2023
                2023
                : 3
                : 32
                Affiliations
                [1 ]Genome Analysis Center, Yamanashi Central Hospital, 1-1-1 Fujimi, Kofu, Yamanashi, Japan
                [2 ]GRID grid.417333.1, ISNI 0000 0004 0377 4044, Lung Cancer and Respiratory Disease Center, Yamanashi Central Hospital, ; 1-1-1 Fujimi, Kofu, Yamanashi, Japan
                [3 ]Department of Radiology, Yamanashi Central Hospital, 1-1-1 Fujimi, Kofu, Yamanashi, Japan
                [4 ]GRID grid.417333.1, ISNI 0000 0004 0377 4044, Department of Gastroenterology, , Yamanashi Central Hospital, ; 1-1-1 Fujimi, Kofu, Yamanashi, Japan
                [5 ]GRID grid.26999.3d, ISNI 0000 0001 2151 536X, The University of Tokyo, ; 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan
                Author information
                http://orcid.org/0000-0002-8002-834X
                Article
                261
                10.1038/s43856-023-00261-5
                9959956
                36841870
                23a7f207-aca6-4aab-a3ab-77a6befe74c1
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 12 July 2022
                : 10 February 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100006680, Takeda Medical Research Foundation;
                Funded by: FundRef https://doi.org/10.13039/100008732, Uehara Memorial Foundation;
                Funded by: FundRef https://doi.org/10.13039/501100008673, Yasuda Memorial Medical Foundation (Yasuda Medical Foundation);
                Funded by: FundRef https://doi.org/10.13039/501100001691, MEXT | Japan Society for the Promotion of Science (JSPS);
                Award ID: JP18K16292
                Award ID: 20H03668
                Award Recipient :
                Categories
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                © The Author(s) 2023

                viral infection,radiography
                viral infection, radiography

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