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ABSTRACT Background: SARS-CoV-2 has evolved rapidly, resulting in emergence of lineages with competitive advantage over one another. Co-infections with different SARS-CoV-2 lineages can give rise to recombinant lineages. To date, XBB lineage is the most widespread recombinant lineage worldwide, with the recently named XBB.1.16 lineage causing a surge in the number of COVID-19 cases in India. Methodology: The present study involved retrieval of SARS-CoV-2 genome sequences from India (between 1st December 2022 and 8th April 2023) through GISAID; sequences were curated, followed by lineage and phylogenetic analysis. Demographic and clinical data from Maharashtra, India were collected telephonically, recorded in Microsoft (R) Excel, and analysed using IBM (R) SPSS statistics, version 29.0.0.0 (241). Results: A total of 2,944 sequences were downloaded from the GISAID database, of which 2,856 were included in the study following data curation. The sequences from India were dominated by the XBB.1.16* lineage (36.17%) followed by XBB.2.3* (12.11%) and XBB.1.5* (10.36%). Of the 2,856 cases, 693 were from Maharashtra; 386 of these were included in the clinical study. The clinical features of COVID-19 cases with XBB.1.16* infection (XBB.1.16* cases, 276 in number) showed that 92% of those had a symptomatic disease, with fever (67%), cough (42%), rhinorrhoea (33.7%), body ache (14.5%) and fatigue (14.1%) being the most common symptoms. Presence of comorbidity was found in 17.7% of the XBB.1.16* cases. Among the XBB.1.16* cases, 91.7% were vaccinated with at least one dose of vaccine against COVID-19. While 74.3% of XBB.1.16* cases were home-isolated; 25.7% needed hospitalization/institutional quarantine, of these, 33.8% needed oxygen therapy. Out of 276 XBB.1.16* cases, seven (2.5%) cases succumbed to the disease. Majority of XBB.1.16* cases who died belonged to an elderly age group (60 years and above), had underlying comorbid condition/s, and needed supplemental oxygen therapy. The clinical features of COVID-19 cases infected with other co-circulating Omicron variants were similar to XBB.1.16* cases. Conclusion: The study reveals that XBB.1.16* lineage has become the most predominant SARS-CoV-2 lineage in India. The study also shows that the clinical features and outcome of XBB.1.16* cases were similar to those of other co-circulating Omicron lineage infected cases in Maharashtra, India. Keywords: XBB.1.16, XBB.1.16.1, XBB.1.16*, XBB, Omicron variant, COVID-19, SARS-CoV-2, Clinical features
Subject(s)
Coinfection , Pain , Fever , Cough , COVID-19 , FatigueABSTRACT
Background: The SARS-CoV-2 has evolved to produce new variants causing successive waves of infection. Currently, six variants are being monitored by the World Health Organization that are replacing BA.5. These include BQ.1*, BA.5 with one or several of five mutations (R346X, K444X, V445X, N450D, N460X), BA.2.75*, XBB*, BA.4.6*, and BA.2.30.2*. BQ.1 and XBB variants are more immune evasive and have spread quickly throughout the world. With the concern of the potential severity of infections caused by these variants, the present study describes the clinical characteristics and outcomes of these major variants in Maharashtra. Material and Methods: A total of 1039 Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) positive SARS-CoV-2 samples, with a cycle threshold value (Ct) less than 25, were processed for SARS-CoV-2 whole genome sequencing between 10th July 2022 and 10th December 2022. All corresponding demographic and clinical data were recorded and analyzed using MicrosoftTM ExcelTM and Epi InfoTM. Results: Out of 1039 samples sequenced, 829 (79.79%) were assigned Pango lineages, of which BA.2.75 (67.31%) was the predominant Omicron variant, followed by the XBB* (17.13%), BA.2.38* (5.43%), BA.2.10* (3.62%) and BA.5* (3.50%). A total of 494 cases were contacted telephonically, of which 455 (92.11%) were symptomatic with mild symptoms. Fever (78.46%) was the most common symptom, followed by rhinorrhoea (46.37%), cough (42.20%), myalgia (19.56%) and fatigue (18.24%). Of the 494 cases, 379 (76.72%) cases recovered at home, and 115 (23.28%) were institutionally quarantined/ hospitalized. Among the home-isolated and hospitalized cases, 378 (99.74%) and 101 (87.83%) recovered with symptomatic treatment, whereas 01 (0.26%) and 14 (12.17%) succumbed to the disease, respectively. Of the 494 cases, 449 (90.89%) were vaccinated with at least one dose of the COVID-19 vaccine, 40 (8.10%) were unvaccinated, and for 05 (1.01%) cases, vaccine data was not available. Conclusion: The current study indicates that the XBB* variant is causing mild disease in India. However, as XBB* possess both immune-escape and infectivity-enhancing mutations, it has the potential to spread to other parts of the world rapidly.
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Fever , Myalgia , COVID-19 , FatigueABSTRACT
The modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Genomic surveillance has come to the forefront during the coronavirus disease 2019 (COVID-19) pandemic at both local and global scales to identify variants of concern. Tracking variants of concern (VOC) is integral to understanding the evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in space and time. Combining phylogenetics with epidemiological data like case incidence, spatial spread, and transmission dynamics generates actionable information. Here we discuss the genome surveillance done in Pune, India, through sequencing 10,496 samples from infected individuals and integrating them with multiple heterogeneous outbreak data. The rise and fall of VOCs along with shifting transmission dynamics in the time interval of December 2020 to March 2022 was identified. Population-based estimates of the proportion of circulating variants indicated the second and third peak of infection in Pune to be driven by VOCs Kappa (B.1.617.1), Delta (B.1.617.2), and Omicron (B.1.1.529) respectively. Integrating single nucleotide polymorphism changes across all sequenced genomes identified C (Cytosine) > T (Thymine) and G (Guanine) > T (Thymine) substitutions to dominate with higher rates of adaptive evolution in Spike (S), RNA-dependent RNA polymerase (RdRp), and Nucleocapsid (N) genes. Spike Protein mutational profiling during and pre-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified specific recombinant X lineages, XZ, XQ, and XM. BA.1 from Pune was found to be highly divergent by global sequence alignment and hierarchical clustering. Our ''band of five'' outbreak data analytics which includes the integration of five heterogeneous data types indicates that a strong surveillance system with comprehensive high-quality metadata was critical to understand the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. We anticipate the use of such integrated workflows to be critical for pandemic preparedness in the future.
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Coronavirus Infections , COVID-19ABSTRACT
BackgroundThe SARS-CoV-2 Omicron variants BA.2.74, BA.2.75 and BA.2.76 have appeared recently in India and have already spread to over 40 countries. They have acquired additional mutations in their spike protein compared to BA.2, branching away on the SARS-CoV-2 phylogenetic tree. These added mutations, over and above those of the parental BA.2 variant, have raised concerns about the impact on viral pathogenicity, transmissibility, and immune evasion properties of the new variants. Material and MethodsA total of 990 RT-PCR positive SARS-CoV-2 samples, with a cycle threshold value (Ct) less than 25, were processed for SARS-CoV-2 whole genome sequencing between 3rd June 2022 to 7th August 2022. All corresponding demographic and clinical data were recorded and analyzed using Microsoft(R) Excel. ResultsOut of 990 samples sequenced, BA.2.75 (23.03%) was the predominant Omicron sublineage, followed by BA.2.38 (21.01%), BA.5 (9.70%), BA.2 (9.09%), BA.2.74 (8.89%) and BA.2.76 (5.56%). A total of 228 cases of BA.2.74, BA.2.75 and BA.2.76 were contacted by telephone, of which 215 (94.30%) were symptomatic with mild symptoms, and 13 (5.70%) had no symptoms. Fever (82.02%) was the most common symptom, followed by cough (49.12%), cold (35.97%), fatigue (27.19%), headache (21.05%) and myalgia (20.61%). Of the 228 cases, 195 (85.53%) cases recovered at home, and 33 (14.47%) required institutional quarantine. Recovery with conservative treatment was observed in 92.98% of cases, while 4.83% required additional oxygen therapy. Only 03 (1.32%) cases had poor outcomes resulting in death, and the remaining 225 (98.68%) had a good outcome. Among the 228 cases, 219 (96.05%) cases were vaccinated with COVID-19 vaccine; of these 72.60% had received both doses, 26.03% had also received the precautionary booster dose, while 1.37% were incompletely vaccinated with a single dose of vaccine. ConclusionThe current study indicates that the three BA.2 sublineages are causing mild disease in India. However, BA.2.75 has key mutations that are notable for accelerated growth and transmission and require close and effective monitoring.
Subject(s)
Headache , Fever , COVID-19 , Myalgia , FatigueABSTRACT
Background: The SARS-CoV-2 Delta variant (B.1.617.2) was first detected in India in late 2020 and soon became the predominant lineage owing to its high transmissibility. Over time, the virus has acquired mutations and has evolved into many new sub-lineages. AY.4 is one such sub-lineage that grew in frequency globally. Therefore, we aimed to compare the severity of infection due to Delta sub-lineages to Delta infections in Pune, Maharashtra, India. Material and Methods: Whole-genome sequencing and analysis of 255 SARS-CoV-2 positive samples, collected between 1st August to 1st September 2021, by BJ Government Medical College, Pune, was carried out at the Indian Institute of Science Education and Research (IISER), Pune and the Council of Scientific and Industrial Research-Institute of Genomics and Integrative Biology (CSIR-IGIB), New Delhi. Individual-level data on these patients were collected from ICMR COVID-19 Data Portal. Additional information regarding the presence of any symptoms, comorbidities, hospitalization, international travel history within 14 days and vaccination status was collected by telephonic interview with each patient by the BJGMC Sequencing Team.
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India has become the third worst-hit nation by the COVID-19 pandemic caused by the SARS-CoV-2 virus. Here, we investigated the molecular, phylogenomic, and evolutionary dynamics of SARS-CoV-2 in western India, the most affected region of the country. A total of 90 genomes were sequenced. Four nucleotide variants, namely C241T, C3037T, C14408T (Pro4715Leu), and A23403G (Asp614Gly), located at 5UTR, Orf1a, Orf1b, and Spike protein regions of the genome, respectively, were predominant and ubiquitous (90%). Phylogenetic analysis of the genomes revealed four distinct clusters, formed owing to different variants. The major cluster (cluster 4) is distinguished by mutations C313T, C5700A, G28881A are unique patterns and observed in 45% of samples. We thus report a newly emerging pattern of linked mutations. The predominance of these linked mutations suggests that they are likely a part of the viral fitness landscape. A novel and distinct pattern of mutations in the viral strains of each of the districts was observed. The Satara district viral strains showed mutations primarily at the 3' end of the genome, while Nashik district viral strains displayed mutations at the 5' end of the genome. Characterization of Pune strains showed that a novel variant has overtaken the other strains. Examination of the frequency of three mutations i.e., C313T, C5700A, G28881A in symptomatic versus asymptomatic patients indicated an increased occurrence in symptomatic cases, which is more prominent in females. The age-wise specific pattern of mutation is observed. Mutations C18877T, G20326A, G24794T, G25563T, G26152T, and C26735T are found in more than 30% study samples in the age group of 10-25. Intriguingly, these mutations are not detected in the higher age range 61-80. These findings portray the prevalence of unique linked mutations in SARS-CoV-2 in western India and their prevalence in symptomatic patients. ImportanceElucidation of the SARS-CoV-2 mutational landscape within a specific geographical location, and its relationship with age and symptoms, is essential to understand its local transmission dynamics and control. Here we present the first comprehensive study on genome and mutation pattern analysis of SARS-CoV-2 from the western part of India, the worst affected region by the pandemic. Our analysis revealed three unique linked mutations, which are prevalent in most of the sequences studied. These may serve as a molecular marker to track the spread of this viral variant to different places.