Clinical characteristics and novel mutations of omicron subvariant XBB in Tamil Nadu, India – a cohort study

Selvavinayagam, Sivaprakasam T.; Karishma, Sree J.; Hemashree, Kannan; Yong, Yean K.; Suvaithenamudhan, Suvaiyarasan; Rajeshkumar, Manivannan; Aswathy, Bijulal; Kalaivani, Vasudevan; Priyanka, Jayapal; Kumaresan, Anandhazhvar; Kannan, Meganathan; Gopalan, Natarajan; Chandramathi, Samudi; Vignesh, Ramachandran; Murugesan, Amudhan; Anshad, Abdul R.; Ganesh, Balasubramanian; Joseph, Narcisse; Babu, Hemalatha; Govindaraj, Sakthivel; Larsson, Marie; Kandasamy, Shree L.; Palani, Sampath; Singh, Kamalendra; Byrareddy, Siddappa N.; Velu, Vijayakumar; Shankar, Esaki M.; Raju, Sivadoss

doi:10.1016/j.lansea.2023.100272

Cited by 12 publications

(11 citation statements)

References 25 publications

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“…These findings are similar to those from Maharashtra where co-morbidities were reported in 17.7% of cases, of which hypertension was the most common (47.9%), followed by diabetes mellitus (39.6%) and asthma (12.5%) [13]. Study from Chennai, Tamil Nadu reported diabetes (38%), hypertension (28%) and cardiovascular disease (13%) to be the significant co-morbidities present in patients infected with XBB variant [16]. Among XBB.1.16 cases, maximum number of positive cases were from Jaipur district (796/1413, 56.33%) followed by other districts which might be attributed to high positivity in Jaipur and timely transport of positive samples to sequencing laboratory.…”

Section: Discussionsupporting

confidence: 58%

Genomic surveillance of SARS-CoV-2 and emergence of XBB.1.16 variant in Rajasthan

Sharma,

Gautam,

Sharma

et al. 2024

Preprint

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Background & objectives: Genomic surveillance of positive SARS-CoV-2 samples is important to monitor the genetic changes occurring in virus, this was enhanced after the WHO designation of XBB.1.16 as a variant under monitoring in March 2023. From 5th February till 6th May 2023 all positive SARS-CoV-2 samples were monitored for genetic changes. Methods: A total of 1757 samples having Ct value <25 (for E and ORF gene) from different districts of Rajasthan were processed for Next Generation sequencing (NGS). The FASTA files obtained on sequencing were used for lineage determination using Nextclade and phylogenetic tree construction. Results and discussion: Sequencing and lineage identification was done in 1624 samples. XBB.1.16 was the predominant lineage in 1413(87.0%) cases while rest was other XBB (207, 12.74%) and other lineages (4, 0.2%). Of the 1413 XBB.1.16 cases, 57.47% were males and 42.53% were females. Majority (66.53%) belonged to 19-59 year age. 84.15% of XBB.1.16 cases were infected for the first time. Hospitalization was required in only 2.2% cases and death was reported in 5 (0.35%) patients. Most of the cases were symptomatic and the commonest symptoms were fever, cough and rhinorrhoea. Co-morbidities were present in 414 (29.3%) cases. Enhanced genomic surveillance helped to rapidly identify the spread of XBB variant in Rajasthan. This in turn helped to take control measures to prevent spread of virus and estimate public health risks of the new variant relative to the previously circulating lineages. XBB variant was found to spread rapidly but produced milder disease.

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Section: Discussionsupporting

confidence: 58%

Genomic surveillance of SARS-CoV-2 and emergence of XBB.1.16 variant in Rajasthan

Sharma,

Gautam,

Sharma

et al. 2024

Preprint

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“…Similarly, by comparing the JN.1 with XBB, we show two dynamic mutations - A83V to A83F, V90L to V90Y in the NTD domain and T346R to T346I in the RBD domain. This indicates that these mutations would possibly contribute to the ongoing evolution of viral lineages, and their overall fitness and adaptability [34] Our study identified a dynamic mutation P85K that has gradually evolved from the Wuhan-Hu-1 and BA.2 strain and reshaped into a unique mutation in comparison with XBB [15]. This indicates the genetic drift within the SARS-CoV-2 infection particularly in the JN.1 variant.…”

Section: Discussionmentioning

confidence: 93%

“…Here, the study describes the detection of SARS-CoV-2 Omicron subvariant JN.1 during November and December-2023, as a part of the state public health genomic surveillance activity which has been happening since September 2021. In our recent study, we showed the mutational patterns of Omicron variants and the emergence of the XBB as a dominant variant in January 2023 replacing BA.2 which continued till October 2023 [15, 16]. In September 2023, JN.1 was first identified in the United States [17] followingly many countries like Canada, France, Singapore and the United Kingdom reported the emergence of JN.1 [18–21].…”

Section: Discussionmentioning

confidence: 99%

Emergence of SARS-CoV-2 Omicron Variant JN.1 in Tamil Nadu, India - Clinical Characteristics and Novel Mutations

Selvavinayagam,

Sankar,

Yong

et al. 2024

Preprint

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In December 2023, we observed a notable shift in the COVID-19 landscape, when the JN.1 emerged as a predominant SARS-CoV-2 variant with a 95% incidence. We characterized the clinical profile, and genetic changes in JN.1, an emerging SARS-CoV-2 variant of interest. Whole genome sequencing was performed on SARS-CoV-2 positive samples, followed by sequence analysis. Mutations within the spike protein sequences were analyzed and compared with the previous lineages and sublineages of SARS-CoV-2, to identify the potential impact of these unique mutations on protein structure and possible functionality. Several unique and dynamic mutations were identified herein. Our data provides key insights into the emergence of newer variants of SARS-CoV-2 in our region and highlights the need for robust and sustained genomic surveillance of SARS-CoV-2.

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“…XBB, the recombinant variant of BA.2.10.1 and BA.2.75 sublineages containing ∼43 spike mutations, and its subvariants, namely XBB.1.5, have dominated infections since late 2022 and resulted in a shift to a new monovalent booster vaccine in September 2023 (CDC, Selvavinayagam et al., Wang et al, 2023; WHO 2022). We longitudinally sampled individuals who were exposed to XBB.1.5 via the monovalent mRNA-LNP booster (n = 12) or by XBB-subvariant breakthrough infections (symptom onset between 1/2/2022 and 10/1/2022, n = 10) and assessed the specificity and functionality of antibody and B cell responses ( Figure 5A ).…”

Section: Resultsmentioning

confidence: 99%

Immunological imprinting shapes the specificity of human antibody responses against SARS-CoV-2 variants

Johnston,

Li,

Painter

et al. 2024

Preprint

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SummaryThe spike glycoprotein of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) continues to accumulate substitutions, leading to breakthrough infections of vaccinated individuals and prompting the development of updated booster vaccines. Here, we determined the specificity and functionality of antibody and B cell responses following exposure to BA.5 and XBB variants in individuals who received ancestral SARS-CoV-2 mRNA vaccines. BA.5 exposures elicited antibody responses that primarily targeted epitopes conserved between the BA.5 and ancestral spike, with poor reactivity to the XBB.1.5 variant. XBB exposures also elicited antibody responses that targeted epitopes conserved between the XBB.1.5 and ancestral spike. However, unlike BA.5, a single XBB exposure elicited low levels of XBB.1.5-specific antibodies and B cells in some individuals. Pre-existing cross-reactive B cells and antibodies were correlated with stronger overall responses to XBB but weaker XBB-specific responses, suggesting that baseline immunity influences the activation of variant-specific SARS-CoV-2 responses.HighlightsVariant breakthrough infections boost ancestral cross-reactive antibodies and B cellsFirst and second BA.5 exposures fail to elicit variant-specific antibodies and B cellsXBB infections and monovalent vaccinations elicit XBB.1.5-specific responses in some individualsXBB.1.5-specific responses correlate with low levels of pre-existing humoral immunity

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Clinical characteristics and novel mutations of omicron subvariant XBB in Tamil Nadu, India – a cohort study

Cited by 12 publications

References 25 publications

Genomic surveillance of SARS-CoV-2 and emergence of XBB.1.16 variant in Rajasthan

Genomic surveillance of SARS-CoV-2 and emergence of XBB.1.16 variant in Rajasthan

Emergence of SARS-CoV-2 Omicron Variant JN.1 in Tamil Nadu, India - Clinical Characteristics and Novel Mutations

Immunological imprinting shapes the specificity of human antibody responses against SARS-CoV-2 variants

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