The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) resulted in a global emergence during the past three years since cases were first reported. The emergence of new variants will impose a risk of future surges (Wang et al., 2020; Zhu et al., 2020). Given the widespread and continuous evolution of SARS-CoV-2, numerous variants of concern (VOCs) have emerged and successively dominated multiple waves of the COVID-19 pandemic globally (Boehm et al., 2021). The new VOCs are often associated with increased transmissibility and/or immune evasion properties, which led to their rapid spread globally (Karim and Karim, 2022). Currently, the Omicron variant (B.1.1.529) is the predominant VOC around the world, since its emergence in South Africa in November 2021 (Petersen et al., 2022). From a genomic perspective, it shares several mutations with the previously identified VOCs, such as Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2), but it also harbors a large number of specific mutations (Mohapatra et al., 2023). Up to now, a series of Omicron sub-lineages including BA.1 (original Omicron), BA.2, BA.3, BA.4, BA.5, and XBB have emerged and then caused the waves of COVID-19 globally due to further neutralization escape (Ai et al., 2022; Khan et al., 2022; Planas et al., 2022; Qu et al., 2022; Mohapatra et al., 2023). This highlights the importance of continuous genomic monitoring of SARS-CoV-2 variants.

Since the outbreak of COVID-19 in late 2019, China has adhered to policies of zero-COVID for almost three years with strictly enforced lockdowns and other restrictive measures, including social distancing, school closure, mask use, and case isolation (Lai et al., 2020; Liu et al., 2022). Given the attenuated pathogenicity of omicron subvariants and increasing vaccination coverage, China lifted the zero-COVID strategies, notably by announcing the ‘10 measures’ about the optimization of COVID-19 rules on 7 December 2022 (Xinhua, 2022). After that, China experiences a nationwide outbreak of COVID-19. Leung et al. (2023) estimated that the cumulative infection attack rate in Beijing was 75.7% (95% credible interval (CrI): 60.7–84.4) on 22 December 2022 and 92.3% (95% CrI: 91.4–93.1) on 31 January 2023. A recent study by Liang et al. (2023) showed that the cumulative SARS-CoV-2 infection rate rose rapidly to 70% within three weeks after the ending of the zero-COVID policy in Macao. A study conducted in Guangzhou also revealed that the infection attack ratio reached to 80.7% (95% CrI: 72.2–86.8) at 30 days after easing the zero-COVID policy (Huang et al., 2023). Such an unprecedented epidemic raised concerns about specific and real-time data on the viral genetic sequencing, monitoring of variants, and disease impact (World Health Organization, 2022).

Shanghai, with a population of 25 million, is a leading economic center in China. The prevalence of SARS-CoV-2 variants in Shanghai can be considered a snapshot of China. Herein, we report the clinical and genetic characteristics of SARS-CoV-2 infections among children with COVID-19 in Shanghai after ending the zero-COVID policy in December 2022, based on viral genetic sequencing and clinical data.

In this study, we have reported the first comprehensive clinical and viral genomic analysis of SARS-CoV-2 infections among children hospitalized with COVID-19 in Shanghai after ending the zero-COVID policy. Whole genome sequencing of samples obtained from the enrolled 64 pediatric patients revealed that all cases clustered into the Omicron BA.5.2* lineage, with the dominant omicron sub-lineages of BA.5.2.48 and BF.7.14. This result was in line with our previous study based on 8,254 SARS-CoV-2 complete genomes available on the GISAID database from the Chinese mainland during December 2022 and January 2023, which indicated that the genomes corresponded to 88 Pango-nomenclature-system-named subvariants, with the dominant lineages of BA.5.2.48 (4,881/8254, 59.1%) and BF.7.14 (2,223/8254, 26.9%), and the proportion of these dominant lineages were not significant changed over the two months of outbreak (Liu and Xu, 2023). In addition, BA.5.2.48 and BF.7.14 were also found to be the dominant lineages among SARS-CoV-2 positive passengers on flights from China to Italy in late December 2022 (Novazzi et al., 2023). However, the lineages found to be dominant internationally during the same period, such as BQ.1, BQ.1.1, and XBB.1.5 were quickly cleared and did not prevail in China (Liu and Xu, 2023). Taken together, all these results demonstrated that the emerging BA.5.2.48 and BF.7.14 were the absolutely dominant drivers of the current COVID-19 outbreak after ending the zero-COVID policy, which could be attributed to the high fitness of lineages or a random founder effect in China.

Fever and cough were the most common symptoms among children with COVID-19 in this study. This result was consistent with the earlier community outbreak in Shanghai driven by BA.2.2.1 sub-lineage in spring 2022 (Ao et al., 2022; Ling et al., 2022; Shen et al., 2023). However, the demographic characteristics, clinical symptoms, laboratory findings, and outcomes might vary between different SARS-CoV-2 variants in children hospitalized with COVID-19 (Boncuoglu et al., 2022; Quintero et al., 2022; Tagarro et al., 2022; Sahin et al., 2023). Consequently, we further compared the clinical features of children with BA.5.2.48 and BF.7.14 infections. We found that the BA5.2.48 infections were more frequently observed to experience vomiting/diarrhea and less frequently present cough compared to the BF.7.14 infections among patients without comorbidities. To figure out susceptible mutations related to the variation of symptoms, we assessed the associations of the mutations with the symptoms of vomiting/diarrhea and cough. We found that the frequency of the characteristic mutation nsp12:L247F, S:C1243F, and ORF7a:H47Y was significantly varied among those with cough or vomiting/diarrhea than without. These observations suggest that these three characteristic mutations might contribute to the variation of symptoms between children infected with BF.7.14 and BA.5.2.48 by affecting the tissue tropism of the variants or other mechanisms. However, possibly arose bias due to the limited sample size in this study. Besides, the results might also be affected by the demographic characteristics, especially age. Thus, the interpretation of the results must be cautious and might not precisely reflect the broader population. Given the rapid evolution of SARS-CoV-2, further studies are still needed to elucidate the clinical features and severity of different variants with specific mutations.

Adaptive mutations in the SARS-CoV-2 genome could alter its pathogenic potential, and at the same time would increase the infectivity and immune escape capacity. Single amino acid changes are worth monitoring because they can be phenotypically relevant. Perhaps one of the best exemplars of the impacts of amino acid changes in the SARS-CoV-2 is the D614G mutation in S protein. D614G substitution was first identified in early 2020 and rapidly spread throughout the global population by increasing the infectivity and stability of virion (Korber et al., 2020; Zhang et al., 2020; Plante et al., 2021). With this background, we further investigated the unique amino acid changes in the BA.5.2.48 and BF.7.14 sub-lineages, and predicted the effects of these mutations on the stability and function of viral proteins. Stability is a parameter which is crucial to judge the functional and structural activity of a protein. Protein stability dictates the conformational structure of the protein, thereby determining its function. Any change in protein stability may cause misfolding, degradation or aberrant conglomeration of proteins. Understanding the stability changes in SARS-CoV-2 proteins is essential for predicting virus infectivity. Changes in Gibbs free energy of unfolding (ΔΔG) between the wild-type and mutant proteins could predict the effects of mutations on the stability of protein structure (Pan et al., 2022). In order to ascertain the significance of mutations on protein function, we analyzed the pathogenicity of the mutations as deleterious or neutral. It is important to note that in case of protein, damaging mostly defines instability. Generally, this is used for human proteins. As a consequence, if the human protein is damaging in nature because of mutations, then the human protein–protein interactions may occur with high or low binding affinity. Now in case of virus, similar consequences may happen, which means if the virus protein is damaged because of mutations, it may interact with human proteins with similar binding affinity. As a result, the virus may acquire characteristics like transmissibility, escaping antibodies. For example, the D614G was predicted to be deleterious and instable using I-mutant and PredictSNP servers. Thus, the basic premise for the study was that mutations will be contributing to the viral evolution only if they are deleterious and neutral mutations would not be affecting the protein function (Laskar and Ali, 2021).

We found 5 high-frequency amino acid changes (N: Q241K, nsp2: V94L, nsp12: L247F, S: C1243F, ORF7a: H47Y) in the BA.5.2.48 and BF.7.14 sub-lineages. Among these mutations, the C1243F mutation in S protein, L247F mutation in nsp12, and H47Y mutation in ORF7a protein were predicted to have a deleterious effect on the protein function. S protein decorates the surface of coronavirus and plays a critical role in viral entry (Gallagher and Buchmeier, 2001). It comprises two functional subunits responsible for binding to the host cell receptor (S1 subunit) and membrane fusion (S2 subunit) (Walls et al., 2020). In the S1 subunit, there is an N-terminal domain (14–305 residues) and a receptor-binding domain (RBD, 319–541 residues); the fusion peptide (FP) (788–806 residues), heptapeptide repeat sequence 1 (HR1) (912–984 residues), HR2 (1,163–1,213 residues), transmembrane domain (1,213–1,237 residues), and intracellular domain (1,237–1,273 residues) comprise the S2 subunit (Huang et al., 2020). The C1243F mutation is located in the intracellular domain of S2 subunit. The mutations in the intracellular domain are unlikely to drive immune evasion. However, the mutations in this domain may affect the S protein expression at the cell surface and syncytia formation by mediating intracellular trafficking and membrane location of S protein (Cattin-Ortola et al., 2021; Li et al., 2022).

nsp12, also named RNA-dependent RNA polymerase (RdRp), catalyzes the synthesis of viral RNA and thus plays a central role in the replication and transcription cycle, with the assistance of nsp7 and nsp8 as cofactors. The structure of the nsp12 contains a right-hand RdRp domain (367–920 residues) and a nidovirus RdRp-associated nucleotidyltransferase domain (NiRAN, 60–249 residues) (Gao et al., 2020). The L247F mutation is located in the NiRAN domain, which lies at the N terminal end of the RdRp. Although the NiRAN domain is essential for viral propagation, its functions during the viral life cycle remain unclear. A recent study revealed that the NiRAN domain catalyzes the covalent link of RNA 5′ end to the first residue of nsp9, thus being an intermediate to form cap core (GpppA) with GTP catalyzed again by NiRAN (Yan et al., 2022). Therefore, the L247F mutation in nsp12 may affect the SARS-CoV-2 replication in the host cells.

ORF7a protein is a type-I transmembrane protein, consisting of an N-terminal signaling region (1–15 residues), an immunoglobulin-like ectodomain (16–96 residues), a hydrophobic transmembrane domain (97–116 residues), and a typical endoplasmic reticulum retention motif (117–121 residues) (Zhou et al., 2021). The H47Y mutation is located in the ectodomain. A recent study suggested that the Immunoglobulin-like fold ectodomain of the ORF7a interacts with high efficiency to the CD14+ monocytes in human peripheral blood, and ORF7a may also suppress the antigen-presenting ability of these monocytes and trigger the significant upregulation of multiple proinflammatory cytokines (Zhou et al., 2021). Further in vitro and in vivo studies are needed to verify the role of ORF7a: H47Y mutation in viral fitness.

Our results revealed that the current large-scale COVID-19 outbreak in Shanghai after ending the zero-COVID policy was driven by the emerging BA.5.2.48 and BF.7.14 variants with unique deleterious mutations. In addition, this study described the clinical characteristics of pediatric cases infected with BA.5.2.48 and BF.7.14. Continuous genomic monitoring and clinical manifestation assessments of the emerging variants will be crucial for countering the ongoing COVID-19 pandemic.

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: https://gisaid.org, EPI_ISL_17371203 to EPI_ISL_17371266.

The studies involving humans were approved by Children’s Hospital of Fudan University. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required from the participants or the participants’ legal guardians/next of kin in accordance with the national legislation and institutional requirements.

PL: Conceptualization, Formal analysis, Methodology, Writing – original draft, Writing – review & editing. JC: Conceptualization, Investigation, Resources, Writing – review & editing. HT: Data curation, Investigation, Writing – review & editing. JL: Investigation, Validation, Writing – review & editing. LL: Resources, Validation, Writing – review & editing. MX: Investigation, Resources, Writing – review & editing. XZ: Investigation, Resources, Writing – review & editing. XF: Investigation, Resources, Writing – review & editing. XW: Methodology, Resources, Writing – review & editing. HZ: Investigation, Resources, Writing – review & editing. RJ: Investigation, Resources, Writing – review & editing. YG: Investigation, Resources, Writing – review & editing. YZ: Investigation, Resources, Writing – review & editing. MZ: Conceptualization, Project administration, Supervision, Writing – review & editing. JX: Conceptualization, Project administration, Supervision, Writing – review & editing.