Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2026
Genomic surveillance and molecular evolution of SARS-CoV-2 in Zhangzhou, China (2022-2025).
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Xie Wenjie, Chen Xiaowan, Su Ting, Lin Shule, He Zhibin, Zhang Tianlin
Аннотация
BACKGROUND: SARS-CoV-2 evolution has shifted towards convergent variants such as the NB.1.8.1 and PQ series. However, the correlation between these genomic shifts and clinical phenotypes is unclear. We aimed to delineate the viral evolutionary trajectory, relative replacement dynamics, and clinical Ct-value correlations in Zhangzhou, China.
METHODS: We retrospectively analysed 593 SARS-CoV-2 genomes collected between 2022 and 2025. High-quality sequences were typed using the PANGOLIN software. Non-parametric tests and Spearman's correlation were employed to assess the relationships between dominant lineages, patient age, and diagnostic N-gene cycle threshold (Ct) values).
RESULTS: Genomic surveillance revealed dynamic lineage replacements from Omicron BA.5.2/BF.7 to XBB, followed by XDV.1, and culminating in the dominance of the NB.1.8.1 and PQ lineages. Clinical N-gene Ct-value distributions were comparable across major lineages (P > 0.05). Patient age was not associated with N-gene Ct values (Spearman r = 0.01, P = 0.842).
CONCLUSION: The sequential replacement of SARS-CoV-2 lineages in Zhangzhou occurred without detectable shifts in clinical N-gene Ct-value distributions or age-related infection patterns. These findings support sustained regional genomic surveillance but should not be interpreted as direct evidence of unchanged intrinsic viral fitness or transmissibility.
METHODS: We retrospectively analysed 593 SARS-CoV-2 genomes collected between 2022 and 2025. High-quality sequences were typed using the PANGOLIN software. Non-parametric tests and Spearman's correlation were employed to assess the relationships between dominant lineages, patient age, and diagnostic N-gene cycle threshold (Ct) values).
RESULTS: Genomic surveillance revealed dynamic lineage replacements from Omicron BA.5.2/BF.7 to XBB, followed by XDV.1, and culminating in the dominance of the NB.1.8.1 and PQ lineages. Clinical N-gene Ct-value distributions were comparable across major lineages (P > 0.05). Patient age was not associated with N-gene Ct values (Spearman r = 0.01, P = 0.842).
CONCLUSION: The sequential replacement of SARS-CoV-2 lineages in Zhangzhou occurred without detectable shifts in clinical N-gene Ct-value distributions or age-related infection patterns. These findings support sustained regional genomic surveillance but should not be interpreted as direct evidence of unchanged intrinsic viral fitness or transmissibility.