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<p>Metagenomic next-generation sequencing (mNGS) is widely used to diagnose complex infections in hospitalized patients, particularly those associated with COVID-19 which has garnered significant concern over the past five years. To investigate the molecular epidemic of the viral variant and the potential co-infection pathogens, we conducted retrospective mNGS analysis of 254 SARS-CoV-2-positive specimens collected from 200 hospitalized patients between March and September 2023. Phylogenetic analysis of the identified Omicron subvariants showed minimal evolutionary divergence, with no association between sub-lineages and pneumonia severity. Notably, mNGS demonstrated enhanced detection of polymicrobial coinfections, identifying bacterial, fungal, and viral co-pathogens in 92.5% (185/200) of cases. Pneumonia severity was associated with advanced age (proportion of elderly patients: 61.1 vs 78.3%; p = 0.032) and comorbid conditions, particularly diabetes mellitus (OR 2.03, 95% CI 1.03–4.02, p = 0.041), but showed no correlation with SARS-CoV-2 sub-lineages or coinfecting pathogens. While mNGS enhances coinfection diagnosis, COVID-19 outcomes are predominantly driven by host factors rather than Omicron subvariant evolution. Prioritized monitoring of elderly and comorbid individuals remained critical for severe pneumonia management.</p>

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Characteristics of SARS-CoV-2 variants and potential co-infected pathogens in hospitalized patients based on metagenomic next-generation sequencing

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月29日

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  • Xinxin Li,
  • Chenyue Tang,
  • Min Zhou,
  • Jianqing Mi,
  • Jialin Liu,
  • Lizhong Han,
  • Xiaoqi Yu,
  • Xinxin Zhang

摘要

Metagenomic next-generation sequencing (mNGS) is widely used to diagnose complex infections in hospitalized patients, particularly those associated with COVID-19 which has garnered significant concern over the past five years. To investigate the molecular epidemic of the viral variant and the potential co-infection pathogens, we conducted retrospective mNGS analysis of 254 SARS-CoV-2-positive specimens collected from 200 hospitalized patients between March and September 2023. Phylogenetic analysis of the identified Omicron subvariants showed minimal evolutionary divergence, with no association between sub-lineages and pneumonia severity. Notably, mNGS demonstrated enhanced detection of polymicrobial coinfections, identifying bacterial, fungal, and viral co-pathogens in 92.5% (185/200) of cases. Pneumonia severity was associated with advanced age (proportion of elderly patients: 61.1 vs 78.3%; p = 0.032) and comorbid conditions, particularly diabetes mellitus (OR 2.03, 95% CI 1.03–4.02, p = 0.041), but showed no correlation with SARS-CoV-2 sub-lineages or coinfecting pathogens. While mNGS enhances coinfection diagnosis, COVID-19 outcomes are predominantly driven by host factors rather than Omicron subvariant evolution. Prioritized monitoring of elderly and comorbid individuals remained critical for severe pneumonia management.