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

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.

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Publication Details

Journal
Scientific Reports
Published
2025-05-29
DOI
https://doi.org/10.1038/s41598-025-04111-3
Citations
1
Primary Topic
SARS-CoV-2 and COVID-19 Research
Type
article
Field-Weighted Citation Impact
1.40

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article

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

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1 citations
Scientific Reports
SARS-CoV-2 and COVID-19 Research
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article

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

Lizhong Han, Min Zhou, Chenyue Tang, Xiaoqi Yu, Xinxin Li, Xinxin Zhang, Jialin Liu, Jian‐Qing Mi
article en
1 citations

Abstract

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.

Scientific ReportsVol. 15(1)
Shanghai Jiao Tong University (CN), Ruijin Hospital (CN), Shanghai Institute of Hematology (CN)
National Key Research and Development Program of China
Zero hunger
Openalex Percentile: Top 20%
SARS-CoV-2 and COVID-19 Research
1.40
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