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. 2024 Aug 12;19(12):1071-1080.
doi: 10.1080/17460913.2024.2357994. Epub 2024 Jun 20.

Analysis of pulmonary microecology and clinical characteristics of patients carrying human herpesvirus

Jing Luo  1 , Rui Xie  1 , Chongxi Bao  1 , Jinyan Lin  1 , Yang Xu  1 , Xuexin Yan  1 , Zhen Yang  1 , Li Feng  1 , Jianing Wu  1 , Dan Chen  1 , Zaiqing He  1 , Jinliang Kong  1
Affiliations

Analysis of pulmonary microecology and clinical characteristics of patients carrying human herpesvirus

Jing Luo et al. Future Microbiol. .

Abstract

Aim: To investigate the impact of human herpes virus (HHV) carriage on lung microbiota, and its correlation with clinical features and laboratory indicators in patients.Methods: Retrospective analysis was conducted on 30 outpatient lung infection cases, which were divided into HHV (n = 15) and non-HHV (n = 15) groups. mNGS detected microbial composition. Microbial diversity and abundance were tested using Shannon and Chao1 indices. Their relationship with laboratory indicators were explored.Results: Significant differences in microbial abundance and distribution were found between two groups (p < 0.05). Moreover, HHV group showed negative correlations (p < 0.05) between Prevotella, Porphyromonas, Streptococcus and basophil/eosinophil percentages.Conclusion: HHV carriage impacts lung microbiota, emphasizing the need for clinicians to pay attention to HHV reactivation in outpatient lung infection patients.

Keywords: human herpesvirus; lung microbiome; mNGS; viral reactivation.

Plain language summary

This study looked at how a common virus called human herpesvirus (HHV) affects the bacteria in our lungs. We wanted to see if HHV is linked to how sick we feel and what tests show. We split 30 people who had lung infections into two groups – 15 with HHV and 15 without – and checked how sick they felt, did some tests, and looked at the types of bacteria in their lungs. Both groups felt similarly sick and got better with medicine, but people with HHV had fewer of a certain type of blood cell. People with and without HHV also had different types of bacteria in their lungs. This study helps us understand why people get sick with lung infections and how to make them better. It might also help doctors decide how to treat people with lung infections.

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Conflict of interest statement

The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Figures

Figure 1.
Figure 1.
Comparison of α-diversity of microbial communities between the HHV group and the non-HHV group (a & b). No significant difference was observed in Shannon index (A) and Chao1 index (B) between the two groups (p > 0.05).
Figure 2.
Figure 2.
The β-diversity analysis of microbial communities in HHV and non-HHV groups. (A) PCoA scatter plot based on Bray-Curtis distance; (B) PCoA scatter plot based on Jaccard-Curtis distance. The abscissa represents one principal component, the ordinate represents another principal component, and the percentage represents the contribution of the principal component to the sample difference. Each point in the graph represents a sample, and the circle represents the confidence interval.
Figure 3.
Figure 3.
Signature biomarkers at different classification levels in the two groups. (A) Histogram of two groups of significantly different species; (B) cladogram of two groups of significantly different species.
Figure 4.
Figure 4.
Species with significant differences in the relative abundance of at the phylum level. (A) Genus level, and (B) between the HHV and non-HHV groups. *p < 0.05; **p < 0.01; ***p < 0.001.
Figure 5.
Figure 5.
Spearman correlation analysis between laboratory examination results and signature biomarkers at the genus level in the HHV group and non-HHV group patients. *p < 0.05. Bas %: Percentage of basophils; EOS %: Percentage of eosinophils; Lym %: Percentage of lymphocytes; Mon %: Percentage of monocytes; Neut %: Percentage of neutrophils; PLT: Platelet count; RBC: Red blood cell count; WBC: White blood cell count.
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