P-677. Differentially Expressed Genes in Patients with Legionella and Streptococcus Pneumonia

TL;DR

This study identifies distinct gene expression patterns in blood from patients with Legionella and Streptococcus pneumonia, which could improve diagnostic methods for pneumonia.

Contribution

The study reveals differentially expressed genes that distinguish Legionella from Streptococcus pneumonia, offering insights for host-response diagnostics.

Findings

2408 differentially expressed genes were identified, with 1031 upregulated in Legionella patients.

Legionella-related genes were linked to interferon activation and intracellular processes, while Streptococcus genes were tied to inflammation and cell signaling.

Transcriptional profiles of Legionella resembled those of influenza, suggesting shared immune responses.

Abstract

Streptococcus pneumoniae (SP) and Legionella pneumophila (LP) are important etiological pathogens of community-acquired pneumonia (CAP). Empiric treatment of CAP targeting typical organisms may be associated with worse outcomes in patients with Legionnaires' disease. We questioned whether differentially expressed genes (DEGs) in whole blood could discriminate between patients with streptococcal and legionella infections, which might impact current host-response diagnostics under development.Figure 1.Volcano Plot of DEGs Streptococcus pneumoniae vs Legionella pneumophila.*DEGs with positive Log2 fold change marked in red illustrate genes relatively upregulated in patients with Streptococcus vs Legionella. DEGs with negative Log2 fold change marked in blue illustrate genes relatively upregulated in patients with Legionella vs Streptococcus.Figure 2.The Heatmap of Sample-to-Sample Distances.*The heatmap was constructed using Euclidian distance metrics. Darker colors indicate lower distances and higher similarity between samples. The dendrograms on the top and left sides of the heatmap illustrate the hierarchical clustering of the samples.

Volcano Plot of DEGs Streptococcus pneumoniae vs Legionella pneumophila.

*DEGs with positive Log2 fold change marked in red illustrate genes relatively upregulated in patients with Streptococcus vs Legionella. DEGs with negative Log2 fold change marked in blue illustrate genes relatively upregulated in patients with Legionella vs Streptococcus.

The Heatmap of Sample-to-Sample Distances.

*The heatmap was constructed using Euclidian distance metrics. Darker colors indicate lower distances and higher similarity between samples. The dendrograms on the top and left sides of the heatmap illustrate the hierarchical clustering of the samples.

This study used data prospectively collected from patients admitted with pneumonia from 2019 to 2021. Twenty patients with confirmed LP and 13 with SP had whole blood RNA-sequencing. DEGs between the samples were analyzed using RStudio packages "BiocManager", “dplyr”, “DESeq2”, “ggplot”, and “pheatmap”. DEGs were defined as those with an adjusted p-value cutoff of < 0.05. Functional enrichment analysis was conducted using the ToppFun tool to identify significant biological processes and pathways in genes.

A total of 2408 DEGs were identified, with 1031 genes upregulated in patients with LP (Figure 1). Genes activated in patients with LP were associated with an interferon activation pathway. The transcriptional profile reflected cellular processes related to cell membranes, vacuoles, and cytoplasmic transport. In patients with SP, the prostaglandin synthesis pathway was activated. Upregulated biological and cellular processes included inflammatory response, cell migration, cell-cell signaling, and kinase activity. Notably, the transcriptional signatures of patients with LP resembled influenza infection. The heatmap of sample-to-sample distances showed that most samples with the same pathogen clustered together (Figure 2). Confounding factors may have included underlying conditions and treatments such as steroid administration.

Patients with LP and SP pneumonia have different gene expression patterns in whole blood. Differences in other intracellular pathogens, such as Mycoplasma pneumoniae, should be explored as they may affect the accuracy of host-related diagnostics.

Edward E. Walsh, MD, Merck, Sharpe and Dohme: Advisor/Consultant|Merck, Sharpe and Dohme: Grant/Research Support|Moderna: Advisor/Consultant|Moderna: Grant/Research Support|Pfizer: Advisor/Consultant|Pfizer: Grant/Research Support|Sanofi: Advisor/Consultant|Sanofi: Honoraria Ann R. Falsey, MD, ADMA Biologics: Advisor/Consultant|ADMA Biologics: Honoraria|AstraZeneca: Advisor/Consultant|AstraZeneca: Grant/Research Support|AstraZeneca: Honoraria|CynaVac: Grant/Research Support|GSK: Advisor/Consultant|GSK: Honoraria|Merck: Advisor/Consultant|Merck: Honoraria|Moderna, Inc.: Advisor/Consultant|Moderna, Inc.: Grant/Research Support|Moderna, Inc.: Honoraria|Pfizer: Grant/Research Support|Sanofi Pasteur: Advisor/Consultant|Sanofi Pasteur: Honoraria Angela R. Branche, MD, Cyanvac: Grant/Research Support|Merck: Advisor/Consultant|Moderna: Advisor/Consultant|Moderna: Grant/Research Support|Pfizer: Grant/Research Support|Sanofi: Advisor/Consultant

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