What question did this study set out to answer?

To identify robust, reproducible molecular subtypes of bacterial sepsis across multiple transcriptomic datasets to address clinical heterogeneity.

March 14, 2018Critical Care Medicine

Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters

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To identify robust, reproducible molecular subtypes of bacterial sepsis across multiple transcriptomic datasets to address clinical heterogeneity.
Conducted unsupervised transcriptomic clustering across multiple independent gene expression datasets from patients with bacterial sepsis.
Identified three distinct, robust transcriptomic clusters that delineate the biological heterogeneity of bacterial sepsis.
Provided a molecular stratification framework to support precision medicine strategies and targeted immunomodulatory interventions.

Authors

TSTimothy E. SweeneyInfinera (United States)TATej D. AzadJohns Hopkins University MDMichele DonatoHackensack University Medical Center

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Implication

Transcriptomic analysis reveals three distinct molecular subtypes in bacterial sepsis, suggesting a framework for precision immunomodulatory therapies.

Cite This Study

Sweeney et al. (2018) studied this question.

synapsesocial.com/papers/69da10cd2a25b240b7a3e21a https://doi.org/10.1097/ccm.0000000000003084

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Implication

Transcriptomic analysis reveals three distinct molecular subtypes in bacterial sepsis, suggesting a framework for precision immunomodulatory therapies.

Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters

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Discussion

Implication

Cite This Study

Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters

Key Points

Discussion

Implication

Cite This Study

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