Combining Single-Cell and Bulk Transcriptomic Analysis with Machine Learning Reveals LDHA as a Lactate-Associated Biomarker for Diagnosis and Prognosis in Sepsis - Takeaways - MDSpire

Combining Single-Cell and Bulk Transcriptomic Analysis with Machine Learning Reveals LDHA as a Lactate-Associated Biomarker for Diagnosis and Prognosis in Sepsis

  • By

  • Zhiying Lin

  • Hanping Shi

  • Xiaohong Chen

  • Chunli Yang

  • February 24, 2026

  • 0 min

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  • 1

    Sepsis is a leading cause of mortality in ICUs, characterized by a dysregulated host response to infection.

  • 2

    Lactate is recognized as an active signaling metabolite involved in immune regulation and is linked to sepsis severity.

  • 3

    The study integrates single-cell RNA sequencing and bulk transcriptomic data to identify lactate-associated immune cell populations.

  • 4

    LDHA was identified as a potential biomarker for diagnosing and predicting outcomes in sepsis patients.

  • 5

    Machine learning approaches were utilized to construct a lactate-related diagnostic model for sepsis.

Original Source(s)

Combining Single-Cell and Bulk Transcriptomic Analysis with Machine Learning Reveals LDHA as a Lactate-Associated Biomarker for Diagnosis and Prognosis in Sepsis

  • by Zhiying Lin, Hanping Shi, Xiaohong Chen, Chunli Yang

  • February 24, 2026

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