Longitudinal blood transcriptome profiling reveals immune dynamics in sepsis and septic shock
This study characterized longitudinal whole-blood transcriptomic dynamics in sepsis and septic shock patients using serial   RNA sequencing. Eleven adult patients (5 sepsis, 6 septic shock) and 4 healthy controls were enrolled at the Korea University    Ansan Hospital (IRB No. 2024AS0030). Whole blood was collected using PAXgene tubes at hospital day 1 (HD#1), day 3 (HD#3),   and day 7 (HD#7). Total RNA was extracted, ribosomal and globin RNA were depleted using TruSeq Stranded Total RNA Library   Prep with Globin kit, and paired-end sequencing (2×100 bp) was performed on an Illumina NovaSeq X Plus platform.   Transcriptomic analysis identified a neutrophil-driven gene expression signature reflecting early hyperinflammatory   responses, tracking disease severity and temporal progression, and predicting 28-day mortality across multiple external   cohorts. This dataset comprises 35 longitudinal blood transcriptome samples with 70 paired-end FASTQ files. This work was   supported by the National Research Foundation of Korea (NRF) grants RS-2025-00563782 and RS-2023-00220894.
This study characterized longitudinal whole-blood transcriptomic dynamics in sepsis and septic shock patients using serial   RNA sequencing. Eleven adult patients (5 sepsis, 6 septic shock) and 4 healthy controls were enrolled at the Korea University    Ansan Hospital (IRB No. 2024AS0030). Whole blood was collected using PAXgene tubes at hospital day 1 (HD#1), day 3 (HD#3),   and day 7 (HD#7). Total RNA was extracted, ribosomal and globin RNA were depleted using TruSeq Stranded Total RNA Library   Prep with Globin kit, and paired-end sequencing (2×100 bp) was performed on an Illumina NovaSeq X Plus platform.   Transcriptomic analysis identified a neutrophil-driven gene expression signature reflecting early hyperinflammatory   responses, tracking disease severity and temporal progression, and predicting 28-day mortality across multiple external   cohorts. This dataset comprises 35 longitudinal blood transcriptome samples with 70 paired-end FASTQ files. This work was   supported by the National Research Foundation of Korea (NRF) grants RS-2025-00563782 and RS-2023-00220894.
Department of Biomedical Sciences, Seoul National University Graduate School