TBI Patient PBMC Transcriptomics with Longitudinal Immune Response Data

65 longitudinal transcriptomic profiles of PBMCs from traumatic brain injury patients, collected at Day 1, Day 7, and Month 6 post-injury, alongside 24 healthy controls. The dataset includes gene co-expression network analysis, metabolomic inference, and epigenomic profiling, authored by Abderrahmane Sadek and published in 2026. It identifies a conserved monocyte activation program linked to clinical outcomes.

Use Cases

• Identify conserved transcriptional immune signatures based on weighted gene co-expression network analysis.
• Analyze longitudinal dynamics of monocyte abundance and activation states post-traumatic brain injury.
• Validate candidate biomarker modules for clinical severity prediction using external infection datasets.
• Investigate metabolic reprogramming in monocytes based on inferred aspartate–arginine–ornithine axis activity.
• Study epigenomic regulation of immune programs via H3K27ac chromatin state profiling.

Strengths

• Includes longitudinal sampling at three distinct time points (Day 1, Day 7, Month 6) for 65 TBI patient samples.
• Validation performed across independent PBMC and monocyte datasets from bacterial and viral infections.
• Integrates multiple analysis layers: transcriptomics, computational deconvolution, metabolomic modeling, and epigenomic profiling.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect bias inherent to the specific patient cohort and sampling methodology.

Provenance

Source

figshare

Collection Method

Transcriptomic profiling of PBMCs, computational deconvolution, flow cytometry validation, genome-scale metabolic modeling, and ChIP-sequencing.

Time Range

Samples collected at Day 1, Day 7, and Month 6 post-injury.

Freshness

Last updated 2026-03-19 05:17:31