Table 5_Pilot longitudinal integrated transcriptomic–metabolomic study reveals immune and

Integrated transcriptomic and metabolomic profiles from a longitudinal cohort of 12 non-hospitalized healthcare workers with long COVID and 35 matched controls. The dataset includes whole-blood RNA sequencing data from the NanoString nCounter PanCancer Immune Panel and serum metabolite analysis via untargeted UHPLC-MS. It was authored by Estefanía Espín and last updated on June 4, 2026.

Use Cases

• Identify candidate biomarkers for long COVID based on 63 differentially expressed genes and 24 annotated metabolites.
• Analyze coordinated immune-metabolic dysregulation through integrated network and pathway analysis.
• Investigate longitudinal metabolic trajectories, such as oxoglutarate levels, in post-acute infection sequelae.
• Study neutrophil-associated inflammatory pathways (e.g., S100A8, LY96) in persistent post-viral symptoms.

Strengths

• Integrated multi-omic data combining transcriptomic and metabolomic profiles from the same cohort.
• Longitudinal design with samples collected pre- and post-infection.
• Focus on an underrepresented population: 12 non-hospitalized healthcare workers with long COVID.

Limitations

• Small cohort size (12 cases) limits statistical power and generalizability.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data is stored in a DOCX file (675.4 KB), which may require extraction and formatting for analysis.

Provenance

Source

figshare

Collection Method

Whole-blood RNA profiled using NanoString nCounter PanCancer Immune Panel; serum metabolites analyzed via untargeted UHPLC-MS.

Freshness

Last updated 2026-06-04 05:44:38; freshness should be verified.