Table 2_Pilot longitudinal integrated transcriptomic–metabolomic study reveals immune and

A longitudinal cohort of 12 non-hospitalized healthcare workers with long COVID and 35 matched controls, profiled post-SARS-CoV-2 infection. The dataset contains integrated transcriptomic and metabolomic data, identifying 63 differentially expressed genes and 24 annotated metabolites. It was authored by Estefanía Espín and last updated on 2026-06-04.

Use Cases

• Identify candidate biomarkers for long COVID based on differential gene expression and metabolite abundance.
• Analyze coordinated immune-metabolic dysregulation based on integrated network and pathway analysis.
• Study longitudinal trajectories of specific metabolites, such as oxoglutarate, in post-acute infection outcomes.
• Investigate the role of neutrophil-associated inflammatory pathways in persistent symptoms like fatigue and brain fog.

Strengths

• Integrated multi-omics data from transcriptomic (NanoString nCounter PanCancer Immune Panel) and metabolomic (untargeted UHPLC-MS) platforms.
• Longitudinal design with samples collected pre- and post-infection from a defined cohort.
• Focus on an underrepresented population of non-hospitalized healthcare workers.
• Results include 63 differentially expressed genes and 24 annotated metabolites with statistical correction.

Limitations

• Small cohort size (12 cases, 35 controls) limits statistical power and generalizability.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data is stored in a DOCX file format (676.4 KB), which may require extraction and conversion for analysis.

Provenance

Source

figshare

Collection Method

Whole-blood RNA profiling and serum metabolomic analysis from a longitudinal cohort.

Time Range

Post-SARS-CoV-2 infection period (specific dates not provided).

Freshness

Last updated 2026-06-04 05:44:39; freshness should be verified.