Table 4_Pilot longitudinal integrated transcriptomic–metabolomic study reveals immune and

12 non-hospitalized healthcare workers with long COVID and 35 matched controls provide longitudinal multi-omics data. The dataset includes whole-blood transcriptomic profiling via the NanoString nCounter PanCancer Immune Panel and serum metabolomic analysis using untargeted mass spectrometry. Author Estefanía Espín published this research on figshare in June 2026 under a CC-BY-4.0 license.

Use Cases

• Identify candidate biomarkers for long COVID based on 63 differentially expressed genes and 24 annotated metabolites.
• Analyze coordinated immune-metabolic dysregulation via integrated network and pathway analysis focusing on necroptosis and serotonergic synapse signaling.
• Investigate longitudinal metabolic trajectories, such as oxoglutarate levels, in post-acute infection phenotypes.
• Study persistent innate immune activation patterns, including neutrophil-associated markers like S100A8 and LY96, in mild long COVID cases.

Strengths

• Integrated multi-omics data from transcriptomic and metabolomic profiling on the same longitudinal cohort.
• Focus on an underrepresented population: 12 non-hospitalized healthcare workers with long COVID and 35 matched controls.
• Analysis identified specific molecular features, including 63 differentially expressed genes and 24 annotated metabolites.

Limitations

• The cohort size of 12 long COVID cases is small, limiting statistical power and generalizability.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Longitudinal cohort study with integrated transcriptomic and metabolomic profiling.

Freshness

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