Longitudinal Immune and Metabolic Signatures in Non-Hospitalized Long COVID Patients

A longitudinal cohort of 12 non-hospitalized healthcare workers with long COVID and 35 matched controls. The dataset contains integrated transcriptomic and metabolomic profiles from whole blood and serum, analyzed using the NanoString nCounter PanCancer Immune Panel and untargeted mass spectrometry. It was authored by Estefanía Espín and shared under a CC-BY-4.0 license on figshare in June 2026.

Use Cases

• Identify candidate biomarkers for long COVID based on the 63 differentially expressed genes and 24 annotated metabolites.
• Analyze coordinated immune-metabolic dysregulation based on integrated network analysis highlighting pathways like necroptosis and serotonergic synapse signaling.
• Study longitudinal metabolic trajectories, such as oxoglutarate levels, in post-acute COVID-19 sequelae.
• Investigate neutrophil-associated inflammatory pathways based on markers like S100A8 and LY96 identified in the transcriptomic analysis.

Strengths

• Integrated multi-omic data from transcriptomics and metabolomics on 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.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Whole-blood RNA profiled with NanoString nCounter PanCancer Immune Panel; serum metabolites analyzed with untargeted ultra-high-performance liquid chromatography–mass spectrometry.

Freshness

Last updated 2026-06-04 05:42:32; freshness should be verified.