Multi-Omics Analysis of Long COVID Across Species and Tissues

Integrated transcriptomic, proteomic, and metabolomic datasets from Syrian hamster models and human cohorts studying Post-COVID Syndrome. The data spans acute infection through post-acute stages up to 12 months post-infection and was authored by Alexia Tasoula. The dataset is 22.0 MB and was last updated in May 2026.

Use Cases

• Identify persistent mitochondrial dysfunction signatures based on suppressed oxidative phosphorylation pathways.
• Analyze immune dysregulation patterns based on prolonged inflammatory signaling in lung and peripheral blood mononuclear cells.
• Compare tissue-specific metabolic recovery based on transcriptional profiles from skeletal muscle, heart, kidney, and nervous system.
• Investigate longitudinal serum proteomic changes based on mitochondrial stress and oxidative stress signatures at 1 and 6 months post-infection.

Strengths

• Integrated multi-omics data covering transcriptomic, proteomic, and metabolomic layers.
• Cross-species analysis includes both Syrian hamster models and human patient cohorts.
• Longitudinal data extends up to 12 months post-infection.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The primary data file is a 22.0 MB DOCX document, which may require format conversion for analysis.

Provenance

Source

Alexia Tasoula via figshare

Collection Method

Integrated multi-omics analysis performed on transcriptomic, proteomic, and metabolomic datasets.

Time Range

Spans acute infection through post-acute stages up to 12 months post-infection.

Freshness

Last updated 2026-05-21 09:06:02