Immunometabolic Profiles of TB-Responsive Memory T Cell Subsets from a Longitudinal Cohort

A 2026 study by Vaishnavi Kaipilyawar investigates the link between metabolic states in Mycobacterium tuberculosis-responsive memory CD4+ T cell subsets and long-term protective immunity. The dataset, a 4.5 MB supplementary document, integrates transcriptomic, metabolic, and functional profiling data from individuals with latent TB infection and an independent longitudinal cohort of progressors and non-progressors. It was published on figshare under a CC-BY-4.0 license.

Use Cases

• Identifying metabolic signatures predictive of TB progression based on fatty acid oxidation and glycolytic reprogramming profiles.
• Correlating T cell differentiation states (T-SCM, T-CM, T-TM, T-EM) with antimycobacterial function using integrated multi-platform data.
• Validating immunometabolic findings in an independent longitudinal cohort (GSE112104) of Mtb-exposed individuals.
• Investigating the relationship between exhaustion markers, pro-inflammatory profiles, and disease progression.

Strengths

• Data integrates multi-platform validation, combining RNA-sequencing, protein-level metabolic profiling, and functional assays.
• Includes analysis from an independent, longitudinal cohort (GSE112104) for validation.
• Published under a permissive CC-BY-4.0 license, facilitating reuse.

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 4.5 MB DOCX document, which may require format conversion for computational analysis.

Provenance

Source

figshare, authored by Vaishnavi Kaipilyawar.

Collection Method

Transcriptomic, metabolic, and functional profiling of memory T cell subsets from peripheral blood, validated in an independent cohort.

Time Range

Study period is not specified, but data was published in 2026.

Freshness

Last updated 2026-04-10 05:59:04.

Geography

Includes data from an independent cohort from Brazil (GSE112104).