Blood Transcriptomic Signatures for Mycobacterium Avium Complex Pulmonary Disease

Wen-Yuan Lin's study provides blood transcriptomic data from 120 patients to distinguish Mycobacterium avium complex pulmonary disease from colonization. The dataset includes training and validation cohorts from two medical centers in Taiwan and identifies a five-gene core signature. It was last updated on 2026-05-23.

Use Cases

• Training machine learning classifiers for disease diagnosis based on blood transcriptomic signatures.
• Analyzing immune response and tissue remodeling pathways based on the identified five-gene core signature.
• Validating candidate biomarker panels for Mycobacterium avium complex infections using external cohorts.

Strengths

• Includes data from 120 patients across training and validation cohorts, providing a basis for model evaluation.
• Identifies a specific five-gene core signature (IGKV1D-39, IGKV6-21, OVCH1, PLAU, DMD) with reported biological relevance.
• Machine learning models demonstrated performance with areas under the ROC curve up to 0.78 in external validation.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect geographic bias inherent to the two medical centers in Taiwan.

Provenance

Source

figshare

Collection Method

Peripheral blood transcriptomes were profiled from MAC-positive patients enrolled from two medical centers.

Freshness

Last updated 2026-05-23 09:00:09; freshness should be verified.

Geography

Taiwan