Single-gene transcripts for subclinical tuberculosis: an individual participant data meta-analysis

Area of Science:

• Biomarker discovery
• Molecular diagnostics
• Tuberculosis research

Background:

• Blood RNA signatures can accelerate tuberculosis translation.
• Single-gene transcripts may offer similar accuracy to multi-gene signatures for subclinical tuberculosis detection.
• Interferon-gamma release assays (IGRAs) are a benchmark for comparison.

Purpose of the Study:

• To test if single-gene transcripts accurately detect subclinical tuberculosis.
• To compare single-gene transcript accuracy against multi-gene signatures.
• To benchmark clinical utility against IGRAs.

Main Methods:

• Individual participant data meta-analysis of PubMed-indexed studies.
• Comparison of multi-gene signatures vs. single-gene transcripts for subclinical tuberculosis detection.
• Decision curve analysis for evaluating preventive treatment strategies.

Main Results:

• Five single-gene transcripts showed accuracy equivalent to the best multi-gene signature.
• Single-gene transcripts demonstrated consistent sensitivity and specificity across high- and low-burden settings.
• Single-gene transcripts offered greater net benefit than IGRAs for preventive treatment in high-burden settings.

Conclusions:

• Single-gene transcripts are equivalent to multi-gene signatures for detecting subclinical tuberculosis.
• Single-gene transcripts show potential for clinical utility in stratifying preventive treatment.
• Combining single-gene transcripts with IGRAs provides the highest net benefit in low-burden settings.