Integrative transcriptomic meta-analysis reveals conserved transcriptional signatures and predictive biomarkers for active tuberculosis: a pathway-based machine learning approach.

While inflammatory biomarkers displayed consistent improvement trends, the differences did not reach statistical significance: C-reactive protein levels measured 27.74 ± 34.43 mg/L in the intervention group versus 29.29 ± 27.75 mg/L in controls ( p = 0.256), and erythrocyte sedimentation rate values were 35.75 ± 29.37 mm/h in the intervention group compared to 33.22 ± 28.93 mm/h in controls ( p = 0.351).

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The meta-analysis revealed 347 genes with highly significant and consistent effect sizes (meta-analysis FDR <0.05) across at least three datasets, with 214 genes showing consistent upregulation and 133 genes showing consistent downregulation.

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