Fig. 10 | Scientific Reports

Fig. 10

From: A machine learning model and molecular clusters of epigenetic chromatin regulators in tuberculosis based on bioinformatics and clinical samples

Fig. 10

Clinical validation of DE-CRs in patient blood samples.(A-B) Reverse transcription-quantitative PCR (RT-qPCR) validation of the 15 DE-CRs in blood samples from an independent clinical cohort. (A) Comparison between healthy controls (n = 15) and the overall TB group (n = 18, combining PTB and TBM). Only IFIT3 exhibits significant upregulation in the TB group, confirming its role as a promising blood-based biomarker. (versus control group, #< 0.01) (B) Comparison across healthy controls (n = 15), pulmonary TB (PTB, n = 9), and tuberculous meningitis (TBM, n = 9) subgroups. IFIT3 is significantly upregulated in PTB and TBM patients compared to controls. However, it does not differ between the two clinical forms of TB, supporting its utility as a pan-TB biomarker (versus control group, #< 0.01).

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