Neutrophil-specific transcriptomic profiling reveals a novel signature for active tuberculosis diagnosis

Tuberculosis remains a leading cause of mortality worldwide. Rapid and accurate diagnosis of active tuberculosis (ATB) is critical for its effective treatment and disease control. However, current sputum-based detection methods have limited diagnostic coverage for ATB, resulting in missed cases and treatment delay. In this study, we performed neutrophil RNA sequencing (RNA-seq) to identify ATB-specific transcriptional signatures. Through integrated analysis of differentially expressed genes (DEGs) across 173 samples (67 ATB, 42 latent tuberculosis infection [LTBI], and 64 healthy controls [HC]), followed by quantitative Real-time polymerase chain reaction (qPCR) validation using 141 samples (31 ATB, 53 LTBI, 57 HC). A novel 4-gene neutrophil-derived tuberculosis signature (neu-TB) was screened by Lasso model prediction, and further evaluation were performed in two independent cohorts (<i>n</i> = 332). The signature achieved exceptional discrimination between ATB and LTBI (area under curve [AUC] = 0.975; 95% confidence interval [CI]: 0.949-1.000; <i>P</i> < 0.0001), with 96.8% sensitivity and 92.5% specificity. When distinguishing ATB from HC, the performance remained superior (AUC = 0.980, 91.9% sensitivity, 96.5% specificity). Notably, the signature effectively differentiated ATB from other pulmonary diseases (AUC = 0.969, 95% CI: 0.943-0.995, 93.0% sensitivity, 87.9% specificity). This study represents the first application of immune cell subset-specific transcriptomic profiling to overcome the technical limitations, which are frequently confounded by heterogeneous cellular backgrounds in whole blood or peripheral blood mononuclear cell (PBMC) analyses. The development of this 4-gene neu-TB signature not only establishes a novel methodology for identifying transcriptomic biomarkers but also demonstrates promising clinical applicability for ATB diagnostics.IMPORTANCEThe most urgent need in pulmonary TB diagnosis is developing a rapid, non-sputum, biomarker-based diagnostic test. Here, we first identified a novel transcriptomic signature and addressed these challenges through two key innovations: (i) cell-type-specific resolution: by focusing on neutrophils-the most abundant immune cell in TB blood signatures and key mediators of host-pathogen interactions-we reduce biological noise and enhance biomarker precision. (ii) Rigorous multi-cohort validation: the 4-gene neutrophil-derived TB signature (neu-TB) was selected via RNA-seq of purified neutrophils (<i>n</i> = 141) and validated by qPCR in two independent cohorts (total <i>n</i> = 332), achieving 93% sensitivity/88% specificity in distinguishing active TB from latent infection and non-TB controls.

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Publication Details

Journal
Microbiology Spectrum
Published
2026-03-12
DOI
https://doi.org/10.1128/spectrum.01915-25
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
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article

Neutrophil-specific transcriptomic profiling reveals a novel signature for active tuberculosis diagnosis

H. Xin, Xingzhu Geng, Lei Gao, Xiaobing Zhang et al.
Microbiology Spectrum
Tuberculosis Research and Epidemiology
article

Neutrophil-specific transcriptomic profiling reveals a novel signature for active tuberculosis diagnosis

H. Xin, Xingzhu Geng, Lei Gao, Xiaobing Zhang, Jie Hu, Qi Chen, Liguo Liu, Qi Jin, Song Liu, Qianting Yang
article en

Abstract

Tuberculosis remains a leading cause of mortality worldwide. Rapid and accurate diagnosis of active tuberculosis (ATB) is critical for its effective treatment and disease control. However, current sputum-based detection methods have limited diagnostic coverage for ATB, resulting in missed cases and treatment delay. In this study, we performed neutrophil RNA sequencing (RNA-seq) to identify ATB-specific transcriptional signatures. Through integrated analysis of differentially expressed genes (DEGs) across 173 samples (67 ATB, 42 latent tuberculosis infection [LTBI], and 64 healthy controls [HC]), followed by quantitative Real-time polymerase chain reaction (qPCR) validation using 141 samples (31 ATB, 53 LTBI, 57 HC). A novel 4-gene neutrophil-derived tuberculosis signature (neu-TB) was screened by Lasso model prediction, and further evaluation were performed in two independent cohorts (<i>n</i> = 332). The signature achieved exceptional discrimination between ATB and LTBI (area under curve [AUC] = 0.975; 95% confidence interval [CI]: 0.949-1.000; <i>P</i> < 0.0001), with 96.8% sensitivity and 92.5% specificity. When distinguishing ATB from HC, the performance remained superior (AUC = 0.980, 91.9% sensitivity, 96.5% specificity). Notably, the signature effectively differentiated ATB from other pulmonary diseases (AUC = 0.969, 95% CI: 0.943-0.995, 93.0% sensitivity, 87.9% specificity). This study represents the first application of immune cell subset-specific transcriptomic profiling to overcome the technical limitations, which are frequently confounded by heterogeneous cellular backgrounds in whole blood or peripheral blood mononuclear cell (PBMC) analyses. The development of this 4-gene neu-TB signature not only establishes a novel methodology for identifying transcriptomic biomarkers but also demonstrates promising clinical applicability for ATB diagnostics.IMPORTANCEThe most urgent need in pulmonary TB diagnosis is developing a rapid, non-sputum, biomarker-based diagnostic test. Here, we first identified a novel transcriptomic signature and addressed these challenges through two key innovations: (i) cell-type-specific resolution: by focusing on neutrophils-the most abundant immune cell in TB blood signatures and key mediators of host-pathogen interactions-we reduce biological noise and enhance biomarker precision. (ii) Rigorous multi-cohort validation: the 4-gene neutrophil-derived TB signature (neu-TB) was selected via RNA-seq of purified neutrophils (<i>n</i> = 141) and validated by qPCR in two independent cohorts (total <i>n</i> = 332), achieving 93% sensitivity/88% specificity in distinguishing active TB from latent infection and non-TB controls.

Microbiology Spectrum
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Peking Union Medical College Hospital (CN), Shenzhen Third People’s Hospital (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 26%
Tuberculosis Research and Epidemiology
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