ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2022
Development and Validation of a Parsimonious Tuberculosis Gene Signature Using the digital NanoString nCounter Platform.
Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Gene signature discovery and systematic validation across diverse clinical cohorts for TB prognosis and response to treatment.PLoS computational biology · 2023Pooled it
- A PTPRO-Related Five-Gene Blood Transcriptional Signature with Diagnostic Potential for Tuberculosis.Biomedicines · 2026Article
- Prominence of Mycobacterium tuberculosis biomarkers among sputum culture-negative clinic attendees, independent of Ultra status.Journal of infection and public health · 2025Article
- Analysis of the cross-study replicability of tuberculosis gene signatures using 49 curated human transcriptomic datasets.Tuberculosis (Edinburgh, Scotland) · 2025Article
- Developing a Predictive Model for Metastatic Potential in Pancreatic Neuroendocrine Tumor.The Journal of clinical endocrinology and metabolism · 2024Article
- Distinguish active tuberculosis with an immune-related signature and molecule subtypes: a multi-cohort analysis.Scientific reports · 2024Article
- Integrating pathogen- and host-derived blood biomarkers for enhanced tuberculosis diagnosis: a comprehensive review.Frontiers in immunology · 2024Review
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Authors and funding
13 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundBlood-based biomarkers for diagnosing active tuberculosis (TB), monitoring treatment response, and predicting risk of progression to TB disease have been reported. However, validation of the biomarkers across multiple independent cohorts is scarce. A robust platform to validate TB biomarkers in different populations with clinical end points is essential to the development of a point-of-care clinical test. NanoString nCounter technology is an amplification-free digital detection platform that directly measures mRNA transcripts with high specificity. Here, we determined whether NanoString could serve as a platform for extensive validation of candidate TB biomarkers.
methodsThe NanoString platform was used for performance evaluation of existing TB gene signatures in a cohort in which signatures were previously evaluated on an RNA-seq dataset. A NanoString codeset that probes 107 genes comprising 12 TB signatures and 6 housekeeping genes (NS-TB107) was developed and applied to total RNA derived from whole blood samples of TB patients and individuals with latent TB infection (LTBI) from South India. The TBSignatureProfiler tool was used to score samples for each signature. An ensemble of machine learning algorithms was used to derive a parsimonious biomarker.
resultsGene signatures present in NS-TB107 had statistically significant discriminative power for segregating TB from LTBI. Further analysis of the data yielded a NanoString 6-gene set (NANO6) that when tested on 10 published datasets was highly diagnostic for active TB.
conclusionsThe NanoString nCounter system provides a robust platform for validating existing TB biomarkers and deriving a parsimonious gene signature with enhanced diagnostic performance.
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