Evidence map›Paper›PMID 39505948›Full record

ArticleScientific reports2024

Specific human gene expression in response to infection is an effective marker for diagnosis of latent and active tuberculosis.

Ritah Nakiboneka, Natasha Walbaum, Emmanuel Musisi, Michael Nevels, Tonney Nyirenda, Marriott Nliwasa, Chisomo L Msefula, Derek Sloan, Wilber Sabiiti

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
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  7. Review
  8. Swift and portable detection ofFrontiers in microbiology · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Ritah NakibonekaDivision of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, KY16 9TF, UK.
Natasha WalbaumDivision of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, KY16 9TF, UK.
Emmanuel MusisiDivision of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, KY16 9TF, UK.
Michael NevelsBiomedical Sciences Research Complex (BSRC), School of Biology, University of St Andrews, St Andrews, UK.
Tonney NyirendaDepartment of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi.
Marriott NliwasaDepartment of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi.
Chisomo L MsefulaDepartment of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi.
Derek SloanDivision of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, KY16 9TF, UK.
Wilber SabiitiDivision of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, KY16 9TF, UK. ws31@st-andrews.ac.uk.

Funding

Wellcome TrustWellcome Trust 204821/Z/16/Z
6 · The paper itself

Abstract

RNA sequencing and microarray analysis revealed transcriptional markers expressed in whole blood can differentiate active pulmonary TB (ATB) from other respiratory diseases (ORDs), and latent TB infection (LTBI) from healthy controls (HC). Here we describe a streamlined reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) assay that could be applied at near point-of-care for diagnosing and distinguishing ATB from ORDs and LTBI from HC. A literature review was undertaken to identify the most plausible host-gene markers (HGM) of TB infection. Primers, and dual labelled hydrolysis probes were designed and analytically evaluated for accuracy in an in-vitro model of infection using a lung fibroblast cell-line. Best performing genes were multiplexed into panels of 2-4 targets and taken forward for clinical evaluation. Mycobacteria Growth Indicator Tube and QuantiFERON-TB Gold Plus were used as reference tests for ATB and LTBI respectively. A total of 16 HGM were selected and incorporated into five multiplex RT-qPCR panels. PCR assay efficiency of all evaluated targets was ≥ 90% with a median analytical sensitivity of 292 copies/µl [IQR: 215.0-358.3 copies/µl], and a median limit of quantification of 61.7 copies/µl [IQR: 29.4-176.3 copies/µl]. Clinically, ATB was characterised by higher gene expression than ORDs, while LTBI was associated with lower gene expression than HC, Kruskal-Wallis p < 0.0001. Crucially, BATF2, CD64, GBP5, C1QB, GBP6, DUSP3, and GAS6 exhibited high differentiative ability for ATB from ORDs, LTBI or HC while KLF2, PTPRC, NEMF, ASUN, and ZNF296 independently discriminated LTBI from HC. Our results show that different HGM maybe required for ATB and LTBI differentiation from ORDs or HC respectively and demonstrate the feasibility of host gene-based RT-qPCR to diagnose ATB and LTBI at near point-of-care.

Indexed as

BiomarkersLatent TuberculosisAdultFemaleHumansMaleMycobacterium tuberculosisTuberculosisTuberculosis, PulmonaryBiomarkersActive tuberculosisDiagnosisHost gene expressionLatent tuberculosisReverse transcriptase-quantitative PCR

Identifiers

PMID39505948
PMCPMC11541504

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.