Evidence map›Paper›PMID 38962817›Full record

ArticleThe Journal of infectious diseases2025

A DNA Methylation Signature From Buccal Swabs to Identify Tuberculosis Infection.

Lovisa Karlsson, Isabelle Öhrnberg, Shumaila Sayyab, David Martínez-Enguita, Mika Gustafsson, Patricia Espinoza, Melissa Méndez-Aranda, Cesar Ugarte-Gil, Lameck Diero, Ronald Tonui and 2 more

Abstract read
In one paragraph

Article in The Journal of infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Future Prospects for Using Clinical Phenotypes in Tuberculosis Precision Medicine-An Approach for Clinical Management.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
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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

12 authors.

Lovisa KarlssonDivision of Inflammation and Infection, Department of Biomedical and Clinical Sciences.ORCID 0000-0003-2704-1788
Isabelle ÖhrnbergDivision of Inflammation and Infection, Department of Biomedical and Clinical Sciences.
Shumaila SayyabDivision of Inflammation and Infection, Department of Biomedical and Clinical Sciences.ORCID 0000-0002-6048-775X
David Martínez-EnguitaBioinformatics, Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden.ORCID 0000-0002-6363-6298
Mika GustafssonBioinformatics, Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden.
Patricia EspinozaFacultad de Medicina.
Melissa Méndez-ArandaLaboratorios de Investigación y Desarrollo, Facultad de Ciencias e Ingeniería.
Cesar Ugarte-GilFacultad de Medicina.
Lameck DieroAMPATH Kenya.
Ronald TonuiAMPATH Kenya.
Jakob PauesDivision of Inflammation and Infection, Department of Biomedical and Clinical Sciences.
Maria LermDivision of Inflammation and Infection, Department of Biomedical and Clinical Sciences.ORCID 0000-0002-5092-9892

Funding

Heart and Lung Foundation 20180613Swedish Research Council 2018-02961
6 · The paper itself

Abstract

backgroundTuberculosis (TB) is among the largest infectious causes of death worldwide, and there is a need for a time- and resource-effective diagnostic methods. In this novel and exploratory study, we show the potential of using buccal swabs to collect human DNA and investigate the DNA methylation (DNAm) signatures as a diagnostic tool for TB.

methodsBuccal swabs were collected from patients with pulmonary TB (n = 7), TB-exposed persons (n = 7), and controls (n = 9) in Sweden. Using Illumina MethylationEPIC array, the DNAm status was determined.

resultsWe identified 5644 significant differentially methylated CpG sites between the patients and controls. Performing the analysis on a validation cohort of samples collected in Kenya and Peru (patients, n = 26; exposed, n = 9; control, n = 10) confirmed the DNAm signature. We identified a TB consensus disease module, significantly enriched in TB-associated genes. Last, we used machine learning to identify a panel of 7 CpG sites discriminative for TB and developed a TB classifier. In the validation cohort, the classifier performed with an area under the curve of 0.94, sensitivity of 0.92, and specificity of 1.

conclusionsIn summary, the result from this study shows clinical implications of using DNAm signatures from buccal swabs to explore new diagnostic strategies for TB.

Indexed as

DNA MethylationMouth MucosaTuberculosisTuberculosis, PulmonaryAdultCase-Control StudiesCpG IslandsFemaleHumansKenyaMaleMiddle AgedMycobacterium tuberculosisPeruSensitivity and SpecificitySwedenbiosignaturebuccal swabsclassifierDNA methylationtuberculosis

Identifiers

PMID38962817
PMCPMC11793033

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.