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Enregistrement W3089213251 · doi:10.1016/j.ebiom.2020.102977

Biosignatures: The answer to Tuberculosis diagnosis in children?

2020· article· en· W3089213251 sur OpenAlexaboutno aff
Pierre Goussard, Gerhard Walzl

Notice bibliographique

RevueEBioMedicine · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueTuberculosis Research and Epidemiology
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTuberculosisMycobacterium tuberculosisMedicineSputumGeneXpert MTB/RIFPandemicVirologyInfectious disease (medical specialty)ImmunologyDiseaseCoronavirus disease 2019 (COVID-19)Internal medicinePathology

Résumé

récupéré en direct d'OpenAlex

The world is in the grip of a COVID-19 pandemic but tuberculosis (TB) remains responsible for the greatest number of deaths from a single infectious disease worldwide. Of the 10 million new cases of active TB each year, approximately 10% occur in children younger than 15 years of age, resulting in an estimated 80,000 deaths [[1]Global tuberculosis report 2019. World Health Organization, Geneva2019Google Scholar], much higher than due to COVID-19. The oldest TB test in use is the direct microscopic detection of acid-fast staining bacteria, which is simple, relatively low tech but not high throughput and with merely 50–60% sensitivity [[2]Bloom BR Atun R Cohen T et al.Tuberculosis.in: Holmes KK Bertozzi S Bloom BR Jha P Major Infectious Diseases. 3rd ed. The International Bank for Reconstruction and Development / The World Bank, WashingtonDC2017Crossref Google Scholar]. The detection of Mycobacterium tuberculosis (MTB) through culture of the organism or the detection of its genetic material through nucleic acid amplification assays from host samples, like sputum, remains the preferred definitive evidence for TB. Culture methods are plagued by a plethora of challenges, including slow growth rate of the bacterium (more than 10 days for a positive and more than 40 days for a negative result), the need for confirmatory tests, and the need for expensive and advanced laboratory infrastructure that is not widely available in resource-limited settings, where such tests are most needed. The GeneXpert MTB/RIF test, an automated cartridge-based nucleic acid amplification test for simultaneous rapid (2 h) tuberculosis diagnosis and rapid antibiotic resistance testing against rifampicin as resistance marker, has advanced the diagnostic field significantly. However, it is still mainly used in a centralized manner, is relatively expensive (>US$ 10 per test) and requires sophisticated instrumentation. The search for biomarker-based TB tests is therefore ongoing and is based on the notion that the host immune response has very sensitive detection and response mechanisms. These host responses can in turn be detected through the measurement of levels of immune reactants, including gene expression levels, inflammatory protein concentrations, noncoding RNA molecules, small metabolites or cellular activation markers. In the present issue of EBioMedicine, Togun et al report that unstimulated but not stimulated levels of cytokines in an overnight culture assay with MTB antigens differentiate between TB, regardless of microbiological confirmation, and other diseases in TB-exposed, symptomatic children in The Gambia with sensitivity and specificity of 72.2% (95% CI: 60.4, 82.1%) and 75.0% (95% CI: 64.9, 83.4%), respectively [[3]Togun et alGoogle Scholar]. Adult pulmonary TB studies have shown the potential of blood-based host protein biomarkers in the diagnosis of TB disease but studies in children are either lacking or very small. Chegou et al, in a study including sites in five African countries, showed that a seven-marker blood host signature diagnosed TB in symptomatic adults with a sensitivity of 93.8%, specificity of 73.3%, and positive and negative predictive values of 60.6% and 96.4%, respectively, regardless of HIV infection status or study site [[4]Chegou NN Sutherland JS Malherbe S et al.Diagnostic performance of a seven-marker serum protein biosignature for the diagnosis of active TB disease in African primary healthcare clinic attendees with signs and symptoms suggestive of TB.Thorax. 2016; 71: 785-794https://doi.org/10.1136/thoraxjnl-2015-207999Crossref PubMed Scopus (116) Google Scholar]. Yang et al reported an eight-protein biosignature to diagnose TB in a high-burden setting with a sensitivity and specificity of 75% and 84% [[5]Yang Q Chen Q Zhang M et al.Identification of eight-protein biosignature for diagnosis of tuberculosis.Thorax. 2020; 75: 576-583https://doi.org/10.1136/thoraxjnl-2018-213021Crossref PubMed Scopus (22) Google Scholar]. Only a few studies were conducted in children, where the diagnostic hurdle is even higher than in adults. Sudbury et al reported high sensitivity (84.2%) and negative predictive value (92.6%) for the combination of IL-2, IL-13 and IP-10, indicating that these biomarkers have the potential to form the basis of a combined rule-in/rule-out test for TB infection [[6]Sudbury EL Otero L Tebruegge M et al.Mycobacterium tuberculosis-specific cytokine biomarkers for the diagnosis of childhood TB in a TB-endemic setting.J. Clin. Tuberc. Other. Mycobact. Dis. 2019; 16 (Published 2019 Apr 25)100102https://doi.org/10.1016/j.jctube.2019.100102Crossref Scopus (18) Google Scholar]. Anderson et al assessed mRNA transcript signatures in children with suspected tuberculosis from South Africa, Kenya, and Malawi, and compared them with the profiles of children with other diseases. A 51-transcript biosignature diagnosed culture-confirmed TB in a validation sample set with a sensitivity of 82.9% and specificity of 83.6% [[7]Anderson ST Kaforou M Brent AJ et al.Diagnosis of childhood tuberculosis and host RNA expression in Africa.N Engl. J. Med. 2014; 370: 1712-1723Crossref PubMed Scopus (254) Google Scholar]. The number of markers that constitute a diagnostic signature matters as cost and complexity of point-of-care (POC) tests are heavily affected by each additional target. The Togun study shows that a three-marker diagnostic signature differentiates between TB and other diseases. The low number of markers increases the likelihood for subsequent successful development of a POC test. As individual or combinations of host markers lack specificity, researchers have investigated responses that are specific to the pathogen of interest. Increased specificity would have to offset the longer lag time to a result and the increased need for laboratory infrastructure and expertise. Others [[8]Yao X Liu Y Liu Y et al.Multiplex analysis of plasma cytokines/chemokines showing different immune responses in active TB patients, latent TB infection and healthy participants.Tuberculosis (Edinb). 2017; 107: 88-94https://doi.org/10.1016/j.tube.2017.07.013Crossref PubMed Scopus (30) Google Scholar,[9]Chegou NN Detjen AK Thiart L et al.Utility of host markers detected in Quantiferon supernatants for the diagnosis of tuberculosis in children in a high-burden setting.PLoS One. 2013; 8 (Published 2013 May 15): e64226https://doi.org/10.1371/journal.pone.0064226Crossref PubMed Scopus (59) Google Scholar] have also found that unstimulated host marker levels have significant diagnostic utility, either alone or in conjunction with MTB antigen-stimulated marker levels, also in children [[10]Chegou NN Detjen AK Thiart L et al.Utility of host markers detected in Quantiferon supernatants for the diagnosis of tuberculosis in children in a high-burden setting.PLoS One. 2013; 8 (Published 2013 May 15): e64226https://doi.org/10.1371/journal.pone.0064226Crossref PubMed Scopus (58) Google Scholar]. Interestingly, all contributing markers in the Togun study were derived from unstimulated supernatants, rendering the stimulation step unnecessary, a certain benefit as this suggests that direct ex vivo samples, like finger stick blood samples, could be used in a POC test. It is not clear why ex vivo, unstimulated host marker levels would contribute more to a diagnostic signature than pathogen antigen-specific measurements. Maximally stimulated immune cells in peripheral blood that are unable to increase cytokine production after additional stimulation, cells that are prone to cellular death in culture or the production of certain cytokines in culture that suppress the secretion of other markers could all contribute to this phenomenon. The WHO-endorsed target product profile (TPP) criteria recommended minimal targets of 66% sensitivity and 98% specificity for a new diagnostic test for TB in children were not met in this study. However, the report by Togun et al should be seen as important as it is one of only a few studies in symptomatic children that investigates non-sputum diagnostic approaches and delivers encouraging results. The diagnostic performance of the three-marker unstimulated test by Togun et al suggests that ex vivo sample types, like finger stick blood, should be pursued and that top performing signatures could contribute to the development of POC tests. However, the conversion of laboratory assays, like multiplex cytokine arrays in this study, into POC tests, like antibody-based lateral flow tests with available reporter particles is not straight forward. Detection limits of lateral flow tests, specific dilution requirements for different markers, and availability of suitable antibody pairs come into play. The road from a laboratory-based assay to a robust POC test is therefore long with high attrition rates. Nevertheless, without promising candidate biosignatures such developments cannot even begin. The development of robust diagnostic biomarkers must continue with urgency. Dr. Walzl reports grants from NIAID, grants from South African National Research Foundation, during the conduct of the study; In addition, Dr. Walzl has a patent ‘Host biomarkers for immunodiagnosis and monitoring of tuberculosis disease’ pending, and a patent ‘Method for diagnosing tuberculosis’ issued. Dr Walzl and Prof Beate Kampmann are co-investigators on a grant (NIAID, R01AI128765). Both authors contributed equally to writing this commentary. A three-marker protein biosignature distinguishes tuberculosis from other respiratory diseases in Gambian childrenThis novel biosignature of childhood TB derived from unstimulated supernatants is promising. Independent validation with further optimisation will improve its performance and translational potential. Full-Text PDF Open Access

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,335
Score d'incertitude au seuil0,760

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,023
Tête enseignante GPT0,318
Écart entre enseignants0,295 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2020
Routes d'admission1
Résumé présentoui

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