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Enregistrement W4413922943 · doi:10.1101/2025.08.27.25334397

Comparison of phylogenetic metrics of transmission in symptomatic and asymptomatic tuberculosis

2025· preprint· en· W4413922943 sur OpenAlexaff
Késia Esther da Silva, Paulo César Pereira dos Santos, Daniel Henrique Tsuha, Katharine S. Walter, Eunice Atsuko Totumi Cunha, Caroline Colijn, Ted Cohen, Roberto Dias de Oliveira, José Victor Bortolotto Bampi, Mariana Garcia Croda, Crhistinne Cavalheiro Maymone Gonçalves, Luiz Henrique Ferraz Demarchi, Júlio Croda, Jason R. Andrews

Notice bibliographique

RevuemedRxiv · 2025
Typepreprint
Langueen
DomaineMedicine
ThématiqueTuberculosis Research and Epidemiology
Établissements canadiensSimon Fraser University
Organismes subventionnairesNational Institutes of HealthUniversidade Federal de Mato Grosso do SulConselho Nacional de Desenvolvimento Científico e Tecnológico
Mots-clésAsymptomaticPhylogenetic treeTransmission (telecommunications)TuberculosisPhylogenetic relationshipVirologyBiologyComputational biologyEvolutionary biologyGeographyComputer scienceMedicineInternal medicineGeneticsPathologyTelecommunications

Résumé

récupéré en direct d'OpenAlex

Summary Background Understanding drivers of Mycobacterium tuberculosis ( Mtb ) transmission remains a critical challenge in high-burden settings. Tuberculosis control efforts traditionally target symptomatic individuals, yet the role of asymptomatic cases in sustaining transmission is increasing recognized. Methods We conducted a genomic and epidemiological analysis of Mtb isolates collected in Mato Grosso do Sul, Brazil, between 2008 and 2024. From 2017 to 2022, active case finding was performed in three of the state’s largest prisons, whereby sputum was collected from individuals irrespective of symptoms and tested by GeneXpert and culture. We evaluated several metrics of recent transmission from symptomatic and asymptomatic individuals, including phylogenetic clustering, Time-scaled Haplotype Density (THD), Local Branching Index (LBI), and transmission probabilities inferred using the Bayesian Reconstruction and Evolutionary Analysis of Transmission Histories (BREATH). Findings We sequenced 2,362 Mtb strains, of which 3.5% (115/2,362) were resistant to at least one drug, and 0.6% (16/2,362) were multi-drug resistant. Most strains were lineage 4, and 78.2% of all isolates were part of a genomic cluster. Among 2,362 individuals with tuberculosis, 1,137 were incarcerated at the time of diagnosis. Among these, 505 were identified through active case finding: 277 had symptomatic disease and 228 had asymptomatic tuberculosis. There was no significant difference in phylogenetic clustering proportion (77% vs. 85%; p= 0.816), THD (median 0.50 vs. 0.39; p = 0.120), or LBI (median 0.00863 vs. 0.00871; p = 0.086) between symptomatic and asymptomatic individuals. Bayesian transmission trees revealed no significant difference in the number of secondary infections inferred from symptomatic compared with asymptomatic individuals (p = 0.56). These findings were consistent across genomic clusters and robust to model assumptions. Interpretation We identified no differences in transmission from symptomatic compared with asymptomatic individuals, using several genomic measures of transmission, underscoring the substantial contribution that asymptomatic tuberculosis makes to transmission at the population level. Evidence before this study We searched PubMed from inception to June 1, 2025, without language restrictions, using the terms “tuberculosis”, “asymptomatic”, “transmission”, “infectiousness” and “genomic epidemiology”. We also reviewed reference lists of relevant studies and reports from the WHO Global Tuberculosis Programme. Most available evidence on the contribution of asymptomatic tuberculosis to transmission comes from cross-sectional contact studies, which typically use tuberculin skin tests or interferon gamma release assays to measure Mycobacterium tuberculosis infection risk in contacts. These studies have generally found no major differences in infection risk between contacts of symptomatic and asymptomatic individuals, but they measure lifetime infection risk and cannot establish the source of exposure. Few studies have used genomic epidemiology to directly assess transmission by symptom status, and those that exist have been small in scale and limited in scope. Mathematical modelling has suggested that asymptomatic individuals could account for a substantial proportion of transmission, but empirical, population-level data from high-incidence settings remain scarce. Added value of this study We combined genomic, epidemiological, and clinical data from over 2,362 M. tuberculosis isolates collected in Mato Grosso do Sul, Brazil, including more than 500 cases identified through active case finding in prisons, to directly compare multiple genomic metrics of transmission between symptomatic and asymptomatic individuals. We found no significant difference in genomic clustering, phylogenetic epidemic success, or the number of estimated secondary infections between groups. Our study is among the largest to date to evaluate transmission resulting in tuberculosis disease by symptom status. These findings provide robust, population-based evidence that asymptomatic tuberculosis can contribute to transmission at levels comparable to symptomatic disease, even in settings with extensive case finding. Implications of all the available evidence Our findings, in combination with previous evidence, indicate that symptom-based case detection strategies are insufficient to substantially reduce tuberculosis transmission. In high-burden settings, systematic screening irrespective of symptoms, is essential to identify and treat infectious cases earlier. Public health programmes should prioritize expanding active case finding in both high-risk institutional settings and the community to capture asymptomatic individuals who may sustain transmission.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,008
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,003
Score d'incertitude au seuil0,008

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,008
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
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 Opus0,045
Tête enseignante GPT0,380
Écart entre enseignants0,335 · 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 source (Gemma direct ou Codex distillé), 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
Publié2025
Routes d'admission1
Résumé présentoui

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