Unraveling tuberculosis patient cluster transmission chains : integrating WGS-based network with clinical and epidemiological insights

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dc.contributor.authorSadovska, Darja
dc.contributor.authorOzere, Iveta
dc.contributor.authorPole, Ilva
dc.contributor.authorĶimsis, Jānis
dc.contributor.authorVaivode, Annija
dc.contributor.authorVīksna, Anda
dc.contributor.authorNorvaiša, Inga
dc.contributor.authorBogdanova, Ineta
dc.contributor.authorUlanova, Viktorija
dc.contributor.authorČapligina, Valentīna
dc.contributor.authorBandere, Dace
dc.contributor.authorRanka, Renāte
dc.contributor.institutionDepartment of Infectology
dc.contributor.institutionDepartment of Pharmaceutical Chemistry
dc.date.accessioned2024-06-21T21:16:13Z
dc.date.available2024-06-21T21:16:13Z
dc.date.issued2024
dc.descriptionCopyright © 2024 Sadovska, Ozere, Pole, Ķimsis, Vaivode, Vīksna, Norvaiša, Bogdanova, Ulanova, Čapligina, Bandere and Ranka.
dc.description.abstractBACKGROUND: Tuberculosis remains a global health threat, and the World Health Organization reports a limited reduction in disease incidence rates, including both new and relapse cases. Therefore, studies targeting tuberculosis transmission chains and recurrent episodes are crucial for developing the most effective control measures. Herein, multiple tuberculosis clusters were retrospectively investigated by integrating patients' epidemiological and clinical information with median-joining networks recreated based on whole genome sequencing (WGS) data of Mycobacterium tuberculosis isolates. METHODS: Epidemiologically linked tuberculosis patient clusters were identified during the source case investigation for pediatric tuberculosis patients. Only M. tuberculosis isolate DNA samples with previously determined spoligotypes identical within clusters were subjected to WGS and further median-joining network recreation. Relevant clinical and epidemiological data were obtained from patient medical records. RESULTS: We investigated 18 clusters comprising 100 active tuberculosis patients 29 of whom were children at the time of diagnosis; nine patients experienced recurrent episodes. M. tuberculosis isolates of studied clusters belonged to Lineages 2 (sub-lineage 2.2.1) and 4 (sub-lineages 4.3.3, 4.1.2.1, 4.8, and 4.2.1), while sub-lineage 4.3.3 (LAM) was the most abundant. Isolates of six clusters were drug-resistant. Within clusters, the maximum genetic distance between closely related isolates was only 5-11 single nucleotide variants (SNVs). Recreated median-joining networks, integrated with patients' diagnoses, specimen collection dates, sputum smear microscopy, and epidemiological investigation results indicated transmission directions within clusters and long periods of latent infection. It also facilitated the identification of potential infection sources for pediatric patients and recurrent active tuberculosis episodes refuting the reactivation possibility despite the small genetic distance of ≤5 SNVs between isolates. However, unidentified active tuberculosis cases within the cluster, the variable mycobacterial mutation rate in dormant and active states, and low M. tuberculosis genetic variability inferred precise transmission chain delineation. In some cases, heterozygous SNVs with an allelic frequency of 10-73% proved valuable in identifying direct transmission events. CONCLUSION: The complex approach of integrating tuberculosis cluster WGS-data-based median-joining networks with relevant epidemiological and clinical data proved valuable in delineating epidemiologically linked patient transmission chains and deciphering causes of recurrent tuberculosis episodes within clusters.en
dc.description.statusPeer reviewed
dc.format.extent3044416
dc.identifier.citationSadovska, D, Ozere, I, Pole, I, Ķimsis, J, Vaivode, A, Vīksna, A, Norvaiša, I, Bogdanova, I, Ulanova, V, Čapligina, V, Bandere, D & Ranka, R 2024, 'Unraveling tuberculosis patient cluster transmission chains : integrating WGS-based network with clinical and epidemiological insights', Frontiers in Public Health, vol. 12, 1378426. https://doi.org/10.3389/fpubh.2024.1378426
dc.identifier.doi10.3389/fpubh.2024.1378426
dc.identifier.issn2296-2565
dc.identifier.otherPubMedCentral: PMC11144917
dc.identifier.urihttps://dspace.rsu.lv/jspui/handle/123456789/15534
dc.identifier.urlhttps://www-webofscience-com.db.rsu.lv/wos/alldb/full-record/WOS:001236736900001
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85195005441&partnerID=8YFLogxK
dc.language.isoeng
dc.relation.ispartofFrontiers in Public Health
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectHumans
dc.subjectMycobacterium tuberculosis/genetics
dc.subjectMale
dc.subjectTuberculosis/transmission
dc.subjectFemale
dc.subjectRetrospective Studies
dc.subjectChild
dc.subjectWhole Genome Sequencing
dc.subjectChild, Preschool
dc.subjectAdolescent
dc.subjectCluster Analysis
dc.subjectAdult
dc.subjectInfant
dc.subjectEpidemiology
dc.subjectTransmission
dc.subject3.1 Basic medicine
dc.subject3.3 Health sciences
dc.subject1.1. Scientific article indexed in Web of Science and/or Scopus database
dc.subjectSDG 3 - Good Health and Well-being
dc.titleUnraveling tuberculosis patient cluster transmission chains : integrating WGS-based network with clinical and epidemiological insightsen
dc.type/dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article

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