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. 2025 Aug 24;15(1):31106.
doi: 10.1038/s41598-025-15076-8.

Genomic epidemiology of Mycobacterium tuberculosis in Wales

Affiliations

Genomic epidemiology of Mycobacterium tuberculosis in Wales

Nicole Pacchiarini et al. Sci Rep. .

Abstract

Identification of factors contributing to tuberculosis (TB) transmission can guide targeted measures to reduce morbidity. Varying findings for factors associated with TB genomic clustering exist. We describe Mycobacterium tuberculosis strain diversity, drug-resistance, and ongoing transmission in Wales using single nucleotide polymorphisms (SNP)-based typing to infer lineage and clusters. TB cohort data on isolates from Welsh residents from 2012 to 2022, patient level data from the National TB Surveillance System and SNP-based data, were merged. Descriptive epidemiology and logistic regression modelling were used to identify factors associated with genotypic clustering. 215 cases were included in the cluster analysis (66% male and 46% born outside of the UK); 115/215 belonged to 30 genomic clusters belonging to lineages 2-4. Most clusters corresponded to Lineage 4 and were distributed within South Wales. There were significant differences in the distribution of ethnicity, age group, and deprivation (Welsh Index of Multiple Deprivation, WIMD) in our sample compared to the Welsh population. Resistance to rifampicin and isoniazid and predicted resistance to ethambutol, aminoglycosides, pyrazinamide, and quinolone was low. Factors associated with increased odds of clustering included being UK-born and having pulmonary disease. Due to the identification of the above factors associated with TB genomic clustering, as well as the differences in ethnicity, age group, and WIMD quintile, prevention strategies for TB screening targeted towards these groups may be considered. Future work may evaluate the utility of additional control measures within these populations when the onset case in a genomic cluster has any of these characteristics.

Keywords: Genomic cluster; Tuberculosis; United Kingdom; Wales; Whole genome sequencing.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Flowchart of cases eligible and included in the clustering analysis and cases eligible and included in the resistance analysis of all eligible TB cases over the study period.
Fig. 2
Fig. 2
(a) Timeline of genotypic TB clusters in Wales, 2012–2022. Clusters are ordered on the y-axis by TB lineage, and the number of cases is indicated by the size of the dots. TB Lineages are given by the point colours: Lineage 2 = orange; Lineage 3 = purple; Lineage 4 = blue; Lineage unknown = grey. (b) Map showing the number of genotypic clusters per local authority, in Wales, 2012–2022. Pie chart size indicates the number of cases, colour indicates the cluster ID. Note: A small number of clusters are shown as comprising N = 1 cases over the study period because other linked cases were notified outside the study window or could not be retrieved from NTBS.
Fig. 3
Fig. 3
Distribution of ethnic groups, age groups and WIMD in the study population (blue) vs. the Welsh population (Census data from 2021) (pink). Note: Unknowns within the study data have not been visualised, counts can be found within Table 1.
Fig. 4
Fig. 4
Resistance profile of Mycobacterium tuberculosis in Wales, 2014–2022.

References

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