- ABSTRACT.
- INTRODUCTION
- MATERIALS AND METHODS
- Design overview.
- Study population, setting, and data sources.
- Study outcome for clustering.
- Study exposures for clustering.
- Analytical strategy.
- Data preparation and cleaning.
- Study population.
- Assignment of shared international type and spoligotyping families.
- Characteristics of the participants with two samples included in the study.
- Visualization of relationship among spoligotypes.
- Descriptive statistics of clustering of mycobacterial isolates.
- Estimation of the proportion of TB cases due recent transmission.
- Independent factors associated with clustering in the participants living with HIV.
- Sensitivity analysis.
- Ethical approval.
- RESULTS
- Study population.
- Spoligotype patterns and families.
- Characteristics of the nine participants with two samples.
- Visualization of relationship among spoligotypes.
- Descriptive statistics of clustering of mycobacterial isolates.
- Estimation of the proportion of TB cases due to recent transmission.
- Independent factors associated with clustering in persons living with HIV.
- DISCUSSION
- ACKNOWLEDGMENTS
- REFERENCES
ProCite
RefWorks
Reference Manager
BibTeX
Zotero
EndNote
-
1.
World Health Organization , 2018. Global Tuberculosis Report 2018. Geneva, Switzerland: World Health Organization.
-
2.
Auld SC , Shah NS , Cohen T , Martinson NA , Gandhi NR , 2018. Where is tuberculosis transmission happening? Insights from the literature, new tools to study transmission and implications for the elimination of tuberculosis. Respirology 23: 807–817.
-
3.
Mathema B , Kurepina NE , Bifani PJ , Kreiswirth BN , 2006. Molecular epidemiology of tuberculosis: current insights. Clin Microbiol Rev 19: 658–685.
-
4.
Kasaie P , Dowdy DW , Kelton WD , 2014. Estimating the proportion of tuberculosis recent transmission via simulation. Proceedings of the Winter Simulation Conference 7--10 Dec. 2014, Savannah, GA, IEEE, 1469–1480.
-
5.
Murray M , Nardell E , 2002. Molecular epidemiology of tuberculosis: achievements and challenges to current knowledge. Bull World Health Organ 80: 477–482.
-
6.
Barnes PF , Cave MD , 2003. Molecular epidemiology of tuberculosis. N Engl J Med 349: 1149–1156.
-
7.
Glynn JR , Crampin AC , Yates MD , Traore H , Mwaungulu FD , Ngwira BM , Ndlovu R , Drobniewski F , Fine PE , 2005. The importance of recent infection with Mycobacterium tuberculosis in an area with high HIV prevalence: a long-term molecular epidemiological study in northern Malawi. J Infect Dis 192: 480–487.
-
8.
Murray M , 2002. Sampling bias in the molecular epidemiology of tuberculosis. Emerg Infect Dis 8: 363–369.
-
9.
Glynn JR , Vynnycky E , Fine PE , 1999. Influence of sampling on estimates of clustering and recent transmission of Mycobacterium tuberculosis derived from DNA fingerprinting techniques. Am J Epidemiol 149: 366–371.
-
10.
Oppong JR , Denton CJ , Moonan PK , Weis SE , 2007. Foreign-born status and geographic patterns of tuberculosis genotypes in Tarrant County, Texas. Prof Geogr 59: 478–491.
-
11.
Murray M , 2002. Determinants of cluster distribution in the molecular epidemiology of tuberculosis. Proc Natl Acad Sci USA 99: 1538–1543.
-
12.
Fok A , Numata Y , Schulzer M , FitzGerald MJ , 2008. Risk factors for clustering of tuberculosis cases: a systematic review of population-based molecular epidemiology studies. Int J Tuberc Lung Dis 12: 480–492.
-
13.
World Health Organization , 2016. Global Tuberculosis Report 2016. Geneva, Switzerland: World Health Organization.
-
14.
World Health Organization , 2016. World Health Statistics 2016: Monitoring Health for the SDGs Sustainable Development Goals: Geneva, Switzerland: World Health Organization.
-
15.
Kamerbeek J , Schouls L , Kolk A , Van Agterveld M , Van Soolingen D , Kuijper S , Bunschoten A , Molhuizen H , Shaw R , Goyal M , 1997. Simultaneous detection and strain differentiation of Mycobacterium tuberculosis for diagnosis and epidemiology. J Clin Microbiol 35: 907–914.
-
16.
Couvin D , David A , Zozio T , Rastogi N , 2018. Macro-geographical specificities of the prevailing tuberculosis epidemic as seen through SITVIT2, an updated version of the Mycobacterium tuberculosis genotyping database. Infect Genet Evol 72: 31–43.
-
17.
Reyes JF , Francis AR , Tanaka MM , 2008. Models of deletion for visualizing bacterial variation: an application to tuberculosis spoligotypes. BMC Bioinformatics 9: 496.
-
18.
Aandahl RZ , Bhatia S , Vaudagnotto N , Street AG , Francis AR , Tanaka MM , 2020. MERCAT: visualizing molecular epidemiology data combining genetic markers and drug resistance profiles. Infect Genet Evol 77: 104043.
-
19.
Tang C , Reyes JF , Luciani F , Francis AR , Tanaka MM , 2008. spolTools: online utilities for analyzing spoligotypes of the Mycobacterium tuberculosis complex. Bioinformatics 24: 2414–2415.
-
20.
Mears J , Abubakar I , Cohen T , McHugh TD , Sonnenberg P , 2015. Effect of study design and setting on tuberculosis clustering estimates using Mycobacterial Interspersed Repetitive Units-Variable Number Tandem Repeats (MIRU-VNTR): a systematic review. BMJ Open 5: e005636.
-
21.
Murray M , Alland D , 2002. Methodological problems in the molecular epidemiology of tuberculosis. Am J Epidemiol 155: 565–571.
-
22.
Yang C , et al.2015. Transmission of Mycobacterium tuberculosis in China: a population-based molecular epidemiology study. Clin Infect Dis 61: 219–227.
-
23.
Smith CM , Maguire H , Anderson C , Macdonald N , Hayward AC , 2017. Multiple large clusters of tuberculosis in London: a cross-sectional analysis of molecular and spatial data. ERJ Open Res 3: 00098–2016.
-
24.
Small PM , Hopewell PC , Singh SP , Paz A , Parsonnet J , Ruston DC , Schecter GF , Daley CL , Schoolnik GK , 1994. The epidemiology of tuberculosis in San Francisco. A population-based study using conventional and molecular methods. N Engl J Med 330: 1703–1709.
-
25.
King G , Zeng L , 2001. Logistic regression in rare events data. Polit Anal 9: 137–163.
-
26.
Scott AN , Menzies D , Tannenbaum TN , Thibert L , Kozak R , Joseph L , Schwartzman K , Behr MA , 2005. Sensitivities and specificities of spoligotyping and mycobacterial interspersed repetitive unit-variable-number tandem repeat typing methods for studying molecular epidemiology of tuberculosis. J Clin Microbiol 43: 89–94.
-
27.
Nava-Aguilera E , Lopez-Vidal Y , Harris E , Morales-Perez A , Mitchell S , Flores-Moreno M , Villegas-Arrizon A , Legorreta-Soberanis J , Ledogar R , Andersson N , 2011. Clustering of Mycobacterium tuberculosis cases in Acapulco: spoligotyping and risk factors. Clin Dev Immunol 2011: 408375.
-
28.
Rosales S , Pineda-Garcia L , Ghebremichael S , Rastogi N , Hoffner SE , 2010. Molecular diversity of Mycobacterium tuberculosis isolates from patients with tuberculosis in Honduras. BMC Microbiol 10: 208.
-
29.
Gori A et al.2005. Spoligotyping and Mycobacterium tuberculosis. Emerg Infect Dis 11: 1242–1248.
-
30.
Winter JR , Smith CJ , Davidson JA , Lalor MK , Delpech V , Abubakar I , Stagg HR , 2020. The impact of HIV infection on tuberculosis transmission in a country with low tuberculosis incidence: a national retrospective study using molecular epidemiology. BMC Med 18: 385.
-
31.
Mathema B , Andrews JR , Cohen T , Borgdorff MW , Behr M , Glynn JR , Rustomjee R , Silk BJ , Wood R , 2017. Drivers of tuberculosis transmission. J Infect Dis 216: S644–S653.
-
32.
Nava-Aguilera E , Andersson N , Harris E , Mitchell S , Hamel C , Shea B , Lopez-Vidal Y , Villegas-Arrizon A , Morales-Perez A , 2009. Risk factors associated with recent transmission of tuberculosis: systematic review and meta-analysis. Int J Tuberc Lung Dis 13: 17–26.
-
33.
Stucki D et al.2016. Standard genotyping overestimates transmission of Mycobacterium tuberculosis among immigrants in a low-incidence country. J Clin Microbiol 54: 1862–1870.
-
34.
Sepkowitz KA , 1996. How contagious is tuberculosis? Clin Infect Dis 23: 954–962.
-
35.
Foreman TW et al.2016. CD4+ T-cell-independent mechanisms suppress reactivation of latent tuberculosis in a macaque model of HIV coinfection. Proc Natl Acad Sci USA 113: E5636–E5644.
-
36.
Balcells ME , Garcia P , Meza P , Pena C , Cifuentes M , Couvin D , Rastogi N , 2015. A first insight on the population structure of Mycobacterium tuberculosis complex as studied by spoligotyping and MIRU-VNTRs in Santiago, Chile. PLoS One 10: e0118007.
-
37.
Woodman M , Haeusler IL , Grandjean L , 2019. Tuberculosis genetic epidemiology: a Latin American perspective. Genes (Basel) 10: 53.
-
38.
Wiens KE et al.2018. Global variation in bacterial strains that cause tuberculosis disease: a systematic review and meta-analysis. BMC Med 16: 196.
-
39.
Banuls AL , Sanou A , Anh NT , Godreuil S , 2015. Mycobacterium tuberculosis: ecology and evolution of a human bacterium. J Med Microbiol 64: 1261–1269.
-
40.
Stucki D et al.2016. Mycobacterium tuberculosis lineage 4 comprises globally distributed and geographically restricted sublineages. Nat Genet 48: 1535–1543.
-
41.
Tarashi S , Fateh A , Mirsaeidi M , Siadat SD , Vaziri F , 2017. Mixed infections in tuberculosis: the missing part in a puzzle. Tuberculosis (Edinb) 107: 168–174.
-
42.
Ssengooba W , Cobelens FG , Nakiyingi L , Mboowa G , Armstrong DT , Manabe YC , Joloba ML , de Jong BC , 2015. High genotypic discordance of concurrent Mycobacterium tuberculosis isolates from sputum and blood of HIV-infected individuals. PLoS One 10: e0132581.
-
43.
Shin SS , Modongo C , Ncube R , Sepako E , Klausner JD , Zetola NM , 2015. Advanced immune suppression is associated with increased prevalence of mixed-strain Mycobacterium tuberculosis infections among persons at high risk for drug-resistant tuberculosis in Botswana. J Infect Dis 211: 347–351.
-
44.
McIvor A , Koornhof H , Kana BD , 2017. Relapse, re-infection and mixed infections in tuberculosis disease. Pathog Dis 75: ftx020.
-
45.
Cohen T , van Helden PD , Wilson D , Colijn C , McLaughlin MM , Abubakar I , Warren RM , 2012. Mixed-strain Mycobacterium tuberculosis infections and the implications for tuberculosis treatment and control. Clin Microbiol Rev 25: 708–719.
-
46.
Jagielski T , Minias A , van Ingen J , Rastogi N , Brzostek A , Zaczek A , Dziadek J , 2016. Methodological and clinical aspects of the molecular epidemiology of Mycobacterium tuberculosis and other mycobacteria. Clin Microbiol Rev 29: 239–290.
-
47.
Delgado-Rodriguez M , Llorca J , 2004. Bias. J Epidemiol Community Health 58: 635–641.
-
48.
Van Soolingen D , 2001. Molecular epidemiology of tuberculosis and other mycobacterial infections: main methodologies and achievements. J Intern Med 249: 1–26.
-
49.
Saelens JW et al.2015. Whole genome sequencing identifies circulating Beijing-lineage Mycobacterium tuberculosis strains in Guatemala and an associated urban outbreak. Tuberculosis (Edinb) 95: 810–816.
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Characterization of the Proportion of Clustered Tuberculosis Cases in Guatemala: Insights from a Molecular Epidemiology Study, 2010–2014
ABSTRACT.
There is little information about the amount of recent tuberculosis transmission in low-income settings. Genetic clustering can help identify ongoing transmission events. A retrospective observational study was performed on Mycobacterium tuberculosis isolates from persons living with HIV (PLHIV) and HIV-seronegative participants who submitted samples to a referral tuberculosis laboratory in Guatemala City, Guatemala from 2010 to 2014. Genotyping results were classified according to the international spoligotyping database, SITVIT2. Spoligotype patterns were categorized as clustered or nonclustered depending on their genotype. The proportion of clustering and the index of recent transmission index (RTIn-1) were estimated. In the RTIn-1 method, clustered cases represent recent transmission, whereas nonclustered cases represent reactivation of older tuberculosis infections. As a secondary aim, the potential risk factors associated with clustering in isolates from the subset of participants living with HIV were explored. From 2010 to 2014, a total of 479 study participants were confirmed as culture-positive tuberculosis cases. Among the 400 available isolates, 71 spoligotype patterns were identified. Overall, the most frequent spoligotyping families were Latin American-Mediterranean (LAM) (39%), followed by T (22%) and Haarlem (14%). Out of the 400 isolates, 365 were grouped in 36 clusters (range of cluster size: 2–92). Thus, the proportion of clustering was 91% and the RTIn-1 was 82%. Among PLHIV, pulmonary tuberculosis was associated with clustering (OR = 4.3, 95% CI 1.0–17.7). Our findings suggest high levels of ongoing transmission of M. tuberculosis in Guatemala as revealed by the high proportion of isolates falling into genomic clusters.
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Author Notes
Financial support: MEC was supported by the Schlumberger Foundation Faculty, Houston, TX, for the Future Fellowship.
Authors’ addresses: María Eugenia Castellanos, Global Health Institute, College of Public Health, University of Georgia, Athens, GA, Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, and Public Health and Tropical Medicine, College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Queensland, Australia, E-mail: maria.castellanosreynosa@jcu.edu.au. Dalia Lau-Bonilla, Department of Biochemistry and Microbiology, Universidad del Valle de Guatemala, Guatemala, E-mail: dalialau@gmail.com. Anneliese Moller and Eduardo Arathoon, Asociación de Salud Integral, Guatemala City, Guatemala, E-mails: amollers.al@gmail.com and earathoon@hotmail.com. Blanca Samayoa, Asociación de Salud Integral, Guatemala City, Guatemala, and Facultad de Ciencias Químicas y Farmacia, Universidad de San Carlos de Guatemala, Guatemala, E-mail: besamayoah@gmail.com. Frederick Quinn, Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, GA, E-mail: fquinn@uga.edu. Mark Ebell and Kevin Dobbin, Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, E-mails: ebell@uga.edu and dobbinke@uga.edu. Christopher Whalen, Global Health Institute, College of Public Health, University of Georgia, Athens, GA, and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, E-mail: ccwhalen@uga.edu.