#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

High-resolution mapping of tuberculosis transmission: Whole genome sequencing and phylogenetic modelling of a cohort from Valencia Region, Spain


Autoři: Yuanwei Xu aff001;  Irving Cancino-Muñoz aff002;  Manuela Torres-Puente aff002;  Luis M. Villamayor aff003;  Rafael Borrás aff004;  María Borrás-Máñez aff005;  Montserrat Bosque aff006;  Juan J. Camarena aff007;  Ester Colomer-Roig aff003;  Javier Colomina aff005;  Isabel Escribano aff008;  Oscar Esparcia-Rodríguez aff009;  Ana Gil-Brusola aff010;  Concepción Gimeno aff011;  Adelina Gimeno-Gascón aff012;  Barbará Gomila-Sard aff013;  Damiana González-Granda aff014;  Nieves Gonzalo-Jiménez aff015;  María Remedio Guna-Serrano aff011;  José Luis López-Hontangas aff010;  Coral Martín-González aff016;  Rosario Moreno-Muñoz aff013;  David Navarro aff004;  María Navarro aff017;  Nieves Orta aff018;  Elvira Pérez aff019;  Josep Prat aff020;  Juan Carlos Rodríguez aff012;  María Montserrat Ruiz-García aff014;  Herme Vanaclocha aff019;  Caroline Colijn aff001;  Iñaki Comas aff002
Působiště autorů: Centre for Mathematics of Precision Healthcare, Department of Mathematics, Imperial College London, London, United Kingdom aff001;  Instituto de Biomedicina de Valencia, Consejo Superior de Investigaciones Científicas, Valencia, Spain aff002;  Genomics and Health Unit, FISABIO Public Health, Valencia, Spain aff003;  Microbiology Service, Hospital Clínico Universitario, Valencia, Spain aff004;  Microbiology and Parasitology Service, Hospital Universitario de La Ribera, Alzira, Spain aff005;  Microbiology Service, Hospital Arnau de Vilanova, Valencia, Spain aff006;  Microbiology Service, Hospital Universitario Dr. Peset, Valencia, Spain aff007;  Microbiology Laboratory, Hospital Virgen de los Lírios, Alcoy, Spain aff008;  Microbiology Service, Hospital de Denia, Denia, Spain aff009;  Microbiology Service, Hospital Universitari i Politècnic La Fe, Valencia, Spain aff010;  Microbiology Service, Hospital General Universitario de Valencia, Valencia, Spain aff011;  Microbiology Service, Hospital General Universitario de Alicante, Alicante, Spain aff012;  Microbiology Service, Hospital General Universitario de Castellón, Castellon, Spain aff013;  Microbiology Service, Hospital Lluís Alcanyis, Xativa, Spain aff014;  Microbiology Service, Hospital General Universitario de Elche, Elche, Spain aff015;  Microbiology Service, Hospital Universitario de San Juan de Alicante, Alicante, Spain aff016;  Microbiology Service, Hospital de la Vega Baixa, Orihuela, Spain aff017;  Microbiology Service, Hospital San Francesc de Borja, Gandía, Spain aff018;  Subdirección General de Epidemiología y Vigilancia de la Salud, Dirección General de Salud Pública, Valencia, Spain aff019;  Microbiology Service, Hospital de Sagunto, Sagunto, Spain aff020;  Department of Mathematics, Simon Fraser University, Burnaby, British Columbia, Canada aff021
Vyšlo v časopise: High-resolution mapping of tuberculosis transmission: Whole genome sequencing and phylogenetic modelling of a cohort from Valencia Region, Spain. PLoS Med 16(10): e32767. doi:10.1371/journal.pmed.1002961
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pmed.1002961

Souhrn

Background

Whole genome sequencing provides better delineation of transmission clusters in Mycobacterium tuberculosis than traditional methods. However, its ability to reveal individual transmission links within clusters is limited. Here, we used a 2-step approach based on Bayesian transmission reconstruction to (1) identify likely index and missing cases, (2) determine risk factors associated with transmitters, and (3) estimate when transmission happened.

Methods and findings

We developed our transmission reconstruction method using genomic and epidemiological data from a population-based study from Valencia Region, Spain. Tuberculosis (TB) incidence during the study period was 8.4 cases per 100,000 people. While the study is ongoing, the sampling frame for this work includes notified TB cases between 1 January 2014 and 31 December 2016. We identified a total of 21 transmission clusters that fulfilled the criteria for analysis. These contained a total of 117 individuals diagnosed with active TB (109 with epidemiological data). Demographic characteristics of the study population were as follows: 80/109 (73%) individuals were Spanish-born, 76/109 (70%) individuals were men, and the mean age was 42.51 years (SD 18.46). We found that 66/109 (61%) TB patients were sputum positive at diagnosis, and 10/109 (9%) were HIV positive. We used the data to reveal individual transmission links, and to identify index cases, missing cases, likely transmitters, and associated transmission risk factors. Our Bayesian inference approach suggests that at least 60% of index cases are likely misidentified by local public health. Our data also suggest that factors associated with likely transmitters are different to those of simply being in a transmission cluster, highlighting the importance of differentiating between these 2 phenomena. Our data suggest that type 2 diabetes mellitus is a risk factor associated with being a transmitter (odds ratio 0.19 [95% CI 0.02–1.10], p < 0.003). Finally, we used the most likely timing for transmission events to study when TB transmission occurred; we identified that 5/14 (35.7%) cases likely transmitted TB well before symptom onset, and these were largely sputum negative at diagnosis. Limited within-cluster diversity does not allow us to extrapolate our findings to the whole TB population in Valencia Region.

Conclusions

In this study, we found that index cases are often misidentified, with downstream consequences for epidemiological investigations because likely transmitters can be missed. Our findings regarding inferred transmission timing suggest that TB transmission can occur before patient symptom onset, suggesting also that TB transmits during sub-clinical disease. This result has direct implications for diagnosing TB and reducing transmission. Overall, we show that a transition to individual-based genomic epidemiology will likely close some of the knowledge gaps in TB transmission and may redirect efforts towards cost-effective contact investigations for improved TB control.

Klíčová slova:

Epidemiology – Genetic networks – Infectious disease control – Infectious disease epidemiology – Medical risk factors – Phylogenetic analysis – Tuberculosis – Tuberculosis diagnosis and management


Zdroje

1. Lönnroth K, Migliori GB, Abubakar I, D’Ambrosio L, de Vries G, Diel R, et al. Towards tuberculosis elimination: an action framework for low-incidence countries. Eur Respir J. 2015;45:928–52. doi: 10.1183/09031936.00214014 25792630

2. Barry CE 3rd, Boshoff HI, Dartois V, Dick T, Ehrt S, Flynn J, et al. The spectrum of latent tuberculosis: rethinking the biology and intervention strategies. Nat Rev Microbiol. 2009;7:845. doi: 10.1038/nrmicro2236 19855401

3. Drain PK, Bajema KL, Dowdy D, Dheda K, Naidoo K, Schumacher SG, et al. Incipient and subclinical tuberculosis: a clinical review of early stages and progression of infection. Clin Microbiol Rev. 2018;31:e00021–18. doi: 10.1128/CMR.00021-18 30021818

4. Lin PL, Flynn JL. The end of the binary era: revisiting the spectrum of tuberculosis. J Immunol. 2018;201:2541–8. doi: 10.4049/jimmunol.1800993 30348659

5. Wyllie DH, Davidson JA, Grace Smith E, Rathod P, Crook DW, Peto TEA, et al. A quantitative evaluation of MIRU-VNTR typing against whole-genome sequencing for identifying Mycobacterium tuberculosis transmission: a prospective observational cohort study. EBioMedicine. 2018;34:122–30. doi: 10.1016/j.ebiom.2018.07.019 30077721

6. Hatherell H-A, Colijn C, Stagg HR, Jackson C, Winter JR, Abubakar I. Interpreting whole genome sequencing for investigating tuberculosis transmission: a systematic review. BMC Med. 2016;14:21. doi: 10.1186/s12916-016-0566-x 27005433

7. Gardy JL, Johnston JC, Sui SJH, Cook VJ, Shah L, Brodkin E, et al. Whole-genome sequencing and social-network analysis of a tuberculosis outbreak. N Engl J Med. 2011;364:730–9. doi: 10.1056/NEJMoa1003176 21345102

8. Roetzer A, Diel R, Kohl TA, Rückert C, Nübel U, Blom J, et al. Whole genome sequencing versus traditional genotyping for investigation of a Mycobacterium tuberculosis outbreak: a longitudinal molecular epidemiological study. PLoS Med. 2013;10(2): e1001387. doi: 10.1371/journal.pmed.1001387 23424287

9. Stucki D, Ballif M, Bodmer T, Coscolla M, Maurer A-M, Droz S, et al. Tracking a tuberculosis outbreak over 21 years: strain-specific single-nucleotide polymorphism typing combined with targeted whole-genome sequencing. J Infect Dis. 2015;211:1306–16. doi: 10.1093/infdis/jiu601 25362193

10. Folkvardsen DB, Norman A, Andersen ÅB, Rasmussen EM, Jelsbak L, Lillebaek T. Genomic epidemiology of a major Mycobacterium tuberculosis outbreak: retrospective cohort study in a low-incidence setting using sparse time-series sampling. J Infect Dis. 2017;216:366–74. doi: 10.1093/infdis/jix298 28666374

11. van Soolingen D. Whole-genome sequencing of Mycobacterium tuberculosis as an epidemiological marker. Lancet Respir Med. 2014;2:251–2. doi: 10.1016/S2213-2600(14)70049-9 24717616

12. Guerra-Assunção J, Crampin A, Houben R, Mzembe T, Mallard K, Coll F, et al. Large-scale whole genome sequencing of M. tuberculosis provides insights into transmission in a high prevalence area. Elife. 2015;4:e05166.

13. Wood DE, Salzberg SL. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol. 2014;15:R46. doi: 10.1186/gb-2014-15-3-r46 24580807

14. Comas I, Coscolla M, Luo T, Borrell S, Holt KE, Kato-Maeda M, et al. Out-of-Africa migration and Neolithic coexpansion of Mycobacterium tuberculosis with modern humans. Nat Genet. 2013;45:1176–82. doi: 10.1038/ng.2744 23995134

15. Feuerriegel S, Schleusener V, Beckert P, Kohl TA, Miotto P, Cirillo DM, et al. PhyResSE: a web tool delineating Mycobacterium tuberculosis antibiotic resistance and lineage from whole-genome sequencing data. J Clin Microbiol. 2015;53:1908–14. doi: 10.1128/JCM.00025-15 25854485

16. Miotto P, Tessema B, Tagliani E, Chindelevitch L, Starks AM, Emerson C, et al. A standardised method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis. Eur Respir J. 2017;50:1701354. doi: 10.1183/13993003.01354-2017 29284687

17. Cancino-Muñoz I, Moreno-Molina M, Furió V, Goig GA, Torres-Puente M, Chiner-Oms Á, et al. Cryptic resistance mutations associated with misdiagnoses of multidrug-resistant tuberculosis. J Infect Dis. 2019;220:316–20. doi: 10.1093/infdis/jiz104 30875421

18. Chiner-Oms Á, Sánchez-Busó L, Corander J, Gagneux S, Harris SR, Young D, et al. Genomic determinants of speciation and spread of the Mycobacterium tuberculosis complex. Sci Adv. 2019;5:eaaw3307. doi: 10.1126/sciadv.aaw3307 31448322

19. Meehan CJ, Goig GA, Kohl TA, Verboven L, Dippenaar A, Ezewudo M, et al. Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues. Nat Rev Microbiol. 2019;17:533–45. doi: 10.1038/s41579-019-0214-5 31209399

20. Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30:1312–3. doi: 10.1093/bioinformatics/btu033 24451623

21. Comas I, Homolka S, Niemann S, Gagneux S. Genotyping of genetically monomorphic bacteria: DNA sequencing in Mycobacterium tuberculosis highlights the limitations of current methodologies. PLoS ONE. 2009;4(11): e7815. doi: 10.1371/journal.pone.0007815 19915672

22. Leigh JW, Bryant D. POPART: full-feature software for haplotype network reconstruction. Methods Ecol Evol. 2015;6:1110–6.

23. Duchêne S, Holt KE, Weill F-X, Le Hello S, Hawkey J, Edwards DJ, et al. Genome-scale rates of evolutionary change in bacteria. Microb Genomics. 2016;2:e000094.

24. Volz EM, Frost SDW. Scalable relaxed clock phylogenetic dating. Virus Evol. 2017;3:vex025. doi: 10.1093/ve/vex025

25. Menardo F, Duchêne S, Brites D, Gagneux S. The molecular clock of Mycobacterium tuberculosis. PLoS Pathog. 2019;15(9): e1008067. doi: 10.1371/journal.ppat.1008067 31513651

26. Didelot X, Fraser C, Gardy J, Colijn C. Genomic infectious disease epidemiology in partially sampled and ongoing outbreaks. Mol Biol Evol. 2017;34:997–1007. doi: 10.1093/molbev/msw275 28100788

27. Merker M, Barbier M, Cox H, Rasigade J-P, Feuerriegel S, Kohl TA, et al. Compensatory evolution drives multidrug-resistant tuberculosis in Central Asia. Elife. 2018;7:e38200. doi: 10.7554/eLife.38200 30373719

28. Rodrigo T, Caylà JA, García de Olalla P, Galdós-Tangüis H, Jansà JM, Miranda P, et al. Characteristics of tuberculosis patients who generate secondary cases. Int J Tuberc Lung Dis. 1997;1:352–7. 9432392

29. Comas I, Gardy JL. TB Transmission: closing the gaps. EBioMedicine. 2018;34:4–5. doi: 10.1016/j.ebiom.2018.07.020 30072212

30. Jajou R, Neeling A de, Hunen R van, Vries G de, Schimmel H, Mulder A, et al. Epidemiological links between tuberculosis cases identified twice as efficiently by whole genome sequencing than conventional molecular typing: a population-based study. PLoS ONE. 2018;13(4):e0195413. doi: 10.1371/journal.pone.0195413 29617456

31. Fox GJ, Nhung NV, Sy DN, Hoa NLP, Anh LTN, Anh NT, et al. Household-contact investigation for detection of tuberculosis in Vietnam. N Engl J Med. 2018;378:221–9. doi: 10.1056/NEJMoa1700209 29342390

32. Stimson J, Gardy J, Mathema B, Crudu V, Cohen T, Colijn C. Beyond the SNP threshold: identifying outbreak clusters using inferred transmissions. Mol Biol Evol. 2019;36:587–603. doi: 10.1093/molbev/msy242 30690464

33. Walker TM, Lalor MK, Broda A, Ortega LS, Morgan M, Parker L, et al. Assessment of Mycobacterium tuberculosis transmission in Oxfordshire, UK, 2007–12, with whole pathogen genome sequences: an observational study. Lancet Respir Med. 2014;2:285–92. doi: 10.1016/S2213-2600(14)70027-X 24717625

34. Glynn JR, Guerra-Assunção JA, Houben RMGJ, Sichali L, Mzembe T, Mwaungulu LK, et al. Whole genome sequencing shows a low proportion of tuberculosis disease is attributable to known close contacts in rural Malawi. PLoS ONE. 2015;10(7):e0132840. doi: 10.1371/journal.pone.0132840 26181760

35. Yang C, Lu L, Warren JL, Wu J, Jiang Q, Zuo T, et al. Internal migration and transmission dynamics of tuberculosis in Shanghai, China: an epidemiological, spatial, genomic analysis. Lancet Infect Dis. 2018;18:788–95. doi: 10.1016/S1473-3099(18)30218-4 29681517

36. Behr M, Warren S, Salamon H, Hopewell P, de Leon AP, Daley C, et al. Transmission of Mycobacterium tuberculosis from patients smear-negative for acid-fast bacilli. Lancet. 1999;353:444–9. doi: 10.1016/s0140-6736(98)03406-0 9989714

37. Tostmann A, Kik SV, Kalisvaart NA, Sebek MM, Verver S, Boeree MJ, et al. Tuberculosis transmission by patients with smear-negative pulmonary tuberculosis in a large cohort in the Netherlands. Clin Infect Dis. 2008;47:1135–42. doi: 10.1086/591974 18823268

38. Klinkenberg D, Backer JA, Didelot X, Colijn C, Wallinga J. Simultaneous inference of phylogenetic and transmission trees in infectious disease outbreaks. PLoS Comput Biol. 2017;13(5):e1005495. doi: 10.1371/journal.pcbi.1005495 28545083

39. Hall M, Woolhouse M, Rambaut A. Epidemic reconstruction in a phylogenetics framework: transmission trees as partitions of the node set. PLoS Comput Biol. 2016;11:e1004613. doi: 10.1371/journal.pcbi.1004613 26717515

40. De Maio N, Wu C-H, Wilson DJ. SCOTTI: efficient reconstruction of transmission within outbreaks with the structured coalescent. PLoS Comput Biol. 2016;12(12):e1005130. doi: 10.1371/journal.pcbi.1005130 27681228

41. Campbell F, Strang C, Ferguson N, Cori A, Jombart T. When are pathogen genome sequences informative of transmission events? PLoS Pathog. 2018;14(2):e1006885. doi: 10.1371/journal.ppat.1006885 29420641

42. Esmail H, Dodd PJ, Houben RMGJ. Tuberculosis transmission during the subclinical period: could unrelated cough play a part? Lancet Respir Med. 2018;6:244–6. doi: 10.1016/S2213-2600(18)30105-X 29595504

43. Houben RMGJ, Esmail H, Emery JC, Joslyn LR, McQuaid CF, Menzies NA, et al. Spotting the old foe—revisiting the case definition for TB. Lancet Respir Med. 2019;7:199–201. doi: 10.1016/S2213-2600(19)30038-4 30823971

44. Dowdy DW, Basu S, Andrews JR. Is passive diagnosis enough?: The impact of subclinical disease on diagnostic strategies for tuberculosis. Am J Respir Crit Care Med. 2013;187:543–51. doi: 10.1164/rccm.201207-1217OC 23262515

Štítky
Interní lékařství

Článek vyšel v časopise

PLOS Medicine


2019 Číslo 10
Nejčtenější tento týden
Nejčtenější v tomto čísle
Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

Svět praktické medicíny 1/2024 (znalostní test z časopisu)
nový kurz

Koncepce osteologické péče pro gynekology a praktické lékaře
Autoři: MUDr. František Šenk

Sekvenční léčba schizofrenie
Autoři: MUDr. Jana Hořínková

Hypertenze a hypercholesterolémie – synergický efekt léčby
Autoři: prof. MUDr. Hana Rosolová, DrSc.

Význam metforminu pro „udržitelnou“ terapii diabetu
Autoři: prof. MUDr. Milan Kvapil, CSc., MBA

Všechny kurzy
Kurzy Podcasty Doporučená témata Časopisy
Přihlášení
Zapomenuté heslo

Zadejte e-mailovou adresu, se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se

#ADS_BOTTOM_SCRIPTS#