Genotyping and Whole-Genome Sequencing to Identify Tuberculosis Transmission to Pediatric Patients in British Columbia, Canada, 2005–2014

Guthrie, Jennifer L.; Pizzi, Andy Delli; Roth, David; Kong, Clare; Jorgensen, Danielle; Rodrigues, Mabel; Tang, Patrick; Cook, Victoria; Johnston, James C.; Gardy, Jennifer L.

doi:10.1093/infdis/jiy278

Cited by 26 publications

(24 citation statements)

References 23 publications

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“…A primary use of Mtbc WGS is the identification of recent transmission chains and its direction at high resolution. While some studies have used thresholds from 0 to <50 SNPs [109][110][111] , a threshold of 5-or 12-SNP genetic distances is most frequently used to identify possible epidemiological links and recent transmission 30,32 . For WGS-based distinction of relapse versus reinfection, studies have used often arbitrary thresholds of < 6 or <10 SNPs to define reactivation, and >100 to >1306 to define re-infection 46,112,113 .…”

Section: Variant Calling For Other Purposesmentioning

confidence: 99%

Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues

et al. 2019

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Whole genome sequencing (WGS) of Mycobacterium tuberculosis has rapidly evolved from a research tool to a clinical application for the diagnosis and management of tuberculosis and in public health surveillance. This evolution has been facilitated by the dramatic drop in costs, advances in technology, and concerted efforts to translate sequencing data into actionable information. There is however a risk that, in the absence of a consensus and international standards, the widespread use of WGS technology may result in data and processes that lack harmonisation, comparability and validation. In this review, we outline the current landscape of WGS pipelines and applications and set out best practices for M. tuberculosis WGS, including standards for bioinformatics pipelines, curated repository of resistance-causing variants, phylogenetic analyses, quality control processes, and standardised reporting. 1. Introduction Mycobacterium tuberculosis complex (Mtbc) pathogens are collectively the top infectious disease killer globally, causing 10 million new tuberculosis (TB) cases annually 1. Increasingly, 95 new TB cases are already resistant to rifampicin and isoniazid (termed multidrug resistance; 96 MDR-TB), the key first line drugs 1. Tackling the spread and drug resistance burden of this pathogen requires concerted global effort in prevention, diagnosis, treatment and surveillance.

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Section: Variant Calling For Other Purposesmentioning

confidence: 99%

Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues

et al. 2019

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“…Despite the complexity in quantifying where M tuberculosis transmission occurs in children at the population level, understanding this key question is essential to design appropriate and effective public health programmes to detect, diagnose, and treat children with tuberculosis. 13 studies [14][15][16][17][18][19][20][21][22][23][24][25][26] published between 2003 and 2018 that made use of diverse methodologies and designs shed light on this topic. This description is specific to the type of study, and is thus described for each study type in later sections.…”

Section: Epidemiological Evidence: Investigating Where Paediatric Tubmentioning

confidence: 99%

Paediatric tuberculosis transmission outside the household: challenging historical paradigms to inform future public health strategies

Martínez

Cords

et al. 2019

The Lancet Respiratory Medicine

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Tuberculosis is a major cause of death and disability among children globally, yet children have been neglected in global tuberculosis control efforts. Historically, tuberculosis in children has been thought of as a family disease, and because of this, household contact tracing of children after identification of an adult tuberculosis case has been emphasised as the principal public health intervention. However, the population-level effect of household contact tracing is predicated on the assumption that most paediatric tuberculosis infections are acquired within the household. In this Personal View, we focus on accumulating scientific evidence indicating that the majority of

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“…This is more likely, using SNP cut-offs, where selection (say for antibiotic resistance) has led to higher SNP differences than expected. In addition, in practice WGS data are not only used to refute direct transmission, but to produce clusters that inform onward analyses, reports on the extent of recent transmission, outbreak analysis and reconstruction and even public health policy; see (Guthrie et al 2018) for one example.…”

Section: Discussionmentioning

confidence: 99%

Beyond the SNP threshold: identifying outbreak clusters using inferred transmissions

Stimson

Gardy

Mathema

et al. 2018

Preprint

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Whole genome sequencing (WGS) is increasingly used to aid the understanding of pathogen transmission. A first step in analysing WGS data is usually to define "transmission clusters", sets of cases that are potentially linked by direct transmission. This is often done by including two cases in the same cluster if they are separated by fewer SNPs than a specified threshold. However, there is little agreement as to what an appropriate threshold should be. We propose a probabilistic alternative, suggesting that the key inferential target for transmission clusters is the number of transmissions separating cases. We characterise this by combining the number of SNP differences and the length of time over which those differences have accumulated, using information about case timing, molecular clock and transmission processes. Our framework has the advantage of allowing for variable mutation rates across the genome and can incorporate other epidemiological data. We use two tuberculosis studies to illustrate the impact our approach: with British Columbia data by using spatial divisions; with Republic of Moldova data by incorporating antibiotic resistance. Simulation results indicate that our transmission-based method is better at identifying direct transmissions than a SNP threshold, with dissimilarity between clusterings of on average 0.27 bits compared to 0.37 bits for the SNP threshold method and 0.84 bits for randomly permuted data. These results show that it is likely to outperform the SNP threshold where clock rates are variable and sample collection times are spread out. We implement the method in the R package transcluster.

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Genotyping and Whole-Genome Sequencing to Identify Tuberculosis Transmission to Pediatric Patients in British Columbia, Canada, 2005–2014

Abstract: Retrospective genotyping and whole-genome sequencing over a 10-year period suggested that pediatric tuberculosis in British Columbia is a mosaic and factors including age, birthplace, and travel history must all be considered together when inferring a pediatric patient’s likely exposure.

Cited by 26 publications

References 23 publications

Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues

Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues

Paediatric tuberculosis transmission outside the household: challenging historical paradigms to inform future public health strategies

Beyond the SNP threshold: identifying outbreak clusters using inferred transmissions

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