Bioinformatics Seminars

Bioinformatics Seminar

Time: 10:45am Tuesdays.
Level 7 Seminar Room 2, WEHI1

28 March 2017

Tuberculosis among the Canadian Inuit: combining epidemiology, genomics and bioinformatics to understand a public health crisis

Robyn Lee
The Peter Doherty Institute of Infection and Immunity

Between 2011-2012, there were 50 microbiologically-confirmed cases of the respiratory disease, tuberculosis (TB), in a small village in the Canadian Arctic. This represented an incidence of over 5% of the village for that year, greater than any other place in the world at the time. A previous molecular genotyping study in the Arctic suggested that there was limited strain diversity, suggestive of either a Founder effect or ongoing transmission within and between communities. Similarly, these older typing methods suggested a single clonal outbreak was occurring. To more accurately resolve transmission in this context, we applied whole genome sequencing to the outbreak, and in combination with epidemiologic data, identified ~6 different subgroups of transmission. To address the public health concern that a new, hyper-virulent strain was responsible for this event and had recently arrived in the Arctic, we then expanded this study to all Northern communities - with samples spanning over a 22-year period and revealed the same strain of TB had been circulating the North since the early 20th century. Finally, we aimed to investigate another extraordinary aspect of this outbreak: ~20% of those with recent infection were found to progress to active TB disease; it has previously been reported that ~5% will progress to disease in the first few years following infection. Our analysis found that the total number of contacts with active TB disease (or with different genotypes of TB) was most predictive of progression - potentially serving as a useful marker for developing disease in this context. These combined studies increased our understanding of TB in the Canadian North, informed regional public health interventions, and illustrate the importance of combining epidemiologic, genomic and bioinformatics approaches for infectious disease research.

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