Vinicius M. Fava, PharmD, PhD
Research Associate 
Research Institute of McGill University Health Centre
McGill University
Vinicius M. Fava, PharmD, PhD
Research Associate
Research Institute of McGill University Health Centre
McGill University

Approximately 200,000 people contract leprosy every year, making it the second most common mycobacterial disease. This is surprising, because an effective treatment exists and Mycobacterium leprae  (M. leprae), the organism that causes the disease, is only mildly infectious at best. Indeed, exposure to the slow-growing bacterium alone does not cause leprosy; disease risk depends on the interplay of several environmental and genetic factors. 

In a recent Plos Neglected Tropical Diseases article, Vinicius Fava and his colleagues in Erwin Schurr’s laboratory at McGill University showcase how deep sequencing complements genome-wide association studies (GWAS) to pinpoint mutations that protected individuals from contracting leprosy.1 To do this, the researchers compared patient genomes with those of people who encountered the bacteria but did not fall ill. These risk factors shed light on the pathways that M. leprae  hijacks to attack the body, enabling scientists to develop new ways to stop the bacterium’s spread.

How do researchers study genetic susceptibility to infectious diseases? 

We use one of two approaches: GWAS or deep sequencing. Both are very good approaches, but they test different aspects of genetic susceptibility. With GWAS, we are looking at the genome-wide level and can identify common variants, but we have low power to detect rare ones. Another challenge of GWAS is that you can identify a region that contains several genes, but you cannot distinguish which gene is linked to the phenotype. The advantage of deep sequencing is that you identify everything. You can discover novel and rare mutations that you could never discover with GWAS. But it is more expensive, so you only focus on a very narrow region.

What are some important considerations when genetic risk factors?

The most important thing is to characterize both your cases and your control group. If you study susceptibility to an infectious disease in adults, it may be caused by genetic factors that are very different than if you were studying the disease in kids or in younger adults. For polygenic diseases with multiple causative variants, you have to create the most homogeneous cohort you can, otherwise you dilute the genetic components and your genetic analysis loses power. If your case or your control group is not homogeneous, it becomes very challenging to find something that is meaningful for the disease.

How did you identify novel susceptibility genes and how could these genes influence disease risk?

We revisited previously identified GWAS loci to see if, when we look for variants that alter proteins, we could identify genes that contribute to disease. We identified four genes in three different loci.1  One gene, IL18R1, has been associated with infectious disease but also with immune-related diseases such as Crohn’s disease. The challenge to understand how this gene confers disease risk is that it has different functions: it is a pro-inflammatory cytokine, but only during the adaptive immune response, when IL-12 is present. In the absence of IL-12, IL18R1 is actually anti-inflammatory. So, it really depends on at which point of the disease pathogenesis IL18R1 is active to understand how it contributes to leprosy. Other studies have found eQTLs—noncoding mutations that increase or decrease gene levels—in IL18R1 that lower its expression and protect against leprosy. Because we found a depletion of mutations in leprosy patients compared to control, we think that IL18R1 mutations promote a pro-inflammatory innate immune response instead of dampening the anti-inflammatory response.

How do you plan to follow up on these findings?

We have to evaluate the impact of these mutations on the protein: which function do they affect, and do they improve or decrease function? We construct these mutations with CRISPR technology in cell lines that we think are important for the phenotype—usually macrophages—and then evaluate different assays to determine how these changes contribute to disease. With these studies, we try to identify mechanisms M. leprae uses to survive and proliferate. Once we identify pathways, we can see if they're drug targetable and design better treatments for the disease or new ways to reduce transmission. 

Reference

  1. V.M. Fava et al., “Deep resequencing identifies candidate functional genes in leprosy GWAS loci,” Plos Negl Trop Dis, 15(12):e0010029, 2021.
RR Logo