The genetics of infectious disease susceptibility: has the evidence for epistasis been overestimated?

Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia and Oceania

The human genetic factors that affect resistance to infectious disease are poorly understood. Here we report a genome-wide association study in 17,000 severe malaria cases and population controls from 11 countries, informed by sequencing of family trios and by direct typing of candidate loci in an additional 15,000 samples. We identify five replicable associations with genome-wide levels of evidence including a newly implicated variant on chromosome 6. Jointly, these variants account for around one-tenth of the heritability of severe malaria, which we estimate as ~23% using genome-wide genotypes. We interrogate available functional data and discover an erythroid-specific transcription start site underlying the known association in ATP2B4, but are unable to identify a likely causal mechanism at the chromosome 6 locus.  Previously reported HLA associations do not replicate in these samples. This large dataset will provide a foundation for further research on the genetic determinants of malaria resistance in diverse populations.

Four genome-wide associated loci are currently known for malaria susceptibility. Here, the authors expand on earlier work by combining data from 11 malaria-endemic countries and additional population sequencing informing an African-enriched imputation reference panel, with findings including a previously unreported association on chromosome 6.

Genome-wide association studies of severe P. falciparum malaria susceptibility: progress, pitfalls and prospects

Background

P. falciparum malaria has been recognized as one of the prominent evolutionary selective forces of human genome that led to the emergence of multiple host protective alleles. A comprehensive understanding of the genetic bases of severe malaria susceptibility and resistance can potentially pave ways to the development of new therapeutics and vaccines. Genome-wide association studies (GWASs) have recently been implemented in malaria endemic areas and identified a number of novel association genetic variants. However, there are several open questions around heritability, epistatic interactions, genetic correlations and associated molecular pathways among others. Here, we assess the progress and pitfalls of severe malaria susceptibility GWASs and discuss the biology of the novel variants.

Results

We obtained all severe malaria susceptibility GWASs published thus far and accessed GWAS dataset of Gambian populations from European Phenome Genome Archive (EGA) through the MalariaGen consortium standard data access protocols. We noticed that, while some of the well-known variants including HbS and ABO blood group were replicated across endemic populations, only few novel variants were convincingly identified and their biological functions remain to be understood. We estimated SNP-heritability of severe malaria at 20.1% in Gambian populations and showed how advanced statistical genetic analytic methods can potentially be implemented in malaria susceptibility studies to provide useful functional insights.

Conclusions

The ultimate goal of malaria susceptibility study is to discover a novel causal biological pathway that provide protections against severe malaria; a fundamental step towards translational medicine such as development of vaccine and new therapeutics. Beyond singe locus analysis, the future direction of malaria susceptibility requires a paradigm shift from single -omics to multi-stage and multi-dimensional integrative functional studies that combines multiple data types from the human host, the parasite, the mosquitoes and the environment. The current biotechnological and statistical advances may eventually lead to the feasibility of systems biology studies and revolutionize malaria research.

Dissecting the genetic architecture of a stepwise infection process

How a host fights infection depends on an ordered sequence of steps, beginning with attempts to prevent a pathogen from establishing an infection, through to steps that mitigate a pathogen's control of host resources or minimize the damage caused during infection. Yet empirically characterizing the genetic basis of these steps remains challenging. Although each step is likely to have a unique genetic and environmental signature, and may therefore respond to selection in different ways, events that occur earlier in the infection process can mask or overwhelm the contributions of subsequent steps. In this study, we dissect the genetic architecture of a stepwise infection process using a quantitative trait locus (QTL) mapping approach. We control for variation at the first line of defence against a bacterial pathogen and expose downstream genetic variability related to the host's ability to mitigate the damage pathogens cause. In our model, the water-flea Daphnia magna, we found a single major effect QTL, explaining 64% of the variance, that is linked to the host's ability to completely block pathogen entry by preventing their attachment to the host oesophagus; this is consistent with the detection of this locus in previous studies. In susceptible hosts allowing attachment, however, a further 23 QTLs, explaining between 5% and 16% of the variance, were mapped to traits related to the expression of disease. The general lack of pleiotropy and epistasis for traits related to the different stages of the infection process, together with the wide distribution of QTLs across the genome, highlights the modular nature of a host's defence portfolio, and the potential for each different step to evolve independently. We discuss how isolating the genetic basis of individual steps can help to resolve discussion over the genetic architecture of host resistance.

Epistatic interactions between mutations of TACI (TNFRSF13B) and TCF3 result in a severe primary immunodeficiency disorder and systemic lupus erythematosus

Common variable immunodeficiency disorders (CVID) are a group of primary immunodeficiencies where monogenetic causes account for only a fraction of cases. On this evidence, CVID is potentially polygenic and epistatic although there are, as yet, no examples to support this hypothesis. We have identified a non-consanguineous family, who carry the C104R (c.310T>C) mutation of the Transmembrane Activator Calcium-modulator and cyclophilin ligand Interactor (TACI, TNFRSF13B) gene. Variants in TNFRSF13B/TACI are identified in up to 10% of CVID patients, and are associated with, but not solely causative of CVID. The proband is heterozygous for the TNFRSF13B/TACI C104R mutation and meets the Ameratunga et al. diagnostic criteria for CVID and the American College of Rheumatology criteria for systemic lupus erythematosus (SLE). Her son has type 1 diabetes, arthritis, reduced IgG levels and IgA deficiency, but has not inherited the TNFRSF13B/TACI mutation. Her brother, homozygous for the TNFRSF13B/TACI mutation, is in good health despite profound hypogammaglobulinemia and mild cytopenias. We hypothesised that a second unidentified mutation contributed to the symptomatic phenotype of the proband and her son. Whole-exome sequencing of the family revealed a de novo nonsense mutation (T168fsX191) in the Transcription Factor 3 (TCF3) gene encoding the E2A transcription factors, present only in the proband and her son. We demonstrate mutations of TNFRSF13B/TACI impair immunoglobulin isotype switching and antibody production predominantly via T-cell-independent signalling, while mutations of TCF3 impair both T-cell-dependent and -independent pathways of B-cell activation and differentiation. We conclude that epistatic interactions between mutations of the TNFRSF13B/TACI and TCF3 signalling networks lead to the severe CVID-like disorder and SLE in the proband.

The Evolutionary Consequences of Stepwise Infection Processes

Molecular and cellular studies reveal that the resistance of hosts to parasites and pathogens is a cascade-like process with multiple steps required to be passed for successful infection. By contrast, much of evolutionary reasoning is based on strongly simplified, one- or two-step infection processes with simple genetics or on resistance being a quantitative trait. Here we attempt a conceptual unification of these two perspectives with the aim of cross-fostering research and filling some of the gaps in our concepts of the ecology and evolution of disease. This conceptual unification has a profound impact on the way we understand the genetics and evolution of host resistance, ecological immunity, evolution of virulence, defence portfolios, and host-pathogen coevolution.

Prediction and Prevention of Parasitic Diseases Using a Landscape Genomics Framework

Substantial heterogeneity exists in the dispersal, distribution and transmission of parasitic species. Understanding and predicting how such features are governed by the ecological variation of landscape they inhabit is the central goal of spatial epidemiology. Genetic data can further inform functional connectivity among parasite, host and vector populations in a landscape. Gene flow correlates with the spread of epidemiologically relevant phenotypes among parasite and vector populations (e.g., virulence, drug and pesticide resistance), as well as invasion and re-invasion risk where parasite transmission is absent due to current or past intervention measures. However, the formal integration of spatial and genetic data ('landscape genetics') is scarcely ever applied to parasites. Here, we discuss the specific challenges and practical prospects for the use of landscape genetics and genomics to understand the biology and control of parasitic disease and present a practical framework for doing so.

A Population Biology Perspective on the Stepwise Infection Process of the Bacterial Pathogen Pasteuria ramosa in Daphnia

The infection process of many diseases can be divided into series of steps, each one required to successfully complete the parasite's life and transmission cycle. This approach often reveals that the complex phenomenon of infection is composed of a series of more simple mechanisms. Here we demonstrate that a population biology approach, which takes into consideration the natural genetic and environmental variation at each step, can greatly aid our understanding of the evolutionary processes shaping disease traits. We focus in this review on the biology of the bacterial parasite Pasteuria ramosa and its aquatic crustacean host Daphnia, a model system for the evolutionary ecology of infectious disease. Our analysis reveals tremendous differences in the degree to which the environment, host genetics, parasite genetics and their interactions contribute to the expression of disease traits at each of seven different steps. This allows us to predict which steps may respond most readily to selection and which steps are evolutionarily constrained by an absence of variation. We show that the ability of Pasteuria to attach to the host's cuticle (attachment step) stands out as being strongly influenced by the interaction of host and parasite genotypes, but not by environmental factors, making it the prime candidate for coevolutionary interactions. Furthermore, the stepwise approach helps us understanding the evolution of resistance, virulence and host ranges. The population biological approach introduced here is a versatile tool that can be easily transferred to other systems of infectious disease.

Effects of epistasis on infectivity range during host-parasite coevolution

Understanding how parasites adapt to changes in host resistance is crucial to evolutionary epidemiology. Experimental studies have demonstrated that parasites are more capable of adapting to gradual, rather than sudden changes in host phenotype, as the latter may require multiple mutations that are unlikely to arise simultaneously. A key, but as yet unexplored factor is precisely how interactions between mutations (epistasis) affect parasite evolution. Here, we investigate this phenomenon in the context of infectivity range, where parasites may experience selection to infect broader sets of genotypes. When epistasis is strongly positive, we find that parasites are unlikely to evolve broader infectivity ranges if hosts exhibit sudden, rather than gradual changes in phenotype, in close agreement with empirical observations. This is due to a low probability of fixing multiple mutations that individually confer no immediate advantage. When epistasis is weaker, parasites are more likely to evolve broader infectivity ranges if hosts make sudden changes in phenotype, which can be explained by a balance between mutation supply and selection. Thus, we demonstrate that both the rate of phenotypic change in hosts and the form of epistasis between mutations in parasites are crucial in shaping the evolution of infectivity range.