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bioRxiv2018

Response to Problems in interpreting and using GWAS of conditional phenotypes illustrated by alcohol GWAS

Introduction Introduction Methods Results Discussion References In recent correspondence, Holmes and Davey Smith highlight Problems in interpreting and using GWAS of conditional phenotypes illustrated by alcohol GWAS1. The authors suggest that a negative genetic correlation between BMI and alcohol consumption, which we previously reported in the UK Biobank sample, is spurious2. In regards to the approach we used to run our genome-wide association study (GWAS) of alcohol consumption adjusted for age and weight, the authors state that the negative genetic correlation with BMI was induced by the very nature of their statistical model. We agree that their commentary highlights a potential difficulty in epidemiological research. Conditioning a test of ...

genetics↗

bioRxiv2018

MinION sequencing enables rapid whole genome assembly of Rickettsia typhi in a resource-limited setting

The infrastructure challenges and costs of next-generation sequencing have been largely overcome, for many sequencing applications, by Oxford Nanopore Technologies portable MinION sequencer. However the question remains open whether MinION-based bacterial whole-genome sequencing (WGS) is by itself sufficient for the accurate assessment of phylogenetic and epidemiological relationships between isolates and whether such tasks can be undertaken in resource-limited settings. To investigate this question, we sequenced the genome of an isolate of Rickettsia typhi, an important and neglected cause of fever across much of the tropics and subtropics, for which only three genomic sequences previously existed. We prepared and sequenced libraries on a MinION in Vientiane, Lao PDR using v9.5 chemistry and in parallel we sequenced the same isolate on the Illumina platform in a genomics laboratory in the UK. The MinION sequence reads yielded a single contiguous assembly, in which the addition of Illumina data revealed 226 base-substitution and 5,856 in/del errors. The combined assembly represents the first complete genome sequence of a human R. typhi isolate collected in the last 50 years and differed from the genomes of existing strains collected over a 90-year time period at very few sites, and with no re-arrangements. Filtering based on the known error profile of MinION data improved the accuracy of the Nanopore-only assembly. However, the frequency of false-positive errors remained greater than true sequence divergence from recorded sequences. While Nanopore-only sequencing cannot yet recover phylogenetic signal in R. typhi, such an approach may be applicable for more diverse organisms.

genomics↗

bioRxiv2018

The Influence Of Social Behavior On Selection and Spread of Virulent Pathogen Strains

1Infectious disease interventions like contact precautions and vaccination have proven effective in disease control and elimination. The priority given to interventions can depend strongly on how virulent the pathogen is, and interventions may also depend partly for their success on social processes that respond adaptively to disease dynamics. However, mathematical models of competition between pathogen strains with differing natural history profiles typically assume that human behaviour is fixed. Here, our objective is to model the influence of social behaviour on the competition between pathogen strains with differing virulence. We couple a compartmental Susceptible-Infectious-Recovered model for a resident pathogen strain and a mutant strain with higher virulence, with a differential equation of a population where individuals learn to adopt protective behaviour from others according to the prevalence of infection of the two strains and the perceived severity of the respective strains in the population. We perform invasion analysis, time series analysis and phase plane analysis to show that perceived severities of pathogen strains and the efficacy of infection control against them can greatly impact the invasion of more virulent strain. We demonstrate that adaptive social behaviour enables invasion of the mutant strain under plausible epidemiological scenarios, even when the mutant strain has a lower basic reproductive number than the resident strain. Surprisingly, in some situations, increasing the perceived severity of the resident strain can facilitate invasion of the more virulent mutant strain. Our results demonstrate that for certain applications, it may be necessary to include adaptive social behaviour in models of the emergence of virulent pathogens, so that the models can better assist public health efforts to control infectious diseases.

evolutionary biology↗

bioRxiv2018

Viral Fitness Across a Continuum from Lysis to Latency

The prevailing paradigm in ecological studies of viruses and their microbial hosts is that the reproductive success of viruses depends on the proliferation of the \"predator\", i.e., the virus particle. Yet, viruses are obligate intracellular parasites, and the virus genome - the actual unit of selection - can persist and proliferate from one cell generation to the next without lysis or the production of new virus particles. Here, we propose a theoretical framework to quantify the invasion fitness of viruses using an epidemiological cell-centric metric that focuses on the proliferation of viral genomes inside cells instead of virus particles outside cells. This cell-centric metric enables direct comparison of viral strategies characterized by obligate killing of hosts (e.g., via lysis), persistence of viral genomes inside hosts (e.g., via lysogeny), and strategies along a continuum between these extremes (e.g., via chronic infections). As a result, we can identify environmental drivers, life history traits, and key feedbacks that govern variation in viral propagation in nonlinear population models. For example, we identify threshold conditions given relatively low densities of susceptible cells and relatively high growth rates of infected cells in which lysogenic and other chronic strategies have higher potential viral reproduction than lytic strategies. Altogether, the theoretical framework helps unify the ongoing study of eco-evolutionary drivers of viral strategies in natural environments.

ecology↗

bioRxiv2018

FAVITES: simultaneous simulation of transmission networks, phylogenetic trees, and sequences

MotivationThe ability to simulate epidemics as a function of model parameters allows insights that are unobtainable from real datasets. Further, reconstructing transmission networks for fast-evolving viruses like HIV may have the potential to greatly enhance epidemic intervention, but transmission network reconstruction methods have been inadequately studied, largely because it is difficult to obtain \"truth\" sets on which to test them and properly measure their performance.\n\nResultsWe introduce FAVITES, a robust framework for simulating realistic datasets for epidemics that are caused by fast-evolving pathogens like HIV. FAVITES creates a generative model to produce contact networks, transmission networks, phylogenetic trees, and sequence datasets, and to add error to the data. FAVITES is designed to be extensible by dividing the generative model into modules, each of which is expressed as a fixed API that can be implemented using various models. We use FAVITES to simulate HIV datasets and study the realism of the simulated datasets. We then use the simulated data to study the impact of the increased treatment efforts on epidemiological outcomes. We also study two transmission network reconstruction methods and their effectiveness in detecting fast-growing clusters.\n\nAvailability and implementationFAVITES is available at https://github.com/niemasd/FAVITES, and a Docker image can be found on DockerHub (https://hub.docker.com/r/niemasd/favites).

bioinformatics↗

bioRxiv2018

Rapid Identification of Stable Clusters in Bacterial Populations Using the Adjusted Wallace Coefficient

Whole-genome sequencing (WGS) of microbial pathogens has become an essential part of modern epidemiological investigations. Although WGS data can be analyzed using a number of different approaches, such as traditional phylogenetic methods, a critical requirement for global systems for pathogen surveillance is the development of approaches for transforming sequence data into WGS-based subtypes, which creates a nomenclature that describes their higher-order relationships to one another. To this end, subtype similarity thresholds are needed to define clusters of subtypes representing lineages of interest. WGS-based subtyping presents a challenge since both the addition of novel genome sequences and small adjustments in similarity thresholds can have a dramatic impact on cluster composition and stability. We present the Neighbourhood Adjusted Wallace Coefficient (nAWC), a method for evaluating cluster stability based on computing cluster concordance between neighbouring similarity thresholds. The nAWC can be used to identify areas in in which distance thresholds produce robust clusters. Using datasets from Salmonella enterica and Campylobacter jejuni, representing strongly and weakly clonal bacterial species respectively, we show that clusters generated using such thresholds are both stable and reflect basic units in their overall population structure. Our results suggest that the nAWC could be useful for defining robust clusters compatible with nomenclatures for global WGS-based surveillance networks, which require stable clusters to be defined that both harness the discriminatory power of WGS data while allowing for long-term tracking of strains of interest.

genomics↗

bioRxiv2018

Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry

One in four adults worldwide are either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, is most informative for predicting risk of obesity sequellae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio adjusted for BMI (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.

genetics↗

bioRxiv2018

BGEN: a binary file format for imputed genotype and haplotype data

The impact of modern technology on genetic epidemiology has been significant, with studies comprising millions of individuals assessed at tens of millions of genetic variants now becoming common. Studies on this scale provide logistical and analytic challenges starting with the issue of efficiently storing, transmitting, and accessing underlying data. Here we present a binary file format (the BGEN format) that can store both directly-typed and statistically imputed genotype data, and achieves substantial space savings by data compression and the use of an efficient representation for probabilities. We investigate the properties of this format using imputed data from the UK BiLEVE study, demonstrating both storage efficiency, and fast data loading performance on the order of hundreds of millions of imputed genotypes per second. To make using BGEN as easy as possible, we provide a detailed specification and a freely available reference implementation, and we leverage this by developing additional tools including an indexing tool (bgenix) and an R package (rbgen) that permits loading of BGEN-encoded data into the R statistical programming environment. The UK Biobank is one of a number of projects that have used BGEN for release of imputed data, and we expect the format to continue to be widely implemented and used.

bioinformatics↗

bioRxiv2018

Discovery of a Streptococcus pneumoniae serotype 33F capsular polysaccharide locus that lacks wcjE and contains a wcyO pseudogene

ObjectivesAs part of large on-going vaccine impact studies in Fiji and Mongolia, we identified 25/2750 (0.9%) of nasopharyngeal swabs by microarray that were positive for Streptococcus pneumoniae contained pneumococci with a divergent 33F capsular polysaccharide locus (designated 33F-1). We investigated the 33F-1 capsular polysaccharide locus to better understand the genetic variation and its potential impact on serotyping results.\n\nMethodsWhole genome sequencing was conducted on ten 33F-1 pneumococcal isolates. Initially, sequence reads were used for molecular serotyping by PneumoCaT. Phenotypic typing of 33F-1 isolates was then performed using the Quellung reaction and latex agglutination. Genome assemblies were used in phylogenetic analyses of each gene in the capsular locus to investigate genetic divergence.\n\nResultsAll ten pneumococcal isolates with the 33F-1 cps locus typed as 33F by Quellung and latex agglutination. Unlike the reference 33F capsule locus sequence, DNA microarray and PneumoCaT analyses found that 33F-1 pneumococci lack the wcjE gene, and instead contain wcyO with a frameshift mutation. Phylogenetic analyses found the wzg, wzh, wzd, wze, wchA, wciG and glf genes in the 33F-1 cps locus had higher DNA sequence similarity to homologues from other serotypes than to the 33F reference sequence.\n\nConclusionsWe have discovered a novel genetic variant of serotype 33F, which lacks wcjE and contains a wcyO pseudogene. This finding adds to the understanding of molecular epidemiology of pneumococcal serotype diversity, which is poorly understood in low and middle-income countries.

microbiology↗

bioRxiv2018

Azithromycin resistance through interspecific acquisition of an epistasis dependent efflux pump component and transcriptional regulator in Neisseria gonorrhoeae

Mosaic interspecifically acquired alleles of the multiple transferable resistance (mtr) efflux pump operon correlate with reduced susceptibility to azithromycin in Neisseria gonorrhoeae in epidemiological studies. However, whether and how these alleles cause resistance is unclear. Here, we use population genomics, transformations, and transcriptional analyses to dissect the relationship between variant mtr alleles and azithromycin resistance. We find that the locus encompassing the mtrR transcriptional repressor and the mtrCDE pump is a hotspot of interspecific recombination introducing alleles from N. meningitidis and N. lactamica into N. gonorrhoeae, with multiple rare haplotypes in linkage disequilibrium at mtrD and the mtr promoter region. Transformations demonstrated that resistance is mediated through epistasis between these two loci and that the full length of the mosaic mtrD allele is required. Gene expression profiling revealed the mechanism of resistance in mosaics couples the novel mtrDalleles with promoter mutations enhancing expression of the pump. Overall, our results demonstrate that epistatic interactions at mtr gained from multiple Neisseria has contributed to azithromycin resistance in the gonococcal population.\n\nAUTHOR SUMMARYNeisseria gonorrhoeae is the sexually transmitted bacterial pathogen responsible for over 100 million cases of gonorrhea worldwide each year. The incidence of reduced susceptibility to the macrolide class antibiotic azithromycin has increased in the past decade; however, a large proportion of the genetic basis of resistance to this drug remains unexplained. Recently, resistance has been shown to be highly associated with mosaic alleles of the multiple transferable resistance (mtr) efflux pump, which have been gained via horizontal gene exchange with other Neisseria. However, if and how these alleles caused resistance was unknown. Here, we demonstrate that resistance has been gained through epistasis between mtrD and the mtr promoter region using evidence from both population genomics and experimental genetic manipulation. Epistasis also acts within the mtrD locus alone, requiring the full length of the gene for phenotypic resistance. Transcriptomic profiling indicates that the mechanism of resistance in mosaics is likely derived from both structural changes to mtrD, coupled with promoter mutations that result in regulatory changes to mtrCDE.

microbiology↗

bioRxiv2018

Xpert Ultra can unambiguously identify specific rifampicin resistance-conferring mutations

Introduction Introduction Methods Microorganisms Results Conclusions References The deluge of data produced by XpertMTB/RIF (Cepheid) can help improve global rifampicin-resistant tuberculosis (RR-TB) control strategies through molecular epidemiological surveillance (1, 2). Recently, a new version of the test - Xpert Ultra (hereinafter called Ultra) was released (3). Determining the relationship between RR-conferring rpoB mutations, Ultra probes, and melting temperature shifts ({Delta}Tm) - the difference between mutant and wildtype melting temperatures - allows Ultra results to be utilized for rapid detection of RR-TB strains and related underlying rpoB mutations. ...

microbiology↗

bioRxiv2018

A single pair of leucokinin neurons are modulated by feeding state and regulate sleep-metabolism interactions

Dysregulation of sleep and feeding has widespread health consequences. Despite extensive epidemiological evidence for interactions between sleep and metabolic function, little is known about the neural or molecular basis underlying the integration of these processes. Drosophila melanogaster potently suppress sleep in response to starvation, and powerful genetic tools allow for mechanistic investigation of sleep-metabolism interactions. We have previously identified neurons expressing the neuropeptide leucokinin (Lk) as being required for starvation-mediated changes in sleep. Here, we demonstrate an essential role for Lk neuropeptide in metabolic regulation of sleep. Further, we find that the activity of Lk neurons is modulated by feeding state and circulating nutrients, with reduced activity in response to glucose and increased activity under starvation conditions. Both genetic silencing and laser-mediated microablation localize Lk-mediated sleep regulation to a single pair of Lk neurons within the lateral horn (LHLK) that project near primary sleep and metabolic centers of the brain. A targeted screen identified a critical role for AMP-activated protein kinase (AMPK) in starvation-modulated changes in sleep. Disruption of AMPK function in Lk neurons suppresses sleep and increases LHLK activity in fed flies, phenocopying the starvation state. Taken together, these findings localize feeding state-dependent regulation of sleep to a single pair of neurons within the fruit fly brain and provide a system for investigating the cellular basis of sleep-metabolism interactions.

neuroscience↗

bioRxiv2018

Genomic determinants of sympatric speciation of the Mycobacterium tuberculosis complex across evolutionary timescales.

BACKGROUNDModels on how bacterial lineages differentiate increase our understanding on early bacterial speciation events and about the genetic loci involved. Here, we analyze the population genomics events leading to the emergence of the tuberculosis pathogen.\n\nRESULTSThe emergence is characterized by a combination of recombination events involving core pathogenesis functions and purifying selection on early diverging loci. We identify the phoR gene, the sensor kinase of a two-component system involved in virulence, as a key functional player subject to pervasive positive selection after the divergence of the MTBC from its ancestor. Previous evidence showed that phoR mutations played a central role in the adaptation of the pathogen to different host species. Now we show that phoR have been under selection during the early spread of human tuberculosis, during later expansions and in on-going transmission events.\n\nCONCLUSIONSOur results show that linking pathogen evolution across evolutionary and epidemiological timescales point to past and present virulence determinants.

evolutionary biology↗

bioRxiv2018

Combining landscape genomics and ecological modelling to investigate local adaptation of indigenous Ugandan cattle to East Coast fever

East Coast fever (ECF) is a fatal sickness affecting cattle populations of eastern, central, and southern Africa. The disease is transmitted by the tick Rhipicephalus appendiculatus, and caused by the protozoan Theileria parva parva, which invades host lymphocytes and promotes their clonal expansion. Importantly, indigenous cattle show tolerance to infection in ECF-endemically stable areas. Here, the putative genetic bases underlying ECF-tolerance were investigated using molecular data and epidemiological information from 823 indigenous cattle from Uganda. Vector distribution and host infection risk were estimated over the study area and subsequently tested as triggers of local adaptation by means of landscape genomics analysis. We identified 41 and seven candidate adaptive loci for tick resistance and infection tolerance, respectively. Among the genes associated with the candidate adaptive loci are PRKG1 and SLA2. PRKG1 was already described as associated with tick resistance in indigenous South African cattle, due to its role into inflammatory response. SLA2 is part of the regulatory pathways involved into lymphocytes proliferation. Additionally, local ancestry analysis suggested the zebuine origin of the genomic region candidate for tick resistance.\n\nAuthor summaryThe tick-borne parasite Theileria parva parva infects cattle populations of eastern, central and southern Africa, by causing a highly fatal pathology called \"East Coast fever\". The disease is especially severe for the exotic breeds imported to Africa, as well as outside the endemic areas of East Africa. In these regions, indigenous cattle populations can survive to infection, and this tolerance might result from unique adaptations evolved to fight the disease. We investigated this hypothesis by using a method named \"landscape genomics\", with which we compared the genetic characteristics of indigenous Ugandan cattle coming from areas at different infection risk, and located genomic sites potentially attributable to tolerance. In particular, the method pinpointed two genes, one (PRKG1) involved into inflammatory response and potentially affecting East Coast fever vector attachment, the other (SLA2) involved into lymphocytes proliferation, a process activated by T. parva parva infection. Our findings can orientate future research on the genetic basis of East Coast fever-tolerance, and derive from a general method that can be applied to investigate adaptation in analogous host-vector-parasite systems. Characterization of the genetic factors underlying East Coast-fever-tolerance represents an essential step towards enhancing sustainability and productivity of local agroecosystems.

evolutionary biology↗

bioRxiv2018

Trans-ethnic polygenic analysis supports genetic overlaps of lumbar disc degeneration with height, body mass index, and bone mineral density

Lumbar disc degeneration (LDD) is age-related break-down in the fibrocartilaginous joints between lumbar vertebrae. It is a major cause of low back pain and is conventionally assessed by magnetic resonance imaging (MRI). Like most other complex traits, LDD is likely polygenic and influenced by both genetic and environmental factors. However, genome-wide association studies (GWASs) of LDD have uncovered few susceptibility loci due to the limited sample size. Previous epidemiology studies of LDD also reported multiple heritable risk factors, including height, body mass index (BMI), bone mineral density (BMD), lipid levels, etc. Genetics can help elucidate causality between traits and suggest loci with pleiotropic effects. One such approach is polygenic score (PGS) which summarizes the effect of multiple variants by the summation of alleles weighted by estimated effects from GWAS. To investigate genetic overlaps of LDD and related heritable risk factors, we calculated the PGS of height, BMI, BMD and lipid levels in a Chinese population-based cohort with spine MRI examination and a Japanese case-control cohort of lumbar disc herniation (LDH) requiring surgery. Because most large-scale GWASs were done in European populations, PGS of corresponding traits were created using weights from European GWASs. We calibrated their prediction performance in independent Chinese samples, then tested associations with MRI-derived LDD scores and LDH affection status. The PGS of height, BMI, BMD and lipid levels were strongly associated with respective phenotypes in Chinese, although phenotype variances explained were lower than in Europeans which would reduce the power to detect genetic overlaps. Despite of this, the PGS of BMI and lumbar spine BMD were significantly associated with LDD scores; and the PGS of height was associated with the increased the liability of LDH. Furthermore, linkage disequilibrium score regression suggested that, osteoarthritis, another degenerative disorder that shares common features with LDD, also showed genetic correlations with height, BMI and BMD. The findings suggest a common key contribution of biomechanical stress to the pathogenesis of LDD and will direct the future search for pleiotropic genes.

genetics↗

bioRxiv2018

Evolutionary emergence of infectious diseases in heterogeneous host populations

Emergence and re-emergence of pathogens are notoriously difficult to predict. The erratic nature of those events is reinforced by the stochastic nature of pathogen evolution during the early phase of an epidemic. For instance, mutations allowing pathogens to escape host resistance may boost pathogen spread and promote emergence. Yet, the ecological factors that govern such evolutionary emergence remain elusive both because of the lack of ecological realism of current theoretical frameworks and the difficulty of experimentally testing their predictions. Here we develop a theoretical model to explore the effects of the heterogeneity of the host population on the probability of pathogen emergence, with or without pathogen evolution. We show that evolutionary emergence and the spread of escape mutations in the pathogen population is more likely to occur when the host population contains an intermediate proportion of resistant hosts. We also show that lower pathogen inoculum size and higher diversity of host resistance decrease the probability of evolutionary emergence. Crucially, we present experimental confirmations of these predictions using lytic bacteriophages infecting their bacterial hosts containing diverse CRISPR-Cas immune defenses. We discuss the implications of these results for cross-species spillover and for the management of emerging infectious diseases.\n\nSignificance statementCan we predict the emergence of infectious diseases? The probability that an epidemic breaks out is highly dependent on the ability of the pathogen to acquire new adaptive mutations and to induce evolutionary emergence. Forecasting pathogen emergence thus requires a good understanding of the interplay between epidemiology and evolution taking place at the onset of an outbreak. Here, we provide a comprehensive theoretical framework to analyze the impact of host population heterogeneity on the probability of pathogen evolutionary emergence. We use this model to predict the impact of the fraction of susceptible hosts, the inoculum size of the pathogen and the diversity of host resistance on pathogen emergence. Our experiments using lytic bacteriophages and CRISPR-resistant bacteria support our theoretical predictions.

evolutionary biology↗

bioRxiv2018

De novo mutations drive the spread of macrolide resistant Mycoplasma genitalium: mathematical modelling study

BackgroundThe rapid spread of azithromycin resistance in sexually transmitted Mycoplasma genitalium infections is a growing concern. It is not yet clear to what degree macrolide resistance in M. genitalium results from the emergence of de novo mutations or the transmission of resistant strains.\n\nMethodsWe analyzed epidemiological data and developed a compartmental model to investigate the contribution of de novo macrolide resistance mutations to the spread of antimicrobial-resistant M. genitalium. We fitted the model to data from France, Denmark and Sweden and estimated treatment rates of infected individuals and the time point of azithromycin introduction.\n\nResultsWe found a high probability of de novo resistance (12%, 95% CI 8-17%), which is responsible for the observed rapid spread of antimicrobial resistant M. genitalium. The estimated per capita treatment rate in France was lower than in Denmark and Sweden but confidence intervals for the three estimates overlap. The estimated dates of introduction of azithromycin in each country are consistent with published reports.\n\nConclusionsSince de novo resistance is the main driver of macrolide resistance in M. genitalium, blind treatment of urethritis with azithromycin is not recommended. Clinical management strategies for M. genitalium should limit the unnecessary use of macrolides.

microbiology↗

bioRxiv2018

When parasites are selected to kill the young

The impact of infectious disease is often very different in juveniles and adults, but theory has focused on the drivers of stage-dependent defense in hosts rather than the potential for stage-dependent virulence evolution. Stage-structure has the potential to be important to the evolution of pathogens because it exposes parasites to heterogeneous environments in terms of both host characteristics and transmission routes. We develop a stage-structured (juvenile-adult) epidemiological model and examine the evolutionary outcomes of stage-specific virulence under the classic assumption of a transmission-virulence trade-off. We show that selection on virulence against adults remains consistent with the classic theory. However, the evolution of juvenile virulence is sensitive to both demography and transmission pathway with higher virulence against juveniles being favored either when the transmission pathway is assortative (juveniles preferentially interact together) and the juvenile stage is short, or in contrast when the transmission pathway is disassortative and the juvenile stage is long. These results highlight the potentially profound effects of host stage-structure on determining parasite virulence in nature. This new perspective may have broad implications for both understanding and managing disease severity. Impact summaryUnderstanding the evolution of parasite virulence remains one of the most important questions in evolutionary ecology. Virulence is often very different in young and old hosts, but previous theory has presumed that these differences are attributed to adaptation in host defense rather than parasite adaptation. However, stage-structure within host populations can expose parasites to heterogeneous environments, which may lead to differential selection on parasite virulence (stage-specific virulence). Surprisingly, no study has investigated the effects of hosts stage-structure on the evolution of stage-specific virulence. We present a theoretical analysis to examine when selection can favor higher virulence against juveniles (juvenile-virulence) versus adults (adult-virulence). Our key result is that higher juvenile-virulence is selected for either when the transmission is assortative within age classes and maturation is slow, or when the transmission is disassortative (occurring predominantly between-classes) and maturation is relatively fast. These at first sight contrasting outcomes can be understood as adaptation to the exploitation of the more available host stage. Although the data on assortativity in infectious disease systems is limited, empirical studies for the virulence of Great Island Virus in guillemots (Uria aalge) and for salmon louse in pink salmon (Oncorhynchus gorbuscha) are consistent with our predictions. Our work provides testable predictions for stage-specific virulence and presents a novel mechanism that may explain variation in virulence in nature. There are also management implications for conservation, public health, vaccination programs, and farming to understanding the drivers of stage dependent virulence.

ecology↗