Should we aim for genetic improvement of host resistance or tolerance to infectious disease?
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Date
01/12/2017Author
Lough, Graham
Metadata
Abstract
A host can adopt two strategies when facing infection: resistance, where host immune
responses prevent or reduce pathogen replication; or tolerance, which refers to all
mechanisms that reduce the impact of the infection on host health or performance.
Both strategies may be under host genetic control, and could thus be targeted for
genetic improvement. Although there is ample evidence of genetic variation in
resistance to infection, there is limited evidence to suggest that individuals also differ
genetically in tolerance. Furthermore, although resistance and tolerance are typically
considered as alternative host defense mechanisms, relatively little is known about the
genetic relationship between them and how they change together over time and jointly
determine infection outcome. In this thesis, two datasets from experimental challenge
infection experiments were considered for investigating tolerance genetics: Porcine
Reproductive & Respiratory Syndrome (PRRS), an endemic viral disease which
causes loss of growth and mortality in growing pigs; and Listeria monoctyogenes
(Lm), a bacterium which causes food-borne infections in mammals. The two datasets
differed substantially in size and genetic structure; the PRRS dataset consists of
thousands of records from outbred commercial pig populations, whereas the Listeria
dataset comprises much fewer records from genetically diverse highly inbred strains
of a mice as a model species. The aims of this thesis were to: 1) Identify if genetic
variation in host tolerance to infection exists, with case studies in PRRS and listeria,
using conventional reaction-norm methodology; 2) Identify if host tolerance, along
with resistance, changes longitudinally as infection progresses; 3) Identify whether the
WUR genotype is associated with tolerance slope; 4) Analyse the dynamic relationship
between host performance and pathogen load over the time-course of infection by
examining the relationship at different stages of infection using GWAS; 5) Develop
novel trajectory methodology to offer insight into health-infection dynamics, and
identify whether there is genetic variation in trajectories; 6) Develop novel trajectory-derived
phenotypes that analyse changes in host performance with respect to changes
in pathogen load, as an alternative to tolerance, and identify whether genetic variation
exists. This study found that conventional reaction-norm methodology is limited to
capture genetic variation in tolerance in outbred populations without measures of
performance in the absence of infection. However, by utilising repeated longitudinal
data on the same dataset, stages of infection (early, mid and late) were defined for each
individual, based on host pathogen load. Using these stages of infection, genetic
variation in tolerance was identified over all stages of infection and at mid to late stage
of infection. Genetic correlation between resistance and tolerance was strong and
positive over all stages of infection, and evidence suggested that resistance and
tolerance may be under pleiotropic control. Furthermore, this research found that
genetic correlations between resistance and growth changed considerably over time,
and that individuals who expressed high genetic resistance early in infection tended to
grow slower during that time-period, but were more likely to clear the virus by late
stage, and thus recover in growth. However, at mid-late stage of infection, those with
high virus load also had high growth, indicating potential epidemiological problems
with genetic selection of host resilience to infection. Furthermore, genome wide
association studies for pathogen load and growth associated with different stages of
infection did not identify novel genetic loci associated with these traits than those
previously reported for the whole infection period. By adopting conventional
methodology, this study found genetic variation in tolerance of genetically diverse
mouse strains to Lm and pigs to PRRS, despite statistical problems. The relationship
between resistance and tolerance indicated that both traits should be considered in
genetic selection programs. By adopting novel trajectory analysis, this study
demonstrated that level of expression of resistance and tolerance changed throughout
the experimental infection period and, furthermore, that expression of resistance,
followed by tolerance, determined survival of infection. Survivors and non-survivors
followed different infection trajectories, which were partially determined by genetics.
By deriving novel phenotypes from trajectories that explained changes in growth in
relation to change in pathogen load at specific time points, and applying these to the
PRRS data, this study did not identify genetic variation in these phenotypes. The
genetic signal in these phenotypes may have been masked by the fact that individuals
were likely at different stages of infection. In summary, this study has shown that
genetic improvement of tolerance, in addition to resistance may be desirable, but could
be difficult to achieve in practice due to shortcomings in obtaining accurate and
unbiased tolerance estimates based on conventional reaction-norms. Infection
trajectories have proven to be a promising tool for achieving an optimally timed
balance between resistance and tolerance, but further work is needed to incorporate
them in genetic improvement programs.