Is anorexia during infection in animals affected by food composition?

Kyriazakis, Ι.

doi:10.1016/j.anifeedsci.2010.01.001

Cited by 31 publications

(26 citation statements)

References 40 publications

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“…A reduction in feed intake would be expected to occur mainly during the initial stages of infection (Coltherd et al 2009;Kyriazakis, 2010), and it might be that this would only have been evident above a certain level of infection pressure (Sandberg et al 2006). Therefore, it cannot be excluded that diluting effects of mice infected below such a level of infection pressure did not allow us to statistically detect the presence of anorexia.…”

Section: Body Weight Food Intake and Fat Percentagementioning

confidence: 92%

“…Development of immunity to gastrointestinal nematodes usually coincides with periods of high growth rates and thus high nutrient requirements ). In addition, parasitic infection can be accompanied by variable pathology (Garside et al 2000) and anorexia (Kyriazakis, 2010), which can readily lead to nutrient scarcity even when animals are fed on good quality foods. Under these conditions, hosts may be forced to allocate scarce nutrient resources between the competing traits of growth and parasite control .…”

Section: Introductionmentioning

confidence: 99%

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Interactive effects of protein nutrition, genetic growth potential andHeligmosomoides bakeriinfection pressure on resilience and resistance in mice

Coltherd

Babayan

Bünger³

et al. 2011

Parasitology

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SUMMARYThe ability of animals to cope with an increasing parasite load, in terms of resilience and resistance, may be affected by both nutrient supply and demand. Here, we hypothesized that host nutrition and growth potential interact and influence the ability of mice to cope with different parasite doses. Mice selected for high (ROH) or low (ROL) body weight were fed a low (40 g/kg; LP) or high (230 g/kg; HP) protein diet and infected with 0, 50, 100, 150, 200 or 250 L3infectiveHeligmosomoides bakerilarvae. ROH-LP mice grew less at doses of 150 L3and above, whilst growth of ROH-HP and of ROL mice was not affected by infection pressure. Total worm burdens reached a plateau at doses of 150L3, whilst ROH mice excreted fewer worm eggs than ROL mice. Serum antibodies increased with infection dose and ROH mice were found to have higher parasite-specific IgG1 titres than ROL mice. In contrast, ROL had higher total IgE titres than ROH mice, only on HP diets. The interaction between host nutrition and growth potential appears to differentially affect resilience and resistance in mice. However, the results support the view that parasitism penalises performance in animals selected for higher growth.

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Section: Body Weight Food Intake and Fat Percentagementioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Interactive effects of protein nutrition, genetic growth potential andHeligmosomoides bakeriinfection pressure on resilience and resistance in mice

Coltherd

Babayan

Bünger³

et al. 2011

Parasitology

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“…Although complex, the mechanism for inappetance in ostertagiosis was modelled as a function of the rate of immune acquisition, as it has been suggested that this reduction is associated with components of the immune response (e.g. cytokines), and related pathological and inflammatory responses (Fox et al., 1989, Kyriazakis, 2010, Kyriazakis, 2014). Consequently, the calf consumes insufficient resources to fulfil its requirements.…”

Section: Methodsmentioning

confidence: 99%

Modelling the consequences of targeted selective treatment strategies on performance and emergence of anthelmintic resistance amongst grazing calves

Berk

Laurenson

Forbes

et al. 2016

International Journal for Parasitology: Drugs and Drug Resistan

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The development of anthelmintic resistance by helminths can be slowed by maintaining refugia on pasture or in untreated hosts. Targeted selective treatments (TST) may achieve this through the treatment only of individuals that would benefit most from anthelmintic, according to certain criteria. However TST consequences on cattle are uncertain, mainly due to difficulties of comparison between alternative strategies. We developed a mathematical model to compare: 1) the most ‘beneficial’ indicator for treatment selection and 2) the method of selection of calves exposed to Ostertagia ostertagi, i.e. treating a fixed percentage of the population with the lowest (or highest) indicator values versus treating individuals who exceed (or are below) a given indicator threshold. The indicators evaluated were average daily gain (ADG), faecal egg counts (FEC), plasma pepsinogen, combined FEC and plasma pepsinogen, versus random selection of individuals. Treatment success was assessed in terms of benefit per R (BPR), the ratio of average benefit in weight gain to change in frequency of resistance alleles R (relative to an untreated population). The optimal indicator in terms of BPR for fixed percentages of calves treated was plasma pepsinogen and the worst ADG; in the latter case treatment was applied to some individuals who were not in need of treatment. The reverse was found when calves were treated according to threshold criteria, with ADG being the best target indicator for treatment. This was also the most beneficial strategy overall, with a significantly higher BPR value than any other strategy, but its degree of success depended on the chosen threshold of the indicator. The study shows strong support for TST, with all strategies showing improvements on calves treated selectively, compared with whole-herd treatment at 3, 8, 13 weeks post-turnout. The developed model appeared capable of assessing the consequences of other TST strategies on calf populations.

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“…By reducing resources allocated to other functions, such as searching for and digesting food, the host may be able to direct resources to the immune response, resulting in temporary body weight loss. This has been put forward as the evolutionary basis of pathogen-induced anorexia and 'sickness' behaviours [12,[126][127][128]. Our previous applications of the resource allocation theory to assess the effect of genetic resistance on the long-term effects of infection, showed that hosts with greater genetic resistance may suffer greater performance loss (e.g.…”

Section: Discussionmentioning

confidence: 99%

Should we aim for genetic improvement in host resistance or tolerance to infectious disease?

Lough¹

2013

Frontiers Research Topics

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2.3.4 Step 1: Animal models to estimate the genetic relationship between resistance and performance prior to and post infection ……………………..… 31 2.3.5 Step 2: Multi-trait models to examine evidence for genetic variation in tolerance: growth associated with low versus high VL ………………………… 2.3.6 Step 3: Univariate random regression models for estimating genetic variation in tolerance …….. 2.3.7 Step 4: Random regression model using simulated performance in absence of infection for estimating genetic variance in tolerance ……...…. 34 2.4 Results ..……………………………………………... 36 2.4.1 Step 1: Relationship between resistance and performance prior to and post infection ..…...…... 36 2.4.2 Step 2: multi-trait models to examine evidence for genetic variation in tolerance ……………….. 39 2.4.3 Step 3: Estimation of genetic variance in tolerance using univariate random regression Models ………………………………………………...… 40 2.4.4 Step 4: Random regression models including simulated performance in absence of infection for estimating genetic variance in tolerance ………... 43 xii 2.5 Discussion …………………………………………... 47 2.5.1 Summary of findings …………………….… 47 2.5.2 Statistical considerations ……...…………… 49 2.5.3 Implications for genetic improvement of tolerance of pigs to PRRS and other diseases …… 52 2.5.4 Conclusions ………………………………... 55 Appendix 2.1 ………………………………….………………. 57 2.1 Simulating ADG in absence of infection …………… 57 2.1.1 Step 1: Calculate sire breeding values for growth under infection (ADG I) .…………………. 57 2.1.2 Step 2: Calculate sire breeding values for growth in the absence of infection (ADG 0) .…….. 58 2.1.3 Step 3: Calculate phenotypic values for growth without infection for progeny (half sibs) (P Prog) .... 58 Chapter 3 ……………………………………………...…………..… Harnessing longitudinal information to identify genetic variation in tolerance of pigs to Porcine Reproductive and Respiratory Syndrome virus infection ……………………… 61 xiv 3.4.2 Association of the WUR genotype with tolerance …………………………………………. 77 3.4.3 The importance of stages of infection to identify genetic variation in tolerance ……………………. 77 3.4.4 Implications for breeding programmes and conclusions ………………………………………. 79 Appendix 3.1 ……………………………………………….…. 80 3.1 Stage of infection defined by duration ……………… 80 3.2 Genetic variation in tolerance at different stages of infection ………………………………………………… 80 3.3 Genetic variation in tolerance across all stages of infection ……………………………………………….... 81 3.4 Relationship between level, slope and resistance from 21-42 dpi ………………………………………………... 82 3.5 Association of WUR genotype with tolerance slope .. 83 3.6 Relationship between level, slope and resistance across all duration stages of infection ………………………...... 83 Chapter 4 ………………………………………………………….…. 84 Genome-wide association studies for resistance and growth at different stages of infection ……………………………….

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Is anorexia during infection in animals affected by food composition?

Cited by 31 publications

References 40 publications

Interactive effects of protein nutrition, genetic growth potential andHeligmosomoides bakeriinfection pressure on resilience and resistance in mice

Interactive effects of protein nutrition, genetic growth potential andHeligmosomoides bakeriinfection pressure on resilience and resistance in mice

Modelling the consequences of targeted selective treatment strategies on performance and emergence of anthelmintic resistance amongst grazing calves

Should we aim for genetic improvement in host resistance or tolerance to infectious disease?

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