Harnessing longitudinal information to identify genetic variation in tolerance of pigs to Porcine Reproductive and Respiratory Syndrome virus infection

Background: High resistance (the ability of the host to reduce pathogen load) and tolerance (the ability to maintain high performance at a given pathogen load) are two desirable host traits for producing animals that are resilient to infections. For Porcine Reproductive and Respiratory Syndrome (PRRS), one of the most devastating swine diseases worldwide, studies have identified substantial genetic variation in resistance of pigs, but evidence for genetic variation in tolerance has so far been inconclusive. Resistance and tolerance are usually considered as static traits. In this study, we used longitudinal viremia measurements of PRRS virus infected pigs to define discrete stages of infection based on viremia profile characteristics. These were used to investigate host genetic effects on viral load (VL) and growth at different stages of infection, to quantify genetic variation in tolerance at these stages and throughout the entire 42-day observation period, and to assess whether the single nucleotide polymorphism (SNP) WUR10000125 (WUR) with known large effects on resistance confers significant differences in tolerance. Results: Genetic correlations between resistance and growth changed considerably over time. Individuals that expressed high genetic resistance early in infection tended to grow slower during that time-period, but were more likely to experience lower VL and recovery in growth by the later stage. The WUR genotype was most strongly associated with VL at early- to mid-stages of infection, and with growth at mid- to late-stages of infection. Both, single-stage and repeated measurements random regression models identified significant genetic variation in tolerance. The WUR SNP was significantly associated only with the overall tolerance slope fitted through all stages of infection, with the genetically more resistant AB pigs for the WUR SNP being also more tolerant to PRRS. Conclusions: The results suggest that genetic selection for improved tolerance of pigs to PRRS is possible in principle, but may be feasible only with genomic selection, requiring intense recording schemes that involve repeated measurements to reliably estimate genetic effects. In the absence of such records, consideration of the WUR genotype in current selection schemes appears to be a promising strategy to improve simultaneously resistance and tolerance of growing pigs to PRRS.</p

Sexual Size Dimorphism and Body Condition in the Australasian Gannet

Funding: The research was financially supported by the Holsworth Wildlife Research Endowment. Acknowledgments We thank the Victorian Marine Science Consortium, Sea All Dolphin Swim, Parks Victoria, and the Point Danger Management Committee for logistical support. We are grateful for the assistance of the many field volunteers involved in the study.Peer reviewedPublisher PD

Use of multi-trait and random regression models to identify genetic variation in tolerance to porcine reproductive and respiratory syndrome virus

Background: A host can adopt two response strategies to infection: resistance (reduce pathogen load) and tolerance (minimize impact of infection on performance). Both strategies may be under genetic control and could thus be targeted for genetic improvement. Although there is evidence that supports a genetic basis for resistance to porcine reproductive and respiratory syndrome (PRRS), it is not known whether pigs also differ genetically in tolerance. We determined to what extent pigs that have been shown to vary genetically in resistance to PRRS also exhibit genetic variation in tolerance. Multi-trait linear mixed models and random regression sire models were fitted to PRRS Host Genetics Consortium data from 1320 weaned pigs (offspring of 54 sires) that were experimentally infected with a virulent strain of PRRS virus to obtain genetic parameter estimates for resistance and tolerance. Resistance was defined as the inverse of within-host viral load (VL) from 0 to 21 (VL21) or 0 to 42 (VL42) days post-infection and tolerance as the slope of the reaction-norm of average daily gain (ADG21, ADG42) on VL21 or VL42. Results: Multi-trait analysis of ADG associated with either low or high VL was not indicative of genetic variation in tolerance. Similarly, random regression models for ADG21 and ADG42 with a tolerance slope fitted for each sire did not result in a better fit to the data than a model without genetic variation in tolerance. However, the distribution of data around average VL suggested possible confounding between level and slope estimates of the regression lines. Augmenting the data with simulated growth rates of non-infected half-sibs (ADG0) helped resolve this statistical confounding and indicated that genetic variation in tolerance to PRRS may exist if genetic correlations between ADG0 and ADG21 or ADG42 are low to moderate. Conclusions: Evidence for genetic variation in tolerance of pigs to PRRS was weak when based on data from infected piglets only. However, simulations indicated that genetic variance in tolerance may exist and could be detected if comparable data on uninfected relatives were available. In conclusion, of the two defense strategies, genetics of tolerance is more difficult to elucidate than genetics of resistance.</p

Extended high-frequency audiometry in research and clinical practice

Audiometric testing in research and in clinical settings rarely considers frequencies above 8 kHz. However, the sensitivity of young healthy ears extends to 20 kHz, and there is increasing evidence that testing in the extended high-frequency (EHF) region, above 8 kHz, might provide valuable additional information. Basal (EHF) cochlear regions are especially sensitive to the effects of aging, disease, ototoxic drugs, and possibly noise exposure. Hence, EHF loss may be an early warning of damage, useful for diagnosis and for monitoring hearing health. In certain environments, speech perception may rely on EHF information, and there is evidence for an association between EHF loss and speech perception difficulties, although this may not be causal: EHF loss may instead be a marker for sub-clinical damage at lower frequencies. If there is a causal relation, then amplification in the EHF range may be beneficial if the technical difficulties can be overcome. EHF audiometry in the clinic presents with no particular difficulty, the biggest obstacle being lack of specialist equipment. Currently, EHF audiometry has limited but increasing clinical application. With the development of international guidelines and standards, it is likely that EHF testing will become widespread in future

The impact of using the Ida “My Hearing Explained” tool on audiologists’ language and patient understanding of hearing test results:a comparison with standard audiogram explanations

Objective: Explore the impact of Ida’s “My Hearing Explained” (MHE) tool on audiologists’ language and patients’ understanding/interpretation of hearing test results.Design: Audiologists were video-recorded in two sequential conditions: 1) giving standard audiogram explanations to 13 patients and, 2) following discretionary self-training, giving explanations using the MHE tool (nine patients). Outcomes of interest were audiologists’ language complexity, use of jargon, and audiologist-patient interactivity. Semi-structured patient interviews, conducted 1-7 days after appointments, were analysed using inductive qualitative content analysis. Patient recall was verified.Study Sample: Four audiologists from one United Kingdom audiology service, and 22 patients (mean age 63.5 yrs) participated.Results: In comparison to standard audiogram explanations, audiologists’ language was simpler and audiologist-patient interactivity greater with the MHE tool. Interview data analysis revealed differences between explanation types within the themes of “Understanding” and “Interpretation.” 54% (standard audiogram) and 22% (MHE tool) of patients expressed a desire for takeaway information. 31% (standard audiogram) and 67% (MHE tool) of patients reported their explanation helped them relay their results to others. Four patients (one receiving the MHE tool) incorrectly recalled information, suggesting inadequate understanding in these cases.Conclusions: The MHE tool has potential for improving the accessibility and comprehensibility of hearing test results