Evaluation of longevity modeling censored records in Nellore

The aim of the present study was to evaluate the prediction ability of models that cope with longevity phenotypic expression as uncensored and censored in Nellore cattle. Longevity was defined as the difference between the dates of last weaned calf and cow birth. There were information of 77 353 females, being 61 097 cows with uncensored phenotypic information and 16 256 cows with censored records. These data were analyzed considering three different models: (1) Gaussian linear model (LM), in which only uncensored records were considered; and two models that consider both uncensored and censored records: (2) Censored Gaussian linear model (CLM); and (3) Weibull frailty hazard model (WM). For the model prediction ability comparisons, the data set was randomly divided into training and validation sets, containing 80% and 20% of the records, respectively. There were considered 10 repetitions applying the following restrictions: (a) at least three animals per contemporary group in the training set; and (b) sires with more than 10 progenies with uncensored records (352 sires) should have daughters in the training and validation sets. The variance components estimated using the whole data set in each model were used as true values in the prediction of breeding values of the animals in the training set. The WM model showed the best prediction ability, providing the lowest χ² average and the highest number of sets in which a model had the smallest value of χ² statistics. The CLM and LM models showed prediction abilities 2.6% and 3.7% less efficient than WM, respectively. In addition, the accuracies of sire breeding values for LM and CLM were lower than those obtained for WM. The percentages of bulls in common, considering only 10% of sires with the highest breeding values, were around 75% and 54%, respectively, between LM–CLM and LM–WM models, considering all sires, and 75% between LM–CLM and LM–WM, when only sires with more than 10 progenies with uncensored records were taken into account. These results are indicative of reranking of animals in terms of genetic merit between LM, CLM and WM. The model in which censored records of longevity were excluded from the analysis showed the lowest prediction ability. The WM provides the best predictive performance, therefore this model would be recommended to perform genetic evaluation of longevity in this population.     

Comparison among three approaches for evaluation of sexual precocity in Nellore cattle

Restricted breeding seasons used in beef cattle produce censored data for reproduction traits measured in regard to these seasons. To analyze these data, adequate methods must be used. The objective of this paper was to compare three approaches aiming to evaluate sexual precocity in Nellore cattle. The final data set contained 6699 records of age at first conception (AFC14) (in days) and of heifer pregnancy (HP14) (binary) obtained from females exposed to the bulls for the first time at about 14 months of age. Records of females that did not calve in the following year after being exposed to a sire were considered censored (77.5% of total). The models used to obtain genetic parameters and expected progeny differences (EPDs) were a Weibull mixed and a censored linear model for AFC14 and threshold model for HP14. The mean heritabilities obtained were 0.76 and 0.44, respectively, for survival and censored linear models (for AFC14), and 0.58 for HP14. Ranking and Pearson correlations varied (in absolute values) from 0.54 to 0.99 (considering different percentages of sires selected), indicating moderate changes in the classification. Considering survival analysis as the best selection criterion (that would result in the best response to selection), it was observed that selection for HP14 would lead to a more significant decrease in selection response if compared with selection for AFC14 analysed by censored linear model, from which results were very similar to the survival analysis.     

Birnbaum–Saunders frailty regression models: Diagnostics and application to medical data

In survival models, some covariates affecting the lifetime could not be observed or measured. These covariates may correspond to environmental or genetic factors and be considered as a random effect related to a frailty of the individuals explaining their survival times. We propose a methodology based on a Birnbaum–Saunders frailty regression model, which can be applied to censored or uncensored data. Maximum‐likelihood methods are used to estimate the model parameters and to derive local influence techniques. Diagnostic tools are important in regression to detect anomalies, as departures from error assumptions and presence of outliers and influential cases. Normal curvatures for local influence under different perturbations are computed and two types of residuals are introduced. Two examples with uncensored and censored real‐world data illustrate the proposed methodology. Comparison with classical frailty models is carried out in these examples, which shows the superiority of the proposed model.     

The Incubation Periods of Dengue Viruses

Dengue viruses are major contributors to illness and death globally. Here we analyze the extrinsic and intrinsic incubation periods (EIP and IIP), in the mosquito and human, respectively. We identified 146 EIP observations from 8 studies and 204 IIP observations from 35 studies. These data were fitted with censored Bayesian time-to-event models. The best-fitting temperature-dependent EIP model estimated that 95% of EIPs are between 5 and 33 days at 25°C, and 2 and 15 days at 30°C, with means of 15 and 6.5 days, respectively. The mean IIP estimate was 5.9 days, with 95% expected between days 3 and 10. Differences between serotypes were not identified for either incubation period. These incubation period models should be useful in clinical diagnosis, outbreak investigation, prevention and control efforts, and mathematical modeling of dengue virus transmission.     

Genetic evaluation of ovulatory disorders in Austrian Fleckvieh cows: a comparison between linear models and survival analysis

The objective of this study was to compare linear models and survival analysis for genetic evaluation of ovulatory disorders, which included veterinary treatments of silent heat/anestrus and cystic ovaries. Data of 23 450 daughters of 274 Austrian Fleckvieh sires were analyzed. For linear model analyses, ovulatory disorders were defined as a binary response (presence or absence) in the time periods from calving to 150 days after calving and from calving to 300 days after calving. For survival analysis, ovulatory disorders were defined either as the number of days from calving to the day of the first treatment for an ovulatory disorder (uncensored record) or from calving to the day of culling, or the last day of the period under investigation (until 150 or 300 days after calving; censored record). Estimates of heritability were very similar (0.016 to 0.020) across methods and periods. Correlations between sire estimated breeding value from linear model and survival analysis were 0.98, whereas correlations between different time periods were somewhat lower (0.95 and 0.96). The results showed that the length of time period had a larger effect on genetic evaluation than methodology.     

Analysis of rabbit doe longevity using a semiparametric log-Normal animal frailty model with time-dependent covariates

Data on doe longevity in a rabbit population were analysed using a semiparametric log-Normal animal frailty model. Longevity was defined as the time from the first positive pregnancy test to death or culling due to pathological problems. Does culled for other reasons had right censored records of longevity. The model included time dependent covariates associated with year by season, the interaction between physiological state and the number of young born alive, and between order of positive pregnancy test and physiological state. The model also included an additive genetic effect and a residual in log frailty. Properties of marginal posterior distributions of specific parameters were inferred from a full Bayesian analysis using Gibbs sampling. All of the fully conditional posterior distributions defining a Gibbs sampler were easy to sample from, either directly or using adaptive rejection sampling. The marginal posterior mean estimates of the additive genetic variance and of the residual variance in log frailty were 0.247 and 0.690.     

Bilirubin binding to normal and modified human erythrocyte membranes: Effect of phospholipases,neuraminidase, trypsin and CaCl2

Diisopropyl phosphorofluoridate (DFP) is a type I organophosphorus compound and produces delayed neurotoxicity (OPIDN) in adult hens. A single dose of DFP (1.7 mg/kg, sc.) produces mild ataxia in hens in 7-14 days, which develops into severe ataxia or paralysis as the disease progresses. We have previously shown altered expression of several proteins (e.g. Ca²⁺/calmodulin-dependent protein kinase II (CaM kinase II) -subunit, tau, tubulin, neurofilament protein (NF), vimentin, GFAP) and an immediate early gene (e.g. c-fos) in DFP-treated hens. Here we show an increase in protein kinase A (PKA) protein level and activity in the spinal cord at 1-day and 5-days time periods after DFP administration. We also determined the protein levels of protein kinase C (PKC), CaM kinase II and several phosphatases (i.e. phosphatase 1 (PP1), phosphatase 2A (PP2A), phosphatase 2B (PP2B) in the spinal cord of DFP-treated hens after 1, 5, 10, and 20 days). There was increase in CaM kinase II subunit level after 10 and 20 days of treatment, and decrease in PKC level at 1-day and 20-days time periods in spinal cord mitochondria. In contrast, the cerebrum, which is resistant to DFP-induced axonal degeneration, did not show change in PKA and CaM Kinase II levels at any time period DFP post-administration. No alteration was found in the protein levels of PP1, PP2A, and PP2B at any time period. An early induction in PKA, which is an important protein kinase in signal transduction, followed by that of CaM kinase might be contributing towards the development of OPIDN in DFP-treated hens.     

Intermittent hypoxia-induced protein phosphatase 2A activation reduces PC12 cell proliferation and differentiation

Background

Intermittent hypoxia (IH) plays a critical role in sleep breathing disorder-associated hippocampus impairments, including neurocognitive deficits, irreversible memory and learning impairments. IH-induced neuronal injury in the hippocampus may result from reduced precursor cell proliferation and the relative numbers of postmitotic differentiated neurons. However, the mechanisms underlying IH-induced reactive oxygen species (ROS) generation effects on cell proliferation and neuronal differentiation remain largely unknown.

Results

ROS generation significantly increased after 1–4 days of IH without increased pheochromocytoma-12 (PC12) cell death, which resulted in increased protein phosphatase 2A (PP2A) mRNA and protein levels. After 3–4 days of IH, extracellular signal-regulated kinases 1/2 (ERK1/2) protein phosphorylation decreased, which could be reversed by superoxide dismutase (SOD), 1,10-phenanthroline (Phe), the PP2A phosphorylation inhibitors, okadaic acid (OKA) and cantharidin, and the ERK phosphorylation activator nicotine (p < 0.05). In particular, the significantly reduced cell proliferation and increased proportions of cells in the G₀/G₁ phase after 1–4 days of IH (p < 0.05), which resulted in decreased numbers of PC12 cells, could be reversed by treatment with SOD, Phe, PP2A inhibitors and an ERK activator. In addition, the numbers of nerve growth factor (NGF)-induced PC12 cells with neurite outgrowths after 3–4 days of IH were less than those after 4 days of RA, which was also reversed by SOD, Phe, PP2A inhibitors and an ERK activator.

Conclusions

Our results suggest that IH-induced ROS generation increases PP2A activation and subsequently downregulates ERK1/2 activation, which results in inhibition of PC12 cell proliferation through G₀/G₁ phase arrest and NGF-induced neuronal differentiation.     

Genetic relationship of discrete-time survival with fertility and production in dairy cattle using bivariate models

Bivariate analyses of functional longevity in dairy cattle measured as survival to next lactation (SURV) with milk yield and fertility traits were carried out. A sequential threshold-linear censored model was implemented for the analyses of SURV. Records on 96 642 lactations from 41 170 cows were used to estimate genetic parameters, using animal models, for longevity, 305 d-standardized milk production (MY305), days open (DO) and number of inseminations to conception (INS) in the Spanish Holstein population; 31% and 30% of lactations were censored for DO and INS, respectively. Heritability estimates for SURV and MY305 were 0.11 and 0.27 respectively; while heritability estimates for fertility traits were lower (0.07 for DO and 0.03 for INS). Antagonist genetic correlations were estimated between SURV and fertility (-0.78 and -0.54 for DO and INS, respectively) or production (-0.53 for MY305), suggesting reduced functional longevity with impaired fertility and increased milk production. Longer days open seems to affect survival more than increased INS. Also, high productive cows were more problematic, less functional and more liable to being culled. The results suggest that the sequential threshold model is a method that might be considered at evaluating genetic relationship between discrete-time survival and other traits, due to its flexibility.     

Survival,growth and sexual maturation in Atlantic salmon exposed to infectious pancreatic necrosis: a multi-variate mixture model approach

Background

Outbreaks of infectious pancreatic necrosis (IPN) in Atlantic salmon can result in reduced growth rates in a fraction of the surviving fish (runts). Genetic and environmental variation also affects growth rates within different categories of healthy animals and runts, which complicates identification of runts. Mixture models are commonly used to identify the underlying structures in such data, and the aim of this study was to develop Bayesian mixture models for the genetic analysis of health status (runt/healthy) of surviving fish from an IPN outbreak.

Methods

Five statistical models were tested on data consisting of 10 972 fish that died and 3959 survivors with recorded growth data. The most complex models (4 and 5) were multivariate normal-binary mixture models including growth, sexual maturity and field survival traits. Growth rate and liability of sexual maturation were treated as two-component normal mixtures, assuming phenotypes originated from two potentially overlapping distributions, (runt/normal). Runt status was an unobserved binary trait. These models were compared to mixture models with fewer traits (Models 2 and 3) and a classical linear animal model for growth (Model 1).

Results

Assuming growth as a mixture trait improved the predictive ability of the statistical model considerably (Model 2 vs. 1). The final models (4 and 5) yielded the following results: estimated (underlying) heritabilities were moderate for growth in healthy fish (0.32 ± 0.04 and 0.35 ± 0.05), runt status (0.39 ± 0.07 and 0.36 ± 0.08) and sexual maturation (0.33 ± 0.05), and high for field survival (0.47 ± 0.03 and 0.48 ± 0.03). Growth in healthy animals, runt status and survival showed consistent favourable genetic associations. Sexual maturation showed an unfavourable non-significant genetic correlation with runt status, but favourable genetic correlations with other traits. The estimated fraction of healthy fish was 81-85%. The estimated breeding values for runt status and (normal) growth were consistent for the most complex models (4 and 5), but showed imperfect correlations with estimated breeding values from the simpler models.

Conclusions

Modelling growth in IPN survivors as a mixture trait improved the predictive ability of the model compared with a classical linear model. The results indicated considerable genetic variation in health status among survivors. Mixture modelling may be useful for the genetic analysis of diseases detected mainly through indicator traits.     

Inhibitory Peptide of Mitochondrial μ-Calpain Protects against Photoreceptor Degeneration in Rhodopsin Transgenic S334ter and P23H Rats

Mitochondrial μ-calpain and apoptosis-inducing factor (AIF)-dependent photoreceptor cell death has been seen in several rat and mouse models of retinitis pigmentosa (RP). Previously, we demonstrated that the specific peptide inhibitor of mitochondrial μ-calpain, Tat-µCL, protected against retinal degeneration following intravitreal injection or topical eye-drop application in Mertk gene-mutated Royal College of Surgeons rats, one of the animal models of RP. Because of the high rate of rhodopsin mutations in RP patients, the present study was performed to confirm the protective effects of Tat-µCL against retinal degeneration in rhodopsin transgenic S334ter and P23H rats. We examined the effects of intravitreal injection or topical application of the peptide on retinal degeneration in S334ter and P23H rats by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) assay, electroretinogram (ERG), immunohistochemistry for AIF, and histological staining. In S334ter rats, we found that intravitreal injection or topical application of the peptide prevented photoreceptor cell death from postnatal (PN) 15 to 18 days, the time of early-stage retinal degeneration. Topical application of the peptide also delayed attenuation of ERG responses from PN 28 to 56 days. In P23H rats, topical application of the peptide protected against photoreceptor cell death and nuclear translocation of AIF on PN 30, 40, and 50 days, as the primary stages of degeneration. We observed that topical application of the peptide inhibited the thinning of the outer nuclear layer and delayed ERG attenuations from PN 30 to 90 days. Our results demonstrate that the mitochondrial μ-calpain and AIF pathway is involved in early-stage retinal degeneration in rhodopsin transgenic S334ter and P23H rats, and inhibition of this pathway shows curative potential for rhodopsin mutation-caused RP.     

Association Tests for a Censored Quantitative Trait and Candidate Genes in Structured Populations with Multilevel Genetic Relatedness

Summary Several statistical methods for detecting associations between quantitative traits and candidate genes in structured populations have been developed for fully observed phenotypes. However, many experiments are concerned with failure‐time phenotypes, which are usually subject to censoring. In this article, we propose statistical methods for detecting associations between a censored quantitative trait and candidate genes in structured populations with complex multiple levels of genetic relatedness among sampled individuals. The proposed methods correct for continuous population stratification using both population structure variables as covariates and the frailty terms attributable to kinship. The relationship between the time‐at‐onset data and genotypic scores at a candidate marker is modeled via a parametric Weibull frailty accelerated failure time (AFT) model as well as a semiparametric frailty AFT model, where the baseline survival function is flexibly modeled as a mixture of Polya trees centered around a family of Weibull distributions. For both parametric and semiparametric models, the frailties are modeled via an intrinsic Gaussian conditional autoregressive prior distribution with the kinship matrix being the adjacency matrix connecting subjects. Simulation studies and applications to the Arabidopsis thaliana line flowering time data sets demonstrated the advantage of the new proposals over existing approaches.     

Genetic parameters for social effects on survival in cannibalistic layers: Combining survival analysis and a linear animal model

Background

Mortality due to cannibalism in laying hens is a difficult trait to improve genetically, because censoring is high (animals still alive at the end of the testing period) and it may depend on both the individual itself and the behaviour of its group members, so-called associative effects (social interactions). To analyse survival data, survival analysis can be used. However, it is not possible to include associative effects in the current software for survival analysis. A solution could be to combine survival analysis and a linear animal model including associative effects. This paper presents a two-step approach (2STEP), combining survival analysis and a linear animal model including associative effects (LAM).

Methods

Data of three purebred White Leghorn layer lines from Institut de Sélection Animale B.V., a Hendrix Genetics company, were used in this study. For the statistical analysis, survival data on 16,780 hens kept in four-bird cages with intact beaks were used. Genetic parameters for direct and associative effects on survival time were estimated using 2STEP. Cross validation was used to compare 2STEP with LAM. LAM was applied directly to estimate genetic parameters for social effects on observed survival days.

Results

Using 2STEP, total heritable variance, including both direct and associative genetic effects, expressed as the proportion of phenotypic variance, ranged from 32% to 64%. These results were substantially larger than when using LAM. However, cross validation showed that 2STEP gave approximately the same survival curves and rank correlations as LAM. Furthermore, cross validation showed that selection based on both direct and associative genetic effects, using either 2STEP or LAM, gave the best prediction of survival time.

Conclusion

It can be concluded that 2STEP can be used to estimate genetic parameters for direct and associative effects on survival time in laying hens. Using 2STEP increased the heritable variance in survival time. Cross validation showed that social genetic effects contribute to a large difference in survival days between two extreme groups. Genetic selection targeting both direct and associative effects is expected to reduce mortality due to cannibalism in laying hens.     

TLR Accessory Molecule RP105 (CD180) Is Involved in Post-Interventional Vascular Remodeling and Soluble RP105 Modulates Neointima Formation

Background

RP105 (CD180) is TLR4 homologue lacking the intracellular TLR4 signaling domain and acts a TLR accessory molecule and physiological inhibitor of TLR4-signaling. The role of RP105 in vascular remodeling, in particular post-interventional remodeling is unknown.

Methods and Results

TLR4 and RP105 are expressed on vascular smooth muscle cells (VSMC) as well as in the media of murine femoral artery segments as detected by qPCR and immunohistochemistry. Furthermore, the response to the TLR4 ligand LPS was stronger in VSMC from RP105^−/− mice resulting in a higher proliferation rate. In RP105^−/− mice femoral artery cuff placement resulted in an increase in neointima formation as compared to WT mice (4982±974 µm² vs.1947±278 µm²,p = 0.0014). Local LPS application augmented neointima formation in both groups, but in RP105^−/− mice this effect was more pronounced (10316±1243 µm² vs.4208±555 µm²,p = 0.0002), suggesting a functional role for RP105. For additional functional studies, the extracellular domain of murine RP105 was expressed with or without its adaptor protein MD1 and purified. SEC-MALSanalysis showed a functional 2∶2 homodimer formation of the RP105-MD1 complex. This protein complex was able to block the TLR4 response in whole blood ex-vivo. In vivo gene transfer of plasmid vectors encoding the extracellular part of RP105 and its adaptor protein MD1 were performed to initiate a stable endogenous soluble protein production. Expression of soluble RP105-MD1 resulted in a significant reduction in neointima formation in hypercholesterolemic mice (2500±573 vs.6581±1894 µm²,p<0.05), whereas expression of the single factors RP105 or MD1 had no effect.

Conclusion

RP105 is a potent inhibitor of post-interventional neointima formation.     

Comparative Analyses of QTLs Influencing Obesity and Metabolic Phenotypes in Pigs and Humans

The pig is a well-known animal model used to investigate genetic and mechanistic aspects of human disease biology. They are particularly useful in the context of obesity and metabolic diseases because other widely used models (e.g. mice) do not completely recapitulate key pathophysiological features associated with these diseases in humans. Therefore, we established a F2 pig resource population (n = 564) designed to elucidate the genetics underlying obesity and metabolic phenotypes. Segregation of obesity traits was ensured by using breeds highly divergent with respect to obesity traits in the parental generation. Several obesity and metabolic phenotypes were recorded (n = 35) from birth to slaughter (242 ± 48 days), including body composition determined at about two months of age (63 ± 10 days) via dual-energy x-ray absorptiometry (DXA) scanning. All pigs were genotyped using Illumina Porcine 60k SNP Beadchip and a combined linkage disequilibrium-linkage analysis was used to identify genome-wide significant associations for collected phenotypes. We identified 229 QTLs which associated with adiposity- and metabolic phenotypes at genome-wide significant levels. Subsequently comparative analyses were performed to identify the extent of overlap between previously identified QTLs in both humans and pigs. The combined analysis of a large number of obesity phenotypes has provided insight in the genetic architecture of the molecular mechanisms underlying these traits indicating that QTLs underlying similar phenotypes are clustered in the genome. Our analyses have further confirmed that genetic heterogeneity is an inherent characteristic of obesity traits most likely caused by segregation or fixation of different variants of the individual components belonging to cellular pathways in different populations. Several important genes previously associated to obesity in human studies, along with novel genes were identified. Altogether, this study provides novel insight that may further the current understanding of the molecular mechanisms underlying human obesity.     

Analyses of lamb survival of Scottish Blackface sheep

Scottish Blackface lamb viability records at birth, and postnatal survival from 1 day to 14 days, from 15 days to 120 days and from 121 days to 180 days were used to determine influential factors and to estimate variance components of lamb survival traits. The binary trait viability at birth was analysed using a linear model whereas the postnatal survival traits were analysed as continuous traits using a Weibull model. The data consisted of about 15 000 survival records of lambs born from 1996 to 2005 on two farms in Scotland. The models included fixed factors that had significant effects and random direct and maternal additive genetic effects and maternal litter effects for viability at birth, and sire and maternal litter effects for the postnatal survival traits. The possible effect of maternal behaviour measured around lambing on lamb survival was investigated in separate analyses. Male lambs were found to be at a higher risk of mortality than females during all periods considered. The effect of type of birth and age of dam was more important during the preweaning period than at later ages. The postnatal hazard rate was not significantly affected by the behaviour score of the dams. The genetic merit of dams had more influence on viability at birth than the genetic merit of lambs themselves. Estimates of heritability for postnatal survival traits were in the range of 0.18 to 0.33 and were significantly greater than zero. These results indicate that lamb survival can be improved through farm management practices and genetic selection. Both animal and maternal genetic effects should be considered in breeding programmes for improving viability at birth.     

Estimation of genetic parameters for partial egg production periods by means of random regression models

We estimated genetic parameters for egg production in different periods by means of random regression models, aiming at selection based on partial egg production from a generation of layers. The production was evaluated for each individual by recording the number of eggs produced from 20 to 70 weeks of age, with partial records taken every three weeks for a total of 17 periods. The covariance functions were estimated with a random regression model by the restricted maximum likelihood method. A model composed of third-order polynomials for the additive effect, ninth-order polynomials for the permanent environment, and a residual variance structure with five distinct classes, was found to be most suitable for adjusting the egg production data for laying hens. The heritability estimates varied from 0.04 to 0.14. The genetic correlations were all positive, varying from 0.10 to 0.99. Selection applied in partial egg production periods will result in greater genetic profit for the adjacent periods. However, as the distance in time between periods increases, selection becomes less efficient. Selection based on the second period (23 to 25 weeks of age), where greater heritability was estimated, would note benefit the final egg-laying cycle periods.     

A genome‐wide association study of the frailty index highlights brain pathways in ageing

Frailty is a common geriatric syndrome and strongly associated with disability, mortality and hospitalization. Frailty is commonly measured using the frailty index (FI), based on the accumulation of a number of health deficits during the life course. The mechanisms underlying FI are multifactorial and not well understood, but a genetic basis has been suggested with heritability estimates between 30 and 45%. Understanding the genetic determinants and biological mechanisms underpinning FI may help to delay or even prevent frailty. We performed a genome‐wide association study (GWAS) meta‐analysis of a frailty index in European descent UK Biobank participants (n = 164,610, 60–70 years) and Swedish TwinGene participants (n = 10,616, 41–87 years). FI calculation was based on 49 or 44 self‐reported items on symptoms, disabilities and diagnosed diseases for UK Biobank and TwinGene, respectively. 14 loci were associated with the FI (p < 5*10⁻⁸). Many FI‐associated loci have established associations with traits such as body mass index, cardiovascular disease, smoking, HLA proteins, depression and neuroticism; however, one appears to be novel. The estimated single nucleotide polymorphism (SNP) heritability of the FI was 11% (0.11, SE 0.005). In enrichment analysis, genes expressed in the frontal cortex and hippocampus were significantly downregulated (adjusted p < 0.05). We also used Mendelian randomization to identify modifiable traits and exposures that may affect frailty risk, with a higher educational attainment genetic risk score being associated with a lower degree of frailty. Risk of frailty is influenced by many genetic factors, including well‐known disease risk factors and mental health, with particular emphasis on pathways in the brain.     

The Effect of Cooled Perches on Immunological Parameters of Caged White Leghorn Hens during the Hot Summer Months

The objective of this study was to determine if thermally cooled perches improve hen immunity during hot summer. White Leghorn pullets at 16 week of age were randomly assigned to 18 cages of 3 banks at 9 hens per cage. Each bank was assigned to 1 of the 3 treatments up to 32 week of age: 1) thermally cooled perches, 2) perches with ambient air, and 3) cages without perches. Hens were exposed to natural ambient temperatures from June through September 2013 in Indiana with a 4 h acute heat episode at 27.6 week of age. The packed cell volume, heterophil to lymphocyte (H/L) ratio, plasma concentrations of total IgG, and cytokines of interleukin-1β and interleukin-6, plus lipopolysaccharide-induced tumor necrosis factor-α factor were measured at both 27.6 and 32 week of age. The mRNA expressions of these cytokines, toll-like receptor-4, and inducible nitric oxide synthase were also examined in the spleen of 32 week-old hens. Except for H/L ratio, thermally cooled perches did not significantly improve currently measured immunological indicators. These results indicated that the ambient temperature of 2013 summer in Indiana (24°C, 17.1 to 33.1°C) was not high enough and the 4 h heat episode at 33.3°C (32 to 34.6°C) was insufficient in length to evoke severe heat stress in hens. However, cooled perch hens had a lower H/L ratio than both air perch hens and control hens at 27.6 week of age and it was still lower compared to control hens (P < 0.05, respectively) at 32 week of age. The lowered H/L ratio of cooled perch hens may suggest that they were able to cope with acute heat stress more effectively than control hens. Further studies are needed to evaluate the effectiveness of thermally cooled perches on hen health under higher ambient temperatures.     

The Effects of Melatonin on the Physical Properties of Bones and Egg Shells in the Laying Hen

Laying hens often experience unbalanced calcium utilization which can cause deficiencies in bone and egg mineralization. Because melatonin has been shown to affect bone mineralization in other animals, we examined whether treating hens with melatonin would affect eggshell thickness and improve skeletal performance, thereby reducing skeletal and egg shell defects. Birds were given a diet containing either low (30 µg/kg), medium (300 µg/kg), or high (3 mg/kg) concentrations of melatonin, or control feed through approximately one laying cycle. We examined the weight, length, and strength of egg, femur, tibia, and keel. Hens treated with a high concentration of melatonin showed significant strengthening in their femur and tibia, as measured by maximum force sustained and breaking force, compared to controls. Egg weights from hens treated with melatonin were significantly greater than those from hens that were not treated with melatonin. Conversely, egg shell mass of hens treated with melatonin was significantly lower than those of hens not treated with melatonin. Our data suggest that melatonin may affect the allocation of calcium to bone at the expense of egg shell mineralization.