The Survival Kit:software to analyze survival data including possibly correlated random effects

AbstractThe Survival Kit is a Fortran 90 Software intended for survival analysis using proportional hazards models and their extension to frailty models with a single response time. The hazard function is described as the product of a baseline hazard function and a positive (exponential) function of possibly time-dependent fixed and random covariates. Stratified Cox, grouped data and Weibull models can be used. Random effects can be either log-gamma or normally distributed and can account for a pedigree structure. Variance parameters are estimated in a Bayesian context. It is possible to account for the correlated nature of two random effects either by specifying a known correlation coefficient or estimating it from the data. An R interface of the Survival Kit provides a user friendly way to run the software

Heritability of longevity in Large White and Landrace sows using continuous time and grouped data models

<p>Abstract</p> <p>Background</p> <p>Using conventional measurements of lifetime, it is not possible to differentiate between productive and non-productive days during a sow's lifetime and this can lead to estimated breeding values favoring less productive animals. By rescaling the time axis from continuous to several discrete classes, grouped survival data (discrete survival time) models can be used instead.</p> <p>Methods</p> <p>The productive life length of 12319 Large White and 9833 Landrace sows was analyzed with continuous scale and grouped data models. Random effect of herd*year, fixed effects of interaction between parity and relative number of piglets, age at first farrowing and annual herd size change were included in the analysis. The genetic component was estimated from sire, sire-maternal grandsire, sire-dam, sire-maternal grandsire and animal models, and the heritabilities computed for each model type in both breeds.</p> <p>Results</p> <p>If age at first farrowing was under 43 weeks or above 60 weeks, the risk of culling sows increased. An interaction between parity and relative litter size was observed, expressed by limited culling during first parity and severe risk increase of culling sows having small litters later in life. In the Landrace breed, heritabilities ranged between 0.05 and 0.08 (s.e. 0.014-0.020) for the continuous and between 0.07 and 0.11 (s.e. 0.016-0.023) for the grouped data models, and in the Large White breed, they ranged between 0.08 and 0.14 (s.e. 0.012-0.026) for the continuous and between 0.08 and 0.13 (s.e. 0.012-0.025) for the grouped data models.</p> <p>Conclusions</p> <p>Heritabilities for length of productive life were similar with continuous time and grouped data models in both breeds. Based on these results and because grouped data models better reflect the economical needs in meat animals, we conclude that grouped data models are more appropriate in pig.</p

Carcass conformation and fat cover scores in beef cattle: A comparison of threshold linear models vs grouped data models

Background: Beef carcass conformation and fat cover scores are measured by subjective grading performed by trained technicians. The discrete nature of these scores is taken into account in genetic evaluations using a threshold model, which assumes an underlying continuous distribution called liability that can be modelled by different methods. Methods: Five threshold models were compared in this study: three threshold linear models, one including slaughterhouse and sex effects, along with other systematic effects, with homogeneous thresholds and two extensions with heterogeneous thresholds that vary across slaughterhouses and across slaughterhouse and sex and a generalised linear model with reverse extreme value errors. For this last model, the underlying variable followed a Weibull distribution and was both a log-linear model and a grouped data model. The fifth model was an extension of grouped data models with score-dependent effects in order to allow for heterogeneous thresholds that vary across slaughterhouse and sex. Goodness-of-fit of these models was tested using the bootstrap methodology. Field data included 2,539 carcasses of the Bruna dels Pirineus beef cattle breed. Results: Differences in carcass conformation and fat cover scores among slaughterhouses could not be totally captured by a systematic slaughterhouse effect, as fitted in the threshold linear model with homogeneous thresholds, and different thresholds per slaughterhouse were estimated using a slaughterhouse-specific threshold model. This model fixed most of the deficiencies when stratification by slaughterhouse was done, but it still failed to correctly fit frequencies stratified by sex, especially for fat cover, as 5 of the 8 current percentages were not included within the bootstrap interval. This indicates that scoring varied with sex and a specific sex per slaughterhouse threshold linear model should be used in order to guarantee the goodness-of-fit of the genetic evaluation model. This was also observed in grouped data models that avoided fitting deficiencies when slaughterhouse and sex effects were score-dependent. Conclusions: Both threshold linear models and grouped data models can guarantee the goodness-of-fit of the genetic evaluation for carcass conformation and fat cover, but our results highlight the need for specific thresholds by sex and slaughterhouse in order to avoid fitting deficiencies

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

<p>Abstract</p> <p>Background</p> <p>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).</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p

Impact of upstream moisture structure on a back-building convective precipitation system in south-eastern France during HyMeX IOP13

The present study examines the impact of the environmental moisture structure in the lower troposphere (below 2&thinsp;km above sea level, a.s.l.) on the precipitation development, observed in southern France during Intensive Observation Period (IOP) 13 of the first Special Observation Period of the Hydrological cycle in the Mediterranean Experiment (HyMeX SOP-1), through a series of sensitivity experiments using the non-hydrostatic mesoscale atmospheric numerical model (Meso-NH). The control simulation (CNTL) and all the other 12 sensitivity experiments examined in this study succeed in reproducing a heavy precipitation event (HPE) in the coastal mountainous region of Var in south-eastern France as observed. The sensitivity experiments are designed to investigate the response of the HPE to the variability of the water vapour content upstream in the moist marine atmospheric boundary layer (MABL) and the drier air above. The comparisons between CNTL and the 12 sensitivity experiments show how the life cycle of precipitation associated with the HPE, but also the upstream flow (over the sea), is modified, even for moisture content changes of only 1&thinsp;g&thinsp;kg−1 below 2&thinsp;km&thinsp;a.s.l. Within the low-level wind convergence between southerlies and south-westerlies, a small increase of moisture content in the MABL prolongs moderate precipitation (≥5&thinsp;mm in 15&thinsp;min) and enlarges the area of weak precipitation (≥1&thinsp;mm in 15&thinsp;min). The moistening in the 1–2&thinsp;km&thinsp;a.s.l. layer, just above the MABL, prolongs the duration of moderate precipitation, for a similar total precipitation amount as in CNTL. The drier MABL and 1–2&thinsp;km&thinsp;a.s.l. layer shorten the lifetime of precipitation and reduce the total precipitation amount with respect to CNTL. We also found that the moisture in the MABL has a stronger impact on producing enhanced precipitation (both in terms of amount and intensity) than the moisture just above (1–2&thinsp;km&thinsp;a.s.l.). Also, it is worth noting that adding moisture in the MABL does not necessarily lead to enhanced precipitation amount. In moistening the MABL, the duration of moderate precipitation increases with increasing moisture as does the area covered by weak precipitation, while the area covered by the intense precipitation (≥30&thinsp;mm) decreases. Despite a simplified moisture-profile modification approach, this study suggests that moisture structure in the lower troposphere is key for accurate prediction at short-term range of the timing and location of precipitation in the coastal mountainous region in southern France.</p

Potential impact of the 2017 ACC/AHA guideline on high blood pressure in normotensive patients with stable coronary artery disease: insights from the CLARIFY registry

Aims: The 2017 American College of Cardiology/American Heart Association (ACC/AHA) guideline on high blood pressure (BP) lowered the threshold defining hypertension and BP target in high-risk patients to 130/80 mmHg. Patients with coronary artery disease and systolic BP 130-139 mmHg or diastolic BP 80-89 mmHg should now receive medication to achieve this target. We aimed to investigate the relationship between BP and cardiovascular events in 'real-life' patients with coronary artery disease considered as having normal BP until the recent guideline. Methods and results: Data from 5956 patients with stable coronary artery disease, no history of hypertension or heart failure, and average BP <140/90 mmHg, enrolled in the CLARIFY registry (November 2009 to June 2010), were analysed. In a multivariable-adjusted Cox proportional hazards model, after a median follow-up of 5.0 years, diastolic BP 80-89 mmHg, but not systolic BP 130-139 mmHg, was associated with increased risk of the primary endpoint, a composite of cardiovascular death, myocardial infarction, or stroke (hazard ratio 2.15, 95% confidence interval 1.22-3.81 vs. 70-79 mmHg and 1.12, 0.64-1.97 vs. 120-129 mmHg). No significant increase in risk for the primary endpoint was observed for systolic BP <120 mmHg or diastolic BP <70 mmHg. Conclusion: In patients with stable coronary artery disease defined as having normal BP according to the 140/90 mmHg threshold, diastolic BP 80-89 mmHg was associated with increased cardiovascular risk, whereas systolic BP 130-139 mmHg was not, supporting the lower diastolic but not the lower systolic BP hypertension-defining threshold and treatment target in coronary artery disease. ClinicalTrials identifier: ISRCTN43070564

Developing flexible models for genetic evaluations in smallholder crossbred dairy farms

The productivity of smallholder dairy farms is very low in developing countries. Important genetic gains could be realized using genomic selection, but genetic evaluations need to be tailored for lack of pedigree information and very small farm sizes. To accommodate this situation, we propose a flexible Bayesian model for the genetic evaluation of milk yield, which allows us to simultaneously account for nongenetic random effects for farms and varying SNP variance (BayesR model). First, we used simulations based on real genotype data from Indian crossbred dairy cattle to demonstrate that the proposed model can separate the true genetic and nongenetic parameters even for small farm sizes (2 cows on average) although with high standard errors in scenarios with low heritability. The accuracy of genomic genetic evaluation increased until farm size was approximately 5. We then applied the model to real data from 4,655 crossbred cows with 106,109 monthly test day milk records and 689,750 autosomal SNPs. We estimated a heritability of 0.16 (0.04) for milk yield and using cross-validation, a genomic estimated breeding value (GEBV) accuracy of 0.45 and bias (regression of phenotype on GEBV) of 1.04 (0.26). Estimated genetic parameters were very similar using BayesR, BayesC, and genomic BLUP approaches. Candidate genes near the top variants, IMMP2L and ARHGEF2, have been previously associated with milk protein composition, mastitis resistance, and milk cholesterol content. The estimated heritability and GEBV accuracy for milk yield are much lower than those from intensive or pasture-based systems in many countries. Further increases in the number of phenotyped and genotyped animals in farms with at least 2 cows (preferably 3–5, to allow for dropout of cows) are needed to improve the estimation of genetic effects in these smallholder dairy farms