ABSTRACT
The residual feed intake (RFI) model has recently gained popularity for ranking dairy cows for feed efficiency. The RFI model ranks the cows based on their expected feed intake compared to the observed feed intake, where a negative phenotype (eating less than expected) is favourable. Yet interpreting the biological implications of the regression coefficients derived from RFI models has proven challenging. In addition, multitrait modelling of RFI has been proposed as an alternative to the least square RFI in nutrition and genetic studies. To solve the challenge with the biological interpretation of RFI regression coefficients and suggest ways to improve the modelling of RFI, an interdisciplinary effort was required between nutritionists and geneticists. Therefore, this paper aimed to explore the challenges with the traditional least square RFI model and propose solutions to improve the modelling of RFI. In the traditional least square RFI model, one set of fixed effects is used to solve systematic effects (e.g., seasonal effects and age at calving) for traits with different means and variances. Thereby, measurement and model fitting errors can accumulate in the phenotype, resulting in undesirable effects. A multivariate RFI model will likely reduce this problem, as trait-specific fixed effects are used. In addition, regression coefficients for DM intake on milk energy tend to have more biologically meaningful estimates in multitrait RFI models, which indicates a confounding effect between the fixed effects and regression coefficients in the least square RFI model. However, defining precise expectations for regression coefficients from RFI models or sourcing for accurate feed norm coefficients seems difficult, especially if the coefficients are applied to a wide cattle population with varying diets or management systems, for example. To improve multitrait modelling of RFI, we suggest improving the modelling of changes in energy status. Furthermore, a novel method to derive the energy density of the diet and individual digestive efficiency is proposed. Digestive efficiency is defined as the part of the efficiency associated with digestive processes, which primarily reflects the conversion from gross energy to metabolisable energy. We show the model was insensitive to prior values of energy density in feed and that there was individual variation in digestive efficiency. The proposed method needs further development and validation. In summary, using multitrait RFI can improve the accuracy of the ranking of dairy cows' feed efficiency, consequently improving economic and environmental sustainability on dairy farms.
ABSTRACT
Australian beef cattle experience variable conditions, which may give rise to genotype-by-environment interactions depending on the genotypes' macro- and/or micro-genetic environmental sensitivity (GES). Macro-GES gives rise to genotype-by-environment interactions across definable and shared environments, while micro-GES causes heritable variation of phenotypes, e.g., the performance of progeny from one sire may be more variable than other sires. Yearling weight (YW) is a key trait in Australian Angus cattle that may be impacted by both macro- and micro-GES. Current models for genetic evaluation of YW attempt to account for macro-GES by fitting sire-by-herd interactions (Sâ¯×â¯H). Variation in micro-GES had not yet been estimated for YW in Australian Angus. The aim of this study was to estimate genetic variation due to macro- and micro-GES in YW of Australian Angus cattle. A reaction norm with contemporary group effects as the environmental covariate was fitted either as an alternative to or in combination with a random Sâ¯×â¯H effect to account for macro-GES. Double hierarchical generalised linear models (DHGLM), fitted as sire models, were used to estimate the genetic variance of the dispersion as a measure of micro-GES. Variation due to both macro- and micro-GES were found in YW. The variance of the slope of the reaction norm was 0.02-0.03 (SEs 0.00), while the Sâ¯×â¯H variance accounted for 7% of the phenotypic variance in all models. Results showed that both a random Sâ¯×â¯H effect and a reaction norm should be included to account for both macro-GES and the additional variation captured by an Sâ¯×â¯H effect. The heritability of the dispersion on the measurement scale ranged from 0.06 to 0.10 (SEs 0.00) depending on which model was used. It should therefore be possible to alter both macro- and micro-GES of YW in Australian Angus through selection. However, care should be taken to ensure an appropriate data structure when including sire-by-herd interactions in the mean part of a DHGLM; otherwise, it can cause biased estimates of micro-GES.
Subject(s)
Models, Genetic , Cattle/genetics , Animals , Australia , Phenotype , Genotype , Linear Models , Body Weight/geneticsABSTRACT
Introducción y objetivos El metanálisis DECADE es un análisis de datos de pacientes individuales de ensayos de stents liberadores de fármacos (SLF) con un seguimiento de 10 años. El objetivo del estudio es analizar el riesgo de trombosis definitiva del stent (TS) hasta 10 años después de la intervención coronaria percutánea (ICP) en pacientes tratados con DES de primera y de nueva generación. Métodos Se agruparon los datos de pacientes individuales de cinco ensayos de SLF con un seguimiento de 10 años. El objetivo primario fue la TS hasta 10 años después de la ICP. Los pacientes se dividieron en 2 grupos según la generación de stent implantada (primera y nueva). El análisis de los datos de los participantes individuales se realizó mediante el enfoque de una etapa. Resultados Se incluyeron 9.700 pacientes, 6.866 en el grupo de SLF nuevos y 2.834 en el grupo de SLF de primera generación. A los 10 años, la TS se produjo en 69 de los 6.866 pacientes tratados con SLF de nueva generación y en 91 de los 2.834 pacientes tratados con la SLF de primera generación (1,0% frente a 3,5%, razón de tasas 0,32; IC95%, 0,23-0,45). La tasa de TS fue menor en el grupo de SLF de nueva generación en comparación con el grupo de SLF de primera, de 1-5 años (razón de tasas 0,14; IC95%, 0,08-0,26) y de 5-10 años (razón de tasas 0,23; IC95%, 0,08-0,61) después de la ICP. Conclusiones La incidencia de TS hasta 10 años después de la ICP con los SLF de nueva generación es del 1%. Los SLF de nueva generación se asocian a una menor incidencia de TS a 10 años comparados con los SLF de primera generación, especialmente después de 1 año de la ICP (AU)
Introduction and objectives The DECADE cooperation is a pooled analysis of individual patient data from drug-eluting stent (DES) trials with a 10-year follow-up. This analysis reports the risk of definite stent thrombosis (ST) through to 10 years after percutaneous coronary intervention (PCI) in patients treated with early- and new-generation DES. Methods Individual patient data from 5 DES trials with a 10-year follow-up were pooled. The primary endpoint was definite ST up to 10 years after PCI. Patients were divided into 2 groups as per the generation of DES implanted (early and new DES). Individual participant data were analyzed using a 1-stage approach. Results We included 9700 patients, 6866 in the new DES group and 2834 in the early DES group. Through to 10 years, definite ST occurred in 69 of 6866 patients treated with new DES and in 91 of 2834 patients treated with early DES (1.0% vs 3.5%, adjusted hazard ratio, 0.32; 95%CI, 0.23-0.45). The rate of definite ST was lower in the new DES group than in the early DES group from 1 to 5 years (rate ratio, 0.14; 95%CI, 0.08-0.26) and from 5 to 10 years (rate ratio, 0.23; 95%CI, 0.08-0.61) after PCI. Conclusions The incidence of definite ST through to 10 years after PCI with new-generation DES was 1%. New-generation DES are associated with a lower 10-year incidence of definite ST than early-generation DES, particularly beyond 1 year after PC (AU)