A note on the evaluation of a beta-casein variant in bovine breeds by allele-specific PCR and relevance to β-casomorphin

peer-reviewedThis work was supported by Enterprise Ireland and by a Teagasc Walsh fellowship to A.F. Keating.Two genetic variants of the bovine β-casein gene (A1 and B) encode a histidine residue at codon 67, resulting in potential liberation of a bioactive peptide, β-casomorphin, upon digestion. An allele-specific PCR (AS-PCR) was evaluated to distinguish between the β-casomorphin-releasing variants (A1 and B) and the non-releasing variants. AS-PCR successfully distinguished β-casein variants in 41 of 42 animals as confirmed by sequence analysis. Overall, while the incidence of the homozygous A1 and B animals (i.e., homozygous for the histidine residue; 21.4%) was lower than that for animals without the histidine residue (30.9% respectively), 69% of animals carried at least one allele for the histidine residue at codon 67.Teagasc Walsh Fellowship ProgrammeEnterprise Irelan

Towards evolutionary predictions:Current promises and challenges

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions

Mortality forecasting in Colombia from abridged life tables by sex

[EN] BACKGROUND: An adequate forecasting model of mortality that allows an analysis of different population changes is a topic of interest for countries in demographic transition. Phenomena such as the reduction of mortality, ageing, and the increase in life expectancy are extremely useful in the planning of public policies that seek to promote the economic and social development of countries. To our knowledge, this paper is one of the first to evaluate the performance of mortality forecasting models applied to abridged life tables. OBJECTIVE: Select a mortality model that best describes and forecasts the characteristics of mortality in Colombia when only abridged life tables are available. DATA AND METHOD: We used Colombian abridged life tables for the period 1973-2005 with data from the Latin American Human Mortality Database. Different mortality models to deal with modeling and forecasting probability of death are presented in this study. For the comparison of mortality models, two criteria were analyzed: graphical residuals analysis and the hold-out method to evaluate the predictive performance of the models, applying different goodness of fit measures. RESULTS: Only three models did not have convergence problems: Lee-Carter (LC), Lee-Carter with two terms (LC2), and Age-Period-Cohort (APC) models. All models fit better for women, the improvement of LC2 on LC is mostly for central ages for men, and the APC model's fit is worse than the other two. The analysis of the standardized deviance residuals allows us to deduce that the models that reasonably fit the Colombian mortality data are LC and LC2. The major residuals correspond to children's ages and later ages for both sexes. CONCLUSION: The LC and LC2 models present better goodness of fit, identifying the principal characteristics of mortality for Colombia.Mortality forecasting from abridged life tables by sex has clear added value for studying differences between developing countries and convergence/divergence of demographic changes.Support for the research presented in this paper was provided by a grant from the Ministerio de Economía y Competitividad of Spain, project no. MTM2013-45381-P.Diaz-Rojo, G.; Debón Aucejo, AM.; Giner-Bosch, V. (2018). Mortality forecasting in Colombia from abridged life tables by sex. Genus. Journal of Population Sciences (Online). 74(15):1-23. https://doi.org/10.1186/s41118-018-0038-6S1237415Aburto, J.M., & García-Guerrero, V.M. (2015). El modelo aditivo doble multiplicativo. Una aplicacion a la mortalidad mexicaná. Papeles de Población, 21(84), 9–44.Acosta, K., & Romero, J. (2014). Cambios recientes en las principales causas de mortalidad en Colombia. 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(2014). Demography: forecasting mortality, fertility, migration and population data. R package version 1.18. https://CRAN.R-project.org/package=demography .Hyndman, R.J., & Ullah, M.S (2007). Robust forecasting of mortality and fertility rates: a functional data approach. Computational Statistics & Data Analysis, 51(10), 4942–4956.Kennes, T. (2017). The convergence and robustness of cohort extensions of mortality models. MaRBLe, 1, 36–53.Lee, R., & Carter, L. (1992). Modelling and forecasting U.S. mortality. Journal of the American Statistical Association, 87, 659–671.Lee, R., & Rofman, R. (1994). Modelación y proyección de la mortalidad en Chile. Notas de Poblacion, 6(59), 183–213.Lee, W. (1997). Characterizing exposure-disease association in human populations using the Lorenz curve and Gini index. Statistics in Medicine, 16(7), 729–739.Levitt, S., & Rubio, M. (2000). Understanding crime in Colombia and what can be done about it. 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La mortalidad y la longevidad en la cuantificación del riesgo actuarial para la población de México. PhD thesis: Universitat de Barcelona.Remund, A., Camarda, C.G., Riffe, T., et al. (2017). A cause-of-death decomposition of the young adult mortality hump. Technical report. Rostock, Germany: Max Planck Institute for Demographic Research.Renshaw, A.E., & Haberman, S. (2003). Lee-Carter mortality forecasting with age-specific enhancement. Insurance: Mathematics and Economics, 33(2), 255–272.Renshaw, A.E., & Haberman, S. (2006). A cohort-based extensionto the Lee-Carter model for mortality reduction factors. Insurance: Mathematic and Economics, 38(3), 556–570.Reyes, A.R. (2010). Una aproximación al costo fiscal en pensiones como consecuencia del envejecimiento de la población en Colombia y el efecto de la sobre-mortalidad masculina. Master’s thesis: Universidad Nacional de Colombia.Richards, S. (2008). Detecting year-of-birth mortality patterns with limited data. 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R package version 1.0-8. https://CRAN.R-project.org/package=gnm .Urdinola, B.P., & Queiroz, B.L. (2017). Latin American Human Mortality Database. http://www.lamortalidad.org . Accessed 21 Nov 2015

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

Acute phase and immune-related gene expression in rainbow trout Oncorhynchus mykiss subjected to confinement stress

Under intensive aquaculture conditions, fish are exposed to various stressors, which are unavoidable components of this type of environment. Stressful conditions can lead to an overall reduction in performance, including poor acclimation and growth, impaired reproduction and increased susceptibility to disease. Acute phase genes, as part of the innate immune response, are typically expressed constitutively under normal conditions. Induced by trauma or infection the concentration of major acute phase proteins such as Serum Amyloid A (SAA) can rise dramatically in the blood - up to 1000-fold over normal circulating levels. This study was conducted to determine whether a non-invasive model stressor, confinement, can influence the expression of hepatic rainbow trout acute phase and immune-related genes

A note on the evaluation of a beta-casein variant in bovine breeds by allele-specific PCR and relevance to β-casomorphin

This work was supported by Enterprise Ireland and by a Teagasc Walsh fellowship to A.F. Keating.Two genetic variants of the bovine β-casein gene (A1 and B) encode a histidine residue at codon 67, resulting in potential liberation of a bioactive peptide, β-casomorphin, upon digestion. An allele-specific PCR (AS-PCR) was evaluated to distinguish between the β-casomorphin-releasing variants (A1 and B) and the non-releasing variants. AS-PCR successfully distinguished β-casein variants in 41 of 42 animals as confirmed by sequence analysis. Overall, while the incidence of the homozygous A1 and B animals (i.e., homozygous for the histidine residue; 21.4%) was lower than that for animals without the histidine residue (30.9% respectively), 69% of animals carried at least one allele for the histidine residue at codon 67.Teagasc Walsh Fellowship ProgrammeEnterprise Irelan