Bridging Micro- and Macro-Analyses of the EU Sugar Program: Methods and Insights

Crop Production/Industries,

When is an endophenotype useful to detect association to a disease? Exploring the relationships between disease status, endophenotype and genetic polymorphisms

Objectives: To investigate the conditions and analysis strategies required so that endophenotypes related to a disease help discover genetic variants involved in the disease. Methods: The association with disease susceptibility variants is examined as a function of the relationships between disease status, endophenotype values and the genotype at another disease or endophenotype susceptibility locus assumed to be previously known, using approximate linear models of allele frequencies as a function of these variables and simulations in the context of family studies when the endophenotype is dichotomous. Results: Under genetic mechanisms where the risk allele of the tested locus has an effect exclusively in subjects with the endophenotype, the risk allele frequency differences between affected and unaffected subjects are much greater in the subset of subjects with an endophenotype impairment than in those without such an impairment, and power gains are obtained when testing the association under a joint disease-endophenotype model, both with two-locus or single-locus tests. However, with moderate main effect on the risk of disease or endophenotype impairment, testing directly the association between risk allele and disease or endophenotype is more powerful than testing under a joint disease-endophenotype model. Conclusions: Joint modeling of disease and endophenotype should be used only in parallel with standard disease association testing

Semi-Parametric Maximum Likelihood Method for Interaction in Case-Mother Control-Mother Designs: Package SPmlficmcm

The analysis of interaction effects involving genetic variants and environmental exposures on the risk of adverse obstetric and early-life outcomes is generally performed using standard logistic regression in the case-mother and control-mother design. However such an analysis is inefficient because it does not take into account the natural family-based constraints present in the parent-child relationship. Recently, a new approach based on semi-parametric maximum likelihood estimation was proposed. The advantage of this approach is that it takes into account the parental relationship between the mother and her child in estimation. But a package implementing this method has not been widely available. In this paper, we present SPmlficmcm, an R package implementing this new method and we propose an extension of the method to handle missing offspring genotype data by maximum likelihood estimation. Our choice to treat missing data of the offspring genotype was motivated by the fact that in genetic association studies where the genetic data of mother and child are available, there are usually more missing data on the genotype of the offspring than that of the mother. The package builds a non-linear system from the data and solves and computes the estimates from the gradient and the Hessian matrix of the log profile semi-parametric likelihood function. Finally, we analyze a simulated dataset to show the usefulness of the package

The Impact of an EU-US Transatlantic Trade and Investment Partnership Agreement on Biofuel and Feedstock Markets

We assess the impact of a potential TTIP bilateral free trade agreement on the EU and US bio-economies (feedstock, biofuels, by-products, and related competing crops) and major trade partners in these markets. The analysis develops a multi-market model that incorporates bilateral trade flows (US to EU, EU to US, and similarly with third countries) and is calibrated to OECD-FAO baseline for 2013–2022 to account for recent policy decisions. The major policy reforms from a TTIP involve tariff and TRQ liberalization and their direct contractionary impact on US sugar supply, EU biofuel production, and indirect negative effect on US HFCS production. EU sugar and isoglucose productions expand along with US ethanol and biodiesel and oilseed crushing. EU sugar would flow to the US, US biofuels and vegetable oil to the EU. We further quantify nontariff measures (NTM) affecting these trade flows between the EU and the US. EU oilseed production contracts, and EU crushing expands with improving crushing margins following reduced NTM frictions. Our analysis reveals limited net welfare gains with most net benefits reaped by Brazil and not the two trading partners of the TTIP

The impact of an EU-US Transatlantic Trade and Investment Partnership Agreement on Biofuel and Feedstock Markets

We assess the impact of a potential TTIP bilateral free trade agreement on the EU and US bio-economies (feedstock, biofuels, by-products, and related competing crops) and major trade partners in these markets. The analysis develops a multi-market model that incorporates bilateral trade flows (US to EU, EU to US, and similarly with third countries) and is calibrated to OECD-FAO baseline for 2013–2022 to account for recent policy decisions. The major policy reforms from a TTIP involve tariff and TRQ liberalization and their direct contractionary impact on US sugar supply, EU biofuel production, and indirect negative effect on US HFCS production. EU sugar and isoglucose productions expand along with US ethanol and biodiesel and oilseed crushing. EU sugar would flow to the US, US biofuels and vegetable oil to the EU. We further quantify nontariff measures (NTM) affecting these trade flows between the EU and the US. EU oilseed production contracts, and EU crushing expands with improving crushing margins following reduced NTM frictions. Our analysis reveals limited net welfare gains with most net benefits reaped by Brazil and not the two trading partners of the TTIP

Mapping complex traits using Random Forests

Random Forest is a prediction technique based on growing trees on bootstrap samples of data, in conjunction with a random selection of explanatory variables to define the best split at each node. In the case of a quantitative outcome, the tree predictor takes on a numerical value. We applied Random Forest to the first replicate of the Genetic Analysis Workshop 13 simulated data set, with the sibling pairs as our units of analysis and identity by descent (IBD) at selected loci as our explanatory variables. With the knowledge of the true model, we performed two sets of analyses on three phenotypes: HDL, triglycerides, and glucose. The goal was to approach the mapping of complex traits from a multivariate perspective. The first set of analyses mimics a candidate gene approach with a high proportion of true genes among the predictors while the second set represents a genome scan analysis using microsatellite markers. Random Forest was able to identify a few of the major genes influencing the phenotypes, such as baseline HDL and triglycerides, but failed to identify the major genes regulating baseline glucose levels

The future of global sugar markets: Policies, reforms, and impact

"Sugar is one of the most highly protected agricultural commodities worldwide. This protection depresses trade opportunities and the prices received by exporters without preferential market access. For this reason, dialogues about sugar policy are often polarized and short sound bites caustic. Yet today's sugar markets are being driven by a complex array of dynamic and emerging supply, demand, and policy forces that need to be understood. A number of these forces have the potential to reshape the global market scene. Recent sugar policy reforms in the European Union (EU) have received little attention in North America but may turn the EU into a net importer, with substantial compensation paid to its farmers and displaced processing facilities. High oil prices and the related ethanol boom place Brazil at the fulcrum of new market developments. In the United States, corn sweetener and sugar markets are being integrated with Mexican markets under the North American Free Trade Agreement (NAFTA), raising the question of whether the EU reforms provide a template for new policies. And among developing countries in Africa and elsewhere there are low-cost producers that would benefit from more open trade but others who would be disadvantaged by the loss of preferential markets. This discussion paper presents the proceedings of a one-day conference that served as a forum for the discussion of these and other critical issues affecting global sugar markets, policies, and reform options. The conference was attended by 60 representatives of governments, research institutions, producers and processors from the sugar sector, and other groups interested in sugar markets and policies. The four papers were presented by internationally recognized experts from the EU, Brazil, the United States, and South Africa. Discussion openers and general discussion at the conference added further policy insights, and the papers were edited and revised after the conference to reflect the dialogue that had occurred." from authors' abstractsugar, Ethanol, NAFTA, WTO, Trade policy,

Three-Dimensional Ultrasound Matrix Imaging

Matrix imaging paves the way towards a next revolution in wave physics. Based on the response matrix recorded between a set of sensors, it enables an optimized compensation of aberration phenomena and multiple scattering events that usually drastically hinder the focusing process in heterogeneous media. Although it gave rise to spectacular results in optical microscopy or seismic imaging, the success of matrix imaging has been so far relatively limited with ultrasonic waves because wave control is generally only performed with a linear array of transducers. In this paper, we extend ultrasound matrix imaging to a 3D geometry. Switching from a 1D to a 2D probe enables a much sharper estimation of the transmission matrix that links each transducer and each medium voxel. Here, we first present an experimental proof of concept on a tissue-mimicking phantom through ex-vivo tissues and then, show the potential of 3D matrix imaging for transcranial applications.Comment: 60 pages, 14 figure

Estimating genetic effect sizes under joint disease-endophenotype models in presence of gene-environment interactions

Effects of genetic variants on the risk of complex diseases estimated from association studies are typically small. Nonetheless, variants may have important effects in presence of specific levels of environmental exposures, and when a trait related to the disease (endophenotype) is either normal or impaired. We propose polytomous and transition models to represent the relationship between disease, endophenotype, genotype and environmental exposure in family studies. Model coefficients were estimated using generalized estimating equations and were used to derive gene-environment interaction effects and genotype effects at specific levels of exposure. In a simulation study, estimates of the effect of a genetic variant were substantially higher when both an endophenotype and an environmental exposure modifying the variant effect were taken into account, particularly under transition models, compared to the alternative of ignoring the endophenotype. Illustration of the proposed modeling with the metabolic syndrome, abdominal obesity, physical activity and polymorphisms in the NOX3 gene in the Quebec Family Study revealed that the positive association of the A allele of rs1375713 with the metabolic syndrome at high levels of physical activity was only detectable in subjects without abdominal obesity, illustrating the importance of taking into account the abdominal obesity endophenotype in this analysis