Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis

Allergic rhinitis is the most common clinical presentation of allergy, affecting 400 million people worldwide, with increasing incidence in westernized countries1,2. To elucidate the genetic architecture and understand the underlying disease mechanisms, we carried out a meta-analysis of allergic rhinitis in 59,762 cases and 152,358 controls of European ancestry and identified a total of 41 risk loci for allergic rhinitis, including 20 loci not previously associated with allergic rhinitis, which were confirmed in a replication phase of 60,720 cases and 618,527 controls. Functional annotation implicated genes involved in various immune pathways, and fine mapping of the HLA region suggested amino acid variants important for antigen binding. We further performed genome-wide association study (GWAS) analyses of allergic sensitization against inhalant allergens and nonallergic rhinitis, which suggested shared genetic mechanisms across rhinitis-related traits. Future studies of the identified loci and genes might identify novel targets for treatment and prevention of allergic rhinitis

Developmental Profiles of Eczema, Wheeze, and Rhinitis: Two Population-Based Birth Cohort Studies

The term "atopic march" has been used to imply a natural progression of a cascade of symptoms from eczema to asthma and rhinitis through childhood. We hypothesize that this expression does not adequately describe the natural history of eczema, wheeze, and rhinitis during childhood. We propose that this paradigm arose from cross-sectional analyses of longitudinal studies, and may reflect a population pattern that may not predominate at the individual level.Data from 9,801 children in two population-based birth cohorts were used to determine individual profiles of eczema, wheeze, and rhinitis and whether the manifestations of these symptoms followed an atopic march pattern. Children were assessed at ages 1, 3, 5, 8, and 11 y. We used Bayesian machine learning methods to identify distinct latent classes based on individual profiles of eczema, wheeze, and rhinitis. This approach allowed us to identify groups of children with similar patterns of eczema, wheeze, and rhinitis over time. Using a latent disease profile model, the data were best described by eight latent classes: no disease (51.3%), atopic march (3.1%), persistent eczema and wheeze (2.7%), persistent eczema with later-onset rhinitis (4.7%), persistent wheeze with later-onset rhinitis (5.7%), transient wheeze (7.7%), eczema only (15.3%), and rhinitis only (9.6%). When latent variable modelling was carried out separately for the two cohorts, similar results were obtained. Highly concordant patterns of sensitisation were associated with different profiles of eczema, rhinitis, and wheeze. The main limitation of this study was the difference in wording of the questions used to ascertain the presence of eczema, wheeze, and rhinitis in the two cohorts.The developmental profiles of eczema, wheeze, and rhinitis are heterogeneous; only a small proportion of children (∼ 7% of those with symptoms) follow trajectory profiles resembling the atopic march. Please see later in the article for the Editors' Summary

The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: design, results and future prospects

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites

On hapax legomena and morphological productivity

Quantifying and predicting morphological productivity is a long-standing challenge in corpus linguistics and psycholinguistics. The same challenge reappears in natural language processing in the context of handling words that were not seen in the training set (out-of-vocabulary, or OOV, words). Prior research showed that a good indicator of the productivity of a morpheme is the number of words involving it that occur exactly once (the hapax legomena). A technical connection was adduced between this result and Good-Turing smoothing, which assigns probability mass to unseen events on the basis of the simplifying assumption that word frequencies are stationary. In a large-scale study of 133 affixes in Wikipedia, we develop evidence that success in fact depends on tapping the frequency range in which the assumptions of Good-Turing are violated

Detection and interpretation of shared genetic influences on 42 human traits

International audienceWe performed a scan for genetic variants associated with multiple phenotypes by comparing large genome-wide association studies (GWAS) of 42 traits or diseases. We identified 341 loci (at an FDR of 10%) associated with multiple traits. Several loci are associated with a large number of phenotypes; for example, a nonsynonymous variant in the zinc transporter SLC39A8 influences seven of these traits, including risk of schizophrenia (rs13107325: log-odds ratio = 0.15, P = 2 × 10 −12) and Parkinson's disease (log-odds ratio = −0.15, P = 1.6 × 10 −7), among others. Second, we used these loci to identify traits that share multiple genetic causes in common. For example, variants that increase risk of schizophrenia also tend to increase risk of inflammatory bowel disease. Finally, we developed a method to identify pairs of traits that show evidence of a causal relationship. For example, we show evidence that increased BMI causally increases triglyceride levels

Protein Hydrolysis and Nitrogen Remobilisation in Plant Life and Senescence

In plant cells, as in all other cells, proteins are submitted to permanent turnover, and the intracellular content of a given protein depends on its rate of both synthesis and degradation. The life time of most proteins is shorter than that of the cell. Thus, in young leaves of Lemna minor, the average half-life of protein was estimated to be 7 days, and it was shorter under stress conditions (Davies 1982). Such observations mean that nitrogen and amino acid fluxes are both cylic and permanent. Although protein turnover may appear wasteful, in terms of energy, numerous studies have shown that proteolysis provides multiple functions in cell physiology, and is an essential regulatory mechanism of cell metabolism and development

Wide-genome QTL mapping of fruit quality traits in a tomato RIL population derived from the wild-relative species Solanum pimpinellifolium L.

[EN] QTL and candidate genes associated to fruit quality traits have been identified in a tomato genetic map derived from Solanum pimpinellifolium L., providing molecular tools for marker-assisted breeding. The study of genetic, physiological, and molecular pathways involved in fruit development and ripening has considered tomato as the model fleshy-fruited species par excellence. Fruit quality traits regarding organoleptic and nutritional properties are major goals for tomato breeding programs since they largely decide the acceptance of tomato in both fresh and processing markets. Here we report the genetic mapping of single-locus and epistatic quantitative trait loci (QTL) associated to the fruit size and content of sugars, acids, vitamins, and carotenoids from the characterization of a RIL population derived from the wild-relative Solanum pimpinellifolium TO-937. A genetic map composed of 353 molecular markers including 13 genes regulating fruit and developmental traits was generated, which spanned 1007 cM with an average distance between markers of 2.8 cM. Genetic analyses indicated that fruit quality traits analyzed in this work exhibited transgressive segregation and that additive and epistatic effects are the major genetic basis of fruit quality traits. Moreover, most mapped QTL showed environment interaction effects. FrW7.1 fruit size QTL co-localized with QTL involved in soluble solid, vitamin C, and glucose contents, dry weight/fresh weight, and most importantly with the Sucrose Phosphate Synthase gene, suggesting that polymorphisms in this gene could influence genetic variation in several fruit quality traits. In addition, 1-deoxy-D-xylulose 5-phosphate synthase and Tocopherol cyclase genes were identified as candidate genes underlying QTL variation in beta-carotene and vitamin C. Together, our results provide useful genetic and molecular information regarding fruit quality and new chances for tomato breeding by implementing marker-assisted selection.Thanks are due to Dr. Fernando Yuste-Lisbona and Dr. Antonio Monforte for critical review of the manuscript. This work was funded by the ESPSOL project from the Fundacion Genoma of the Spanish Ministerio de Ciencia y Tecnologia. We also thank research facilities provided by the Campus de Excelencia Internacional Agroalimentario (CeiA3).Capel, C.; Fernandez Del Carmen, MA.; Alba, J.; Lima-Silva, V.; Hernandez-Gras, F.; Salinas, M.; Boronat, A.... (2015). Wide-genome QTL mapping of fruit quality traits in a tomato RIL population derived from the wild-relative species Solanum pimpinellifolium L. 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