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1. Risk allele of gene variant rs6584389 is associated with increased intima-media thickness in patients with type 2 diabetes.

Author

Kozarova M, Malachovska Z, Zidzik J, Javorsky M, Demkova K, Habalova V, and Tkac I

Subjects
Age Factors, Aged, Asymptomatic Diseases, Biomarkers blood, Carotid Artery Diseases diagnostic imaging, Chi-Square Distribution, Diabetes Mellitus, Type 2 blood, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 diagnosis, Diabetic Angiopathies diagnostic imaging, Female, Gene Frequency, Genetic Association Studies, Genetic Predisposition to Disease, Glycated Hemoglobin metabolism, Humans, Linear Models, Male, Middle Aged, PAX2 Transcription Factor genetics, Peripheral Arterial Disease diagnostic imaging, Phenotype, Pulse Wave Analysis, Risk Factors, Carotid Artery Diseases genetics, Carotid Intima-Media Thickness, Chromosomes, Human, Pair 10, Diabetes Mellitus, Type 2 genetics, Diabetic Angiopathies genetics, Peripheral Arterial Disease genetics, Polymorphism, Single Nucleotide
Abstract

Background: Genome-wide association studies identified several gene variants associated with peripheral arterial disease (PAD). Among them, rs6584389 A>C was significantly associated with PAD defined by decreased ankle-brachial index (ABI). The aim of this study was to investigate whether the rs6584389 variant is also associated with the earlier stages of atherosclerosis assessed by intima-media thickness (IMT) or pulse-wave velocity (PWV) in clinically asymptomatic subjects with type 2 diabetes (T2DM), a group of patients with a high cardiovascular risk., Patients and Methods: In total, 111 patients with T2DM (56 females, 55 males) with a mean age 63.0 ± 9.1 years were consecutively included in the study. IMT was measured by ultrasound using 7 MHz linear transducer. PWV was measured using a piezoelectric method. Genotyping for rs6584389 was performed by PCR-HRMA method., Results: The carriers of the risk C-allele of rs6584389 variant had significantly higher mean left-side IMT (AA: 0.67 ± 0.12, AC 0.77 ± 0.21, CC 0.78 ± 0.22 mm; p = 0.04). In multiple linear regression analysis, rs6586389 genotype was significantly associated with all measured IMT parameters. The presence of each risk C-allele predicted an increase in left-side IMT by 0.056 mm (p = 0.017), right-side IMT by 0.053 mm (p = 0.039), average IMT by 0.054 mm (p = 0.023), and maximal IMT by 0.058 mm (p = 0.021). Age and HbA1c levels were also significantly associated with increased IMT in all multivariate models., Conclusions: Gene variant rs6584389 A>C near to PAX2 gene was associated with increased carotid IMT in patients with type 2 diabetes independently of the other main risk factors for atherosclerosis.

Published
2018
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2. Polymorphism rs2073618 of the osteoprotegerin gene as a potential marker of subclinical carotid atherosclerosis in Caucasians with type 2 diabetes mellitus.

Author

Pleskovič A, Ramuš SM, Pražnikar ZJ, Šantl Letonja M, Cokan Vujkovac A, Gazdikova K, Caprnda M, Gaspar L, Kruzliak P, and Petrovič D

Subjects
Aged, Asymptomatic Diseases, Carotid Artery Diseases diagnosis, Carotid Artery Diseases ethnology, Carotid Intima-Media Thickness, Cross-Sectional Studies, Diabetes Mellitus, Type 2 diagnosis, Diabetes Mellitus, Type 2 ethnology, Female, Gene Frequency, Genetic Association Studies, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Osteoprotegerin blood, Phenotype, Risk Assessment, Risk Factors, Slovenia epidemiology, Carotid Artery Diseases genetics, Diabetes Mellitus, Type 2 genetics, Osteoprotegerin genetics, Polymorphism, Single Nucleotide, White People genetics
Abstract

Background: The OPG/RANKL/RANK (osteoprotegerin/receptor-activator of nuclear factor κB ligand/receptor-activator of nuclear factor κB) axis has been recently linked to the development of atherosclerosis and plaque destabilization. We have investigated whether polymorphism rs2073618 of the OPG gene is associated with subclinical markers of carotid atherosclerosis in subjects with type 2 diabetes mellitus (T2DM)., Patients and Methods: 595 subjects with T2DM were enrolled in the cross-sectional study. Subclinical markers of carotid atherosclerosis (carotid intima media thickness, plaque thickness, and plaques presence) were assessed with ultrasound at the time of recruitment. Genotyping for rs2073618 (a missense variant located in exon I of the OPG gene) was performed, and OPG serum levels were determined by ELISA., Results: Compared to the GG genotype, the CC genotype of the rs2073618 polymorphism had a significantly increased risk for the presence of carotid plaque (OR = 2.54, 95 % CI = 1.22-5.28, p = 0.01). No statistically significant difference could be detected (p = 0.68) upon comparing median values of serum OPG levels among studied genotype groups in subjects with T2DM. Multivariable linear regression analyses in T2DM subjects demonstrated that GC and CC genotypes (p = 0.03 and p = 0.003), together with statin therapy (p = 0.009), were independent predictors of the number of carotid segments with plaques., Conclusions: Despite the fact that OPG rs2073618 genotypes failed to predict the serum OPG levels as there was no statistical difference among compared genotypes, our results demonstrate that the rs2073618 polymorphism could be a possible genetic marker for the prediction of increased risk for carotid plaque burden as a measure of advanced subclinical atherosclerosis in T2DM subjects.

Published
2017
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3. The nicotinic receptor alpha5 coding polymorphism rs16969968 as a major target in disease: Functional dissection and remaining challenges

Author

Uwe Maskos, Neurobiologie intégrative des Systèmes cholinergiques / Integrative Neurobiology of Cholinergic Systems (NISC), Sorbonne Université (SU)-Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), he author has received funding to carry out the work of his laboratory described in the Review article, as indicated in the published papers. No funding has been received that is directly relevant to this Review article. The author has no conflict of interest to declare., and Institut Pasteur [Paris] (IP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0301 basic medicine, human genetics, Single-nucleotide polymorphism, Locus (genetics), Genome-wide association study, Disease, Receptors, Nicotinic, Biology, Bioinformatics, Polymorphism, Single Nucleotide, Biochemistry, nicotine addiction, drug discovery, 03 medical and health sciences, Cellular and Molecular Neuroscience, [SCCO]Cognitive science, 0302 clinical medicine, single nucleotide polymorphism, Animals, Humans, nicotinic acetylcholine receptor, Genetic association, [SCCO.NEUR]Cognitive science/Neuroscience, Human genetics, 3. Good health, schizophrenia, Nicotinic acetylcholine receptor, 030104 developmental biology, Nicotinic agonist, positive allosteric modulator, Genome-wide Association Studies, 030217 neurology & neurosurgery
Abstract

International audience; Nicotinic acetylcholine receptors (nAChRs) are major signalling molecules in the central and peripheral nervous system. Over the last decade, they have been linked to a number of major human psychiatric and neurological conditions, like smoking, schizophrenia, Alzheimer's disease and many others. Human Genome-Wide Association Studies (GWAS) have robustly identified genetic alterations at a locus of chromosome 15q to several of these diseases. In this review, we discuss a major coding polymorphism in the alpha5 subunit, referred to as α5SNP, and its functional dissection in vitro and in vivo. Its presence at high frequency in many human populations lends itself to pharmaceutical intervention in the context of 'positive allosteric modulators' (PAMs). We will present the prospects of this novel treatment, and the remaining challenges to identify suitable molecules.

Published
2020

4. Independent and Joint‐<scp>GWAS</scp>for growth traits inEucalyptusby assembling genome‐wide data for 3373 individuals across four breeding populations

Author

Bárbara S. F. Müller, Janeo Eustáquio de Almeida Filho, Aurélio Mendes Aguiar, Alexandre Alves Missiaggia, Orzenil B. Silva-Junior, Dario Grattapaglia, Leandro G. Neves, Elizabete Keiko Takahashi, Bruno Marco de Lima, Carla Garcia, Matias Kirst, Salvador A. Gezan, BÁRBARA S. F. MULLER, UNB, ORZENIL BONFIM DA SILVA JUNIOR, Cenargen, LEANDRO G. NEVES, RAPID GENOMICS LLC, USA, DARIO GRATTAPAGLIA, Cenargen., JANEO E. DE ALMEIDA FILHO, UENF, BRUNO M. LIMA, FIBRIA S.A. TECHNOLOGY CENTER, CARLA C. GARCIA, INTERNATIONAL PAPER OF BRAZIL, ALEXANDRE MISSIAGGIA, FIBRIA S.A. TECHNOLOGY CENTER, AURELIO M. AGUIAR, FIBRIA S.A. TECHNOLOGY CENTER, ELIZABETE TAKAHASHI, CELULOSE NIPO-BRASILEIRA (CENIBRA) S.A., MATIAS KIRST, UNIVERSITY OF FLORIDA, USA, and SALVADOR A. GEZAN, UNIVERSITY OF FLORIDA, USA

Subjects
musculoskeletal diseases, 0106 biological sciences, 0301 basic medicine, Physiology, Population, Inheritance Patterns, Single-nucleotide polymorphism, Genome-wide association study, Plant Science, Biology, Polymorphism, Single Nucleotide, 01 natural sciences, Genome, Linkage Disequilibrium, 03 medical and health sciences, Quantitative Trait, Heritable, High-throughput SNP genotyping, Joint-GWAS, Regional heritability mapping (RHM), SNP, education, Genetic association, Principal Component Analysis, Eucalyptus, education.field_of_study, Genome-wide association study (GWAS), Heritability, Plant Breeding, Meta-analysis, 030104 developmental biology, Evolutionary biology, Tree breeding, Relatedness, Genome, Plant, Genome-Wide Association Study, 010606 plant biology & botany
Abstract

Genome-wide association studies (GWAS) in plants typically suffer from limited statistical power. An alternative to the logistical and cost challenge of increasing sample sizes is to gain power by meta-analysis using information from independent studies. We carried out GWAS for growth traits with six single-marker models and regional heritability mapping (RHM) in four Eucalyptus breeding populations independently and by Joint-GWAS, using gene and segment-based models, with data for 3373 individuals genotyped with a communal EUChip60KSNP platform. While single-single nucleotide polymorphism (SNP) GWAS hardly detected significant associations at high-stringency in each population, gene-based Joint-GWAS revealed nine genes significantly associated with tree height. Associations detected using single-SNP GWAS, RHM and Joint-GWAS set-based models explained on average 3-20% of the phenotypic variance. Whole-genome regression, conversely, captured 64-89% of the pedigree-based heritability in all populations. Several associations independently detected for the same SNPs in different populations provided unprecedented GWAS validation results in forest trees. Rare and common associations were discovered in eight genes involved in cell wall biosynthesis and lignification. With the increasing adoption of genomic prediction of complex phenotypes using shared SNPs and much larger tree breeding populations, Joint-GWAS approaches should provide increasing power to pinpoint discrete associations potentially useful toward tree breeding and molecular applications.

Published
2018

5. Quantitative genetic parameters for growth and wood properties in Eucalyptus 'urograndis' hybrid using near-infrared phenotyping and genome-wide SNP-based relationships

Author

Orzenil B. Silva-Junior, Bruno Marco de Lima, Shawn D. Mansfield, Carla Garcia, Dario Grattapaglia, Eduardo P. Cappa, BRUNO MARCO DE LIMA, USP, EDUARDO P. CAPPA, INSTITUTO NACIONAL DE TECNOLOGI´A AGROPECUARIA (INTA), ARGENTINA, ORZENIL BONFIM DA SILVA JUNIOR, Cenargen, CARLA GARCIA, INTERNATIONAL PAPER DO BRASIL ROD, SHAWN D. MANSFIELD, UNIVERSITY OF BRITISH COLUMBIA, CANADA, and DARIO GRATTAPAGLIA, Cenargen.

Subjects
0106 biological sciences, 0301 basic medicine, Heredity, Plant Science, 01 natural sciences, Lignin, Trees, Spectrum Analysis Techniques, NEAR-INFRARED PEHNOTYPING, Data Management, education.field_of_study, Eucalyptus, Multidisciplinary, Spectroscopy, Near-Infrared, Organic Compounds, Plant Anatomy, Eukaryota, near-Infrared Spectroscopy, Phylogenetic Analysis, Genomics, Plants, Wood, Phylogenetics, Polimorfismo de un Solo Nucleótido, Chemistry, Phenotypes, Phenotype, Genetic gain, Physical Sciences, Medicine, Brazil, Genome, Plant, Research Article, Genetic Research, Computer and Information Sciences, Genética Cuantitativa, Genotype, Science, Population, Infrared Spectroscopy, Quantitative trait locus, Biology, Research and Analysis Methods, Polymorphism, Single Nucleotide, Quantitative Genetics, 03 medical and health sciences, Quantitative Trait, Heritable, MOLECULAR RELATIONSHIP, Species Specificity, Genetic variation, Genetics, Evolutionary Systematics, PEDIGREE RELATIONSHIP, education, Cellulose, Fenotipos, Hybrid, Taxonomy, Evolutionary Biology, Models, Genetic, Directional selection, Organic Chemistry, Organisms, Chemical Compounds, Biology and Life Sciences, Heritability, purl.org/becyt/ford/4.5 [https], Plant Breeding, 030104 developmental biology, Evolutionary biology, Single Nucleotide Polymorphism, Tree breeding, Hybridization, Genetic, purl.org/becyt/ford/4 [https], 010606 plant biology & botany
Abstract

A thorough understanding of the heritability, genetic correlations and additive and non-additive variance components of tree growth and wood properties is a requisite for effective tree breeding. This knowledge is essential to maximize genetic gain, that is, the amount of increase in trait performance achieved annually through directional selection. Understanding the genetic attributes of traits targeted by breeding is also important to sustain decade-long genetic progress, that is, the progress made by increasing the average genetic value of the offspring as compared to that of the parental generation. In this study, we report quantitative genetic parameters for fifteen growth, wood chemical and physical traits for the world-famous Eucalyptus urograndis hybrid (E. grandis × E. urophylla). These traits directly impact the optimal use of wood for cellulose pulp, paper, and energy production. A population of 1,000 trees sampled in a progeny trial was phenotyped directly or following the development and use of near-infrared spectroscopy calibration models. Trees were genotyped with 33,398 SNPs and 24,001 DArT-seq genome-wide markers and genomic realized relationship matrices (GRM) were used for parameter estimation with an individual-tree additive-dominant mixed model. Wood chemical properties and wood density showed stronger genetic control than growth, cellulose and fiber traits. Additive effects are the main drivers of genetic variation for all traits, but dominance plays an equally or more important role for growth, singularly in this hybrid. GRM´s with >10,000 markers provided stable relationships estimates and more accurate parameters than pedigrees by capturing the full genetic relationships among individuals and disentangling the non-additive from the additive genetic component. Low correlations between growth and wood properties indicate that simultaneous selection for wood traits can be applied with minor effects on genetic gain for growth. Conversely, moderate to strong correlations between wood density and chemical traits exist, likely due to their interdependency on cell wall structure such that responses to selection will be connected for these traits. Our results illustrate the advantage of using genomewide marker data to inform tree breeding in general and have important consequences for operational breeding of eucalypt urograndis hybrids. Fil: de Lima, Bruno Marco. Universidade de Sao Paulo; Brasil. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil Fil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Silva Junior, Orzenil B.. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil. Universidade Católica de Brasília; Brasil Fil: Garcia, Carla. No especifíca; Fil: Mansfield, Shawn D.. University of British Columbia; Canadá Fil: Grattapaglia, Dario. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil. Universidade Católica de Brasília; Brasil

Published
2019

6. Genes Interacting with Occupational Exposures to Low Molecular Weight Agents and Irritants on Adult-Onset Asthma in Three European Studies

Author

Marie-Hélène Dizier, Rachel Nadif, Orianne Dumas, Amar J. Mehta, Ismaïl Ahmed, Jan-Paul Zock, Pascale Tubert-Bitter, Juan R. González, Medea Imboden, Emmanuelle Bouzigon, Ivan Curjuric, Deborah Jarvis, Florence Demenais, Marta Rava, Nicole Probst-Hensch, Nicole Le Moual, Manolis Kogevinas, Vieillissement et Maladies chroniques : approches épidémiologique et de santé publique (VIMA), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Spanish National Cancer Research Center (CNIO), Biostatistique, Biomathématique, Pharmacoépidémiologie et Maladies Infectieuses (B2PHI), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut Pasteur [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Center for Research in Environmental Epidemiology (CREAL), Universitat Pompeu Fabra [Barcelona] (UPF)-Catalunya ministerio de salud, Variabilité Génétique et Maladies Humaines, Institut Universitaire d'Hématologie (IUH), Université Paris Diderot - Paris 7 (UPD7)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), Epidemiology & Public Health [Basel, Switzerland], Swiss Tropical and Public Health Institute [Basel]-Medical School University of Basel, Department of Environmental Health [Boston, USA], Harvard School of Public Health, Centre for Research in Environmental Epidemiology (CREAL), Universitat Pompeu Fabra [Barcelona] (UPF), Respiratory Epidemiology and Public Health Group [London, U.K.], National Heart and Lung Institute-Imperial College London, U946, Fondation Jean Dausset/CEPH, Institut National de la Santé et de la Recherche Médicale (INSERM), The genotyping of all three studies was funded by the French National Agency of Research (ANR-PRSP 2009: IAGO), and by the European Commission (contract n° 018996) (GABRIEL) and the Wellcome Trust grant (WT 084703MA), both awarded to the GABRIEL consortium (a multidisciplinary study to identify the genetic and environmental causes of asthma in the European Community). EGEA: Research funded by the French Agency of health safety, environment and work (AFSSET, EST-09-15). SAPALDIA: The Swiss National Science Foundation (grants no 33CS30-148470/1, 33CSCO-134276/1, 33CSCO-108796, 324730_135673, 3247BO-104283, 3247BO-104288, 3247BO-104284, 3247-065896, 3100-059302, 3200-052720, 3200-042532, 4026-028099, PMPDP3_129021/1, PMPDP3_141671/1), the Federal Office for the Environment, the Federal Office of Public Health, the Federal Office of Roads and Transport, the canton's government of Aargau, Basel-Stadt, Basel-Land, Geneva, Luzern, Ticino, Valais, and Zürich, the Swiss Lung League, the canton's Lung League of Basel Stadt/ Basel Landschaft, Geneva, Ticino, Valais, Graubünden and Zurich, Stiftung ehemals Bündner Heilstätten, SUVA, Freiwillige Akademische Gesellschaft, UBS Wealth Foundation, Talecris Biotherapeutics GmbH, Abbott Diagnostics.ECRHS: The co-ordination of ECRHS II was supported by the European Commission, as part of their Quality of Life program. This work was also funded by the US National Institutes of Health (NIH grant 1R01HL062633) and the Carlos III Health Institute of the Spanish Ministry of Health and Consumption (FIS grant 01/3058). The following bodies funded the local studies in ECRHS II included in this paper: Albacete: Fondo de Investigaciones Santarias (FIS) (grant code: 97/0035-01, 99/0034-01 and 99/0034-02), Hospital Universitario de Albacete, Consejeria de Sanidad, Barcelona: SEPAR, Public Health Service (grant code: R01 HL62633-01), Fondo de Investigaciones Santarias (FIS) (grant code:97/0035-01, 99/0034-01 and 99/0034-02) CIRIT (grant code: 1999SGR 00241) Red Respira ISCII, Basel: Swiss National Science Foundation, Swiss Federal Office for Education & Science, Swiss National Accident Insurance Fund (SUVA), USC NIEHS Center grant 5P30 ES07048, Bergen: Norwegian Research Council, Norwegian Asthma & Allergy Association (NAAF), Glaxo Wellcome AS, Norway Research Fund, Erfurt: GSF-National Research Centre for Environment & Health, Deutsche Forschungsgemeinschaft (DFG) (grant code FR 1526/1-1), Galdakao: Basque Health Dept, Grenoble: Programme Hospitalier de Recherche Clinique-DRC de Grenoble 2000 no. 2610, Ministry of Health, Direction de la Recherche Clinique, Ministere de l'Emploi et de la Solidarite, Direction Generale de la Sante, CHU de Grenoble, Comite des Maladies Respiratoires de l’Isere, Hamburg: GSF-National Reasearch Centre for Environment & Health, Deutsche Forschungsgemeinschaft (DFG) (grant code MA 711/4-1), Ipswich and Norwich: Asthma UK (formerly known as National Asthma Campaign), Huelva: Fondo de Investigaciones Santarias (FIS) (grant code: 97/0035-01, 99/0034-01 and 99/0034-02), Oviedo: Fondo de Investigaciones Santarias (FIS) (grant code: 97/0035-01, 99/0034-01 and 99/0034-02), Paris: Ministere de l'Emploi et de la Solidarite, Direction Generale de la Sante, UCB-Pharma (France), Aventis (France), Glaxo France, Programme Hospitalier de Recherche Clinique-DRC de Grenoble 2000 no. 2610, Ministry of Health, Direction de la Recherche Clinique, CHU de Grenoble, Tartu: Estonian Science Foundation, Umeå: Swedish Heart Lung Foundation, Swedish Foundation for Health Care Sciences & Allergy Research, Swedish Asthma & Allergy Foundation, Swedish Cancer & Allergy Foundation, Uppsala: Swedish Heart Lung Foundation, Swedish Foundation for Health Care Sciences & Allergy Research, Swedish Asthma & Allergy Foundation, Swedish Cancer & Allergy Foundation., French National Agency of Research (Francia), Unión Europea. Comisión Europea, Wellcome Trust, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Imperial College London-National Heart and Lung Institute

Subjects
Male, Health, Toxicology and Mutagenesis, [SDV]Life Sciences [q-bio], 05 Environmental Sciences, Toxicology, 0302 clinical medicine, Adult onset asthma, Medicine, 030212 general & internal medicine, Lung function, Public, Environmental & Occupational Health, biology, CLEANING PRODUCTS, SWISS COHORT, NF-kappa B, Respiratory organs diseases, 11 Medical And Health Sciences, Middle Aged, Local study, 3. Good health, ENVIRONMENT INTERACTION, LUNG-FUNCTION, Europe, Occupational Diseases, Irritants, Female, Life Sciences & Biomedicine, Adult, GENETICS, Steering committee, Physical activity, Environmental Sciences & Ecology, OBSTRUCTIVE PULMONARY-DISEASE, Polymorphism, Single Nucleotide, Malalties de l'aparell respiratori, 03 medical and health sciences, Administrative support, Occupational Exposure, Cooperative group, Humans, GENOME-WIDE ASSOCIATION, Asma, Science & Technology, business.industry, Research, Public Health, Environmental and Occupational Health, AIR-POLLUTION, biology.organism_classification, Asthma, Molecular Weight, 030228 respiratory system, Pison, EMERGING ROLES, Particulate Matter, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, WORKPLACE, business, Humanities, Environmental Sciences
Abstract

BACKGROUND: The biological mechanisms by which cleaning products and disinfectants-an emerging risk factor-affect respiratory health remain incompletely evaluated. Studying genes by environment interactions (G × E) may help identify new genes related to adult-onset asthma. OBJECTIVES: We identified interactions between genetic polymorphisms of a large set of genes involved in the response to oxidative stress and occupational exposures to low molecular weight (LMW) agents or irritants on adult-onset asthma. METHODS: Our data came from three large European cohorts: Epidemiological Family-based Study of the Genetics and Environment of Asthma (EGEA), Swiss Cohort Study on Air Pollution and Lung and Heart Disease in Adults (SAPALDIA), and European Community Respiratory Health Survey in Adults (ECRHS). A candidate pathway-based strategy identified 163 genes involved in the response to oxidative stress and potentially related to exposures to LMW agents/irritants. Occupational exposures were evaluated using an asthma job-exposure matrix and job-specific questionnaires for cleaners and healthcare workers. Logistic regression models were used to detect G × E interactions, adjusted for age, sex, and population ancestry, in 2,599 adults (mean age, 47 years; 60% women, 36% exposed, 18% asthmatics). p-Values were corrected for multiple comparisons. RESULTS: Ever exposure to LMW agents/irritants was associated with current adult-onset asthma [OR = 1.28 (95% CI: 1.04, 1.58)]. Eight single nucleotide polymorphism (SNP) by exposure interactions at five loci were found at p < 0.005: PLA2G4A (rs932476, chromosome 1), near PLA2R1 (rs2667026, chromosome 2), near RELA (rs931127, rs7949980, chromosome 11), PRKD1 (rs1958980, rs11847351, rs1958987, chromosome 14), and PRKCA (rs6504453, chromosome 17). Results were consistent across the three studies and after accounting for smoking. CONCLUSIONS: Using a pathway-based selection process, we identified novel genes potentially involved in adult asthma by interaction with occupational exposure. These genes play a role in the NF-κB pathway, which is involved in inflammation. Citation: Rava M, Ahmed I, Kogevinas M, Le Moual N, Bouzigon E, Curjuric I, Dizier MH, Dumas O, Gonzalez JR, Imboden M, Mehta AJ, Tubert-Bitter P, Zock JP, Jarvis D, Probst-Hensch NM, Demenais F, Nadif R. 2017. Genes interacting with occupational exposures to low molecular weight agents and irritants on adult-onset asthma in three European studies. Environ Health Perspect 125:207-214; http://dx.doi.org/10.1289/EHP376. We thank all study members and staff involved in data collections in each cohort: EGEA: We thank the Epidemiological Study on Genetics and Environment of Asthma (EGEA) cooperative group members as follows. Coordination: V. Siroux [epidemiology, principal investigator (PI) since 2013]; F. Demenais (genetics); I. Pin (clinical aspects); R. Nadif (biology); F. Kauffmann (PI 1992–2012). Respiratory epidemiology: Inserm U 700, Paris: M. Korobaeff (EGEA1), F. Neukirch (EGEA1); Inserm U 707, Paris: I. Annesi-Maesano (EGEA1–2); Inserm U1168 (ex-CESP/U 1018), Villejuif: F. Kauffmann, N. Le Moual, R. Nadif, M.P. Oryszczyn (EGEA1–2), R. Varraso; Inserm U 823, Grenoble: V. Siroux. Genetics: Inserm U 393, Paris: J. Feingold; Inserm U 946, Paris: E. Bouzigon, F. Demenais, M.H. Dizier; CNG, Evry: I. Gut (now CNAG, Barcelona, Spain), M. Lathrop (now McGill University, Montreal, Canada). Clinical centers: Grenoble: I. Pin, C. Pison; Lyon: D. Ecochard (EGEA1), F. Gormand, Y. Pacheco; Marseille: D. Charpin (EGEA1), D. Vervloet (EGEA1–2); Montpellier: J. Bousquet; Paris Cochin: A. Lockhart (EGEA1), R. Matran (now in Lille); Paris Necker: E. Paty (EGEA1–2), P. Scheinmann (EGEA1–2); Paris Trousseau: A. Grimfeld (EGEA1–2), J. Just. Data and quality management: Inserm ex-U155 (EGEA1): J. Hochez; Inserm U1168 (ex-CESP/U 1018), Villejuif: N. Le Moual; Inserm ex-U780: C. Ravault (EGEA1–2); Inserm ex-U794: N. Chateigner (EGEA1–2); Grenoble: J. Quentin-Ferran (EGEA1–2). SAPALDIA: We thank the team of the Swiss study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA). Study directorate: N.M. Probst-Hensch (PI; e/g); T. Rochat (p), C. Schindler (s), N. Künzli (e/exp), J.M. Gaspoz (c). Scientific team: J.C. Barthélémy (c), W. Berger (g), R. Bettschart (p), A. Bircher (a), C. Brombach (n), P.O. Bridevaux (p), L. Burdet (p), D. Felber Dietrich (e), M. Frey (p), U. Frey (pd), M.W. Gerbase (p), D. Gold (e), E. de Groot (c), W. Karrer (p), F. Kronenberg (g), B. Martin (pa), A. Mehta (e), D. Miedinger (o), M. Pons (p), F. Roche (c), T. Rothe (p), P. Schmid- Grendelmeyer (a), D. Stolz (p), A. Schmidt-Trucksäss (pa), J. Schwartz (e), A. Turk (p), A. von Eckardstein (cc), E. Zemp Stutz (e). Scientific team at coordinating centers: M. Adam (e), I. Aguilera (exp), S. Brunner (s), D. Carballo (c), S. Caviezel (pa), I. Curjuric (e), A. Di Pascale (s), J. Dratva (e), R. Ducret (s), E. Dupuis Lozeron (s), M. Eeftens (exp), I. Eze (e), E. Fischer (g), M. Foraster (e), M. Germond (s), L. Grize (s), S. Hansen (e), A. Hensel (s), M. Imboden (g), A. Ineichen (exp), A. Jeong (g), D. Keidel (s), A. Kumar (g), N. Maire (s), A. Mehta (e), R. Meier (exp), E. Schaffner (s), T. Schikowski (e), M. Tsai (exp). Abbreviations: (a) allergology, (c) cardiology, (cc) clinical chemistry, (e) epide - miology, (exp) exposure, (g) genetic and molecular biology, (m) meteorology, (n) nutrition, (o) occupational health, (p) pneumology, (pa) physical activity, (pd) pediatrics, (s) statistics. The study could not have been done without the help of the study partici - pants, technical and administrative support and the medical teams and field workers at the local study sites. Local fieldworkers: Aarau: S. Brun, G. Giger, M. Sperisen, M. Stahel; Basel: C. Bürli, C. Dahler, N. Oertli, I. Harreh, F. Karrer, G. Novicic, N. Wyttenbacher; Davos: A. Saner, P. Senn, R. Winzeler; Geneva: F. Bonfils, B. Blicharz, C. Landolt, J. Rochat; Lugano: S. Boccia, E. Gehrig, M.T. Mandia, G. Solari, B. Viscardi; Montana: A.P. Bieri, C. Darioly, M. Maire; Payerne: F. Ding, P. Danieli, A. Vonnez; Wald: D. Bodmer, E. Hochs, R. Kunz, C. Meier, J. Rakic, U. Schafroth, A. Walder. Administrative staff: N. Bauer Ott, C. Gabriel, R. Gutknecht. ECRHS: The ECRHS data incorporated in this analysis would not have been available without the collaboration of the following individuals and their research teams. ECRHS Co-ordinating Centre. P. Burney, D. Jarvis, S. Chinn, J. Knox (ECRHS II), C. Luczynska†, J. Potts. Steering Committee for ECRHS II. P. Burney, D. Jarvis, S. Chinn, U. Ackermann-Liebrich, J.M. Anto, I. Cerveri, R. deMarco†, T. Gislason, J. Heinrich, C. Janson, N. Kunzli, B. Leynaert, F. Neukirch, J. Schouten, J. Sunyer; C. Svanes, P. Vermeire†, M. Wjst. Principal Investigators and Senior Scientific Teams for ECRHS II centers within this analysis: Estonia: Tartu (R. Jogi, A. Soon); France: Paris (F. Neukirch, B. Leynaert, R. Liard, M. Zureik), Grenoble (I. Pin, J. Ferran-Quentin); Germany: Erfurt (J. Heinrich, M. Wjst, C. Frye, I. Meyer), Hamburg (K. Richter, D. Nowak); Norway: Bergen (A. Gulsvik, E. Omenaas, C. Svanes, B. Laerum); Spain: Barcelona (J.M. Anto, J. Sunyer, M. Kogevinas, J.P. Zock, X. Basagana, A. Jaen, F. Burgos), Huelva (J. Maldonado, A. Pereira, J.L. Sanchez), Albacete (J. Martinez-Moratalla Rovira, E. Almar), Galdakao (N. Muniozguren, I. Urritia), Oviedo (F. Payo); Sweden: Uppsala (C. Janson, G. Boman, D. Norback, M. Gunnbjornsdottir), Umeå (E. Norrman, M. Soderberg, K. Franklin, B. Lundback, B. Forsberg, L. Nystrom); Switzerland: Basel (N. Kunzli, B. Dibbert, M. Hazenkamp, M. Brutsche, U. Ackermann-Liebrich); United Kingdom: Norwich (D. Jarvis, B. Harrison), Ipswich (D. Jarvis, R. Hall, D. Seaton). Sí

Published
2016

7. BMC Genomics

Author

Grace C. Davey, Penelope K. Lindeque, Richard Reinhardt, Christophe Klopp, Pascal Favrel, Dario Moraga, Pierre Boudry, Sylvie Lapegue, Patrick Prunet, Arnaud Huvet, Julien de Lorgeril, Jeanne Moal, Viviane Boulo, Elodie Fleury, Christophe Lelong, Christopher Sauvage, Patrick Wincker, François Moreews, Michel Mathieu, Frédérick Gavory, Arnaud Tanguy, Caroline Fabioux, Charlotte Corporeau, Evelyne Bachère, Jenny P. Shaw, Yannick Gueguen, Laboratoire Environnement Ressources Morbihan Pays de Loire (LERMPL), LITTORAL (LITTORAL), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Physiologie et Ecophysiologie des Mollusques Marins (PE2M), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Ecosystèmes lagunaires : organisation biologique et fonctionnement (ECOLAG), Université Montpellier 2 - Sciences et Techniques (UM2)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Centre National de la Recherche Scientifique (CNRS), Adaptation et diversité en milieu marin (ADMM), Institut national des sciences de l'Univers (INSU - CNRS)-Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des Sciences de l'Environnement Marin (LEMAR) (LEMAR), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de Brest (UBO), Plymouth Marine Laboratory (PML), Max-Planck-Institut für Molekulare Genetik (MPIMG), Max-Planck-Gesellschaft, Station commune de Recherches en Ichtyophysiologie, Biodiversité et Environnement (SCRIBE), Institut National de la Recherche Agronomique (INRA), Génétique fonctionnelle, agronomie et santé [IFR 140] (GFAS), Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), National Diagnostics Centre (NDC), National University of Ireland [Galway] (NUI Galway), Laboratoire de Génétique et Pathologie (LGP), Amélioration génétique, du contrôle des performances et de la santé des mollusques marins (AGSAE), Genoscope - Centre national de séquençage [Evry] (GENOSCOPE), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Biological systems and models, bioinformatics and sequences (SYMBIOSE), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), Systèmes d'Elevage, Nutrition Animale et Humaine (SENAH), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure Agronomique de Rennes, Système d'Information des GENomes des Animaux d'Elevage (SIGENAE), Unité de Biométrie et Intelligence Artificielle (ancêtre de MIAT) (UBIA), Laboratoire de Physiologie des Invertébrés (LPI), Physiologie Fonctionnelle des Organismes Marins (PFOM), The research presented in this paper was performed within the framework of several research projects funded by: Genoscope (11/AP2006-2007), Marine Genomics Network of Excellence (GOCE-CT-2004-505403), the European project 'Aquafirst' (513692) in the Sixth Framework Program, ANR 'CgPhysiogène' (ANR-06-GANI-0009) and 'Gametogenes' (ANR-08-GENM-041), ANR-06-GANI-0009,CgPhysiogene,Bases moléculaires des fonctions physiologiques de l'huître Crassostrea gigas : interactions hôte/pathogène/milieu(2006), ANR-08-GENM-0041,Gametogenes,Génomiques de la gamétogénèse chez l'huître creuse Crassostrea gigas(2008), Laboratoire Laboratoire Environnement Ressources Morbihan Pays de Loire (LER/MPL), Institut de Recherche pour le Développement (IRD)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Centre National de la Recherche Scientifique (CNRS), Adaptation et Biologie des Invertébrés en Conditions Extrêmes (ABICE), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Plymouth Marine Laboratory, Institut National de la Recherche Agronomique (INRA)-IFR140, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria Rennes – Bretagne Atlantique, Ecole Nationale Supérieure Agronomique de Rennes-Institut National de la Recherche Agronomique (INRA), Unité de Biométrie et Intelligence Artificielle de Toulouse [Castanet-Tolosan] (UBIA), Institut National de la Recherche Agronomique (INRA)-Plateforme bioinformatique du GIS GENOTOUL - Génopole Toulouse Midi-Pyrénées, Laboratoire de Physiologie des Invertébrés [Plouzané] (LPI), Adaptation et diversité en milieu marin (AD2M), Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff (SBR), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Recherche Agronomique (INRA), Station biologique de Roscoff (SBR), and Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Oyster, genome annotation, génomique fonctionnelle, computer.software_genre, Genome, User-Computer Interface, single nucleotide polymorphisms, Databases, Genetic, crassostrea gigas, structure du génome, Expressed Sequence Tags, base de données, 0303 health sciences, Expressed sequence tag, biology, Database, 04 agricultural and veterinary sciences, Genomics, crustacea, Pacific oyster, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], energy-balance, factor-beta superfamily, DNA microarray, expression des gènes, Biotechnology, lcsh:QH426-470, Sequence analysis, lcsh:Biotechnology, kappa-b, Polymorphism, Single Nucleotide, génomique, 03 medical and health sciences, biology.animal, lcsh:TP248.13-248.65, Genetics, summer mortality, Animals, Crassostrea, 030304 developmental biology, Gene Library, Whole genome sequencing, [SDV.GEN]Life Sciences [q-bio]/Genetics, huître, cell-development, génome, Gene Expression Profiling, linkage maps, Sequence Analysis, DNA, biology.organism_classification, lcsh:Genetics, coquillage, 040102 fisheries, 0401 agriculture, forestry, and fisheries, identification, marine genomics, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], computer, Microsatellite Repeats
Abstract

Background Although bivalves are among the most-studied marine organisms because of their ecological role and economic importance, very little information is available on the genome sequences of oyster species. This report documents three large-scale cDNA sequencing projects for the Pacific oyster Crassostrea gigas initiated to provide a large number of expressed sequence tags that were subsequently compiled in a publicly accessible database. This resource allowed for the identification of a large number of transcripts and provides valuable information for ongoing investigations of tissue-specific and stimulus-dependant gene expression patterns. These data are crucial for constructing comprehensive DNA microarrays, identifying single nucleotide polymorphisms and microsatellites in coding regions, and for identifying genes when the entire genome sequence of C. gigas becomes available. Description In the present paper, we report the production of 40,845 high-quality ESTs that identify 29,745 unique transcribed sequences consisting of 7,940 contigs and 21,805 singletons. All of these new sequences, together with existing public sequence data, have been compiled into a publicly-available Website http://public-contigbrowser.sigenae.org:9090/Crassostrea_gigas/index.html. Approximately 43% of the unique ESTs had significant matches against the SwissProt database and 27% were annotated using Gene Ontology terms. In addition, we identified a total of 208 in silico microsatellites from the ESTs, with 173 having sufficient flanking sequence for primer design. We also identified a total of 7,530 putative in silico, single-nucleotide polymorphisms using existing and newly-generated EST resources for the Pacific oyster. Conclusion A publicly-available database has been populated with 29,745 unique sequences for the Pacific oyster Crassostrea gigas. The database provides many tools to search cleaned and assembled ESTs. The user may input and submit several filters, such as protein or nucleotide hits, to select and download relevant elements. This database constitutes one of the most developed genomic resources accessible among Lophotrochozoans, an orphan clade of bilateral animals. These data will accelerate the development of both genomics and genetics in a commercially-important species with the highest annual, commercial production of any aquatic organism.

Published
2009