Survey
* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project
Download GABRIEL II
Document related concepts
no text concepts found
Transcript
Asthma • One child in 10 in the EU • Childhood asthma costs the EU €3 Billion p.a. • Adult and industrial asthma also €3 Billion • Abnormal airway mucosa • Intermittent inflammation • Association with atopy (incomplete) • Rural environment protective • Rich microbial environment protective • Familial • Strong maternal effects • Birth order effects Asthma and GABRIEL • Aim of GABRIEL – To systematically identify the genetic and environmental factors that control asthma risk • Senior Partners – Imperial College London – University Children's Hospital Munich – CEA / Centre National de Genotypage Paris • 37 Partners 19 Countries – EU contribution €11.5M 4 years – Total spend €25M GABRIEL Genetics • Phase I genome-wide association study • 1000 children 1200 controls • Phase II genome-wide association study • 11,000 asthmatics 15,000 controls • Adult, childhood, industrial and severe asthma • Additional €4.3 million from the Wellcome Trust • Phase III • Genetic epidemiology in 40,000 subjects from exiting population surveys • Phase IV • Genomic epidemiology: global gene expression in 2000 children from different environments Genome-wide Association Asthma 938 cases and 1244 controls: UK, Germany and Austria 317,000 markers Moffatt, Kabesch and Liang et al. Nature 2007 Chr 17 and age of onset Emmanuelle Bouzigon et al NEJM 2008 Chr 17 ORMDL3 SNPs • • • • • Population attributable risk 30% OR ~1.8 in population samples Associated with severity Not associated with atopy Not associated with adult-onset asthma GABRIEL Phase II GWAS Study Asthma GABRIEL I Childhood ALSPAC Childhood FINRISK Childhood BAMSE Childhood PIAMA Childhood PARSIFAL Childhood GABRIEL AS Childhood GAIN Childhood ECRHS Adult EGEA Adult TOMSKA Adult UFA Adult SAPALDIA Adult INDUS Industrial CANADA Adult BUSSEL Adult 1958 BBC Adult SEVER Severe Adult Country of Origin UK and German UK Finland Sweden Holland Germany Mullti-Centre Rural International Pan-European France Russia Russia Swiss Pan-European Canada Australia UK UK TOTALS CASES New Typed Total 990 990 500 500 200 200 350 350 200 200 300 300 1,000 1,000 1,740 1,740 920 920 930 930 300 300 400 400 660 660 800 800 930 930 620 620 700 0 700 400 400 10,250 1,690 11,940 CONTROLS New Typed Total 1,240 1,240 2,000 2,000 200 200 350 350 200 200 300 300 1,000 1,000 1,700 560 400 300 980 800 620 710 1,000 2,000 8,120 6,240 1,700 1,560 400 300 980 800 620 710 2,000 0 14,360 Global gene expression • 30,000 human genes • Measure their level of expression simultaneously • Extraordinary insight into the function of cells and tissues LOD Scores of Genes 27 cis(+/-100k of gene) 25 HLA-DRB1 cis (same chromosome) 21 23 trans 15 CTSS 13 TLR1 HLA-DQB1 FYB HLA-DQA1,HLA-DQA2 IL19 11 LOD 17 19 HLA-DPA1 CNR2 0 1 2 3 4 5 6 7 8 9 • Dixon, Liang, Moffatt et al Nature Genetics 2007 29 • Genome wide association study of gene expression Gene Ontology Category: Immune Response HLA-DQA1 DGKD CD244 AIM2 1 2 3 4 5 CD59 HLA-C IFITM2 SEMA4D B2M 6 7 8 9 10 11 12 Chromosomes IL16 IL2RG IGHA1,IGHG1,IGHG3,MGC27165 13 14 15 17 19 21 X Genomic Epidemiology: Global gene expression in Populations 225 subjects from von Mutius Advanced Surveys Metagenomics • Genetics and genomics of bacteria • Molecular detection of bacteria by sequencing their 16S rRNA genes Phylogeny of bronchial bacteria Airway bacterial flora in health and disease P < 10-16 60 P < 10-16 P < 10-7 50 P < 10-6 P < 0.05 % 40 P < 10-2 Proteobacteria Firmicutes Bacteriodites Actinobacteria Fusobacteria others 30 20 10 0 COPD ASTHMA Disease status CONTROLS Future Needs • Complete the identification of asthma genes – Build on current collaboration • • • • Elucidate the function of asthma genes • • • Copy number variation Resequencing Epigenetics Investigate genes identified by genome-wide studies Identify targets and build models for new therapies Dissect the interaction between genes and environment • Genetic Epidemiology – – – • Genomic Epidemiology – – • Children from the advanced surveys Other Populations and environments Developing biomarkers – • Phenotypes Life-course Exposures Proteomics, metabolomics Metagenomics of airway bacteria • • Larger studies Investigate functional effects of different bacteria Future Needs • Identify environmental factors protective against asthma • Building on samples and knowledge from Advanced Surveys • Provide tools for genomic epidemiology and metagenomics
Related documents