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 GWASStudy Asthma Country of Origin New Typed Total New Typed Total

GABRIEL I Childhood UK and German 990 990 1,240 1,240ALSPAC Childhood UK 500 500 2,000 2,000FINRISK Childhood Finland 200 200 200 200BAMSE Childhood Sweden 350 350 350 350PIAMA Childhood Holland 200 200 200 200

PARSIFAL Childhood Germany 300 300 300 300GABRIEL AS Childhood Mullti-Centre Rural 1,000 1,000 1,000 1,000

GAIN Childhood International 1,740 1,740ECRHS Adult Pan-European 920 920 1,700 1,700EGEA Adult France 930 930 560 1,000 1,560

TOMSKA Adult Russia 300 300 400 400UFA Adult Russia 400 400 300 300

SAPALDIA Adult Swiss 660 660 980 980INDUS Industrial Pan-European 800 800 800 800

CANADA Adult Canada 930 930 620 620BUSSEL Adult Australia 620 620 710 710

1958 BBC Adult UK 0 700 700 2,000 2,000SEVER Severe Adult UK 400 400 0

TOTALS 10,250 1,690 11,940 8,120 6,240 14,360

CASES CONTROLS

Global gene expression

• 30,000 human genes• Measure their level of

expression simultaneously

• Extraordinary insight into the function of cells and tissues

• Genome wide association study of gene expression

• Dixon, Liang, Moffatt et al Nature Genetics 2007

LOD Scores of Genes

Chromosomes

LO

D

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 17 19 21 X

01

23

45

67

89

11

13

15

17

19

21

23

25

27

29

cis(+/-100k of gene)

cis (same chromosome)

trans

Gene Ontology Category:Immune Response

CNR2

CTSS

AIM2

CD244

IL19

DGKD

TLR1

FYB

B2M

HLA-C

HLA-DQA1

HLA-DQA1,HLA-DQA2

HLA-DRB1

HLA-DQB1

HLA-DPA1

IFITM2SEMA4D

CD59IL16

IL2RG IGHA1,IGHG1,IGHG3,MGC27165

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

0

10

20

30

40

50

60

COPD ASTHMA CONTROLS

Disease status

%

Proteobacteria

Firmicutes

Bacteriodites

Actinobacteria

Fusobacteria

others

Airway bacterial flora in health and disease

P < 10-16

P < 10-16

P < 10-6

P < 10-7

P < 10-2

P < 0.05

Future Needs• Complete the identification of asthma genes

– Build on current collaboration• Copy number variation• Resequencing• Epigenetics

• Elucidate the function of asthma genes• Investigate genes identified by genome-wide studies • Identify targets and build models for new therapies

• Dissect the interaction between genes and environment• Genetic Epidemiology

– Phenotypes– Life-course– Exposures

• Genomic Epidemiology– Children from the advanced surveys – Other Populations and environments

• Developing biomarkers– 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