1. Genetic and epigenetic risk factors for asthma Manuel A R Ferreira QUEENSLAND INSTITUTE OF MEDICAL RESEARCH

2. 1. Genetic risk factors

3. 2 453786 101191213 14151617181920 12122XY Linkage studies in Australian samples 12q24 20q13 Ferreira et al. (2005) Am J Hum Genet 77: 1075 Ferreira et al. (2006) Eur J Hum Genet 14: 953 2q33 Evans et al. (2004) J Allergy Clin Immunol 114: 826

4. Chromosome 2q33 1,946 individuals (663 families) 41% 1 offspring (23% : 7% : 11%) 59% >1 offspring (18% : 11% : 30%) 4 continuous traits: FEV 1 FEV 1 /FVC Immunoglobulin E Eosinophilia 28 SNPs (270 Kb)

5. Chromosome 2q33 Threshold for significance: α = 0.05/(4 traits × 28 SNPs) = 0.0005 Univariate association analysis Power: < 30% (Locus explained up to 1.5% of the variance, p = 0.3, dominant model) Threshold for significance: α = 0.05/(1 trait × 28 SNPs) = 0.0018 Multivariate association analysis Fulker et al. (1999), e.g. QTDT Lange et al. (2004), PBAT

6. Chromosome 2q33

8. Genotyped 3 more samples: Holland, Denmark and Tristan da Cunha Island Genotyped more SNPs to increase LD coverage (ICOS and CD28) Test for epistasis using a novel gene-based association method (Purcell et al. )

9. 2. Role of epigenetics in asthma

10. Methylation of CpG dinucleotides M M M M M M M CpG islandGene MethylatedSuppressed Not methylatedActive

11. Methylation and asthma 1. What is the methylation state of known asthma genes? 2. Are there significant differences in methylation levels between individuals? 3. Do methylation levels correlate with clinical markers of asthma? Selected 30 children aged 10-19 (70% asthmatic, 75% atopic) Extracted DNA from peripheral blood leukocytes Quantified methylation state of CpG islands using Sequenom MassSpectometry assay (Ehrich et al. 2005 PNAS 102: 15785) Two genes involved in asthma: IL4 and MS4A2 (beta subunit of the IgE high affinity receptor)

12. Methylation IL4 (Interleukin 4) Mean methylation: 75% Significant differences between CpG sites (P < 0.0001) Lower methylation in regulatory elements Significant differences between individuals (P < 0.0001) e.g. 75% vs 40% (CpG 5) No significant effects of age, sex or steroid medication

13. MS4A2 (FCER1B) Methylation Mean methylation: 90% Significant differences between CpG sites (P < 0.0001) CpG 2 in regulatory element? Significant differences between individuals (P < 0.0001) e.g. 75% vs 30% (CpG 2) No significant effects of age, sex or steroid medication 2006/12/10. CORRECTION: data for CpG2 was found to be unreliable in the Sequenom assay. All other CpGs ok.

14. Significant differences in methylation between individuals. Do these correlate with the expression of asthma phenotypes? Small differences in methylation (~15%) can result in large differences (~40%) in gene transcription Oates et al. (2006) Am J Hum Genet 79: 155 Correlation between methylation and asthma * P < 0.05, ** P < 0.01

16. Summary

17. Potentially relevant transcription factors bind to this promoter region Genetic risk factors Extending our study to validate these results Identified SNPs in the promoter of CD28 that are associated with asthma phenotypes Mostly methylated in PBLs of asthmatic children Role of epigenetics in asthma Significant variation in methylation between CpG sites and between individuals Measured the methylation state of IL4 and MS4A2 This variation is associated with the expression of asthma clinical phenotypes

18. Doctorate scholarship, Ministry of Science, Portugal NHMRC project grant 290274 The Asthma Foundation of Queensland NHMRC Sidney Sax post-doctoral fellowship Acknowledgments Funding Peter Le Souëf Paul R. Burton Brett G. Toelle Colin Robertson Nick Martin David Duffy Emma Whitelaw Grant Montgomery Megan Campbell Leanne McNeill Sri Shekar Zhen Zhen Zhao Renee Mayne Louise O’Gorman Nathan Oates Queensland Institute of Medical Research Princess Margaret Hospital for Children, Perth Woolcock Institute of Medical Research, Sydney Royal Children’s Hospital, Melbourne Sequenom Mathias Ehrich Jeff Bryant