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

Slides:



Advertisements
Similar presentations
Genetic Analysis of Genome-wide Variation in Human Gene Expression Morley M. et al. Nature 2004,430: Yen-Yi Ho.
Advertisements

Genetic research designs in the real world Vishwajit L Nimgaonkar MD, PhD University of Pittsburgh
CBG metaprotein composition shown in Figure 2. Associations also found between the IL28B rs genotype and SVR (p = 5.06×10 -5 ) and between CBG.
Outline Questions from last lecture? P. 40 questions on Pax6 gene Mechanism of Transcription Activation –Transcription Regulatory elements Comparison between.
Cytokines in Asthma: Effects on Human Pulmonary Fibroblasts Shreya Lankala, Agostino Molteni, Betty Herndon UMKC School of Medicine Background & Rationale.
A. Nakonechna 1, J. Antipkin 2, T. Umanets 2, V. Lapshyn 2 1) Royal Liverpool and Broadgreen University Hospitals NHS Trust, Liverpool, United Kingdom.
Association Mapping David Evans. Outline Definitions / Terminology What is (genetic) association? How do we test for association? When to use association.
Traits & Environment Pp What are traits? Hair color Eye color HeightWeight Male vs. Female.
Lab 13: Association Genetics. Goals Use a Mixed Model to determine genetic associations. Understand the effect of population structure and kinship on.
Utilizing DNA testing in identifying multiple gene traits Prof Norman Maiwashe 1,2 (PhD, Pri Sci Nat) 1 ARC-Animal Production Institute 2 Dept. of Animal,
Integrative data mining and visualization of genome-wide SNP profiles in childhood acute lymphoblastic leukaemia. Ahmad Aloqaily Faculty of IT University.
The role of variation in finding functional genetic elements Andy Clark – Cornell Dave Begun – UC Davis.
Class activity: What are my asthma variants doing? In the subset of individuals for whom expression data are available, the T nucleotide allele at rs
Positional Cloning LOD Sib pairs Chromosome Region Association Study Genetics Genomics Physical Mapping/ Sequencing Candidate Gene Selection/ Polymorphism.
Epigenetics of Celiac Disease MEDICEL Malta 2011.
Accounting for age-specific sex-limitation in IgE QTL linkage analysis: example of 11p13 Manuel A R Ferreira, David Duffy & Nick Martin Queensland Institute.
A dynamic program algorithm for haplotype block partitioning Zhang, et. al. (2002) PNAS. 99, 7335.
Give me your DNA and I tell you where you come from - and maybe more! Lausanne, Genopode 21 April 2010 Sven Bergmann University of Lausanne & Swiss Institute.
Low birth weight Zahra N. Sohani Supervisor: Dr. Sonia Anand.
DNA methylation as an epigenetic marker in HIV-2 disease in West Africa? Alberta Davis MRC Laboratories, Gambia 18th January 2013.
Pediatrics Genome Wide Peripheral Blood Leukocyte DNA Methylation Microarrays Identify a Single Association with Inflammatory Bowel Diseases Richard Kellermayer.
 What is genetics?  Genetics is the study of heredity, the process in which a parent passes certain genes onto their children. What does that mean?
Genetic Analysis in Human Disease. Learning Objectives Describe the differences between a linkage analysis and an association analysis Identify potentially.
Linkage and LOD score Egmond, 2006 Manuel AR Ferreira Massachusetts General Hospital Harvard Medical School Boston.
Epigenome 1. 2 Background: GWAS Genome-Wide Association Studies 3.
The medical relevance of genome variability Gabor T. Marth, D.Sc. Department of Biology, Boston College
Sequencing TRAF1 in patients with rheumatoid arthritis Bruce C. Jobse Medical and Population Genetics Broad Institute.
Epigenetics in Celiac Disease MEDICEL Istanbul 2012.
Computational research for medical discovery at Boston College Biology Gabor T. Marth Boston College Department of Biology
The Center for Medical Genomics facilitates cutting-edge research with state-of-the-art genomic technologies for studying gene expression and genetics,
The medical relevance of genome variability Gabor T. Marth, D.Sc. Department of Biology, Boston College Medical Genomics Course – Debrecen,
Epigenetics Heritable characteristics of the genome other than the DNA sequence Heritable during cell-division (mitosis) To a lesser extent also over generations.
Genetic Repositories Australia BACKGROUND GRA supported by an NHMRC Enabling Facility Grant awarded in  GRA supported by an NHMRC Enabling Facility.
Quantitative Genetics. Continuous phenotypic variation within populations- not discrete characters Phenotypic variation due to both genetic and environmental.
Quantitative Genetics
Living things inherit traits in patterns
Companion PowerPoint slide set DNA Methylation & Cadmium Exposure in utero An Epigenetic Analysis Activity for Students This teacher slide set was created.
Fast test for multiple locus mapping By Yi Wen Nisha Rajagopal.
Mx modeling of methylation data: twin correlations [means, SD, correlation] ACE / ADE latent factor model regression [sex and age] genetic association.
EPIGENETIC PATTERNS IN PLACENTAL PROGRAMMING OF PREECLAMPSIA Cindy M. Anderson, PhD, WHNP-BC, FAAN Michelle L. Wright, MS, RN Jody L. Ralph, PhD, RN Eric.
Supplemental Figure 1. False trans association due to probe cross-hybridization and genetic polymorphism at single base extension site. (A) The Infinium.
Genetic simplex modeling of personality in adolescent Australian twins N.A. GILLESPIE 1, D. M. EVANS 1, N.G. MARTIN 1 1 Queensland Institute of Medical.
A simple method to localise pleiotropic QTL using univariate linkage analyses of correlated traits Manuel Ferreira Peter Visscher Nick Martin David Duffy.
Genetics of Gene Expression BIOS Statistics for Systems Biology Spring 2008.
Different microarray applications Rita Holdhus Introduction to microarrays September 2010 microarray.no Aim of lecture: To get some basic knowledge about.
Mutaz A. A. Mustafa, A. A. M. Elhassan, M. E. Ibrahim Institute of Endemic Diseases, University of Khartoum, Khartoum, Sudan
Association Mapping in Families Gonçalo Abecasis University of Oxford.
Date of download: 7/2/2016 Copyright © 2016 American Medical Association. All rights reserved. From: How to Interpret a Genome-wide Association Study JAMA.
Gene Hunting: Design and statistics
Case Study #2 Session 1, Day 3, Liu
Gene-based analysis of regulatory variants identifies 4 putative novel asthma risk genes related to nucleotide synthesis and signaling  Manuel A.R. Ferreira,
Phenotype the set of observable characteristics of an individual resulting from their DNA information.
Power to detect QTL Association
Sex-linked Traits and Pedigrees
GENOME WIDE ASSOCIATION STUDIES (GWAS)
Addition of H19 ‘Loss of Methylation Testing’ for Beckwith-Wiedemann Syndrome (BWS) Increases the Diagnostic Yield  Jochen K. Lennerz, Robert J. Timmerman,
Qing Cheng, Cheng Cheng, Kristine R. Crews, Raul C
Genome-wide association analysis identifies 11 risk variants associated with the asthma with hay fever phenotype  Manuel A.R. Ferreira, PhD, Melanie C.
Exercise: Effect of the IL6R gene on IL-6R concentration
Linkage and Association Analysis of Spectrophotometrically Quantified Hair Color in Australian Adolescents: the Effect of OCA2 and HERC2  Sri N. Shekar,
Genetics Vocabulary Gene – a location on DNA that codes for a trait; located on both sets of chromosomes Allele – the specific gene that comes either from.
Medical genomics BI420 Department of Biology, Boston College
Increased DNA Methylation at the AXIN1 Gene in a Monozygotic Twin from a Pair Discordant for a Caudal Duplication Anomaly  N.A. Oates, J. van Vliet, D.L.
Environmental epigenetics of asthma: An update
Patterns of Inheritance and Karyotyping
A Role for Epigenetics in Psoriasis: Methylated Cytosine–Guanine Sites Differentiate Lesional from Nonlesional Skin and from Normal Skin  Johann E. Gudjonsson,
Methylation of cytosine and consequences of deamination of methyl-C
Qing Cheng, Cheng Cheng, Kristine R. Crews, Raul C
Epigenetic mechanisms and the development of asthma
Presentation transcript:

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

1. Genetic risk factors

XY 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

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)

Chromosome 2q33 Threshold for significance: α = 0.05/(4 traits × 28 SNPs) = 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) = Multivariate association analysis Fulker et al. (1999), e.g. QTDT Lange et al. (2004), PBAT

Chromosome 2q33

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. )

2. Role of epigenetics in asthma

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

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 (70% asthmatic, 75% atopic) Extracted DNA from peripheral blood leukocytes Quantified methylation state of CpG islands using Sequenom MassSpectometry assay (Ehrich et al PNAS 102: 15785) Two genes involved in asthma: IL4 and MS4A2 (beta subunit of the IgE high affinity receptor)

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

MS4A2 (FCER1B) Methylation Mean methylation: 90% Significant differences between CpG sites (P < ) CpG 2 in regulatory element? Significant differences between individuals (P < ) 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.

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

Summary

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

Doctorate scholarship, Ministry of Science, Portugal NHMRC project grant 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