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Predisposition to asthma among the Utah population Craig Teerlink University of Utah Department of Biomedical Informatics Asthma Genomics Conference Utah Department of Health Asthma Program June 7, 2007 Introduction Asthma is a common disorder Effects 7% of US population1 Increased global incidence observed in the last few decades2 Complicated etiology Both environmental and genetic factors are recognized3 Heritable nature of asthma Discordance observed between MZ and DZ twins4 Familial aggregation studies and risk factor analyses provide evidence that asthma clusters in families5,6 A better understanding of predisposing factors may help improve treatment outcomes Introduction to familial analysis study Such studies have been restricted to first degree relatives It is difficult to distinguish between evidence for common genetic factors and common environmental factors among close relatives since close relatives often share their immediate environment In contrast, using a unique Utah resource, we were able to observe increased risk to distant relatives for a severe asthma phenotype definition7 The Utah Population Database Computerized genealogy records 2.2 million Utah pioneers and their descendents Some genealogies have up to 10 generations Has been linked to 440,000+ death certificates from Utah The combined resource allows us to identify individuals who died from asthma (cases) and investigate their ‘relatedness’ Benefits of genealogical approach to familiality Well-established methods The resource has previously been used to provide evidence for a heritable component in other disease settings Can extend analyses to distant relatives (i.e., 2nd or 3rd degree relatives), providing potentially more meaningful results Two types of analysis Relative risk If asthma mortality is familial, a higher risk of asthma mortality will be found among relatives of individuals who died from asthma than would be found for random controls Average relatedness If asthma mortality is familial, more relationships between cases will be found than would be found for random controls Relative risk analysis Method Compare the rate of asthma death in relatives of asthma death cases with the rate of asthma death in the population (UPDB) Results for 1,553 asthma deaths No. of relatives Observed Expected RR P-value 1st degree relatives 7,936 52 30.7 1.69 <0.001 2nd degree relatives 19,319 100 74.8 1.34 0.003 3rd degree relatives 28,601 129 112.2 1.15 0.065 Average relatedness analysis Method Calculate the genetic distance between every pair of cases (i.e., degree of ‘relatedness’) Calculate the average relatedness of all cases (GIF statistic) Repeat for 1000 sets of matched controls Results for 1,553 asthma deaths All cases Ignoring 1st and 2nd degree relatives Case GIF 3.16 1.95 Control GIF 2.42 1.73 P-Value <0.0001 0.026 Contribution to the GIF statistic Contribution to the GIF statistic by 0.5 genetic distance asthma cases matched controls between pairs of 0.4 contribution to GIF individuals for asthma 0.3 mortality 0.2 1,553 cases and 1000 sets of matched 0.1 0.0 controls 1 2 3 4 5 6 7 8 9 10 12 14 genetic distance Summary of familial investigation Used a population based genealogy linked to death certificates Observed significantly increased risk to relatives of individuals who died from asthma Cases are significantly more related than expected by chance Both analyses were significant in close and distant relatives Implications Implications vary according to interest… Genetic epidemiologist: Highly specific phenotype definition and significant results among distant relatives suggests heritable factor Department of health: Risk estimates are on a population basis, so apply well to an entire population An individual: Asthma mortality is rare Increased risk is low and not likely to apply at the individual level Next step Use of clinical data (instead of mortality) to distinguish asthma cases within the genealogy database may produce more meaningful risk estimates to clinicians, public health practitioners, and individuals. Utah Asthma Program community mini- grant may help to perform the next step Acknowledgements, 1 People Lisa Cannon-Albright Matt Hegewald Institutions Resource for Genetic and Epidemiologic Research (Utah Population Database) Utah Department of Health Asthma Program Introduction to linkage analysis study Linkage analysis Attempts to identify disease predisposition loci in the genome Based on the phenomenon of chromosome recombination that occur during meioses Utilizes inheritance information gathered in disease pedigrees Previous genome-wide scans for asthma have implicated almost every chromosome 22 study populations thus far8 > 30 suggestive or significant regions in the genome8 Several genes have been identified/hypothesized in association studies9 Replication is needed for these genes Results are likely to be population-specific Previous results from genome-wide scans for asthma8 9 10 11 12 8 7 5 6 3 4 1 2 21 22 19 20 17 18 16 14 15 13 X • previously published regions A unique data resource for asthma linkage 81 extended pedigrees ascertained for asthma between 1996 and 2000 3 to 6 generations per pedigree 6 to 97 individuals per pedigree 2 to 40 affected individuals per pedigree 1880 individuals included in analysis 744 affected (93% genotyped) 628 unaffected 508 undetermined phenotype status Genotyping Subjects were genotyped on 540 florescent dye-labeled microsatellite markers across the genome Genotyping was performed by Myriad genetics Average spacing of 6 cM between markers Methods Phenotype definition Physician confirmed presence or absence of asthma Based on spirometry measures, medical records and questionnaire Parametric analyses Mode of inheritance is not well-characterized general dominant and recessive model Disease allele frequency of 0.005 (dom) and 0.05 (rec) Both models assumed penetrance of 50% for disease allele carriers and 0.5% for non-disease carriers Genome-wide results 3 a.line1[, 2] 2 1 0 1 2 3 4 5 6 7 8 9 a.line1[, 1] 3 a.line2[, 2] 2 1 0 10 11 12 13 14 15 16 17 18 19 20 21 22 X Genome-wide results, cont. A significant10 result occurred on chromosome 5 LOD = 3.75 ~ 5600:1 odds in favor of linkage Evidence from recessive model Not reported in other genome-wide scans for asthma A nearly suggestive result occurred on chromosome 6 LOD = 2.08 ~ 120:1 odds in favor of linkage Evidence from dominant model Reported in several other genome-wide scans11 Our results in perspective to other published results 9 10 11 12 8 7 5 6 3 4 1 2 21 22 19 20 17 18 16 14 15 13 X • previously published regions Conclusions Our analysis of extended pedigrees identified a novel asthma susceptibility locus at chromosome 5q21 Our analysis confirmed another region of interest (with nearly suggestive evidence) for an asthma susceptibility locus at 6p21. Inclusion of fine mapping markers in regions of interest will improve localization Future linkage analysis in this resource should address phenotypic heterogeneity of asthma A better understanding of genetic factors for asthma may improve disease outcomes Acknowledgements, 2 People: Alun Thomas Lisa Cannon-Albright Nicola Camp Matt Hegewald Marlene Egger Jim Farnham Steven Backus Institutions: The National Library of Medicine Intermountain Healthcare Myriad Genetics Bayer Pharmaceuticals References 1. American Lung Association, Epidemiology and Statistics Unit, Research and Program Services. Trends in asthma morbidity and mortality. May 2005. 2. Braman SS. The global burden of asthma. Chest. 2006 Jul;130(1 Supp):4S-12S. 3. Wechsler ME, Israel E. The genetics of asthma. Semin Respir Crit Care Med. 2002 Aug;23(4):331- 338. 4. Clark JR, Jenkins MA, Hopper JL, et.al. Evidence for genetic associations between asthma, atopy and bronchial hyperresponsiveness: a study of 8- to 18-year old twins. Am J Respir Crit Care Med. 2000;162(6):2188-2193. 5. Burke W, Fesinmeyer M, Reed K, Hampson L. Family history as a predictor of asthma risk. Am J Prev Med 2003;24:160-169. 6. Hao K, Chen C, Wang B, Yang J, Fang Z, Xu X. Familial aggregation of airway responsiveness: a community-based study. Ann Epidemiol 2005;15:737-743. 7. Teerlink CC, Hegewald M, Cannon-Albright. A genealogical assessment of predisposition to asthma mortality. In press. 8. Ferreira MAR, O'Gorman L, Le Souef P, et al. Robust estimation of experiment-wise P values applied to a genome scan on multiple asthma traits identifies a new region of significant linkage on chromosome 20q13. Am J Hum Genet 2005;77:1075-1085. 9. Contopoulos-Ioannidis DG, Kouri IN, Ioannidis JPA. Genetic predisposition to asthma and atopy. Respiration 2007;74:8-12. 10. Lander E, Kruglyak L. Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nat Genet 1995;11(3):241-247. 11. Nicolae D, Cox NJ, Lester LA, et.al. Fine mapping and positional candidate studies identify HLA-G as an asthma susceptibility gene on chromosome 6p21. Am J Hum Genet. 2005;76:349-357.
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