BACKGROUND: Intermediate phenotypes are often measured as a proxy for asthma. It is largely unclear to what extent the same set of environmental or genetic factors regulate these traits. OBJECTIVE: Estimate the environmental and genetic correlations between self-reported and clinical asthma traits. METHODS: A total of 3,073 subjects from 802 families were ascertained through a twin proband. Traits measured included self-reported asthma, airway histamine responsiveness (AHR), skin prick response to common allergens including house dust mite (Dermatophagoides pteronyssinus [D. pter]), baseline lung function, total serum immunoglobulin E (IgE) and eosinophilia. Bivariate and multivariate analyses of eight traits were performed with adjustment for ascertainment and significant covariates. RESULTS: Overall 2,716 participants completed an asthma questionnaire and 2,087 were clinically tested, including 1,289 self-reported asthmatics (92% previously diagnosed by a doctor). Asthma, AHR, markers of allergic sensitization and eosinophilia had significant environmental correlations with each other (range: 0.23-0.89). Baseline forced expiratory volume in 1 s (FEV(1)) showed low environmental correlations with most traits. Fewer genetic correlations were significantly different from zero. Phenotypes with greatest genetic similarity were asthma and atopy (0.46), IgE and eosinophilia (0.44), AHR and D. pter (0.43) and AHR and airway obstruction (-0.43). Traits with greatest genetic dissimilarity were FEV(1) and atopy (0.05), airway obstruction and IgE (0.07) and FEV(1) and D. pter (0.11). CONCLUSION: These results suggest that the same set of environmental factors regulates the variation of many asthma traits. In addition, although most traits are regulated to great extent by specific genetic factors, there is still some degree of genetic overlap that could be exploited by multivariate linkage approaches.
BACKGROUND: Intermediate phenotypes are often measured as a proxy for asthma. It is largely unclear to what extent the same set of environmental or genetic factors regulate these traits. OBJECTIVE: Estimate the environmental and genetic correlations between self-reported and clinical asthma traits. METHODS: A total of 3,073 subjects from 802 families were ascertained through a twin proband. Traits measured included self-reported asthma, airway histamine responsiveness (AHR), skin prick response to common allergens including house dust mite (Dermatophagoides pteronyssinus [D. pter]), baseline lung function, total serum immunoglobulin E (IgE) and eosinophilia. Bivariate and multivariate analyses of eight traits were performed with adjustment for ascertainment and significant covariates. RESULTS: Overall 2,716 participants completed an asthma questionnaire and 2,087 were clinically tested, including 1,289 self-reported asthmatics (92% previously diagnosed by a doctor). Asthma, AHR, markers of allergic sensitization and eosinophilia had significant environmental correlations with each other (range: 0.23-0.89). Baseline forced expiratory volume in 1 s (FEV(1)) showed low environmental correlations with most traits. Fewer genetic correlations were significantly different from zero. Phenotypes with greatest genetic similarity were asthma and atopy (0.46), IgE and eosinophilia (0.44), AHR and D. pter (0.43) and AHR and airway obstruction (-0.43). Traits with greatest genetic dissimilarity were FEV(1) and atopy (0.05), airway obstruction and IgE (0.07) and FEV(1) and D. pter (0.11). CONCLUSION: These results suggest that the same set of environmental factors regulates the variation of many asthma traits. In addition, although most traits are regulated to great extent by specific genetic factors, there is still some degree of genetic overlap that could be exploited by multivariate linkage approaches.
Authors: Manuel A R Ferreira; Louise O'Gorman; Peter Le Souëf; Paul R Burton; Brett G Toelle; Colin F Robertson; Peter M Visscher; Nicholas G Martin; David L Duffy Journal: Am J Hum Genet Date: 2005-10-14 Impact factor: 11.025
Authors: David B Kantor; Nicole Stenquist; Molly C McDonald; Blake J Schultz; Marissa Hauptman; Craig D Smallwood; Kyle A Nelson; Matthew S Perzanowski; Elizabeth C Matsui; Wanda Phipatanakul; Joel N Hirschhorn Journal: J Allergy Clin Immunol Date: 2016-06-15 Impact factor: 10.793
Authors: Michael J McGeachie; Eli A Stahl; Blanca E Himes; Sarah A Pendergrass; John J Lima; Charles G Irvin; Stephen P Peters; Marylyn D Ritchie; Robert M Plenge; Kelan G Tantisira Journal: Pharmacogenet Genomics Date: 2013-06 Impact factor: 2.089
Authors: Alysa E Doyle; Manuel A R Ferreira; Pamela B Sklar; Jessica Lasky-Su; Carter Petty; Steven J Fusillo; Larry J Seidman; Erik G Willcutt; Jordan W Smoller; Shaun Purcell; Joseph Biederman; Stephen V Faraone Journal: Am J Med Genet B Neuropsychiatr Genet Date: 2008-12-05 Impact factor: 3.568
Authors: J A Revez; L Bain; B Chapman; J E Powell; R Jansen; D L Duffy; J Y Tung; B W Penninx; P M Visscher; E J C De Geus; D I Boomsma; D A Hinds; N G Martin; G W Montgomery; M A R Ferreira Journal: Genes Immun Date: 2013-08-15 Impact factor: 2.676
Authors: Ben D Spycher; John Henderson; Raquel Granell; David M Evans; George Davey Smith; Nicholas J Timpson; Jonathan A C Sterne Journal: J Allergy Clin Immunol Date: 2012-08 Impact factor: 10.793