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Ferreira MAR, O'Gorman L, Le Souëf P, Burton PR, Toelle BG, Robertson CF, Visscher PM, Martin NG, Duffy DL. Robust estimation of experimentwise P values applied to a genome scan of multiple asthma traits identifies a new region of significant linkage on chromosome 20q13. Am J Hum Genet 2005; 77:1075-85. [PMID: 16380917 PMCID: PMC1285164 DOI: 10.1086/497997] [Citation(s) in RCA: 33] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2005] [Accepted: 09/08/2005] [Indexed: 11/03/2022] Open
Abstract
Over 30 genomic regions show linkage to asthma traits. Six asthma genes have been cloned, but the putative loci in many linked regions have not been identified. To search for asthma susceptibility loci, we performed genomewide univariate linkage analyses of seven asthma traits, using 202 Australian families ascertained through a twin proband. House-dust mite sensitivity (Dpter) exceeded the empirical threshold for significant linkage at 102 cM on chromosome 20q13, near marker D20S173 (empirical pointwise P = .00001 and genomewide P = .005, both uncorrected for multiple-trait testing). Atopy, bronchial hyperresponsiveness (BHR), and forced expiratory volume in 1 s (FEV1) were also linked to this region. In addition, 16 regions were linked to at least one trait at the suggestive level, including 12q24, which has consistently shown linkage to asthma traits in other studies. Some regions were expected to be false-positives arising from multiple-trait testing. To address this, we developed a new approach to estimate genomewide significance that accounts for multiple-trait testing and for correlation between traits and that does not require a Bonferroni correction. With this approach, Dpter remained significantly linked to 20q13 (empirical genomewide P = .042), and airway obstruction remained linked to 12q24 at the suggestive level. Finally, we extended this method to show that the linkage of Dpter, atopy, BHR, FEV1, asthma, and airway obstruction to chromosome 20q13 is unlikely to be due to chance and may result from a quantitative trait locus in this region that affects several of these traits.
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Abstract
Hispanic individuals trace their ancestry to countries that were previously under Spanish rule, including Mexico, large parts of Central and South America, and some Caribbean islands. Most--but not all--Hispanics have variable proportions of European, Amerindian, and African ancestry. Hispanics are diverse with regard to many factors, including racial ancestry, country of origin, area of residence, socioeconomic status, education, and access to health care. Recent findings suggest that there is marked variation in the prevalence, morbidity, and mortality of asthma in Hispanics in the United States and in Hispanic America. The reasons for differences in asthma and asthma morbidity among and within Hispanic subgroups are poorly understood but are likely due to the interaction between yet-unidentified genetic variants and other factors, including environmental tobacco smoke exposure, obesity, allergen exposure, and availability of health care. Barriers to optimal management of asthma in Hispanics in the United States and in Hispanic America include inadequate access to health care, suboptimal use of antiinflammatory medications, and lack of reference values for spirometric measures of lung function in many subgroups (e.g., Puerto Ricans). Future studies of asthma in Hispanics should include large samples of subgroups that are well characterized with regard to self-reported ethnicity, country of origin, place of birth, area of residence, and indicators of socioeconomic status. Because Hispanics are disproportionately represented among the poor in the United States, implementation of adequate access to health care and social reforms (e.g., improving housing conditions) would likely have a major impact on reducing asthma morbidity in this population.
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Affiliation(s)
- Gary M Hunninghake
- Channing Laboratory, Dept. of Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115, USA
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160
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Hoffjan S, Nicolae D, Ostrovnaya I, Roberg K, Evans M, Mirel DB, Steiner L, Walker K, Shult P, Gangnon RE, Gern JE, Martinez FD, Lemanske RF, Ober C. Gene-environment interaction effects on the development of immune responses in the 1st year of life. Am J Hum Genet 2005; 76:696-704. [PMID: 15726497 PMCID: PMC1199307 DOI: 10.1086/429418] [Citation(s) in RCA: 76] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2004] [Accepted: 02/02/2005] [Indexed: 01/22/2023] Open
Abstract
Asthma is a common disease that results from both genetic and environmental risk factors. Children attending day care in the 1st year of life have lower risks for developing asthma, although the mechanism for this "day care" effect is largely unknown. We investigated the interactions between day care exposure in the 1st 6 mo of life and genotypes for 72 polymorphisms at 45 candidate loci and their effects on cytokine response profiles and on the development of atopic phenotypes in the 1st year of life in the Childhood Onset of Asthma (COAST) cohort of children. Six interactions (at four polymorphisms in three loci) with "day care" that had an effect on early-life immune phenotypes were significant at P<.001. The estimated false-discovery rate was 33%, indicating that an estimated four P values correspond to true associations. Moreover, the "day care" effect at some loci was accounted for by the increased number of viral infections among COAST children attending day care, whereas interactions at other loci were independent of the number of viral infections, indicating the presence of additional risk factors associated with day care environment. This study identified significant gene-environment interactions influencing the early patterning of the immune system and the subsequent development of asthma and highlights the importance of considering environmental risk factors in genetic analyses.
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Affiliation(s)
- Sabine Hoffjan
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - Dan Nicolae
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - Irina Ostrovnaya
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - Kathy Roberg
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - Michael Evans
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - Daniel B. Mirel
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - Lori Steiner
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - Karen Walker
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - Peter Shult
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - Ronald E. Gangnon
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - James E. Gern
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - Fernando D. Martinez
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - Robert F. Lemanske
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
| | - Carole Ober
- Departments of Human Genetics, Statistics, and Obstetrics and Gynecology, The University of Chicago, Chicago; Departments of Pediatrics, Medicine, and Biostatistics and Medical Bioinformatics, University of Wisconsin–Madison, and Wisconsin State Laboratory of Hygiene, Madison; Roche Molecular Systems, Alameda, CA; and Tucson Respiratory Center, University of Arizona, Tucson
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