We propose a new approach for the analysis of copy number variants (CNVs)for genome-wide association studies in family-based designs. Our new overall association test combines the between-family component and the within-family component of the data so that the new test statistic is fully efficient and, at the same time, achieves the complete robustness against population-admixture and stratification, as classical family-based association tests that are based only on the between-family component. Although all data are incorporated into the test statistic, an adjustment for genetic confounding is not needed, not even for the between-family component. The new test statistic is valid for testing either quantitative or dichotomous phenotypes. If external CNV data are available, the approach can also be used in completely ascertained samples. Similar to the approach by Ionita-Laza et al.(1), the proposed test statistic does not required a CNV-calling algorithm and is based directly on the CNV probe intensity data. We show, via simulation studies, that our methodology increases the power of the FBAT statistic to levels comparable to those of population-based designs. The advantages of the approach in practice are demonstrated by an application to a genome-wide association study for body mass index (BMI).

Background

The relationships between total serum IgE levels and gene expression patterns in peripheral blood CD4+ T cells (in all subjects and within each sex specifically) are not known.

Methods

Peripheral blood CD4+ T cells from 223 participants from the Childhood Asthma Management Program (CAMP) with simultaneous measurement of IgE. Total RNA was isolated, and expression profiles were generated with Illumina HumanRef8 v2 BeadChip arrays. Modeling of the relationship between genome-wide gene transcript levels and IgE levels was performed in all subjects, and stratified by sex.

Results

Among all subjects, significant evidence for association between gene transcript abundance and IgE was identified for a single gene, the interleukin 17 receptor B (IL17RB), explaining 12% of the variance (r2) in IgE measurement (p value = 7 × 10-7, 9 × 10-3 after adjustment for multiple testing). Sex stratified analyses revealed that the correlation between IL17RB and IgE was restricted to males only (r2 = 0.19, p value = 8 × 10-8; test for sex-interaction p < 0.05). Significant correlation between gene transcript abundance and IgE level was not found in females. Additionally we demonstrated substantial sex-specific differences in IgE when considering multi-gene models, and in canonical pathway analyses of IgE level.

Conclusions

Our results indicate that IL17RB may be the only gene expressed in CD4+ T cells whose transcript measurement is correlated with the variation in IgE level in asthmatics. These results provide further evidence sex may play a role in the genomic regulation of IgE.

Rationale: Animal models demonstrate that aberrant gene expression in utero can result in abnormal pulmonary phenotypes.

Objectives: We sought to identify genes that are differentially expressed during in utero airway development and test the hypothesis that variants in these genes influence lung function in patients with asthma.

Methods: Stage 1 (Gene Expression): Differential gene expression analysis across the pseudoglandular (n = 27) and canalicular (n = 9) stages of human lung development was performed using regularized t tests with multiple comparison adjustments. Stage 2 (Genetic Association): Genetic association analyses of lung function (FEV1, FVC, and FEV1/FVC) for variants in five differentially expressed genes were conducted in 403 parent-child trios from the Childhood Asthma Management Program (CAMP). Associations were replicated in 583 parent-child trios from the Genetics of Asthma in Costa Rica study.

Measurements and Main Results: Of the 1,776 differentially expressed genes between the pseudoglandular (gestational age: 7–16 wk) and the canalicular (gestational age: 17–26 wk) stages, we selected 5 genes in the Wnt pathway for association testing. Thirteen single nucleotide polymorphisms in three genes demonstrated association with lung function in CAMP (P < 0.05), and associations for two of these genes were replicated in the Costa Ricans: Wnt1-inducible signaling pathway protein 1 with FEV1 (combined P = 0.0005) and FVC (combined P = 0.0004), and Wnt inhibitory factor 1 with FVC (combined P = 0.003) and FEV1/FVC (combined P = 0.003).

Conclusions: Wnt signaling genes are associated with impaired lung function in two childhood asthma cohorts. Furthermore, gene expression profiling of human fetal lung development can be used to identify genes implicated in the pathogenesis of lung function impairment in individuals with asthma.

Background

The glutathione S-transferase M1 (GSTM1) null variant is a common copy number variant associated with adverse pulmonary outcomes, including asthma and airflow obstruction, with evidence of important gene-by-environment interactions with exposures to oxidative stress.

Objective

To explore the joint interactive effects of GSTM1 copy number and tobacco smoke exposure on the development of asthma and asthma-related phenotypes in a family-based cohort of childhood asthmatics.

Methods

We performed quantitative PCR-based genotyping for GSTM1 copy number in children of self-reported white ancestry with mild to moderate asthma in the Childhood Asthma Management Program. Questionnaire data regarding intrauterine (IUS) and postnatal, longitudinal environmental tobacco smoke exposure were available. We performed both family-based and population-based tests of association for the interaction between GSTM1 copy number and tobacco smoke exposure with asthma and asthma-related phenotypes.

Results

Associations of GSTM1 null variants with asthma (p= .03), younger age of asthma symptom onset (p=.03), and greater airflow obstruction (reduced FEV1/FVC, p=.01) were observed among the 50 children (10% of the cohort) with exposure to IUS. In contrast, no associations were observed between GSTM1 null variants and asthma-related phenotypes among children without IUS exposure. Presence of at least one copy of GSTM1 conferred protection.

Conclusion

These findings support an important gene-by-environment interaction between two common factors: increased risk of asthma and asthma-related phenotypes conferred by GSTM1-null homozygosity in children is restricted to those with a history of IUS exposure.

Rationale: Association studies have implicated many genes in asthma pathogenesis, with replicated associations between single-nucleotide polymorphisms (SNPs) and asthma reported for more than 30 genes. Genome-wide genotyping enables simultaneous evaluation of most of this variation, and facilitates more comprehensive analysis of other common genetic variation around these candidate genes for association with asthma.

Objectives: To use available genome-wide genotypic data to assess the reproducibility of previously reported associations with asthma and to evaluate the contribution of additional common genetic variation surrounding these loci to asthma susceptibility.

Methods: Illumina Human Hap 550Kv3 BeadChip (Illumina, San Diego, CA) SNP arrays were genotyped in 422 nuclear families participating in the Childhood Asthma Management Program. Genes with at least one SNP demonstrating prior association with asthma in two or more populations were tested for evidence of association with asthma, using family-based association testing.

Measurements and Main Results: We identified 39 candidate genes from the literature, using prespecified criteria. Of the 160 SNPs previously genotyped in these 39 genes, 10 SNPs in 6 genes were significantly associated with asthma (including the first independent replication for asthma-associated integrin β3 [ITGB3]). Evaluation of 619 additional common variants included in the Illumina 550K array revealed additional evidence of asthma association for 15 genes, although none were significant after adjustment for multiple comparisons.

Conclusions: We replicated asthma associations for a minority of candidate genes. Pooling genome-wide association study results from multiple studies will increase the power to appreciate marginal effects of genes and further clarify which candidates are true “asthma genes.”

Aims

To evaluate phenotypic and genetic variables associated with a poor long-term response to inhaled corticosteroid therapy for asthma, based independently on lung function changes or asthma exacerbations.

Materials & methods

We tested 17 phenotypic variables and polymorphisms in FCER2 and CRHR1 in 311 children (aged 5–12 years) randomized to a 4-year course of inhaled corticosteroid during the Childhood Asthma Management Program (CAMP).

Results

Predictors of recurrent asthma exacerbations are distinct from predictors of poor lung function response. A history of prior asthma exacerbations, younger age and a higher IgE level (p < 0.05) are associated with recurrent exacerbations. By contrast, lower bronchodilator response to albuterol and the minor alleles of RS242941 in CRHR1 and T2206C in FCER2 (p < 0.05) are associated with poor lung function response. Poor lung function response does not increase the risk of exacerbations and vice versa (p = 0.72).

Conclusion

Genetic and phenotypic predictors of a poor long-term response to inhaled corticosteroids differ markedly depending on definition of outcome (based on exacerbations vs lung function). These findings are important in comparing outcomes of clinical trials and in designing future pharmacogenetic studies.

Structural genetic variation, including copy number variation (CNV), constitutes a substantial fraction of total genetic variability and the importance of structural genetic variants in modulating human disease is increasingly being recognized. Early successes in identifying disease-associated CNVs via a candidate gene approach mandate that future disease association studies need to include structural genetic variation. Such analyses should not rely on previously developed methodologies that were designed to evaluate single nucleotide polymorphisms (SNPs). Instead, development of novel technical, statistical, and epidemiologic methods will be necessary to optimally capture this newly-appreciated form of genetic variation in a meaningful manner.