Rationale: Variability in pulmonary disease severity is found in patients with cystic fibrosis (CF) who have identical mutations in the CF transmembrane conductance regulator (CFTR) gene. We hypothesized that one factor accounting for heterogeneity in pulmonary disease severity is variation in the family of genes affecting the biology of interleukin-1 (IL-1), which impacts acquisition and maintenance of Pseudomonas aeruginosa infection in animal models of chronic infection. Methods: We genotyped 58 single nucleotide polymorphisms (SNPs) in the IL-1 gene cluster in 808 CF subjects from the University of North Carolina and Case Western Reserve University (UNC/CWRU) joint cohort. All were homozygous for ΔF508, and categories of “severe” (cases) or “mild” (control subjects) lung disease were defined by the lowest or highest quartile of forced expired volume (FEV1) for age in the CF population. After adjustment for age and gender, genotypic data were tested for association with lung disease severity. Odds ratios (ORs) comparing severe versus mild CF were also calculated for each genotype (with the homozygote major allele as the reference group) for all 58 SNPs. From these analyses, nine SNPs with a moderate effect size, OR ≤ 0.5or > 1.5, were selected for further testing. To replicate the case-control study results, we genotyped the same nine SNPs in a second population of CF parent-offspring trios (recruited from Children’s Hospital Boston), in which the offspring had similar pulmonary phenotypes. For the trio analysis, both family-based and population-based associations were performed. Results: SNPs rs1143634 and rs1143639 in the IL1B gene demonstrated a consistent association with lung disease severity categories (P < 0.10) and longitudinal analysis of lung disease severity (P < 0.10) in CF in both the case-control and family-based studies. In females, there was a consistent association (false discovery rate adjusted joint P-value < 0.06 for both SNPs) in both the analysis of lung disease severity in the UNC/CWRU cohort and the family-based analysis of affection status. Conclusion: Our findings suggest that IL1β is a clinically relevant modulator of CF lung disease.
gene modifiers; cystic fibrosis; CFTR; IL-1 gene family
IL10 is an anti-inflammatory cytokine that has been found to have lower production in macrophages and mononuclear cells from asthmatics. Since reduced IL10 levels may influence the severity of asthma phenotypes, we examined IL10 single-nucleotide polymorphisms (SNPs) for association with asthma severity and allergy phenotypes as quantitative traits. Utilizing DNA samples from 518 Caucasian asthmatic children from the Childhood Asthma Management Program (CAMP) and their parents, we genotyped six IL10 SNPs: 3 in the promoter, 2 in introns, and one in the 3′ UTR. Using family-based association tests, each SNP was tested for association with asthma and allergy phenotypes individually. Population-based association analysis was performed with each SNP locus, the promoter haplotypes and the 6-loci haplotypes. The 3′ UTR SNP was significantly associated with FEV1 as a percent of predicted (FEV1PP) (P=0.0002) in both the family and population analyses. The promoter haplotype GCC was positively associated with IgE levels and FEV1PP (P=0.007 and 0.012, respectively). The promoter haplotype ATA was negatively associated with lnPC20 and FEV1PP (P=0.008 and 0.043, respectively). Polymorphisms in IL10 are associated with asthma phenotypes in this cohort. Further studies of variation in the IL10 gene may help elucidate the mechanism of asthma development in children.
interleukin 10 (IL10); single nucleotide polymorphism (SNP); genetic association; family-based association test (FBAT); haplotype; promoter; 3′; untranslated region (3′UTR)
The response to treatment for asthma is characterized by wide interindividual variability, with a significant number of patients who have no response. We hypothesized that a genomewide association study would reveal novel pharmacogenetic determinants of the response to inhaled glucocorticoids.
We analyzed a small number of statistically powerful variants selected on the basis of a family-based screening algorithm from among 534,290 single-nucleotide polymorphisms (SNPs) to determine changes in lung function in response to inhaled glucocorticoids. A significant, replicated association was found, and we characterized its functional effects.
We identified a significant pharmacogenetic association at SNP rs37972, replicated in four independent populations totaling 935 persons (P = 0.0007), which maps to the glucocorticoid-induced transcript 1 gene (GLCCI1) and is in complete linkage disequilibrium (i.e., perfectly correlated) with rs37973. Both rs37972 and rs37973 are associated with decrements in GLCCI1 expression. In isolated cell systems, the rs37973 variant is associated with significantly decreased luciferase reporter activity. Pooled data from treatment trials indicate reduced lung function in response to inhaled glucocorticoids in subjects with the variant allele (P = 0.0007 for pooled data). Overall, the mean (± SE) increase in forced expiratory volume in 1 second in the treated subjects who were homozygous for the mutant rs37973 allele was only about one third of that seen in similarly treated subjects who were homozygous for the wild-type allele (3.2 ± 1.6% vs. 9.4 ± 1.1%), and their risk of a poor response was significantly higher (odds ratio, 2.36; 95% confidence interval, 1.27 to 4.41), with genotype accounting for about 6.6% of overall inhaled glucocorticoid response variability.
A functional GLCCI1 variant is associated with substantial decrements in the response to inhaled glucocorticoids in patients with asthma. (Funded by the National Institutes of Health and others; ClinicalTrials.gov number, NCT00000575.)
To assess the feasibility of developing a Combined Clinical and Pharmacogenetic Predictive Test, comprised of multiple single nucleotide polymorphisms (SNPs) that is associated with poor bronchodilator response (BDR).
We genotyped SNPs that tagged the whole genome of the parents and children in the Childhood Asthma Management Program (CAMP) and implemented an algorithm using a family-based association test that ranked SNPs by statistical power. The top eight SNPs that were associated with BDR comprised the Pharmacogenetic Predictive Test. The Clinical Predictive Test was comprised of baseline forced expiratory volume in 1 s (FEV1). We evaluated these predictive tests and a Combined Clinical and Pharmacogenetic Predictive Test in three distinct populations: the children of the CAMP trial and two additional clinical trial populations of asthma. Our outcome measure was poor BDR, defined as BDR of less than 20th percentile in each population. BDR was calculated as the percent difference between the prebronchodilator and postbronchodilator (two puffs of albuterol at 180 μg/puff) FEV1 value. To assess the predictive ability of the test, the corresponding area under the receiver operating characteristic curves (AUROCs) were calculated for each population.
The AUROC values for the Clinical Predictive Test alone were not significantly different from 0.50, the AUROC of a random classifier. Our Combined Clinical and Pharmacogenetic Predictive Test comprised of genetic polymorphisms in addition to FEV1 predicted poor BDR with an AUROC of 0.65 in the CAMP children (n= 422) and 0.60 (n= 475) and 0.63 (n= 235) in the two independent populations. Both the Combined Clinical and Pharmacogenetic Predictive Test and the Pharmacogenetic Predictive Test were significantly more accurate than the Clinical Predictive Test (AUROC between 0.44 and 0.55) in each of the populations.
Our finding that genetic polymorphisms with a clinical trait are associated with BDR suggests that there is promise in using multiple genetic polymorphisms simultaneously to predict which asthmatics are likely to respond poorly to bronchodilators.
asthma; bronchodilator response; personalized medicine; pharmacogenetic test; predictive medicine
For genomewide association studies with family-based designs, we propose a Bayesian approach. We show that standard TDT/FBAT statistics can naturally be implemented in a Bayesian framework. We construct a Bayes factor conditional on the offspring phenotype and parental genotype data and then use the data we conditioned on to inform the prior odds for each marker. In the construction of the prior odds, the evidence for association for each single marker is obtained at the population-level by estimating the genetic effect size in the conditional mean model. Since such genetic effect size estimates are statistically independent of the effect size estimation within the families, the actual data set can inform the construction of the prior odds without any statistical penalty. In contrast to Bayesian approaches that have recently been proposed for genomewide association studies, our approach does not require assumptions about the genetic effect size; this makes the proposed method entirely data-driven. The power of the approach was assessed through simulation. We then applied the approach to a genomewide association scan to search for associations between single nucleotide polymorphisms and body mass index in the Childhood Asthma Management Program data.
family-based association tests; Bayes factors; complex traits
Corticotropin - releasing hormone receptor 2 (CRHR2) participates in smooth muscle relaxation response and may influence acute airway bronchodilator response to short – acting β2 agonist treatment of asthma. We aim to assess associations between genetic variants of CRHR2 and acute bronchodilator response in asthma.
We investigated 28 single nucleotide polymorphisms in CRHR2 for associations with acute bronchodilator response to albuterol in 607 Caucasian asthmatic subjects recruited as part of the Childhood Asthma Management Program (CAMP). Replication was conducted in two Caucasian adult asthma cohorts – a cohort of 427 subjects enrolled in a completed clinical trial conducted by Sepracor Inc. (MA, USA) and a cohort of 152 subjects enrolled in the Clinical Trial of Low-Dose Theopylline and Montelukast (LODO) conducted by the American Lung Association Asthma Clinical Research Centers.
Five variants were significantly associated with acute bronchodilator response in at least one cohort (p-value ≤ 0.05). Variant rs7793837 was associated in CAMP and LODO (p-value = 0.05 and 0.03, respectively) and haplotype blocks residing at the 5’ end of CRHR2 were associated with response in all three cohorts.
We report for the first time, at the gene level, replicated associations between CRHR2 and acute bronchodilator response. While no single variant was significantly associated in all three cohorts, the findings that variants at the 5’ end of CRHR2 are associated in each of three cohorts strongly suggest that the causative variants reside in this region and its genetic effect, although present, is likely to be weak.
Asthma; genetics; corticotrophin releasing hormone receptor 2; CRHR2; bronchodilator response; polymorphism; β2 adrenergic receptor agonist
We propose an omnibus family-based association test (MFBAT) that can be applied to multiple markers and multiple phenotypes and that has only one degree of freedom. The proposed test statistic extends current FBAT methodology to incorporate multiple markers as well as multiple phenotypes. Using simulation studies, power estimates for the proposed methodology are compared with the standard methodologies. On the basis of these simulations, we find that MFBAT substantially outperforms other methods, including haplotypic approaches and doing multiple tests with single single-nucleotide polymorphisms (SNPs) and single phenotypes. The practical relevance of the approach is illustrated by an application to asthma in which SNP/phenotype combinations are identified and reach overall significance that would not have been identified using other approaches. This methodology is directly applicable to cases in which there are multiple SNPs, such as candidate gene studies, cases in which there are multiple phenotypes, such as expression data, and cases in which there are multiple phenotypes and genotypes, such as genome-wide association studies that incorporate expression profiles as phenotypes. This program is available in the PBAT analysis package.
family-based association testing (FBAT); genome-wide association studies; FBAT-PC; multiple marker; multiple phenotypes; multiple testing
We introduce a stepwise approach for family-based designs for selecting a set of markers in a gene that are independently associated with the disease. The approach is based on testing the effect of a set of markers conditional on another set of markers. Several likelihood-based approaches have been proposed for special cases, but no model-free based tests have been proposed. We propose two types of tests in a family-based framework that are applicable to arbitrary family structures and completely robust to population stratification. We propose methods for ascertained dichotomous traits and unascertained quantitative traits. We first propose a completely model-free extension of the FBAT main genetic effect test. Then, for power issues, we introduce two model-based tests, one for dichotomous traits and one for continuous traits. Lastly, we utilize these tests to analyze a continuous lung function phenotype as a proxy for asthma in the Childhood Asthma Management Program. The methods are implemented in the free R package fbati.
Binary trait; Candidate gene analysis; Family-based association tests; FBAT-C; Linkage disequilibrium (LD); Model-based test; Model-free test; Nuclear families; Quantitative trait
We propose an omnibus family-based association test (MFBAT), that can be applied to multiple markers and multiple phenotypes and that has only 1 degree of freedom. The proposed test statistic extends current FBAT methodology to incorporate multiple markers as well as multiple phenotypes. Using simulation studies, power estimates for the proposed methodology are compared with the standard methodologies. Based on these simulations, we find that MFBAT substantially outperforms other methods including some haplotypic approaches and doing multiple tests with single SNPs and single phenotypes. The practical relevance of the approach is illustrated by an application to asthma where SNPs/phenotype combinations are identified and reach overall significance that would not have been identified using other approaches. This methodology is directly applicable to cases where there are multiple SNPs, such as candidate gene studies, cases where there are multiple phenotypes, such as expression data, and cases where there are multiple phenotypes and genotypes, such as genome-wide association studies that incorporate expression profiles as phenotypes. This program is available in the PBAT analysis package1.
Family-based association testing (FBAT); genome-wide association studies; FBAT-PC; multiple marker; multiple phenotypes; multiple testing
Asthma is a chronic respiratory disease whose genetic basis has been explored for over two decades, most recently via genome-wide association studies. We sought to find asthma-susceptibility variants by using probands from a single population in both family-based and case-control association designs.
We used probands from the Childhood Asthma Management Program (CAMP) in two primary genome-wide association study designs: (1) probands were combined with publicly available population controls in a case-control design, and (2) probands and their parents were used in a family-based design. We followed a two-stage replication process utilizing three independent populations to validate our primary findings.
We found that single nucleotide polymorphisms with similar case-control and family-based association results were more likely to replicate in the independent populations, than those with the smallest p-values in either the case-control or family-based design alone. The single nucleotide polymorphism that showed the strongest evidence for association to asthma was rs17572584, which replicated in 2/3 independent populations with an overall p-value among replication populations of 3.5E-05. This variant is near a gene that encodes an enzyme that has been implicated to act coordinately with modulators of Th2 cell differentiation and is expressed in human lung.
Our results suggest that using probands from family-based studies in case-control designs, and combining results of both family-based and case-control approaches, may be a way to augment our ability to find SNPs associated with asthma and other complex diseases.
Genetic variants influencing lung function in children and adults may ultimately lead to the development of chronic obstructive pulmonary disease (COPD), particularly in high-risk groups.
We tested for an association between single-nucleotide polymorphisms (SNPs) in the gene encoding matrix metalloproteinase 12 (MMP12) and a measure of lung function (prebronchodilator forced expiratory volume in 1 second [FEV1]) in more than 8300 subjects in seven cohorts that included children and adults. Within the Normative Aging Study (NAS), a cohort of initially healthy adult men, we tested for an association between SNPs that were associated with FEV1 and the time to the onset of COPD. We then examined the relationship between MMP12 SNPs and COPD in two cohorts of adults with COPD or at risk for COPD.
The minor allele (G) of a functional variant in the promoter region of MMP12 (rs2276109 [−82A→G]) was positively associated with FEV1 in a combined analysis of children with asthma and adult former and current smokers in all cohorts (P=2×10−6). This allele was also associated with a reduced risk of the onset of COPD in the NAS cohort (hazard ratio, 0.65; 95% confidence interval [CI], 0.46 to 0.92; P = 0.02) and with a reduced risk of COPD in a cohort of smokers (odds ratio, 0.63; 95% CI, 0.45 to 0.88; P = 0.005) and among participants in a family-based study of early-onset COPD (P = 0.006).
The minor allele of a SNP in MMP12 (rs2276109) is associated with a positive effect on lung function in children with asthma and in adults who smoke. This allele is also associated with a reduced risk of COPD in adult smokers.
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.”
asthma; replication; single-nucleotide polymorphism; integrin β3; association
Discovering genetic associations between genetic markers and gene expression levels can provide insight into gene regulation and, potentially, mechanisms of disease. Such analyses typically involve a linkage or association analysis in which expression data are used as phenotypes. This approach leads to a large number of multiple comparisons and may therefore lack power. We assess the potential of applying canonical correlation analysis to partitioned genomewide data as a method for discovering regulatory variants.
Simulations suggest that canonical correlation analysis has higher power than standard pairwise univariate regression to detect single nucleotide polymorphisms when the expression trait has low heritability. The increase in power is even greater under the recessive model. We demonstrate this approach using the Childhood Asthma Management Program data.
Our approach reduces multiple comparisons and may provide insight into the complex relationships between genotype and gene expression.
Several family-based approaches for testing genetic association with traits obtained from longitudinal or repeated measurement studies have been previously proposed. These approaches utilize the multivariate data more efficiently by using estimated optimal weights to combine univariate tests. We show that these FBAT approaches are still robust against hidden population stratification, but their power can be heavily affected since the estimated weights might provide poor approximation of the true theoretical optimal weights with the presence of population stratification. We introduce a permutation-based approach FBAT-MinP and an equal combination approach FBAT-EW, both of which do not involve the use of estimated weights. Through simulation studies, FBAT-MinP and FBAT-EW are shown to be powerful even in the presence of population stratification, when other approaches may substantially lose their power. An application of these approaches to the Childhood Asthma Management Program (CAMP) study data for testing an association between body mass index and a previously reported candidate SNP is given as an example.
For genome-wide association studies in family-based designs, we propose a new, universally applicable approach. The new test statistic exploits all available information about the association, while, by virtue of its design, it maintains the same robustness against population admixture as traditional family-based approaches that are based exclusively on the within-family information. The approach is suitable for the analysis of almost any trait type, e.g. binary, continuous, time-to-onset, multivariate, etc., and combinations of those. We use simulation studies to verify all theoretically derived properties of the approach, estimate its power, and compare it with other standard approaches. We illustrate the practical implications of the new analysis method by an application to a lung-function phenotype, forced expiratory volume in one second (FEV1) in 4 genome-wide association studies.
In genome-wide association studies, the multiple testing problem and confounding due to population stratification have been intractable issues. Family-based designs have considered only the transmission of genotypes from founder to nonfounder to prevent sensitivity to the population stratification, which leads to the loss of information. Here we propose a novel analysis approach that combines mutually independent FBAT and screening statistics in a robust way. The proposed method is more powerful than any other, while it preserves the complete robustness of family-based association tests, which only achieves much smaller power level. Furthermore, the proposed method is virtually as powerful as population-based approaches/designs, even in the absence of population stratification. By nature of the proposed method, it is always robust as long as FBAT is valid, and the proposed method achieves the optimal efficiency if our linear model for screening test reasonably explains the observed data in terms of covariance structure and population admixture. We illustrate the practical relevance of the approach by an application in 4 genome-wide association studies.
Motivation: Estimating the frequency distribution of copy number variants (CNVs) is an important aspect of the effort to characterize this new type of genetic variation. Currently, most studies report a strong skew toward low-frequency CNVs. In this article, our goal is to investigate the frequencies of CNVs. We employ a two-step procedure for the CNV frequency estimation process. We use family information a posteriori to select only the most reliable CNV regions, i.e. those showing high rates of Mendelian transmission.
Results: Our results suggest that the current skew toward low-frequency CNVs may not be representative of the true frequency distribution, but may be due, among other reasons, to the non-negligible false negative rates that characterize CNV detection methods. Moreover, false positives are also likely, as low-frequency CNVs are hard to detect with small sample sizes and technologies that are not ideally suited for their detection. Without appropriate validation methods, such as incorporation of biologically relevant information (for example, in our case, the transmission of heritable CNVs from parents to offspring), it is difficult to assess the validity of specific CNVs, and even harder to obtain reliable frequency estimates.
Availability: Software implementing the methods described in this article is available for download at the following address: http://www.isites.harvard.edu/icb/icb.do?keyword=k36162
Supplementary informantion: Supplementary data are available at Bioinformatics online.
Rationale: Inhaled β-agonists are one of the most widely used classes of drugs for the treatment of asthma. However, a substantial proportion of patients with asthma do not have a favorable response to these drugs, and identifying genetic determinants of drug response may aid in tailoring treatment for individual patients.
Objectives: To screen variants in candidate genes in the steroid and β-adrenergic pathways for association with response to inhaled β-agonists.
Methods: We genotyped 844 single nucleotide polymorphisms (SNPs) in 111 candidate genes in 209 children and their parents participating in the Childhood Asthma Management Program. We screened the association of these SNPs with acute response to inhaled β-agonists (bronchodilator response [BDR]) using a novel algorithm implemented in a family-based association test that ranked SNPs in order of statistical power. Genes that had SNPs with median power in the highest quartile were then taken for replication analyses in three other asthma cohorts.
Measurements and Main Results: We identified 17 genes from the screening algorithm and genotyped 99 SNPs from these genes in a second population of patients with asthma. We then genotyped 63 SNPs from four genes with significant associations with BDR, for replication in a third and fourth population of patients with asthma. Evidence for association from the four asthma cohorts was combined, and SNPs from ARG1 were significantly associated with BDR. SNP rs2781659 survived Bonferroni correction for multiple testing (combined P value = 0.00048, adjusted P value = 0.047).
Conclusions: These findings identify ARG1 as a novel gene for acute BDR in both children and adults with asthma.
pharmacogenetics; asthma; bronchodilator agents
Genetic association studies of complex traits often rely on standardised quantitative phenotypes, such as percentage of predicted forced expiratory volume and body mass index to measure an underlying trait of interest (eg lung function, obesity). These phenotypes are appealing because they provide an easy mechanism for comparing subjects, although such standardisations may not be the best way to control for confounders and other covariates. We recommend adjusting raw or standardised phenotypes within the study population via regression. We illustrate through simulation that optimal power in both population- and family-based association tests is attained by using the residuals from within-study adjustment as the complex trait phenotype. An application of family-based association analysis of forced expiratory volume in one second, and obesity in the Childhood Asthma Management Program data, illustrates that power is maintained or increased when adjusted phenotype residuals are used instead of typical standardised quantitative phenotypes.
body mass index; confounding factors; covariate adjustment; forced expiratory volume; heritable quantitative traits
Rationale: Replication of gene-disease associations has become a requirement in complex trait genetics.
Objectives: In studies of childhood asthma from two different ethnic groups, we attempted to replicate associations with five potential asthma susceptibility genes previously identified by positional cloning.
Methods: We analyzed two family-based samples ascertained through an asthmatic proband: 497 European-American children from the Childhood Asthma Management Program and 439 Hispanic children from the Central Valley of Costa Rica. We genotyped 98 linkage disequilibrium–tagging single-nucleotide polymorphisms (SNPs) in five genes: ADAM33, DPP10, GPR154 (HUGO name: NPSR1), HLA-G, and the PHF11 locus (includes genes SETDB2 and RCBTB1). SNPs were tested for association with asthma and two intermediate phenotypes: airway hyperresponsiveness and total serum immunoglobulin E levels.
Measurements and Main Results: Despite differing ancestries, linkage disequilibrium patterns were similar in both cohorts. Of the five evaluated genes, SNP-level replication was found only for GPR154 (NPSR1). In this gene, three SNPs were associated with asthma in both cohorts, although the opposite alleles were associated in either study. Weak evidence for locus-level replication with asthma was found in the PHF11 locus, although there was no overlap in the associated SNP across the two cohorts. No consistent associations were observed for the three other genes.
Conclusions: These results provide some further support for the role of genetic variation in GPR154 (NPSR1) and PHF11 in asthma susceptibility and also highlight the challenges of replicating genetic associations in complex traits such as asthma, even for genes identified by linkage analysis.
bronchial hyperreactivity; immunoglobulin E; linkage disequilibrium; NPSR1; single-nucleotide polymorphism
For genome-wide association studies in family-based designs, we propose a powerful two-stage testing strategy that can be applied in situations in which parent-offspring trio data are available and all offspring are affected with the trait or disease under study. In the first step of the testing strategy, we construct estimators of genetic effect size in the completely ascertained sample of affected offspring and their parents that are statistically independent of the family-based association/transmission disequilibrium tests (FBATs/TDTs) that are calculated in the second step of the testing strategy. For each marker, the genetic effect is estimated (without requiring an estimate of the SNP allele frequency) and the conditional power of the corresponding FBAT/TDT is computed. Based on the power estimates, a weighted Bonferroni procedure assigns an individually adjusted significance level to each SNP. In the second stage, the SNPs are tested with the FBAT/TDT statistic at the individually adjusted significance levels. Using simulation studies for scenarios with up to 1,000,000 SNPs, varying allele frequencies and genetic effect sizes, the power of the strategy is compared with standard methodology (e.g., FBATs/TDTs with Bonferroni correction). In all considered situations, the proposed testing strategy demonstrates substantial power increases over the standard approach, even when the true genetic model is unknown and must be selected based on the conditional power estimates. The practical relevance of our methodology is illustrated by an application to a genome-wide association study for childhood asthma, in which we detect two markers meeting genome-wide significance that would not have been detected using standard methodology.
The current state of genotyping technology has enabled researchers to conduct genome-wide association studies of up to 1,000,000 SNPs, allowing for systematic scanning of the genome for variants that might influence the development and progression of complex diseases. One of the largest obstacles to the successful detection of such variants is the multiple comparisons/testing problem in the genetic association analysis. For family-based designs in which all offspring are affected with the disease/trait under study, we developed a methodology that addresses this problem by partitioning the family-based data into two statistically independent components. The first component is used to screen the data and determine the most promising SNPs. The second component is used to test the SNPs for association, where information from the screening is used to weight the SNPs during testing. This methodology is more powerful than standard procedures for multiple comparisons adjustment (i.e., Bonferroni correction). Additionally, as only one data set is required for screening and testing, our testing strategy is less susceptible to study heterogeneity. Finally, as many family-based studies collect data only from affected offspring, this method addresses a major limitation of previous methodologies for multiple comparisons in family-based designs, which require variation in the disease/trait among offspring.
A SNP upstream of the INSIG2 gene, rs7566605, was recently found to be associated with obesity as measured by body mass index (BMI) by Herbert and colleagues. The association between increased BMI and homozygosity for the minor allele was first observed in data from a genome-wide association scan of 86,604 SNPs in 923 related individuals from the Framingham Heart Study offspring cohort. The association was reproduced in four additional cohorts, but was not seen in a fifth cohort. To further assess the general reproducibility of this association, we genotyped rs7566605 in nine large cohorts from eight populations across multiple ethnicities (total n = 16,969). We tested this variant for association with BMI in each sample under a recessive model using family-based, population-based, and case-control designs. We observed a significant (p < 0.05) association in five cohorts but saw no association in three other cohorts. There was variability in the strength of association evidence across examination cycles in longitudinal data from unrelated individuals in the Framingham Heart Study Offspring cohort. A combined analysis revealed significant independent validation of this association in both unrelated (p = 0.046) and family-based (p = 0.004) samples. The estimated risk conferred by this allele is small, and could easily be masked by small sample size, population stratification, or other confounders. These validation studies suggest that the original association is less likely to be spurious, but the failure to observe an association in every data set suggests that the effect of SNP rs7566605 on BMI may be heterogeneous across population samples.
Obesity is an epidemic in the United States of America and developing world, portending an epidemic of related diseases such as diabetes and heart disease. While diet and lifestyle contribute to obesity, half of the population variation in body mass index, a common measure of obesity, is determined by inherited factors. Many studies have reported that common sequence variants in genes are associated with an increased risk for obesity, yet most of these are not reproducible in other study cohorts, suggesting that some are false. Recently, Herbert et al. reported a slightly increased risk of obesity for people carrying two copies of the minor allele at a common variant near INSIG2. We present our attempts to further evaluate this potential association with obesity in additional populations. We find evidence of increased risk of obesity for people carrying two copies of the minor allele in five out of nine cohorts tested, using both family- and population-based testing. We indicate possible reasons for the varied results, with the hope of encouraging a combined analysis across study cohorts to more precisely define the effect of this INSIG2 gene variant.
Rationale: Tumor necrosis factor is a proinflammatory cytokine found in increased concentrations in asthmatic airways. The TNF-α (TNF) and lymphotoxin-α (LTA) genes belong to the TNF gene superfamily located within the human major histocompatibility complex on chromosome 6p in a region repeatedly linked to asthma. The TNF position –308 and LTA NcoI polymorphisms are believed to influence TNF transcription and secretion, respectively. Objectives: This study sought to determine whether polymorphisms in TNF or LTA, or in TNF-LTA haplotypes, are associated with asthma and asthma phenotypes. Methods: We genotyped the TNF –308 and LTA NcoI polymorphisms, and two other haplotype-tagging polymorphisms in the TNF and LTA genes, in 708 children with mild to moderate asthma enrolled in the Childhood Asthma Management Program and in their parents. Using an extension of the family-based association tests in the PBAT program, each polymorphism was tested for association with asthma, age at onset of asthma, and time series data on baseline FEV1 % predicted, postbronchodilator FEV1 % predicted, body mass index, and log of PC20. Measurements and Main Results: Although no associations were found for the individual single-nucleotide polymorphisms, the haplotype analysis found the LTA NcoI_G/LTA 4371T/TNF –308G/TNF 1078G haplotype to be associated with asthma and with all five phenotype groups. Conclusions: We conclude that it is unlikely that the TNF –308 or LTA NcoI polymorphisms influence asthma susceptibility individually, but that this haplotype of variants may be functional or may be in linkage disequilibrium with other functional single-nucleotide polymorphisms.
asthma; haplotypes; lymphotoxin-α polymorphism; tumor necrosis factor
Rationale: Little is known regarding the relationship between parental history of asthma and subsequent airway hyperresponsiveness (AHR) in children with asthma. Objectives: We evaluated this relationship in 1,041 children with asthma participating in a randomized trial of antiinflammatory medications (the Childhood Asthma Management Program [CAMP]). Methods: Methacholine challenge testing was performed before treatment randomization and once per year over an average of 4.5 years postrandomization. Cross-sectional and longitudinal repeated measures analyses were performed to model the relationship between PC20 (the methacholine concentration causing a 20% fall in FEV1) with maternal, paternal, and joint parental histories of asthma. Models were adjusted for potential confounders. Measurements and Main Results: At baseline, AHR was strongly associated with a paternal history of asthma. Children with a paternal history of asthma demonstrated significantly greater AHR than those without such history (median logePC20, 0.84 vs. 1.13; p = 0.006). Although maternal history of asthma was not associated with AHR, children with two parents with asthma had greater AHR than those with no parents with asthma (median logePC20, 0.52 vs. 1.17; p = 0.0008). Longitudinal multivariate analysis of the relation between paternal history of asthma and AHR using repeated PC20 measurements over 44 months postrandomization confirmed a significant association between paternal history of asthma and AHR among children in CAMP. Conclusions: Our findings suggest that the genetic contribution of the father is associated with AHR, an important determinant of disease severity among children with asthma.
airway responsiveness; asthma; genetics; longitudinal analysis; parent of origin
Case-control studies have successfully identified many significant genetic associations for complex diseases, but lack of replication has been a criticism of case-control genetic association studies in general. We selected 12 candidate genes with reported associations to chronic obstructive pulmonary disease (COPD) and genotyped 29 polymorphisms in a family-based study and in a case-control study. In the Boston Early-Onset COPD Study families, significant associations with quantitative and/or qualitative COPD-related phenotypes were found for the tumor necrosis factor (TNF)-α −308G>A promoter polymorphism (P < 0.02), a coding variant in surfactant protein B (SFTPB Thr131Ile) (P = 0.03), and the (GT)31 allele of the heme oxygenase (HMOX1) promoter short tandem repeat (P = 0.02). In the case-control study, the SFTPB Thr131Ile polymorphism was associated with COPD, but only in the presence of a gene-by-environment interaction term (P = 0.01 for both main effect and interaction). The 30-repeat, but not the 31-repeat, allele of HMOX1 was associated (P = 0.04). The TNF −308G>A polymorphism was not significant. In addition, the microsomal epoxide hydrolase “fast” allele (EPHX1 His139Arg) was significantly associated in the case-control study (P = 0.03). Although some evidence for replication was found for SFTPB and HMOX1, none of the previously published COPD genetic associations was convincingly replicated across both study designs.
association studies; case-control studies; emphysema; genetics; single nucleotide polymorphism