Indication of linkage and genetic heterogeneity of asthma according to age at onset on chromosome 7q in 107 French EGEA families

Exploring the origins of asthma: Lessons from twin studies

This thesis explores the contribution of twin studies, particularly those studies originating from the Danish Twin Registry, to the understanding of the aetiology of asthma. First, it is explored how twin studies have established the contribution of genetic and environmental factors to the variation in the susceptibility to asthma, and to the variation in several aspects of the clinical expression of the disease such as its age at onset, its symptomatology, its intermediate phenotypes, and its relationship with other atopic diseases. Next, it is explored how twin studies have corroborated theories explaining asthma's recent increase in prevalence, and last, how these fit with the explanations of the epidemiological trends in other common chronic diseases of modernity.

Obesity and asthma: a coincidence or a causal relationship? A systematic review

BACKGROUND AND AIM

Epidemiological data has established increasing adiposity as a risk factor for incident asthma. However, the mechanisms underlying the association between obesity and asthma are incompletely understood. In the present paper, we review current knowledge of possible mechanisms mediating the observed association between obesity and asthma.

METHODS

Systematic literature review.

RESULTS

Obesity and asthma share some etiological factors, such as a common genetic predisposition and effects of in utero conditions, and may also have common predisposing factors such as physical activity and diet. Obesity results in important changes in the mechanical properties of the respiratory system which could explain the occurrence of asthma. However, there are also plausible biological mechanisms whereby obesity could be expected to either cause or worsen asthma. These include co-morbidities such as gastro-oesophageal reflux, complications from sleep-disordered breathing, breathing at low lung volumes, chronic systemic inflammation, and endocrine factors, including adipokines and reproductive hormones. Obesity related asthma is in general not associated with eosinophilic airway inflammation, and adipokines are likely to play important roles in the inflammatory pathogenesis of asthma in obese individuals.

CONCLUSION

The association between obesity and asthma is not straightforward, and further knowledge is clearly needed, as understanding the underlying mechanisms may lead to new therapeutic options for this high-risk part of the asthma population.

Obesity and asthma: an association modified by age of asthma onset

BACKGROUND

Studies of asthma phenotypes have identified obesity as a component of a group characterized by a high proportion of subjects with adult-onset asthma. However, whether age of asthma onset modifies the association between obesity and asthma is unknown.

OBJECTIVES

We sought to compare the associations between body mass index (BMI) categories with physiological, inflammatory, and clinical parameters across age of asthma onset phenotypes; and to compare the rate of BMI change in relation to asthma duration, by age of onset asthma phenotypes.

METHODS

From the Severe Asthma Research Program, we defined age of asthma onset as early (<12 years of age) and late (≥12 years of age). Comparisons of BMI categories were done within age-of-onset groups, and obesity was also compared across these groups. Multivariable logistic regression analysis was done to evaluate the association between BMI categories with health care use and respiratory symptoms and multivariable linear regression for the association between duration of asthma and weight gain (BMI change per year). An interaction between obesity and age of asthma onset was included in the multivariable analyses.

RESULTS

The study population consisted of 1049 subjects, and the median age for asthma onset was 10 years (interquartile range, 4-25 years); 48% had late-onset asthma (≥12 years of age), and 52% had early-onset asthma (<12 years of age). Compared with obese subjects with late-onset asthma, obese subjects with early-onset asthma had more airway obstruction, bronchial hyperresponsiveness, and higher odds ratios of ever having 3 or more previous oral steroid tapers per year or intensive care unit admissions for asthma per preceding year (interactions between obesity and age of asthma onset were P = .055 and P = .02, respectively). In subjects with early-onset asthma but not in subjects with late-onset asthma, there was a significant association between increasing BMI and duration of asthma after adjusting for confounders. The interaction between asthma duration and age of asthma onset was a P value of less than .01.

CONCLUSION

Asthmatic subjects are differentially affected by obesity based on whether they had asthma early (<12 years of age) or later in life. These results highlight the need to understand obesity as a comorbidity that affects specific clinical phenotypes and not all asthma subjects alike.

The effects of NOS1 gene on asthma and total IgE levels in Taiwanese children, and the interactions with environmental factors

Asthma is a complex disorder, which is known to be affected by interactions between genetic and environmental factors. The aim of this study was to investigate the three microsatellite polymorphisms of GT repeats in intron 2, AAT repeats in intron 20, and CA repeats in exon 29 of the NOS1 gene in 155 asthmatic children and 301 control children, and the interaction with environmental factors in southern Taiwan. Total serum IgE, phadiatop test and genetic polymorphisms were measured. The genotype frequency of 14/14-AAT repeats of the NOS1 gene was significantly higher in the asthmatic group (p = 0.01). Total IgE concentrations were higher in asthmatic children (p = 0.015) carrying the NOS1 14/14-AAT genotype than in subjects with other polymorphisms. The gene and environmental interaction effects were 3.83-fold, 6.86-fold, and 8.04-fold (all corrected p-values <0.001) between subjects carrying at least one NOS1 14-AAT allele and exposure to cockroaches, high levels of total IgE, and positive response against the phadiatop test in asthmatic children. The findings of this study provide strong evidence that NOS1 gene with 14-AAT tandem repeats has a significant effect in asthmatic children. Environmental factors and atopic status will enhance the asthmatic risk for children who carry NOS1 susceptible allele.

Evidence for a pleiotropic QTL on chromosome 5q13 influencing both time to asthma onset and asthma score in French EGEA families

Although many genome screens have been conducted for asthma as a binary trait, there is limited information regarding the genetic factors underlying variation of asthma expression. Phenotypes related to variable disease expression include time to asthma onset and variation in clinical expression as measured by an asthma score built from EGEA data. A recent genome scan conducted for this score led to detection of a new region (18p11) not revealed by analysis of dichotomous asthma. Our goal was to characterize chromosomal regions harboring genes underlying time to asthma onset and to search for pleiotropic QTL influencing both time to asthma onset and the asthma score. We conducted a genome-wide linkage screen for time to asthma onset, modeled by martingale residuals from Cox survival model, in EGEA families with at least two asthmatic sibs. This was followed by a bivariate linkage scan of these residuals and asthma score. Univariate linkage analysis was performed using the Maximum Likelihood Binomial method that we extended to bivariate analysis. This screen revealed two regions potentially linked to time to asthma onset, 1p31 (LOD = 1.70, P = 0.003) and 5q13 (LOD = 1.87, P = 0.002). Bivariate linkage analysis led to a substantial improvement of the linkage signal on 5q13 (P = 0.00007), providing evidence for a pleiotropic QTL influencing both variation of time to asthma onset and of clinical expression. Use of quantitative phenotypes of variable disease expression and suitable statistical methodology can improve the power to detect new regions harboring genes which may play an important role in onset and course of disease.

Evidence for a locus in 1p31 region specifically linked to the co-morbidity of asthma and allergic rhinitis in the EGEA study

OBJECTIVE

A recent genome scan conducted in French EGEA families led to detect linkage of 1p31 to either asthma or allergic rhinitis (AR) and more significantly to asthma associated with AR. The goal of the present study was to assess formally whether 1p31 is a linkage region shared by two different diseases, asthma and AR, or whether it is specific to the co-morbidity asthma plus AR.

METHODS

We used two different statistical approaches: the Triangle Test Statistic (TTS) and the Predivided Sample Test (PST), to search for heterogeneity of linkage to 1p31 according to the affection status being defined by either the presence of the two diseases (asthma plus AR) or the presence of only one disease ('asthma only' or 'AR only' or 'asthma only or AR only').

RESULTS

While no heterogeneity between the 'two diseases' phenotype and the 'one disease' phenotype was detected by the TTS, there was significant evidence for heterogeneity (p = 0.00007/0.002 after correction for multiple testing) using the PST. There was no indication of linkage in sib-pairs with 'one disease' only, while there was significant evidence for linkage in sib-pairs displaying asthma plus AR (p = 0.0002/0.0016 after correction).

CONCLUSION

The present analysis shows that the co-morbidity, asthma plus AR, represents a phenotypic entity, distinct from asthma only or AR only, controlled by a genetic factor located on 1p31.

Impact of the diagnosis definition on linkage detection

Previous genome scan linkage analyses of the disease Kofendrerd Personality Disorder (KPD) with microsatellites led to detect some regions on chromosomes 1, 3, 5, and 9 that were identical for the three populations AI, KA, and DA but with large differences in significance levels. These differences in results may be explained by the different diagnosis definitions depending on the presence/absence of 12 traits that were used in the 3 populations AI, KA, and DA. Heterogeneity of linkage was thus investigated here according to the absence/presence of each of the 12 traits in the 3 populations. For this purpose, two methods, the triangle test statistic and the predivided sample test were applied to search for genetic heterogeneity. Three regions with a strong heterogeneity of linkage were detected: the region on chromosome 1 according to the presence/absence of the traits a and b, the region on chromosome 3 for the trait b, and the region on chromosome 9 for the traits k and l. These 3 regions were the same as those detected by linkage analyses. No novel region was detected by the heterogeneity tests. Concerning chromosome 1, linkage analyses showed a much stronger evidence of linkage for traits a and b and for a combination of these traits than for KPD. Moreover, there was no indication of linkage to any of the other traits used to define the diagnosis of KPD. A genetic factor located on the chromosome 1 may have been detected here which would be involved specifically in traits a and b or in a combination of these traits.

Indication of linkage and genetic heterogeneity for asthma and atopy on chromosomes 8p and 12q in 107 French EGEA families

Using the sample of 107 families with at least two asthmatic siblings, as part of the EGEA study, we have investigated linkage to asthma (or atopy) and genetic heterogeneity according to the presence/absence of atopy (or asthma) using two approaches: (1) the triangle test statistic (TTS), which considers the identical by descent (IBD) distribution among affected sib-pairs discordant for another associated phenotype (eg asthmatic sib-pairs discordant for atopy) and (2) the predivided sample test (PST), which compares the IBD distribution of marker alleles between affected sib-pairs concordant and discordant for the associated phenotype. Two regions, 8p and 12q, already reported to be linked to both asthma and atopy, were examined here. A total of 20 asthmatic sib-pairs discordant for atopy and 24 atopic pairs discordant for asthma were analyzed by both TTS and PST methods and 83 pairs with atopic asthma by PST. Some evidence for linkage was observed for two markers in the 8p23.3-p23.2 region; D8S504 for asthma with genetic heterogeneity according to the presence/absence of atopy and D8S503 for atopy with genetic heterogeneity according to the presence/absence of asthma. In the 12q14.2-q21.33 region, there was also some evidence of linkage to two markers, D12S83 and D12S95, for atopy and asthma, respectively, with genetic heterogeneity according to the presence/absence of the associated trait. Provided the small distance between the two markers on either 8p (16 cM) or 12q (21 cM), it is unclear whether one or two genetic factors are involved in either region.

Testing linkage and gene x environment interaction: comparison of different affected sib-pair methods

The aim of this study was to compare, under different models of gene-environment (G x E) interaction, the power to detect linkage and G x E interaction of different tests using affected sib-pairs. Methods considered were: 1) the maximum likelihood lod-score (MLS), based on the distribution of parental alleles identical by descent (IBD) in affected sibs; 2) the sum of the MLS (sMLS) calculated in affected sib-pairs with 2, 1, or 0 sibs exposed; 3) the predivided sample test (PST), which compares the IBD distribution between affected sib-pairs with 2, 1, or 0 sibs exposed; 4) the triangle test statistic (TTS), which uses the IBD distribution among discordant affected sib-pairs (one exposed, one unexposed); and 5) the mean interaction test (MIT), based on the regression of the proportion of alleles shared IBD among affected sib-pairs on the exposure among sib-pairs. The MLS, sMLS, and MIT allow detection of linkage. However, the sMLS and MIT account for a possible G x E interaction without testing it. In contrast, the PST and the TTS allow detection of both linkage and G x E interaction. Results showed that when exposure cancels the effect of the gene, or changes the direction of this effect (i.e., the protective allele becomes the risk allele), the PST, sMLS, and MIT may provide, under some models, greater power to detect linkage than the MLS. Under models where exposure changes the direction of the effect of the gene, the TTS test may also be more powerful than the other tests accounting for G x E interaction. Under the other models, the MLS remains the most powerful test to detect linkage. However, only the PST and TTS allow the detection of G x E interaction.