Gibbs sampling-based segregation analysis of asthma-associated quantitative traits in a population-based sample of nuclear families

Exploration of the Genetic Epidemiology of Asthma: A Review, with a Focus on Prevalence in Children and Adolescents in the Caribbean

Asthma is a chronic disease caused by the inflammation of the main air passages of the lungs. This paper outlines a review of the published literature on asthma. While a few studies show a trend of rising asthma cases in the Caribbean region, even fewer have explored the genetic epidemiological factors of asthma. This is a literature review that seeks to sum the body of knowledge on the epidemiology of asthma. Specifically, the major objective of the literature review is to provide a unified information base on the current state of factors involved in the genetic epidemiology of asthma. The review is a simple, yet detailed summary of the literature sources and their methodology and findings on the genetic epidemiology of asthma. Further, it seeks to direct this effort to the Caribbean region. The paper then reviews a summarized and synthesized collection of the body of previous research. Of specific interest are peer-reviewed sources that have been published in recent times. The paper provides more recent insight and recapitulates on the previous research, while tracing the intellectual progress on the debate. Where possible, reviewing and discussing the results of the previous literature, this review singles out the gaps and potential future research directions for studying the genetic epidemiology of asthma. Overall, we hope to contribute to a more synthesized knowledge and improved understanding of the previous literature and future potential direction of genetic and epidemiological asthma research.

Study of gene-gene interactions for endophenotypic quantitative traits in Chinese asthmatic children

BACKGROUND

Asthma is a complex disease resulting from interactions between multiple genes and environmental factors. Study of gene-gene interactions could provide insight into the pathophysiology of asthma.

METHODS

We investigated the interactions among 18 single-nucleotide polymorphisms in eight candidate genes for plasma total immunoglobulin E (IgE) concentration and peripheral blood (PB) eosinophil count in 298 Chinese asthmatic children and 175 controls. Generalized multifactor dimensionality reduction and generalized linear model were used to analyze gene-gene interactions for the quantitative traits.

RESULTS

A significant interaction was found between R130Q in IL13 and I50V in IL4RA for plasma total IgE concentration, with a cross-validation (CV) consistency of nine of 10 and a prediction error of 41.1% (P = 0.013). Plasma total IgE concentration was significantly higher in the high-risk than the low-risk groups (P < 0.0001). For PB eosinophil count, significant interaction was found between C-431T in TARC and RsaI_in2 in FCERIB, with a CV consistency of nine of 10 and a prediction error of 40.2% (P = 0.009). PB eosinophil count was significantly higher in the high-risk group than the low-risk groups (P < 0.0001). Generalized linear model also revealed significant gene-gene interaction for the above two endophenotypes with P = 0.013 for plasma total IgE concentration and P = 0.029 for PB eosinophil count respectively.

CONCLUSIONS

Our data suggest significant interactions between IL13 and IL4RA for plasma total IgE concentration, and this is the first report to show significant interaction between TARC and FCERIB for PB eosinophil count in Chinese asthmatic children.

Linkage analysis of a cluster-based quantitative phenotype constructed from pulmonary function test data in 27 multigenerational families with multiple asthmatic members

OBJECTIVE

To identify genes involved in phenotypes that increase one's risk for developing asthma, a complex disease that is likely genetically heterogeneous. Unlike other approaches to locus discovery in the presence of heterogeneity, this method seeks loci that segregate in all or most ascertained families while recognizing that other genes and environmental factors that modify the action of the common gene may vary across families.

METHODS

The method is based on seeking groups of families that differ, between groups, in the way affected individuals express the genotype. Then we use the distance of each individual to the cluster center for his family to define a quantitative trait. This quantitative trait is then subjected to a genome scan using variance components methods.

RESULTS

The method is applied to a data set of 27 multigenerational families with asthma, and a novel locus at 2q33 (at 210 cM) is identified.

CONCLUSIONS

The proposed method has the potential to identify loci near genes that increase risk for asthma related phenotypes. The method could be used for other complex disorders that exhibit locus heterogeneity.

Polymorphism in intron 1 of the interferon-gamma gene influences both serum immunoglobulin E levels and the risk for chronic hepatitis B virus infection in Polynesians

Intron 1 of the interferon-gamma (IFNG) gene contains two polymorphisms. The 12 CA-repeat allele of the +875 IFNGCA microsatellite and the T allele of the +A874T single nucleotide polymorphism (SNP) have been associated with increased in vitro IFNG production and a variety of clinical phenotypes. The purpose of this study was to determine whether these polymorphisms influence total serum IgE levels [tsIgE] and the outcome of a hepatitis B virus (HBV) infection. IFNGCA and +A874T were typed in 186 asthmatics of Niuean ancestry and in Polynesian women with a chronic HBV infection (n = 60) and with natural immunity to the HBV (n = 66). The IFNGCA genotype was associated with [tsIgE] in asthmatic children (n = 51, p = 0.004) but not adults (n = 135, p = 0.87). The data were consistent with a co-dominant influence of the 12 CA-repeat allele on high [tsIgE]. The IFNGCA genotype was also associated with the risk for chronic HBV infection (chi (2) = 11.6, p = 0.003) because of a dominant effect of the 12 CA-repeat allele on developing natural immunity in homozygotes (OR = 5.8, p = 0.003) and heterozygotes (OR = 2.7, p = 0.01). Similar associations were found for the T allele of the +A874T SNP. The possibility that these associations were due to linked alleles in the adjacent 783 bp of the promoter and 3'-untranslated region of the IFNG gene was excluded by direct sequencing. In summary, high-IFNG-producing alleles in intron 1 of the IFNG locus are associated with high [tsIgE] in asthmatic children from Niue and with natural immunity to the HBV in Polynesian women. These findings are consistent with a previous report of an association between +875 IFNGCA and [tsIgE] and provide preliminary evidence of a new association with the outcome of an HBV infection.

Allergen-specific IgG1 provides parsimonious heritability estimates for atopy-associated immune responses to allergens

Although serum total immunoglobulin E (IgE) is generally elevated in atopic conditions, it is an unreliable trait for dissecting the genetic and environmental components contributing to atopic immune responses, because it can be significantly confounded by demographic factors (age, gender, and race) and clinical status (atopic vs nonatopic). Allergen-specific IgE is a discontinuous trait present only in those with sensitivity to allergens. However, all people will produce allergen-specific immunoglobulin G1 (IgG1), which is elevated among those atopically sensitized to specific allergens. We screened 91 Caucasian nuclear families (N = 367) with medical histories of atopic diseases and used variance components analysis to compare heritability estimates for total IgE and IgG1 produced against the common major allergen from house dust mite Dermatophagoides pteronyssinus (Der p 1). An estimate of total IgE heritability was about 48%, although this was significantly confounded by age, gender, and clinical atopic status. In contrast, Der p 1-IgG1 demonstrated a significant inherited component of about 62% that was not influenced by age, gender, or clinical status. For genetic studies of atopic humoral responses, allergen-specific IgG1 may be a more reliable quantitative trait than serum IgE. Moreover, atopy is an inherited deregulation of immune responses to noninfectious antigens, involving antibody isotypes other than IgE.

Key concepts in genetic epidemiology

This article is the first in a series of seven that will provide an overview of central concepts and topical issues in modern genetic epidemiology. In this article, we provide an overall framework for investigating the role of familial factors, especially genetic determinants, in the causation of complex diseases such as diabetes. The discrete steps of the framework to be outlined integrate the biological science underlying modern genetics and the population science underpinning mainstream epidemiology. In keeping with the broad readership of The Lancet and the diverse background of today's genetic epidemiologists, we provide introductory sections to equip readers with basic concepts and vocabulary. We anticipate that, depending on their professional background and specialist knowledge, some readers will wish to skip some of this article.

Familial correlations and inter-relationships of four asthma-associated quantitative phenotypes in 320 French EGEA families ascertained through asthmatic probands

Asthma is a complex disease, associated with biological and physiological phenotypes including immunoglobulin E (IgE) levels, sum of positive skin prick tests to allergens (SPTQ), eosinophil counts (EOS) and percent predicted forced expiratory volume in 1 s (%FEV1). We investigated the patterns of familial correlations and the inter-relationships of these four quantitative phenotypes, using the general class D regressive model, in 320 French EGEA nuclear families ascertained through 204 offspring (set A) and 116 parents (set B). Familial correlations of IgE and SPTQ were consistent with a model including no spouse correlation and equal parent-offspring and sib-sib correlations (rhoPO = rhoSS = 0.25 for IgE and 0.15 for SPTQ), this model being compatible with an additive polygenic model in the whole sample and the two family subsets A and B. Different patterns of familial correlations of EOS and %FEV1 were observed in these two sets. In set A, the best fitting model included no spouse correlation and equality of parent-offspring and sib-sib correlations (rhoPO = rhoSS = 0.14 for EOS and 0.23 for %FEV1). In set B, EOS had only a significant rhoSS of 0.28, while %FEV1 had significant rhoMO of 0.28 and rhoSS of 0.16. Analysis of shared familial determinants between these phenotypes indicated an overlap of at most 30% in rhoFO for IgE and SPTQ and in both rhoFO and rhoMO for IgE and EOS, while determinants of %FEV1 and atopy-related phenotypes appear distinct. These results may have implications for further linkage and association studies with genetic markers.

Clustering patterns of LOD scores for asthma-related phenotypes revealed by a genome-wide screen in 295 French EGEA families

A genome-wide scan for asthma phenotypes was conducted in the whole sample of 295 EGEA families selected through at least one asthmatic subject. In addition to asthma, seven phenotypes involved in the main asthma physiopathological pathways were considered: SPT (positive skin prick test response to at least one of 11 allergens), SPTQ score being the number of positive skin test responses to 11 allergens, Phadiatop (positive specific IgE response to a mixture of allergens), total IgE levels, eosinophils, bronchial responsiveness (BR) to methacholine challenge and %predicted FEV(1). Four regions showed evidence for linkage (P</=0.001): 6q14 for %FEV(1), 12p13 for IgE, 17q22-q24 for SPT and 21q21 for both SPTQ and %FEV(1). Nine other regions indicated smaller linkage signals (0.001<P</=0.005). While most of these regions have been reported by previous asthma and lung function screens, 6q14 appears to be a new region potentially linked to %FEV(1). To determine which of these various asthma phenotypes are more likely to share common genetic determinants, a principal component analysis was applied to the genome-wide LOD scores. This analysis revealed clustering of LODs for asthma, SPT and Phadiatop on one axis and clustering of LODs for %FEV(1), BR and SPTQ on the other, while LODs for IgE and eosinophils appeared to be independent from all other LODs. These results provide new insights into the potential sharing of genetic determinants by asthma-related phenotypes.

An indication of major genes affecting hip and elbow dysplasia in four Finnish dog populations

The aim of the study was to assess the possible existence of major genes influencing hip and elbow dysplasia in four dog populations. A Bayesian segregation analysis was performed separately on each population. In total, 34 140 dogs were included in the data set. Data were analysed with both a polygenic and a mixed inheritance model. Polygenic models included fixed and random environmental effects and additive genetic effects. To apply mixed inheritance models, the effect of a major gene was added to the polygenic models. The major gene was modelled as an autosomal biallelic locus with Mendelian transmission probabilities. Gibbs sampling and a Monte Carlo Markov Chain algorithm were used. The goodness-of-fit of the different models were compared using the residual sum-of-squares. The existence of a major gene was considered likely for hip dysplasia in all the breeds and for elbow dysplasia in one breed. Several procedures were followed to exclude the possible false detection of major genes based on non-normality of data: permuted datasets were analysed, data-transformations were applied, and residuals were judged for normality. Allelic effects at the major gene locus showed nearly to complete dominance, with a recessive, unfavourable allele in both traits. Relatively high estimates of the frequencies of unfavourable alleles in each breed suggest that considerable genetic progress would be possible by selection against major genes. However, the major genes that are possibly affecting hip and elbow dysplasia in these populations will require further study.

Genomic approaches to understanding obstructive sleep apnea

Obstructive sleep apnea (OSA) is an increasingly recognized, common chronic disease in the developed nations and is a complex disease that has high social and economic costs. OSA and its associated 'intermediate' phenotypes-craniofacial structure, body fat distribution and metabolism, and neurological control of the upper airway muscles and of sleep and circadian rhythm-are under a substantial degree of genetic control. Investigating the genetic aetiology of OSA offers a means of better understanding its pathogenesis, with the goal of improving preventive strategies, diagnostic tools and therapies. Molecular studies of OSA itself are in their infancy, but considerable effort and expense has already been expended in attempts to detect genetic loci contributing to OSA-associated intermediate phenotypes, such as obesity. However, many of the fundamental questions relating to the genetic epidemiology of OSA and associated factors remain unanswered. This chapter reviews the current state of knowledge of the genetics of OSA, with a focus on genomic approaches to understanding sleep disorders.

Correcting for nonrandom ascertainment in generalized linear mixed models (GLMMs), fitted using Gibbs sampling

Gibbs sampling-based generalized linear mixed models (GLMMs) provide a convenient and flexible way to extend variance components models for multivariate normally distributed continuous traits to other classes of phenotype. This includes binary traits and right-censored failure times such as age-at-onset data. The approach has applications in many areas of genetic epidemiology. However, the required GLMMs are sensitive to nonrandom ascertainment. In the absence of an appropriate correction for ascertainment, they can exhibit marked positive bias in the estimated grand mean and serious shrinkage in the estimated magnitude of variance components. To compound practical difficulties, it is currently difficult to implement a conventional adjustment for ascertainment because of the need to undertake repeated integration across the distribution of random effects. This is prohibitively slow when it must be repeated at every iteration of the Markov chain Monte Carlo (MCMC) procedure. This paper motivates a correction for ascertainment that is based on sampling random effects rather than integrating across them and can therefore be implemented in a general-purpose Gibbs sampling environment such as WinBUGS. The approach has the characteristic that it returns ascertainment-adjusted parameter estimates that pertain to the true distribution of determinants in the ascertained sample rather than in the general population. The implications of this characteristic are investigated and discussed. This paper extends the utility of Gibbs sampling-based GLMMs to a variety of settings in which family data are ascertained nonrandomly.

Single nucleotide polymorphisms in innate immunity genes: abundant variation and potential role in complex human disease

Under selective pressure from infectious microorganisms, multicellular organisms have evolved immunological defense mechanisms, broadly categorized as innate or adaptive. Recent insights into the complex mechanisms of human innate immunity suggest that genetic variability in genes encoding its components may play a role in the development of asthma and related diseases. As part of a systematic assessment of genetic variability in innate immunity genes, we have thus far have examined 16 genes by resequencing 93 unrelated subjects from three ethnic samples (European American, African American and Hispanic American) and a sample of European American asthmatics. Approaches to discovering and understanding variation and the subsequent implementation of disease association studies are described and illustrated. Although highly conserved across a wide range of species, the innate immune genes we have sequenced demonstrate substantial interindividual variability predominantly in the form of single nucleotide polymorphisms (SNPs). Genetic variation in these genes may play a role in determining susceptibility to a range of common, chronic human diseases which have an inflammatory component. Differences in population history have produced distinctive patterns of SNP allele frequencies, linkage disequilibrium and haplotypes when ethnic groups are compared. These and other factors must be taken into account in the design and analysis of disease association studies.

Genomewide scans of complex human diseases: true linkage is hard to find

Many "complex" human diseases, which involve multiple genetic and environmental determinants, have increased in incidence during the past 2 decades. During the same time period, considerable effort and expense have been expended in whole-genome screens aimed at detection of genetic loci contributing to the susceptibility to complex human diseases. However, the success of positional cloning attempts based on whole-genome screens has been limited, and many of the fundamental questions relating to the genetic epidemiology of complex human disease remain unanswered. Both to review the success of the positional cloning paradigm as applied to complex human disease and to investigate the characteristics of the whole-genome scans undertaken to date, we created a database of 101 studies of complex human disease, which were found by a systematic Medline search (current as of December 2000). We compared these studies, concerning 31 different human complex diseases, with regard to design, methods, and results. The "significance" categorizations proposed by Lander and Kruglyak were used as criteria for the "success" of a study. Most (66.3% [n=67]) of the studies did not show "significant" linkage when the criteria of Lander and Kruglyak (1995) were used, and the results of studies of the same disease were often inconsistent. Our analyses suggest that no single study design consistently produces more-significant results. Multivariate analysis suggests that the only factors independently associated with increased study success are (a) an increase in the number of individuals studied and (b) study of a sample drawn from only one ethnic group. Positional cloning based on whole-genome screens in complex human disease has proved more difficult than originally had been envisioned; detection of linkage and positional cloning of specific disease-susceptibility loci remains elusive.