Asthma is a complex disease that has genetic and environmental causes. The genetic factors associated with susceptibility to asthma remain largely unknown.
We carried out a genomewide association study involving children with asthma. The sample included 793 North American children of European ancestry with persistent asthma who required daily inhaled glucocorticoid therapy and 1988 matched controls (the discovery set). We also tested for genomewide association in an independent cohort of 917 persons of European ancestry who had asthma and 1546 matched controls (the replication set). Finally, we tested for an association between 20 single-nucleotide polymorphisms (SNPs) at chromosome 1q31 and asthma in 1667 North American children of African ancestry who had asthma and 2045 ancestrally matched controls.
In our meta-analysis of all samples from persons of European ancestry, we observed an association, with genomewide significance, between asthma and SNPs at the previously reported locus on 17q21 and an additional eight SNPs at a novel locus on 1q31. The SNP most strongly associated with asthma was rs2786098 (P=8.55x10(-9)). We observed replication of the association of asthma with SNP rs2786098 in the independent series of persons of European ancestry (combined P=9.3x10(-11)). The alternative allele of each of the eight SNPs on chromosome 1q31 was strongly associated with asthma in the children of African ancestry (P=1.6x10(-13) for the comparison across all samples). The 1q31 locus contains the 1q31 locus contains DENND1B, a gene expressed by natural killer cells and dendritic cells. DENND1B protein is predicted to interact with the tumor necrosis factor α receptor [corrected].
We have identified a locus containing DENND1B on chromosome 1q31.3 that is associated with susceptibility to asthma.
"These approaches are best suited to identify common variants within the population that yields a modest risk for a specific disease. GWAS has aided in elucidating some of the heritability of various complex diseases by identifying genetic variants associated with diseases such as asthma [6, 7], Parkinson's disease [8, 9], and autism . Indeed, GWAS has been essential in determining the key underlying genetic components associated with type 2 diabetes (T2D). "
[Show abstract][Hide abstract] ABSTRACT: Elucidating the underlying genetic variations influencing various complex diseases is one of the major challenges currently facing clinical genetic research. Although these variations are often difficult to uncover, approaches such as genome-wide association studies (GWASs) have been successful at finding statistically significant associations between specific genomic loci and disease susceptibility. GWAS has been especially successful in elucidating genetic variants that influence type 2 diabetes (T2D) and obesity/body mass index (BMI). Specifically, several GWASs have confirmed that a variant in transcription factor 7-like 2 (TCF7L2) confers risk for T2D, while a variant in fat mass and obesity-associated protein (FTO) confers risk for obesity/BMI; indeed both of these signals are considered the most statistically associated loci discovered for these respective traits to date. The discovery of these two key loci in this context has been invaluable for providing novel insight into mechanisms of heritability and disease pathogenesis. As follow-up studies of TCF7L2 and FTO have typically lead the way in how to follow up a GWAS discovery, we outline what has been learned from such investigations and how they have implications for the myriad of other loci that have been subsequently reported in this disease context.
International Journal of Endocrinology 02/2014; 2014(17):769671. DOI:10.1155/2014/769671 · 1.95 Impact Factor
"GWAS exploring the genetic basis of disease in African ancestry populations have identified several genes associated with asthma susceptibility (Table 2). GWAS have found that different genetics variants were associated with asthma susceptibility in children of European and African ancestry suggesting different biological mechanisms could be at the basis of asthma susceptibility in these diverse populations [54,55]. "
[Show abstract][Hide abstract] ABSTRACT: Traditionally, biomedical research endeavors in low to middle resources countries have focused on communicable diseases. However, data collected over the past 20 years by the World Health Organization (WHO) show a significant increase in the number of people suffering from non-communicable diseases (e.g. heart disease, diabetes, cancer and pulmonary diseases). Within the coming years, WHO predicts significant decreases in communicable diseases while non-communicable diseases are expected to double in low and middle income countries in sub-Saharan Africa. The predicted increase in the non-communicable diseases population could be economically burdensome for the basic healthcare infrastructure of countries that lack resources to address this emerging disease burden. Biomedical research could stimulate development of healthcare and biomedical infrastructure. If this development is sustainable, it provides an opportunity to alleviate the burden of both communicable and non-communicable diseases through diagnosis, prevention and treatment. In this paper, we discuss how research using biomedical technology, especially genomics, has produced data that enhances the understanding and treatment of both communicable and non-communicable diseases in sub-Saharan Africa. We further discuss how scientific development can provide opportunities to pursue research areas responsive to the African populations. We limit our discussion to biomedical research in the areas of genomics due to its substantial impact on the scientific community in recent years however, we also recognize that targeted investments in other scientific disciplines could also foster further development in African countries.
Globalization and Health 10/2013; 9(1):50. DOI:10.1186/1744-8603-9-50 · 2.25 Impact Factor
"GWAS have been successful in identifying susceptibility genes for asthma through the use of large scale population cohorts and replication approaches [2-7]. However, there remains a need to determine the contribution of these polymorphisms to clinically relevant endpoints in asthma as opposed to disease diagnosis. "
[Show abstract][Hide abstract] ABSTRACT: Asthma genome-wide association studies (GWAS) have identified several asthma susceptibility genes with confidence; however the relative contribution of these genetic variants or single nucleotide polymorphisms (SNPs) to clinical endpoints (as opposed to disease diagnosis) remains largely unknown. Thus the aim of this study was to firstly bridge this gap in knowledge and secondly investigate whether these SNPs or those that are in linkage disequilibrium are likely to be functional candidates with respect to regulation of gene expression, using reported data from the ENCODE project.
Eleven of the key SNPs identified in eight loci from recent asthma GWAS were evaluated for association with asthma and clinical outcomes including percent predicted FEV1, bronchial hyperresponsiveness (BHR) to methacholine, severity defined by British Thoracic Society steps and positive response to skin prick test using the family based association test additive model in a well characterised UK cohort consisting of 370 families with at least two asthmatic children.
GSDMB SNP rs2305480 (Ser311Pro) was associated with asthma diagnosis (p = 8.9x10-4), BHR (p = 8.2x10-4) and severity (p = 1.5x10-4) with supporting evidence from a second GSDMB SNP rs11078927 (intronic). SNPs evaluated in IL33, IL18R1, IL1RL1, SMAD3, IL2RB, PDE4D, CRB1 and RAD50 did not show association with any phenotype tested when corrected for multiple testing. Analysis using ENCODE data provide further insight into the functional relevance of these SNPs.
Our results provide further support for the role of GSDMB SNPs in determining multiple asthma related phenotypes in childhood asthma including associations with lung function and disease severity.
BMC Medical Genetics 09/2013; 14(1):100. DOI:10.1186/1471-2350-14-100 · 2.08 Impact Factor
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