Association of a disintegrin and metalloprotease 33 (ADAM33) gene polymorphisms with the risk of COPD: An updated meta-analysis of 2,644 cases and 4,804 controls

A series of observational studies have been made to investigate the association of the ADAM33 gene polymorphisms with the risk of COPD, but their results were conflicting. Therefore, we performed an updated meta-analysis to quantitatively summarize the associations of ADAM33 gene polymorphisms with the risk of COPD. Thirteen case–control studies referring to nine SNPs were identified: V4 (rs2787094), T+1 (rs2280089), T2 (rs2280090), T1 (rs2280091), S2 (rs528557), S1 (rs3918396), Q−1 (rs612709), F+1 (rs511898) and ST+5 (rs597980). A dominant model (AA+Aa vs. aa), recessive model (AA vs. Aa+aa), additive model (AA vs. aa) and allelic model (A vs. a) were used to evaluate the association of ADAM33 polymorphism with the risk of COPD. The results indicated that significant associations were found for ADAM33 T1, T2, S1, Q−1, F+1 and ST+5 polymorphisms associated with the risk of COPD in different populations. However, no significant associations were found for V4, T+1 and S2 polymorphisms with the risk of COPD in all genetic models, even in the subgroup analysis by ethnicity. This meta-analysis provided evidence that the ADAM33 T1, T2, S1, Q−1, F+1 and ST+5 six locus polymorphisms association with the risk of COPD. Furthermore, T2, Q−1 and ST+5 indicated an association with the risk of COPD in the European populations, whereas T1, T2, S1, F+1 and Q−1 indicated an association with the risk of COPD in the Asian populations.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

Genome-wide association study for sight-threatening diabetic retinopathy reveals association with genetic variation near the GRB2 gene

Aims/hypothesis Diabetic retinopathy is a serious complication of diabetes mellitus and can lead to blindness. A genetic component, in addition to traditional risk factors, has been well described although strong genetic factors have not yet been identified. Here, we aimed to identify novel genetic risk factors for sight-threatening diabetic retinopathy using a genome-wide association study. Methods Retinopathy was assessed in white Australians with type 2 diabetes mellitus. Genome-wide association analysis was conducted for comparison of cases of sight-threatening diabetic retinopathy (n = 336) with diabetic controls with no retinopathy (n = 508). Top ranking single nucleotide polymorphisms were typed in a type 2 diabetes replication cohort, a type 1 diabetes cohort and an Indian type 2 cohort. A mouse model of proliferative retinopathy was used to assess differential expression of the nearby candidate gene GRB2 by immunohistochemistry and quantitative western blot. Results The top ranked variant was rs3805931 with p = 2.66 × 10−7, but no association was found in the replication cohort. Only rs9896052 (p = 6.55 × 10−5) was associated with sight-threatening diabetic retinopathy in both the type 2 (p = 0.035) and the type 1 (p = 0.041) replication cohorts, as well as in the Indian cohort (p = 0.016). The study-wide meta-analysis reached genome-wide significance (p = 4.15 × 10−8). The GRB2 gene is located downstream of this variant and a mouse model of retinopathy showed increased GRB2 expression in the retina. Conclusions/interpretation Genetic variation near GRB2 on chromosome 17q25.1 is associated with sight-threatening diabetic retinopathy. Several genes in this region are promising candidates and in particular GRB2 is upregulated during retinal stress and neovascularisation.

Genetic associations and functional characterization of M1 aminopeptidases and immune-mediated diseases

Endosplasmic reticulum aminopeptidase 1 (ERAP1), endoplasmic reticulum aminopeptidase 2 (ERAP2) and puromycin-sensitive aminopeptidase (NPEPPS) are key zinc metallopeptidases that belong to the oxytocinase subfamily of M1 aminopeptidase family. NPEPPS catalyzes the processing of proteosome-derived peptide repertoire followed by trimming of antigenic peptides by ERAP1 and ERAP2 for presentation on major histocompatibility complex (MHC) Class I molecules. A series of genome-wide association studies have demonstrated associations of these aminopeptidases with a range of immune-mediated diseases such as ankylosing spondylitis, psoriasis, Behçet's disease, inflammatory bowel disease and type I diabetes, and significantly, genetic interaction between some aminopeptidases and HLA Class I loci with which these diseases are strongly associated. In this review, we highlight the current state of understanding of the genetic associations of this class of genes, their functional role in disease, and potential as therapeutic targets.

Genome-wide association analysis identifies 11 risk variants associated with the asthma with hay fever phenotype

Background To date, no genome-wide association study (GWAS) has considered the combined phenotype of asthma with hay fever. Previous analyses of family data from the Tasmanian Longitudinal Health Study provide evidence that this phenotype has a stronger genetic cause than asthma without hay fever. Objective We sought to perform a GWAS of asthma with hay fever to identify variants associated with having both diseases. Methods We performed a meta-analysis of GWASs comparing persons with both physician-diagnosed asthma and hay fever (n = 6,685) with persons with neither disease (n = 14,091). Results At genome-wide significance, we identified 11 independent variants associated with the risk of having asthma with hay fever, including 2 associations reaching this level of significance with allergic disease for the first time: ZBTB10 (rs7009110; odds ratio [OR], 1.14; P = 4 × 10−9) and CLEC16A (rs62026376; OR, 1.17; P = 1 × 10−8). The rs62026376:C allele associated with increased asthma with hay fever risk has been found to be associated also with decreased expression of the nearby DEXI gene in monocytes. The 11 variants were associated with the risk of asthma and hay fever separately, but the estimated associations with the individual phenotypes were weaker than with the combined asthma with hay fever phenotype. A variant near LRRC32 was a stronger risk factor for hay fever than for asthma, whereas the reverse was observed for variants in/near GSDMA and TSLP. Single nucleotide polymorphisms with suggestive evidence for association with asthma with hay fever risk included rs41295115 near IL2RA (OR, 1.28; P = 5 × 10−7) and rs76043829 in TNS1 (OR, 1.23; P = 2 × 10−6). Conclusion By focusing on the combined phenotype of asthma with hay fever, variants associated with the risk of allergic disease can be identified with greater efficiency.

The correlation between reading and mathematics ability at age twelve has a substantial genetic component

Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children’s ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child’s cognitive abilities at age twelve.

Genetic insights into common pathways and complex relationships among iImmune-mediated diseases

Shared aetiopathogenic factors among immune-mediated diseases have long been suggested by their co-familiality and co-occurrence, and molecular support has been provided by analysis of human leukocyte antigen (HLA) haplotypes and genome-wide association studies. The interrelationships can now be better appreciated following the genotyping of large immune disease sample sets on a shared SNP array: the 'Immunochip'. Here, we systematically analyse loci shared among major immune-mediated diseases. This reveals that several diseases share multiple susceptibility loci, but there are many nuances. The most associated variant at a given locus frequently differs and, even when shared, the same allele often has opposite associations. Interestingly, risk alleles conferring the largest effect sizes are usually disease-specific. These factors help to explain why early evidence of extensive 'sharing' is not always reflected in epidemiological overlap. © 2013 Macmillan Publishers Limited. All rights reserved.

Genome-wide association study to identify genetic determinants of severe asthma

Background: The genetic basis for developing asthma has been extensively studied. However, association studies to date have mostly focused on mild to moderate disease and genetic risk factors for severe asthma remain unclear. Objective: To identify common genetic variants affecting susceptibility to severe asthma. Methods: A genome-wide association study was undertaken in 933 European ancestry individuals with severe asthma based on Global Initiative for Asthma (GINA) criteria 3 or above and 3346 clean controls. After standard quality control measures, the association of 480 889 genotyped single nucleotide polymorphisms (SNPs) was tested. To improve the resolution of the association signals identified, non-genotyped SNPs were imputed in these regions using a dense reference panel of SNP genotypes from the 1000 Genomes Project. Then replication of SNPs of interest was undertaken in a further 231 cases and 1345 controls and a meta-analysis was performed to combine the results across studies. Results: An association was confirmed in subjects with severe asthma of loci previously identified for association with mild to moderate asthma. The strongest evidence was seen for the ORMDL3/GSDMB locus on chromosome 17q12-21 (rs4794820, p=1.03×10 (-8)following meta-analysis) meeting genome-wide significance. Strong evidence was also found for the IL1RL1/IL18R1 locus on 2q12 (rs9807989, p=5.59×10 (-8) following meta-analysis) just below this threshold. No novel loci for susceptibility to severe asthma met strict criteria for genome-wide significance. Conclusions: The largest genome-wide association study of severe asthma to date was carried out and strong evidence found for the association of two previously identified asthma susceptibility loci in patients with severe disease. A number of novel regions with suggestive evidence were also identified warranting further study.

Fine mapping and replication of genetic risk Loci in primary sclerosing cholangitis

Background and aims. Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease characterized by progressive inflammation and fibrosis of the bile ducts eventually leading to biliary cirrhosis. Recent genetic studies in PSC have identified associations at 2q13, 2q35, 3p21, 4q27, 13q31 and suggestive association at 10p15. The aim of this study was to further characterize and refine the genetic architecture of PSC. Methods. We analyzed previously reported associated SNPs at four of these non-HLA loci and 59 SNPs tagging the IL-2/IL-21 (4q27) and IL2RA (10p15) loci in 992 UK PSC cases and 5162 healthy UK controls. Results. The most associated SNPs identified were rs3197999 (3p21 (MST1), p = 1.9 × 10 -6, OR A vs G = 1.28, 95% CI (1.16-1.42)); rs4147359 (10p15 (IL2RA), p = 2.6 × 10 -4, OR A vs G = 1.20, 95% CI (1.09-1.33)) and rs12511287 (4q27 (IL-2/IL-21), p = 3.0 × 10 -4, OR A vs T = 1.21, 95% CI (1.09-1.35)). In addition, we performed a meta-analysis for selected SNPs using published summary statistics from recent studies. We observed genome-wide significance for rs3197999 (3p21 (MST1), P combined = 3.8 × 10 -12) and rs4147359 (10p15 (IL2RA), P combined = 1.5 × 10 -8). Conclusion. We have for the first time confirmed the association of PSC with genetic variants at 10p15 (IL2RA) locus at genome-wide significance and replicated the associations at MST1 and IL-2/IL-21 loci in a large homogeneous UK population. These results strongly implicate the role of IL-2/IL2RA pathway in PSC and provide further confirmation of MST1 association. © Informa Healthcare.

Using genome-Wwide complex trait analysis to quantify 'missing heritability' in Parkinson's disease

Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17-38, P = 8.08E - 08) phenotypic variance associated with all types of PD, 15% (95% CI -0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17-44, P = 1.34E - 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered. © Published by Oxford University Press 2012.

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis. © 2011 Macmillan Publishers Limited. All rights reserved.

The multiple sclerosis whole blood mRNA transcriptome and genetic associations indicate dysregulation of specific T cell pathways in pathogenesis

Multiple sclerosis (MS) is an autoimmune disease with a genetic component, caused at least in part by aberrant lymphocyte activity. The whole blood mRNA transcriptome was measured for 99 untreated MS patients: 43 primary progressive MS, 20 secondary progressive MS, 36 relapsing remitting MS and 45 age-matched healthy controls. The ANZgene Multiple Sclerosis Genetics Consortium genotyped more than 300 000 SNPs for 115 of these samples. Transcription from genes on translational regulation, oxidative phosphorylation, immune synapse and antigen presentation pathways was markedly increased in all forms of MS. Expression of genes tagging T cells was also upregulated (P < 10-12) in MS. A T cell gene signature predicts disease state with a concordance index of 0.79 with age and gender as co-variables, but the signature is not associated with clinical course or disability. The ANZgene genome wide association screen identified two novel regions with genome wide significance: one encoding the T cell co-stimulatory molecule, CD40; the other a region on chromosome 12q13-14. The CD40 haplotype associated with increased MS susceptibility has decreased gene expression in MS (P < 0.0007). The second MS susceptibility region includes 17 genes on 12q13-14 in tight linkage disequilibrium. Of these, only 13 are expressed in leukocytes, and of these the expression of one, FAM119B, is much lower in the susceptibility haplotype (P tdthomlt; 10-14). Overall, these data indicate dysregulation of T cells can be detected in the whole blood of untreated MS patients, and supports targeting of activated T cells in therapy for all forms of MS.

Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture

Bone mineral density (BMD) is the most widely used predictor of fracture risk. We performed the largest meta-analysis to date on lumbar spine and femoral neck BMD, including 17 genome-wide association studies and 32,961 individuals of European and east Asian ancestry. We tested the top BMD-associated markers for replication in 50,933 independent subjects and for association with risk of low-trauma fracture in 31,016 individuals with a history of fracture (cases) and 102,444 controls. We identified 56 loci (32 new) associated with BMD at genome-wide significance (P < 5 × 10−8). Several of these factors cluster within the RANK-RANKL-OPG, mesenchymal stem cell differentiation, endochondral ossification and Wnt signaling pathways. However, we also discovered loci that were localized to genes not known to have a role in bone biology. Fourteen BMD-associated loci were also associated with fracture risk (P < 5 × 10−4, Bonferroni corrected), of which six reached P < 5 × 10−8, including at 18p11.21 (FAM210A), 7q21.3 (SLC25A13), 11q13.2 (LRP5), 4q22.1 (MEPE), 2p16.2 (SPTBN1) and 10q21.1 (DKK1). These findings shed light on the genetic architecture and pathophysiological mechanisms underlying BMD variation and fracture susceptibility.

Association between the interleukin 23 receptor and ankylosing spondylitis is confirmed by a new UK case-control study and meta-analysis of published series

Objectives. It has been shown previously that IL-23R variants are associated with AS. We conducted an extended analysis in the UK population and a meta-analysis with the previously published studies, in order to refine these IL-23R associations with AS. Methods. The UK case-control study included 730 new cases and 1331 healthy controls. In the extended study, the 730 cases were combined with 1088 published cases. Allelic associations were analysed using contingency tables. In the meta-analysis, 3482 cases and 3150 controls from four different published studies and the new UK cases were combined. DerSimonian-Laird test was used to calculate random effects pooled odds ratios (ORs). Results. In the UK case-control study with new cases, four of the eight SNPs showed significant associations, whereas in the extended UK study, seven of the eight IL-23R SNPs showed significant associations (P < 0.05) with AS, maximal with rs11209032 (P < 10-5, OR 1.3), when cases with IBD and/or psoriasis were excluded. The meta-analysis showed significant associations with all eight SNPs; the strongest associations were again seen not only with rs11209032 (P = 4.06 × 10-9, OR ∼1.2) but also with rs11209026 (P < 10-10, OR ∼0.6). Conclusions. IL-23R polymorphisms are clearly associated with AS, but the primary causal association(s) is(are) still not established. These polymorphisms could contribute either increased or decreased susceptibility to AS; functional studies will be required for their full evaluation. Additionally, observed stronger associations with SNPs rs11209026 and rs11465804 upon exclusion of IBD and/or psoriasis cases may represent an independent association with AS. © The Author 2009. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved.

Investigating the genetic association between ERAP1 and ankylosing spondylitis

A strong association between ERAP1 and ankylosing spondylitis (AS) was recently identified by the Wellcome Trust Case Control Consortium and the Australo-Anglo-American Spondylitis Consortium (WTCCC-TASC) study. ERAP1 is highly polymorphic with strong linkage disequilibrium evident across the gene. We therefore conducted a series of experiments to try to identify the primary genetic association(s) with ERAP1. We replicated the original associations in an independent set of 730 patients and 1021 controls, resequenced ERAP1 to define the full extent of coding polymorphisms and tested all variants in additional association studies. The genetic association with ERAP1 was independently confirmed; the strongest association was with rs30187 in the replication set (P = 3.4 × 103). When the data were combined with the original WTCCC-TASC study the strongest association was with rs27044 (P = 1.1 × 10-9). We identified 33 sequence polymorphisms in ERAP1, including three novel and eight known non-synonymous polymorphisms. We report several new associations between AS and polymorphisms distributed across ERAP1 from the extended case-control study, the most significant of which was with rs27434 (P = 4.7 × 10-7). Regression analysis failed to identify a primary association clearly; we therefore used data from HapMap to impute genotypes for an additional 205 non-coding SNPs located within and adjacent to ERAP1. A number of highly significant associations (P < 5 × 10-9) were identified in regulatory sequences which are good candidates for causing susceptibility to AS, possibly by regulating ERAP1 expression. © 2009 The Author(s).