A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. © 2013 Mechelli et al.

Genome-Wide Association Studies of Asthma in Population-Based Cohorts Confirm Known and Suggested Loci and Identify an Additional Association near HLA

Rationale: Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies. Objectives: To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations. Methods: The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant (P<5x10-8) and three variants reported as suggestive (P<5×10-7). We also searched for novel associations in APCAT (Stage 1) and followed-up the most promising variants in 4,035 asthmatics and 11,251 healthy controls (Stage 2). Finally, we conducted the first genome-wide screen for interactions with smoking or hay fever. Main Results: We observed association in the same direction for all thirteen previously reported variants and nominally replicated ten of them. One variant that was previously suggestive, rs11071559 in RORA, now reaches genome-wide significance when combined with our data (P = 2.4×10-9). We also identified two genome-wide significant associations: rs13408661 near IL1RL1/IL18R1 (PStage1+Stage2 = 1.1x10-9), which is correlated with a variant recently shown to be associated with asthma (rs3771180), and rs9268516 in the HLA region (PStage1+Stage2 = 1.1x10-8), which appears to be independent of previously reported associations in this locus. Finally, we found no strong evidence for gene-environment interactions with smoking or hay fever status. Conclusions: Population-based cohorts with simple asthma phenotypes represent a valuable and largely untapped resource for genetic studies of asthma. © 2012 Ramasamy et al.

Genome-wide association study for radiographic vertebral fractures: A potential role for the 16q24 BMD locus

Vertebral fracture risk is a heritable complex trait. The aim of this study was to identify genetic susceptibility factors for osteoporotic vertebral fractures applying a genome-wide association study (GWAS) approach. The GWAS discovery was based on the Rotterdam Study, a population-based study of elderly Dutch individuals aged >55years; and comprising 329 cases and 2666 controls with radiographic scoring (McCloskey-Kanis) and genetic data. Replication of one top-associated SNP was pursued by de-novo genotyping of 15 independent studies across Europe, the United States, and Australia and one Asian study. Radiographic vertebral fracture assessment was performed using McCloskey-Kanis or Genant semi-quantitative definitions. SNPs were analyzed in relation to vertebral fracture using logistic regression models corrected for age and sex. Fixed effects inverse variance and Han-Eskin alternative random effects meta-analyses were applied. Genome-wide significance was set at p<5×10-8. In the discovery, a SNP (rs11645938) on chromosome 16q24 was associated with the risk for vertebral fractures at p=4.6×10-8. However, the association was not significant across 5720 cases and 21,791 controls from 14 studies. Fixed-effects meta-analysis summary estimate was 1.06 (95% CI: 0.98-1.14; p=0.17), displaying high degree of heterogeneity (I2=57%; Qhet p=0.0006). Under Han-Eskin alternative random effects model the summary effect was significant (p=0.0005). The SNP maps to a region previously found associated with lumbar spine bone mineral density (LS-BMD) in two large meta-analyses from the GEFOS consortium. A false positive association in the GWAS discovery cannot be excluded, yet, the low-powered setting of the discovery and replication settings (appropriate to identify risk effect size >1.25) may still be consistent with an effect size <1.10, more of the type expected in complex traits. Larger effort in studies with standardized phenotype definitions is needed to confirm or reject the involvement of this locus on the risk for vertebral fractures.

VH gene usage in immunoglobulin E responses of seasonal rhinitis patients allergic to grass pollen is oligoclonal and antigen driven

Background: IgE is the pivotal-specific effector molecule of allergic reactions yet it remains unclear whether the elevated production of IgE in atopic individuals is due to superantigen activation of B cell populations, increased antibody class switching to IgE or oligoclonal allergen-driven IgE responses. Objectives: To increase our understanding of the mechanisms driving IgE responses in allergic disease we examined immunoglobulin variable regions of IgE heavy chain transcripts from three patients with seasonal rhinitis due to grass pollen allergy. Methods: Variable domain of heavy chain-epsilon constant domain 1 cDNAs were amplified from peripheral blood using a two-step semi-nested PCR, cloned and sequenced. Results: The VH gene family usage in subject A was broadly based, but there were two clusters of sequences using genes VH 3-9 and 3-11 with unusually low levels of somatic mutations, 0-3%. Subject B repeatedly used VH 1-69 and subject C repeatedly used VH 1-02, 1-46 and 5a genes. Most clones were highly mutated being only 86-95% homologous to their germline VH gene counterparts and somatic mutations were more abundant at the complementarity determining rather than framework regions. Multiple sequence alignment revealed both repeated use of particular VH genes as well as clonal relatedness among clusters of IgE transcripts. Conclusion: In contrast to previous studies we observed no preferred VH gene common to IgE transcripts of the three subjects allergic to grass pollen. Moreover, most of the VH gene characteristics of the IgE transcripts were consistent with oligoclonal antigen-driven IgE responses.

Mixture models of nucleotide sequence evolution that account for heterogeneity in the substitution process across sites and across lineages

Molecular phylogenetic studies of homologous sequences of nucleotides often assume that the underlying evolutionary process was globally stationary, reversible, and homogeneous (SRH), and that a model of evolution with one or more site-specific and time-reversible rate matrices (e.g., the GTR rate matrix) is enough to accurately model the evolution of data over the whole tree. However, an increasing body of data suggests that evolution under these conditions is an exception, rather than the norm. To address this issue, several non-SRH models of molecular evolution have been proposed, but they either ignore heterogeneity in the substitution process across sites (HAS) or assume it can be modeled accurately using the distribution. As an alternative to these models of evolution, we introduce a family of mixture models that approximate HAS without the assumption of an underlying predefined statistical distribution. This family of mixture models is combined with non-SRH models of evolution that account for heterogeneity in the substitution process across lineages (HAL). We also present two algorithms for searching model space and identifying an optimal model of evolution that is less likely to over- or underparameterize the data. The performance of the two new algorithms was evaluated using alignments of nucleotides with 10 000 sites simulated under complex non-SRH conditions on a 25-tipped tree. The algorithms were found to be very successful, identifying the correct HAL model with a 75% success rate (the average success rate for assigning rate matrices to the tree's 48 edges was 99.25%) and, for the correct HAL model, identifying the correct HAS model with a 98% success rate. Finally, parameter estimates obtained under the correct HAL-HAS model were found to be accurate and precise. The merits of our new algorithms were illustrated with an analysis of 42 337 second codon sites extracted from a concatenation of 106 alignments of orthologous genes encoded by the nuclear genomes of Saccharomyces cerevisiae, S. paradoxus, S. mikatae, S. kudriavzevii, S. castellii, S. kluyveri, S. bayanus, and Candida albicans. Our results show that second codon sites in the ancestral genome of these species contained 49.1% invariable sites, 39.6% variable sites belonging to one rate category (V1), and 11.3% variable sites belonging to a second rate category (V2). The ancestral nucleotide content was found to differ markedly across these three sets of sites, and the evolutionary processes operating at the variable sites were found to be non-SRH and best modeled by a combination of eight edge-specific rate matrices (four for V1 and four for V2). The number of substitutions per site at the variable sites also differed markedly, with sites belonging to V1 evolving slower than those belonging to V2 along the lineages separating the seven species of Saccharomyces. Finally, sites belonging to V1 appeared to have ceased evolving along the lineages separating S. cerevisiae, S. paradoxus, S. mikatae, S. kudriavzevii, and S. bayanus, implying that they might have become so selectively constrained that they could be considered invariable sites in these species.

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 determinants of heel bone properties: Genome-wide association meta-analysis and replication in the GEFOS/GENOMOS consortium

Quantitative ultrasound of the heel captures heel bone properties that independently predict fracture risk and, with bone mineral density (BMD) assessed by X-ray (DXA), may be convenient alternatives for evaluating osteoporosis and fracture risk. We performed a meta-analysis of genome-wide association (GWA) studies to assess the genetic determinants of heel broadband ultrasound attenuation (BUA; n 5 14 260), velocity of sound (VOS; n 5 15 514) and BMD (n 5 4566) in 13 discovery cohorts. Independent replication involved seven cohorts with GWA data (in silico n 5 11 452) and new genotyping in 15 cohorts (de novo n 5 24 902). In combined random effects, meta-analysis of the discovery and replication cohorts, nine single nucleotide polymorphisms (SNPs) had genome-wide significant (P < 5 3 108) associations with heel bone properties. Alongside SNPs within or near previously identified osteoporosis susceptibility genes including ESR1 (6q25.1: rs4869739, rs3020331, rs2982552), SPTBN1 (2p16.2: rs11898505), RSPO3 (6q22.33: rs7741021), WNT16 (7q31.31: rs2908007), DKK1 (10q21.1: rs7902708) and GPATCH1 (19q13.11: rs10416265), we identified a new locus on chromosome 11q14.2 (rs597319 close to TMEM135, a gene recently linked to osteoblastogenesis and longevity) significantly associated with both BUA and VOS (P < 8.23 3 1014). In meta-analyses involving 25 cohorts with up to 14 985 fracture cases, six of 10 SNPs associated with heel bone properties at P < 5 3 106 also had the expected direction of association with any fracture (P < 0.05), including threeSNPswithP < 0.005: 6q22.33 (rs7741021), 7q31.31 (rs2908007) and 10q21.1 (rs7902708). In conclusion, thisGWAstudy reveals the effect of several genescommon to central DXA-derivedBMDand heel ultrasound/DXAmeasures and points to anewgenetic locus with potential implications for better understanding of osteoporosis pathophysiology.

Utility of temporal artery biopsy samples for genome-wide analysis of giant cell arteritis

Giant Cell Arteritis (GCA) is the most common vasculitis affecting the elderly. Archived formalin-fixed paraffin-embedded (FFPE) temporal artery biopsy (TAB) specimens potentially represent a valuable resource for large-scale genetic analysis of this disease. FFPE TAB samples were obtained from 12 patients with GCA. Extracted TAB DNA was assessed by real time PCR before restoration using the Illumina HD FFPE Restore Kit. Paired FFPE-blood samples were genotyped on the Illumina OmniExpress FFPE microarray. The FFPE samples that passed stringent quality control measures had a mean genotyping success of >97%. When compared with their matching peripheral blood DNA, the mean discordant heterozygote and homozygote single nucleotide polymorphisms calls were 0.0028 and 0.0003, respectively, which is within the accepted tolerance of reproducibility. This work demonstrates that it is possible to successfully obtain high-quality microarray-based genotypes FFPE TAB samples and that this data is similar to that obtained from peripheral blood.

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.

Single nucleotide polymorphisms in clinics: Fantasy or reality for cancer?

Single nucleotide polymorphisms (SNPs) have been classically used for dissecting various human complex disorders using candidate gene studies. During the last decade, large scale SNP analysis i.e. genome-wide association studies (GWAS) have provided an agnostic approach to identify possible genetic loci associated with heterogeneous disease such as cancer susceptibility, prognosis of survival or drug response. Further, the advent of new technologies, including microarray based genotyping as well as high throughput next generation sequencing has opened new avenues for SNPs to be used in clinical practice. It is speculated that the utility of SNPs to understand the mechanisms, biology of variable drug response and ultimately treatment individualization based on the individual’s genome composition will be indispensable in the near future. In the current review, we discuss the advantages and disadvantages of the clinical utility of genetic variants in disease risk-prediction, prognosis, clinical outcome and pharmacogenomics. The lessons and challenges for the utility of SNP based biomarkers are also discussed, including the need for additional functional validation studies.

Meta-analysis of genome-wide studies identifies MEF2C SNPs associated with bone mineral density at forearm

Background Forearm fractures affect 1.7 million individuals worldwide each year and most occur earlier in life than hip fractures. While the heritability of forearm bone mineral density (BMD) and fracture is high, their genetic determinants are largely unknown. Aim To identify genetic variants associated with forearm BMD and forearm fractures. Methods BMD at distal radius, measured by dualenergy x-ray absorptiometry, was tested for association with common genetic variants. We conducted a metaanalysis of genome-wide association studies for BMD in 5866 subjects of European descent and then selected the variants for replication in 715 Mexican American samples. Gene-based association was carried out to supplement the single-nucleotide polymorphism (SNP) association test. We then tested the BMD-associated SNPs for association with forearm fracture in 2023 cases and 3740 controls. Results We found that five SNPs in the introns of MEF2C were associated with forearm BMD at a genome-wide significance level (p<5×10-8) in meta-analysis (lead SNP, rs11951031[T] -0.20 SDs per allele, p=9.01×10-9). The gene-based association test suggested an association between MEF2C and forearm BMD ( p=0.003). The association between MEF2C variants and risk of fracture did not achieve statistical significance (SNP rs12521522[A]: OR=1.14 (95% CI 0.92 to 1.35), p=0.14). Meta-analysis also revealed two genome-wide suggestive loci at CTNNA2 and 6q23.2. Conclusions These findings demonstrate that variants at MEF2C were associated with forearm BMD, implicating this gene in the determination of BMD at forearm.

Genome-wide association study of intraocular pressure identifies the GLCCI1/ICA1 region as a glaucoma susceptibility locus

To discover quantitative trait loci for intraocular pressure, amajor risk factor for glaucoma and the only modifiable one,weperformed agenome-wide association studyonadiscoverycohort of2175individualsfromSydney, Australia. We found a novel association between intraocular pressure and a common variant at 7p21 near to GLCCI1 and ICA1. The findings in this region were confirmed through two UK replication cohorts totalling 4866 individuals (rs59072263, Pcombined = 1.10 × 10-8). A copy of the G allele at this SNP is associated with an increase in mean IOP of 0.45 mmHg (95%CI = 0.30-0.61 mmHg). These results lend support to the implication of vesicle trafficking and glucocorticoid inducibility pathways in the determination of intraocular pressure and in the pathogenesis of primary open-angle glaucoma.

Genome-wide association analysis identifies 13 new risk loci for schizophrenia

Schizophrenia is an idiopathic mental disorder with a heritable component and a substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases and 6,243 controls) followed by meta-Analysis with previous schizophrenia GWAS (8,832 cases and 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls and 581 parent-offspring trios). We identified 22 loci associated at genome-wide significance; 13 of these are new, and 1 was previously implicated in bipolar disorder. Examination of candidate genes at these loci suggests the involvement of neuronal calcium signaling. We estimate that 8,300 independent, mostly common SNPs (95% credible interval of 6,300-10,200 SNPs) contribute to risk for schizophrenia and that these collectively account for at least 32% of the variance in liability. Common genetic variation has an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this disorder.

Comparison of the performance of two commercial genome-wide association study genotyping platforms in Han Chinese samples

Most genome-wide association studies to date have been performed in populations of European descent, but there is increasing interest in expanding these studies to other populations. The performance of genotyping chips in Asian populations is not well established. Therefore, we sought to test the performance of widely used fixed-marker, genome-wide association studies chips in the Han Chinese population. Non-HapMap Chinese samples (n = 396) were genotyped using the Illumina OmniExpress and Affymetrix 6.0 platforms, whereas a subset also were genotyped using the Immunochip. Genotyped markers from the Affymetrix 6.0 and Illumina OmniExpress were used for full genome imputation based on the HapMap 2 JPT+CHB (Japanese from Tokyo, Japan and Chinese from Beijing, China) reference panel. The concordance between markers genotypes for the three platforms was very high whether directly genotyped or genotyped and imputed single nucleotide polymorphisms (SNPs; .99.8% for directly genotyped and .99.5% for genotyped and imputed SNPs, respectively) were compared. The OmniExpress chip data enabled more SNPs to be imputed, particularly SNPs with minor allele frequency .5%. The OmniExpress chip achieved better coverage of HapMap SNPs than the Affymetrix 6.0 chip (73.6% vs. 65.9%, respectively, for minor allele frequency .5%). The Affymetrix 6.0 and Illumina OmniExpress chip have similar genotyping accuracy and provide similar accuracy of imputed SNPs. The OmniExpress chip however provides better coverage of Asian HapMap SNPs, although its coverage of HapMap SNPs is moderate. © 2013 Jiang et al.

Genome-wide association studies

Genome-wide association studies (GWAS) are a powerful hypothesis-free tool for the dissection of susceptibility to common heritable human diseases, including osteoporosis. To date, more than 2000 loci for common human diseases have been identified by GWAS. Success using the GWAS model depends on genetic risk being determined by shared stretches of DNA carried with different frequencies in cases and controls, inherited from ancient ancestors, termed the “common disease–common variant” hypothesis. Not all disease risk is caused by common variants, however, and thus GWAS will not detect all variants involved. Successful GWAS performance requires careful quality control, especially as the effect sizes under study are modest, and there are multiple potential sources of error. Conservative interpretation, use of stringent significance thresholds, and replication in independent cohorts are required to ensure results are robust. Despite these challenging parameters, much has been learnt from GWAS and, as the approach matures and is modified to identify a wider range of variants, significantly more will be learnt about the etiopathogenesis of common diseases such as osteoporosis.