SNP‐based heritability and genetic architecture of tarsal osteochondrosis in North American Standardbred horses

Osteochondrosis is a common developmental orthopedic disease characterized by a failure of endochondral ossification. Standardbred horses are recognized as being predisposed to tarsal osteochondrosis. Prior heritability estimates for tarsal osteochondrosis in European Standardbreds and related trotting breeds have been based on pedigree data and range from 17–29%. Here, we report on genetic architecture and heritability based on high‐density genotyping data in a cohort of North American Standardbreds (n = 479) stringently phenotyped for tarsal osteochondrosis. Whole‐genome array genotyping data were imputed to ~2 million single nucleotide polymorphisms (SNPs). SNP‐based heritability of osteochondrosis in this population was explained by 2326 SNPs. The majority of these SNPs (86.6%) had small effects, whereas fewer SNPs had moderate or large effects (10% and 2.9% respectively), which is consistent with a polygenic/complex disease. Heritability was estimated at 0.24 ± 0.16 using two methods of restricted maximum likelihood analysis, as implemented in gcta (with and without a weighted relatedness matrix) and ldak software. Estimates were validated using bootstrapping. Heritability estimates were within the range previously reported and suggest that osteochondrosis is moderately heritable but that a significant portion of disease risk is due to environmental factors and/or genotype × environment interactions. Future identification of the genes/variants that have the most impact on disease risk may allow early recognition of high‐risk individuals.     

Interactions of the eNOS and ACE genes and cigarette smoking in chronic obstructive pulmonary disease

BackgroundChronic obstructive pulmonary disease (COPD) is a complex disorder with unexplained heritability. Interactions of genetic and environmental factors are thought to be crucial in COPD. So, we aim to examine interactions of the endothelial nitric oxide synthase (eNOS) and angiotensin converting enzyme (ACE) genes and cigarette smoking in COPD.MethodsThe eNOS G 894T and ACE ID variants were analyzed in 122 COPD patients and 200 controls from Serbia. The effect of the variants on COPD was assessed by logistic regression. Interactions between eNOS, ACE and cigarette smoking in COPD were evaluated using a case-control model. Interaction between the genes was analyzed in silico.ResultsNo effect of the eNOS G 894T and ACE ID variants on COPD was found in our study. Gene-gene interaction between the eN OS T T and A CE D was identified (p=0.033) in COPD. The interaction is realized within the complex network of biochemical pathways. Gene-environment interactions between the eNOS T and cigarette smoking (p=0.013), and the ACE II and cigarette smoking (p=0.009) were detected in COPD in our study.ConclusionsThis is the first research to reveal interactions of the eNOS and ACE genes and cigarette smoking in COPD progressing our understanding of COPD heritability and contributing to the development of appropriate treatments     

CXCL5 polymorphisms are associated with variable blood pressure in cardiovascular disease-free adults

Age-related macular degeneration (AMD) is a complex and multifaceted disease involving contributions from both genetic and environmental influences. Previous work exploring the genetic contributions of AMD has implicated numerous genomic regions and a variety of candidate genes as modulators of AMD susceptibility. Nevertheless, much of this work has revolved around single-nucleotide polymorphisms (SNPs), and it is apparent that a significant portion of the heritability of AMD cannot be explained through these mechanisms. In this review, we consider the role of common variants, rare variants, copy number variations, epigenetics, microRNAs, and mitochondrial genetics in AMD. Copy number variations in regulators of complement activation genes (CFHR1 and CFHR3) and glutathione S transferase genes (GSTM1 and GSTT1) have been associated with AMD, and several additional loci have been identified as regions of potential interest but require further evaluation. MicroRNA dysregulation has been linked to the retinal pigment epithelium degeneration in geographic atrophy, ocular neovascularization, and oxidative stress, all of which are hallmarks in the pathogenesis of AMD. Certain mitochondrial DNA haplogroups and SNPs in mitochondrially encoded NADH dehydrogenase genes have also been associated with AMD. The role of these additional mechanisms remains only partly understood, but the importance of their further investigation is clear to elucidate more completely the genetic basis of AMD.     

How Many Genetic Variants Remain to Be Discovered?

A great majority of genetic markers discovered in recent genome-wide association studies have small effect sizes, and they explain only a small fraction of the genetic contribution to the diseases. How many more variants can we expect to discover and what study sizes are needed? We derive the connection between the cumulative risk of the SNP variants to the latent genetic risk model and heritability of the disease. We determine the sample size required for case-control studies in order to achieve a certain expected number of discoveries in a collection of most significant SNPs. Assuming similar allele frequencies and effect sizes of the currently validated SNPs, complex phenotypes such as type-2 diabetes would need approximately 800 variants to explain its 40% heritability. Much smaller numbers of variants are needed if we assume rare-variants but higher penetrance models. We estimate that up to 50,000 cases and an equal number of controls are needed to discover 800 common low-penetrant variants among the top 5000 SNPs. Under common and rare low-penetrance models, the very large studies required to discover the numerous variants are probably at the limit of practical feasibility. Under rare-variant with medium- to high-penetrance models (odds-ratios between 1.6 and 4.0), studies comparable in size to many existing studies are adequate provided the genotyping technology can interrogate more and rarer variants.     

Implication of genetic variants near TMEM18, BCDIN3D/FAIM2, and MC4R with coronary artery disease and obesity in Chinese: a angiography-based study

Coronary artery disease (CAD) is multifactorial disease which occurs as a result of the interaction of genetic and environmental factors. Obesity is an independent risk factor for cardiovascular disease. Recent genome-wide association studies have identified several genes associated with obesity in Europeans. We wondered whether these genetic variants were associated with CAD. Three single nucleotide polymorphisms (SNPs) rs7561317 near TMEM18, rs7138803 near BCDIN3D/FAIM2 and rs12970134 near MC4R were examined in 930 Han Chinese subjects based on coronary angiography, using polymerase chain reaction (PCR) followed by restriction fragment length polymorphism (RFLP) analysis. There were no significant differences in genotypes and allele distributions of three SNPs between CAD and CAD-free groups. The AA genotype of SNP rs12970134 near MC4R was associated to obesity both in CAD group and CAD-free group in Han Chinese population (P < 0.001, OR = 2.96, 95% CI 2.01–3.73; and P = 0.003, OR = 2.59, 95% CI 1.86–3.19, respectively). Our observations suggest that the polymorphism rs12970134 near MC4R may be associated to the risk of obesity in Han Chinese population.     

Disproportionate Contributions of Select Genomic Compartments and Cell Types to Genetic Risk for Coronary Artery Disease

Large genome-wide association studies (GWAS) have identified many genetic loci associated with risk for myocardial infarction (MI) and coronary artery disease (CAD). Concurrently, efforts such as the National Institutes of Health (NIH) Roadmap Epigenomics Project and the Encyclopedia of DNA Elements (ENCODE) Consortium have provided unprecedented data on functional elements of the human genome. In the present study, we systematically investigate the biological link between genetic variants associated with this complex disease and their impacts on gene function. First, we examined the heritability of MI/CAD according to genomic compartments. We observed that single nucleotide polymorphisms (SNPs) residing within nearby regulatory regions show significant polygenicity and contribute between 59–71% of the heritability for MI/CAD. Second, we showed that the polygenicity and heritability explained by these SNPs are enriched in histone modification marks in specific cell types. Third, we found that a statistically higher number of 45 MI/CAD-associated SNPs that have been identified from large-scale GWAS studies reside within certain functional elements of the genome, particularly in active enhancer and promoter regions. Finally, we observed significant heterogeneity of this signal across cell types, with strong signals observed within adipose nuclei, as well as brain and spleen cell types. These results suggest that the genetic etiology of MI/CAD is largely explained by tissue-specific regulatory perturbation within the human genome.     

Epistatic Gene-Based Interaction Analyses for Glaucoma in eMERGE and NEIGHBOR Consortium

Primary open angle glaucoma (POAG) is a complex disease and is one of the major leading causes of blindness worldwide. Genome-wide association studies have successfully identified several common variants associated with glaucoma; however, most of these variants only explain a small proportion of the genetic risk. Apart from the standard approach to identify main effects of variants across the genome, it is believed that gene-gene interactions can help elucidate part of the missing heritability by allowing for the test of interactions between genetic variants to mimic the complex nature of biology. To explain the etiology of glaucoma, we first performed a genome-wide association study (GWAS) on glaucoma case-control samples obtained from electronic medical records (EMR) to establish the utility of EMR data in detecting non-spurious and relevant associations; this analysis was aimed at confirming already known associations with glaucoma and validating the EMR derived glaucoma phenotype. Our findings from GWAS suggest consistent evidence of several known associations in POAG. We then performed an interaction analysis for variants found to be marginally associated with glaucoma (SNPs with main effect p-value <0.01) and observed interesting findings in the electronic MEdical Records and GEnomics Network (eMERGE) network dataset. Genes from the top epistatic interactions from eMERGE data (Likelihood Ratio Test i.e. LRT p-value <1e-05) were then tested for replication in the NEIGHBOR consortium dataset. To replicate our findings, we performed a gene-based SNP-SNP interaction analysis in NEIGHBOR and observed significant gene-gene interactions (p-value <0.001) among the top 17 gene-gene models identified in the discovery phase. Variants from gene-gene interaction analysis that we found to be associated with POAG explain 3.5% of additional genetic variance in eMERGE dataset above what is explained by the SNPs in genes that are replicated from previous GWAS studies (which was only 2.1% variance explained in eMERGE dataset); in the NEIGHBOR dataset, adding replicated SNPs from gene-gene interaction analysis explain 3.4% of total variance whereas GWAS SNPs alone explain only 2.8% of variance. Exploring gene-gene interactions may provide additional insights into many complex traits when explored in properly designed and powered association studies.     

A Powerful Pathway-Based Adaptive Test for Genetic Association with Common or Rare Variants

In spite of the success of genome-wide association studies (GWASs), only a small proportion of heritability for each complex trait has been explained by identified genetic variants, mainly SNPs. Likely reasons include genetic heterogeneity (i.e., multiple causal genetic variants) and small effect sizes of causal variants, for which pathway analysis has been proposed as a promising alternative to the standard single-SNP-based analysis. A pathway contains a set of functionally related genes, each of which includes multiple SNPs. Here we propose a pathway-based test that is adaptive at both the gene and SNP levels, thus maintaining high power across a wide range of situations with varying numbers of the genes and SNPs associated with a trait. The proposed method is applicable to both common variants and rare variants and can incorporate biological knowledge on SNPs and genes to boost statistical power. We use extensively simulated data and a WTCCC GWAS dataset to compare our proposal with several existing pathway-based and SNP-set-based tests, demonstrating its promising performance and its potential use in practice.     

Genome‐wide association and genome partitioning reveal novel genomic regions underlying variation in gastrointestinal nematode burden in a wild bird

Identifying the genetic architecture underlying complex phenotypes is a notoriously difficult problem that often impedes progress in understanding adaptive eco‐evolutionary processes in natural populations. Host–parasite interactions are fundamentally important drivers of evolutionary processes, but a lack of understanding of the genes involved in the host's response to chronic parasite insult makes it particularly difficult to understand the mechanisms of host life history trade‐offs and the adaptive dynamics involved. Here, we examine the genetic basis of gastrointestinal nematode (Trichostrongylus tenuis) burden in 695 red grouse (Lagopus lagopus scotica) individuals genotyped at 384 genome‐wide SNPs. We first use genome‐wide association to identify individual SNPs associated with nematode burden. We then partition genome‐wide heritability to identify chromosomes with greater heritability than expected from gene content, due to harbouring a multitude of additive SNPs with individually undetectable effects. We identified five SNPs on five chromosomes that accounted for differences of up to 556 worms per bird, but together explained at best 4.9% of the phenotypic variance. These SNPs were closely linked to genes representing a range of physiological processes including the immune system, protein degradation and energy metabolism. Genome partitioning indicated genome‐wide heritability of up to 29% and three chromosomes with excess heritability of up to 4.3% (total 8.9%). These results implicate SNPs and novel genomic regions underlying nematode burden in this system and suggest that this phenotype is somewhere between being based on few large‐effect genes (oligogenic) and based on a large number of genes with small individual but large combined effects (polygenic).     

Drug-Gene Interactions of Antihypertensive Medications and Risk of Incident Cardiovascular Disease: A Pharmacogenomics Study from the CHARGE Consortium

BackgroundHypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals.MethodsUsing a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases).ResultsAlthough drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (P_interaction > 5.0×10⁻⁸). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (P_interaction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD.     

Venous thromboembolism GWAS reported genetic makeup and the hallmarks of cancer: Linkage to ovarian tumour behaviour

Venous thromboembolism (VTE) is a common cardiovascular disease thought to be the outcome of an intricate interplay between acquired and inherited factors that act together to modify disease risk. Over the years, several single-nucleotide polymorphisms (SNPs) in candidate genes have been associated with disease risk, including F5 rs6025, F2 rs1799963, FGG rs2066865, ABO genetic variants, among others less common. More recently, genome-wide association studies (GWAS) have contributed to the identification of novel VTE-associated SNPs, some of them located in novel genes with no clear role in the haemostatic system, such as SLC44A2 rs2288904 and TSPAN15 rs78707713. Given the existence of a tight relationship between VTE and cancer, with both pathologies sharing biological pathways that allow one to promote the other, these SNPs constitute potential prognostic and predictive biomarkers currently needed for better management of cancer patients. Among solid tumours, ovarian cancer (OC) is one of the most frequently associated with VTE. Indeed, haemostatic components might have a significant impact in OC progression, and therefore, the clinical and biological implications of VTE-associated SNPs should be assessed in patients with this neoplasia.     

Association of Genetic Markers in the BCL-2 Family of Apoptosis-Related Genes with Endometrial Cancer Risk in a Chinese Population

BackgroundIn vitro studies have demonstrated the role of the BCL-2 family of genes in endometrial carcinogenesis. The role of genetic variants in BCL-2 genes and their interactions with non-genetic factors in the development of endometrial cancer has not been investigated in epidemiological studies.ResultsSignificant associations with endometrial cancer risk were found for 9 SNPs in the BCL2 gene (P trend<0.05 for all). For SNPs rs17759659 and rs7243091 (minor allele for both: G), the associations were independent. The odds ratio was 1.27 (95% CI: 1.04–1.53) for women with AG genotype for the SNP rs17759659 and 1.82 (95% CI: 1.21–2.73) for women with the GG genotype for the SNP rs7243091. No interaction between these two SNPs and established non-genetic risk factors of endometrial cancer was noticed.ConclusionGenetic polymorphisms in the BCL2 gene may be associated with the risk of endometrial cancer in Chinese women.     

Lipoproteinstoffwechsel und koronare Herzkrankheit

A better understanding of complex diseases and their genetics has been gained by investigating genetic disorders of lipoprotein metabolism. This has resulted in the development of ddrugs to prevent atherosclerosis, the most frequent cause of death in industrialized countries. Thus, analysis of familial hypercholesterinemia (FH), the most frequent cause of which are mutations on the LDLR gene, has contributed to the development of HMG-CoA reductase inhibitors (statins). Meanwhile, in genome-wide association studies (GWAS), variants in over 90 genes have been found to influence the concentration of plasma lipids. However, these explain only a small fraction of the genetic variance of the traits. Taking the classical polymorphism of Apo-E as an example, it is discussed that one possible reason for the ??missing heritability?? may be the selection of the SNPs on the arrays used in the GWAS. Further, this polymorphism demonstrates how interactions may mask a connection between a genotype and a disease. Genetic studies based on the principle of ??Mendelian randomization?? have established the causal role of a high Lp(a) concentration as a risk factor for coronary heart disease (CHD). For patients with end-stage renal disease, however, a polymorphism (KIV-2 CNV) is a better predictor for CHD than Lp(a) concentration.     

Genome-wide searching of rare genetic variants in WTCCC data

Although they have demonstrated success in searching for common variants for complex diseases, genome-wide association (GWA) studies are less successful in detecting rare genetic variants because of the poor statistical power of most of current methods. We developed a two-stage method that can apply to GWA studies for detecting rare variants. Here we report the results of applying this two-stage method to the Wellcome Trust Case Control Consortium (WTCCC) dataset that include seven complex diseases: bipolar disorder, cardiovascular disease, hypertension (HT), rheumatoid arthritis, Crohn’s disease, type 1 diabetes and type 2 diabetes (T2D). We identified 24 genes or regions that reach genome wide significance. Eight of them are novel and were not reported in the WTCCC study. The cumulative risk (or protective) haplotype frequency for each of the 8 genes or regions is small, being at most 11%. For each of the novel genes, the risk (or protective) haplotype set cannot be tagged by the common SNPs available in chips (r ² < 0.32). The gene identified in HT was further replicated in the Framingham Heart Study, and is also significantly associated with T2D. Our analysis suggests that searching for rare genetic variants is feasible in current GWA studies and candidate gene studies, and the results can severe as guides to future resequencing studies to identify the underlying rare functional variants.     

Two-marker association tests yield new disease associations for coronary artery disease and hypertension

It has been postulated that multiple-marker methods may have added ability, over single-marker methods, to detect genetic variants associated with disease. The Wellcome Trust Case Control Consortium (WTCCC) provided the first successful large genome-wide association studies (GWAS) which included single-marker association analyses for seven common complex diseases. Of those signals detected, only one was associated with coronary artery disease (CAD), and none were identified for hypertension (HTN). Our objective was to find additional genetic associations and pathways for cardiovascular disease by examining the WTCCC data for variants associated with CAD and HTN using two-marker testing methods. We applied two-marker association testing to the WTCCC dataset, which includes ~2,000 affected individuals with each disorder, and a shared pool of ~3,000 controls, all genotyped using Affymetrix GeneChip 500 K arrays. For CAD, we detected single nucleotide polymorphisms (SNP) pairs in three genes showing genome-wide significance: HFE2, STK32B, and DIPC2. The most notable SNP pairs in a non-protein-coding region were at 9p21, a known major CAD-associated region. For HTN, we detected SNP pairs in five genes: GPR39, XRCC4, MYO6, ZFAT, and MACROD2. Four further associated SNP pair regions were at least 70 kb from any known gene. We have shown that novel, multiple-marker, statistical methods can be of use in finding variants in GWAS. We describe many new, associated variants for both CAD and HTN and describe their known genetic mechanisms.     

Comprehensive Assessment of Genetic Sequence Variants in the Antioxidant ‘Master Regulator’ Nrf2 in Idiopathic Parkinson’s Disease

Parkinson’s disease (PD) is a complex neurodegenerative disorder influenced by a combination of genetic and environmental factors. The molecular mechanisms that underlie PD are unknown; however, oxidative stress and impairment of antioxidant defence mechanisms have been implicated as major contributors to disease pathogenesis. Previously, we have reported a PD patient-derived cellular model generated from biopsies of the olfactory mucosa, termed hONS cells, in which the NRF2-mediated antioxidant response pathway genes were among the most differentially-expressed. To date, few studies have examined the role of the NRF2 encoding gene, NFE2L2, and PD. In this study, we comprehensibly assessed whether rare and common NFE2L2 genetic variations modify susceptibility to PD using a large Australian case-control sample (PD=1338, controls=1379). We employed a haplotype-tagging approach that identified an association with the tagging SNP rs2364725 and PD (OR = 0.849 (0.760-0.948), P = 0.004). Further genetic screening in hONS cell lines produced no obvious pathogenic variants in the coding regions of NFE2L2. Finally, we investigated the relationship between xenobiotic exposures and NRF2 function, through gene-environment interactions, between NFE2L2 SNPs and smoking or pesticide exposure. Our results demonstrated a significant interaction between rs2706110 and pesticide exposure (OR = 0.597 (0.393-0.900), P = 0.014). In addition, we were able to identify some age-at-onset modifying SNPs and replicate an ‘early-onset’ haplotype that contains a previously identified ‘functional promoter’ SNP (rs6721961). Our results suggest a role of NFE2L2 genetic variants in modifying PD susceptibility and onset. Our findings also support the utility of testing gene-environment interactions in genetic studies of PD.     

IDO1 and IDO2 Non-Synonymous Gene Variants: Correlation with Crohn's Disease Risk and Clinical Phenotype

BackgroundCrohn''s disease (CD) is a chronic inflammatory disease of the gastrointestinal tract. Genetic polymorphisms can confer CD risk and influence disease phenotype. Indoleamine 2,3 dioxygenase-1 (IDO1) is one of the most over-expressed genes in CD and mediates potent anti-inflammatory effects via tryptophan metabolism along the kynurenine pathway. We aimed to determine whether non-synonymous polymorphisms in IDO1 or IDO2 (a gene paralog) are important either as CD risk alleles or as modifiers of CD phenotype.MethodsUtilizing a prospectively collected database, clinically phenotyped CD patients (n = 734) and non-IBD controls (n = 354) were genotyped for established IDO1 and IDO2 non-synonymous single nucleotide polymorphisms (SNPs) and novel genetic variants elucidated in the literature. Allelic frequencies between CD and non-IBD controls were compared. Genotype-phenotype analysis was conducted. IDO1 enzyme activity was assessed by calculating the serum kynurenine to tryptophan ratio (K/T).ResultsIDO1 SNPs were rare (1.7% non-IBD vs 1.1% CD; p = NS) and not linked to Crohn''s disease diagnosis in this population. IDO1 SNPs did however associate with a severe clinical course, presence of perianal disease, extraintestinal manifestations and a reduced serum K/T ratio during active disease suggesting lower IDO1 function. IDO2 minor allele variants were common and one of them, rs45003083, associated with reduced risk of Crohn''s disease (p = 0.025). No IDO2 SNPs associated with a particular Crohn''s disease clinical phenotype.ConclusionsThis work highlights the functional importance of IDO enzymes in human Crohn''s disease and establishes relative rates of IDO genetic variants in a US population.     

Gene-centric characteristics of genome-wide association studies

Background

The high-throughput genotyping chips have contributed greatly to genome-wide association (GWA) studies to identify novel disease susceptibility single nucleotide polymorphisms (SNPs). The high-density chips are designed using two different SNP selection approaches, the direct gene-centric approach, and the indirect quasi-random SNPs or linkage disequilibrium (LD)-based tagSNPs approaches. Although all these approaches can provide high genome coverage and ascertain variants in genes, it is not clear to which extent these approaches could capture the common genic variants. It is also important to characterize and compare the differences between these approaches.

Methodology/Principal Findings

In our study, by using both the Phase II HapMap data and the disease variants extracted from OMIM, a gene-centric evaluation was first performed to evaluate the ability of the approaches in capturing the disease variants in Caucasian population. Then the distribution patterns of SNPs were also characterized in genic regions, evolutionarily conserved introns and nongenic regions, ontologies and pathways. The results show that, no mater which SNP selection approach is used, the current high-density SNP chips provide very high coverage in genic regions and can capture most of known common disease variants under HapMap frame. The results also show that the differences between the direct and the indirect approaches are relatively small. Both have similar SNP distribution patterns in these gene-centric characteristics.

Conclusions/Significance

This study suggests that the indirect approaches not only have the advantage of high coverage but also are useful for studies focusing on various functional SNPs either in genes or in the conserved regions that the direct approach supports. The study and the annotation of characteristics will be helpful for designing and analyzing GWA studies that aim to identify genetic risk factors involved in common diseases, especially variants in genes and conserved regions.