Selection and evaluation of tagging SNPs in the neuronal-sodium-channel gene SCN1A: implications for linkage-disequilibrium gene mapping

Association studies are widely seen as the most promising approach for finding polymorphisms that influence genetically complex traits, such as common diseases and responses to their treatment. Considerable interest has therefore recently focused on the development of methods that efficiently screen genomic regions or whole genomes for gene variants associated with complex phenotypes. One key element in this search is the use of linkage disequilibrium to gain maximal information from typing a selected subset of highly informative single-nucleotide polymorphism (SNP) markers, now often called "tagging SNPs" (tSNPs). Probably the most common approach to linkage-disequilibrium gene mapping involves a three-step program: (1) characterization of the haplotype structure in candidate genes or genomic regions of interest, (2) identification of tSNPs sufficient to represent the most common haplotypes, and (3) typing of tSNPs in clinical material. Early definitions of tSNPs focused on the amount of haplotype diversity that they explained. To select tSNPs that would have maximal power in a genetic association study, however, we have developed optimization criteria based on the r2 measure of association and have compared these with other criteria based on the haplotype diversity. To evaluate the full program and to assess how well the selected tags are likely to perform, we have determined the haplotype structure and have assessed tSNPs in the SCN1A gene, an important candidate gene for sporadic epilepsy. We find that as few as four tSNPs are predicted to maintain a consistently high r2 value with all other common SNPs in the gene, indicating that the tags could be used in an association study with only a modest reduction in power relative to direct assays of all common SNPs. This implies that very large case-control studies can be screened for variation in hundreds of candidate genes with manageable experimental effort, once tSNPs are identified. However, our results also show that tSNPs identified in one population may not necessarily perform well in another, indicating that the preliminary study to identify tSNPs and the later case-control study should be performed in the same population. Our results also indicate that tSNPs will not easily identify discrepant SNPs, which lie on importantly discriminating but apparently short genealogical branches. This could significantly complicate tagging approaches for phenotypes influenced by variants that have experienced positive selection.     

Selecting tagging SNPs for association studies using power calculations from genotype data

Recent studies have indicated that linkage disequilibrium (LD) between single nucleotide polymorphism (SNP) markers can be used to derive a reduced set of tagging SNPs (tSNPs) for genetic association studies. Previous strategies for identifying tSNPs have focused on LD measures or haplotype diversity, but the statistical power to detect disease-associated variants using tSNPs in genetic studies has not been fully characterized. We propose a new approach of selecting tSNPs based on determining the set of SNPs with the highest power to detect association. Two-locus genotype frequencies are used in the power calculations. To show utility, we applied this power method to a large number of SNPs that had been genotyped in Caucasian samples. We demonstrate that a significant reduction in genotyping efforts can be achieved although the reduction depends on genotypic relative risk, inheritance mode and the prevalence of disease in the human population. The tSNP sets identified by our method are remarkably robust to changes in the disease model when small relative risk and additive mode of inheritance are employed. We have also evaluated the ability of the method to detect unidentified SNPs. Our findings have important implications in applying tSNPs from different data sources in association studies.     

Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with Height

Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10⁻⁶), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10⁻⁸). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 × 10⁻¹¹). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.     

Genetic markers of ovarian follicle number and menopause in women of multiple ethnicities

Oocyte loss has a significant impact on fertility and somatic health. Yet, we know little about factors that impact this process. We sought to identify genetic variants associated with ovarian reserve (oocyte number as measured by antral follicle count, AFC). Based on recently published genome-wide scans that identified loci associated with age of menopause, we also sought to test our hypothesis that follicle number and menopausal age share underlying genetic associations. We analyzed menopause-related variants for association with follicle number in an independent population of approximately 450 reproductive-aged women of European and African ancestry; these women were assessed for AFC, anthropometric, clinical, and lifestyle factors. One SNP strongly associated with later menopausal age in Caucasian women (+1.07?±?0.11?years) in previous work was also associated with higher follicle counts in Caucasians (+2.79?±?1.67 follicles) in our study. This variant is within the Minichromosome Maintenance Complex Component 8 (MCM8) gene, which we found was expressed within oocytes in follicles of the human ovary. In genome-wide scans of AFC, we also identified one marginally genome-wide and several nominally significant SNPs within several other genes associated with follicle number in both ethnic groups. Further, there were overlapping variants associated with multiple ovarian reserve markers (AFC, serum hormone levels, menopausal age). This study provides the first evidence for direct genetic associations underlying both follicle number and menopause and identifies novel candidate genes. Genetic variants associated with ovarian reserve may facilitate discovery of genetic markers to predict reproductive health and lifespan in women.     

Common Genetic Variants in Wnt Signaling Pathway Genes as Potential Prognostic Biomarkers for Colorectal Cancer

Compelling evidence has implicated the Wnt signaling pathway in the pathogenesis of colorectal cancer. We assessed the use of tag single nucleotide polymorphisms (tSNPs) in adenomatous polyposis coli (APC)/β-catenin (CTNNB1) genes to predict outcomes in patients with colorectal cancer. We selected and genotyped 10 tSNP to predict common variants across entire APC and CTNNB1 genes in 282 colorectal cancer patients. The associations of these tSNPs with distant metastasis-free survival and overall survival were evaluated by Kaplan-Meier analysis, Cox regression model, and survival tree analysis. The 5-year overall survival rate was 68.3%. Survival tree analysis identified a higher-order genetic interaction profile consisting of the APC rs565453, CTNNB1 2293303, and APC rs1816769 that was significantly associated with overall survival. The 5-year survival overall rates were 89.2%, 66.1%, and 58.8% for the low-, medium-, and high-risk genetic profiles, respectively (log-rank P = 0.001). After adjusting for possible confounders, including age, gender, carcinoembryonic antigen levels, tumor differentiation, stage, lymphovascular invasion, perineural invasion, and lymph node involvement, the genetic interaction profile remained significant. None of the studied SNPs were individually associated with distant metastasis-free survival and overall survival. Our results suggest that the genetic interaction profile among Wnt pathway SNPs might potentially increase the prognostic value in outcome prediction for colorectal cancer.     

Genome-wide analysis of polymorphisms associated with cytokine responses in smallpox vaccine recipients

The role that genetics play in response to infection or disease is becoming increasingly clear as we learn more about immunogenetics and host-pathogen interactions. Here we report a genome-wide analysis of the effects of host genetic variation on cytokine responses to vaccinia virus stimulation in smallpox vaccine recipients. Our data show that vaccinia stimulation of immune individuals results in secretion of inflammatory and Th1 cytokines. We identified multiple SNPs significantly associated with variations in cytokine secretion. These SNPs are found in genes with known immune function, as well as in genes encoding for proteins involved in signal transduction, cytoskeleton, membrane channels and ion transport, as well as others with no previously identified connection to immune responses. The large number of significant SNP associations implies that cytokine secretion in response to vaccinia virus is a complex process controlled by multiple genes and gene families. Follow-up studies to replicate these findings and then pursue mechanistic studies will provide a greater understanding of how genetic variation influences vaccine responses.     

Genome-wide local ancestry approach identifies genes and variants associated with chemotherapeutic susceptibility in African Americans

Chemotherapeutic agents are used in the treatment of many cancers, yet variable resistance and toxicities among individuals limit successful outcomes. Several studies have indicated outcome differences associated with ancestry among patients with various cancer types. Using both traditional SNP-based and newly developed gene-based genome-wide approaches, we investigated the genetics of chemotherapeutic susceptibility in lymphoblastoid cell lines derived from 83 African Americans, a population for which there is a disparity in the number of genome-wide studies performed. To account for population structure in this admixed population, we incorporated local ancestry information into our association model. We tested over 2 million SNPs and identified 325, 176, 240, and 190 SNPs that were suggestively associated with cytarabine-, 5'-deoxyfluorouridine (5'-DFUR)-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10(-4)). Importantly, some of these variants are found only in populations of African descent. We also show that cisplatin-susceptibility SNPs are enriched for carboplatin-susceptibility SNPs. Using a gene-based genome-wide association approach, we identified 26, 11, 20, and 41 suggestive candidate genes for association with cytarabine-, 5'-DFUR-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10(-3)). Fourteen of these genes showed evidence of association with their respective chemotherapeutic phenotypes in the Yoruba from Ibadan, Nigeria (p<0.05), including TP53I11, COPS5 and GAS8, which are known to be involved in tumorigenesis. Although our results require further study, we have identified variants and genes associated with chemotherapeutic susceptibility in African Americans by using an approach that incorporates local ancestry information.     

Copy number variants and common disorders: filling the gaps and exploring complexity in genome-wide association studies

Genome-wide association scans (GWASs) using single nucleotide polymorphisms (SNPs) have been completed successfully for several common disorders and have detected over 30 new associations. Considering the large sample sizes and genome-wide SNP coverage of the scans, one might have expected many of the common variants underpinning the genetic component of various disorders to have been identified by now. However, these studies have not evaluated the contribution of other forms of genetic variation, such as structural variation, mainly in the form of copy number variants (CNVs). Known CNVs account for over 15% of the assembled human genome sequence. Since CNVs are not easily tagged by SNPs, might have a wide range of copy number variability, and often fall in genomic regions not well covered by whole-genome arrays or not genotyped by the HapMap project, current GWASs have largely missed the contribution of CNVs to complex disorders. In fact, some CNVs have already been reported to show association with several complex disorders using candidate gene/region approaches, underpinning the importance of regions not investigated in current GWASs. This reveals the need for new generation arrays (some already in the market) and the use of tailored approaches to explore the full dimension of genome variability beyond the single nucleotide scale.     

Genome-wide SNP associations with rubella-specific cytokine responses in measles-mumps-rubella vaccine recipients

Genetic polymorphisms are known to affect responses to both viral infection and vaccination. Our previous work has described genetic polymorphisms significantly associated with variations in immune response to rubella vaccine from multiple gene families with known immune function, including HLA, cytokine and cytokine receptor genes, and in genes controlling innate and adaptive immunity. In this study, we assessed cellular immune responses (IFNγ and IL-6) in a cohort of healthy younger individuals and performed genome-wide SNP analysis on these same individuals. Here, we report the first genome-wide association study focused on immune responses following rubella vaccination. Our results indicate that rs16928280 in protein tyrosine phosphatase delta (PTPRD) and a collection of SNPs in ACO1 (encoding an iron regulatory protein) are associated with interindividual variations in IFNγ response to rubella virus stimulation. In contrast, we did not identify any significant genetic associations with rubella-specific IL-6 response. These genetic regions may influence rubella vaccine-induced IFNγ responses and warrant further studies in additional cohorts in order to confirm these findings.     

Genome-wide associated loci influencing interleukin (IL)-10, IL-1Ra, and IL-6 levels in African Americans

Interleukins (ILs) are key mediators of the immune response and inflammatory process. Plasma levels of IL-10, IL-1Ra, and IL-6 are associated with metabolic conditions, show large inter-individual variations, and are under strong genetic control. Therefore, elucidation of the genetic variants that influence levels of these ILs provides useful insights into mechanisms of immune response and pathogenesis of diseases. We conducted a genome-wide association study (GWAS) of IL-10, IL-1Ra, and IL-6 levels in 707 non-diabetic African Americans using 5,396,780 imputed and directly genotyped single nucleotide polymorphisms (SNPs) with adjustment for gender, age, and body mass index. IL-10 levels showed genome-wide significant associations (p < 5 × 10(-8)) with eight SNPs, the most significant of which was rs5743185 in the PMS1 gene (p = 2.30 × 10(-10)). We tested replication of SNPs that showed genome-wide significance in 425 non-diabetic individuals from West Africa, and successfully replicated rs17365948 in the YWHAZ gene (p = 0.02). IL-1Ra levels showed suggestive associations with two SNPs in the ASB3 gene (p = 2.55 × 10(-7)), ten SNPs in the IL-1 gene family (IL1F5, IL1F8, IL1F10, and IL1Ra, p = 1.04 × 10(-6) to 1.75 × 10(-6)), and 23 SNPs near the IL1A gene (p = 1.22 × 10(-6) to 1.63 × 10(-6)). We also successfully replicated rs4251961 (p = 0.009); this SNP was reported to be associated with IL-1Ra levels in a candidate gene study of Europeans. IL-6 levels showed genome-wide significant association with one SNP (RP11-314E23.1; chr6:133397598; p = 8.63 × 10(-9)). To our knowledge, this is the first GWAS on IL-10, IL-1Ra, and IL-6 levels. Follow-up of these findings may provide valuable insight into the pathobiology of IL actions and dysregulations in inflammation and human diseases.     

Functional analysis of HapMap SNPs

Genome-wide association studies (GWAS) have successfully identified many genetic variants associated with complex diseases and traits. However, functional consequence of genetic variants studied in GWAS is not yet fully investigated, which would hinder the application of GWAS. We therefore performed a systematic functional analysis of HapMap SNPs, which have been most commonly used as the reference panel for GWAS. Our study highlights several characteristics of HapMap SNPs and identifies subsets of genetic variants with interesting functional implication. The results show that HapMap SNPs have good coverage within RefSeq genes, especially within known disease-related genes. On the other hand, only a small percentage of SNPs are non-synonymous SNPs while many SNPs are actually located at gene deserts. Moreover, many functionally important variants are not yet still interrogated. A redesigned SNP reference panel with additional functionally important variants would be useful to identify disease-causal variants in the future genome-wide studies.     

Design and coverage of high throughput genotyping arrays optimized for individuals of East Asian, African American, and Latino race/ethnicity using imputation and a novel hybrid SNP selection algorithm

Four custom Axiom genotyping arrays were designed for a genome-wide association (GWA) study of 100,000 participants from the Kaiser Permanente Research Program on Genes, Environment and Health. The array optimized for individuals of European race/ethnicity was previously described. Here we detail the development of three additional microarrays optimized for individuals of East Asian, African American, and Latino race/ethnicity. For these arrays, we decreased redundancy of high-performing SNPs to increase SNP capacity. The East Asian array was designed using greedy pairwise SNP selection. However, removing SNPs from the target set based on imputation coverage is more efficient than pairwise tagging. Therefore, we developed a novel hybrid SNP selection method for the African American and Latino arrays utilizing rounds of greedy pairwise SNP selection, followed by removal from the target set of SNPs covered by imputation. The arrays provide excellent genome-wide coverage and are valuable additions for large-scale GWA studies.     

Effect of Genome-Wide Genotyping and Reference Panels on Rare Variants Imputation

Common variants explain little of the variance of most common disease,prompting large-scale sequencing studies to understand the contribution of rare variants to these diseases.Imputation of rare variants from genome-wide genotypic arrays offers a cost-efficient strategy to achieve necessary sample sizes required for adequate statistical power.To estimate the performance of imputation of rare variants,we imputed 153 individuals,each of whom was genotyped on 3 different genotype arrays including 317k,610k and 1 million single nucleotide polymorphisms(SNPs),to two different reference panels:HapMap2 and 1000 Genomes pilot March 2010 release (lKGpilot) by using IMPUTE version 2.We found that more than 94%and 84%of all SNPs yield acceptable accuracy(info > 0.4) in HapMap2 and lKGpilot-based imputation,respectively.For rare variants(minor allele frequency(MAF) <5%),the proportion of wellimputed SNPs increased as the MAF increased from 0.3%to 5%across all 3 genome-wide association study(GWAS) datasets.The proportion of well-imputed SNPs was 69%,60%and 49%for SNPs with a MAF from 0.3%to 5%for 1M,610k and 317k,respectively. None of the very rare variants(MAF < 0.3%) were well imputed.We conclude that the imputation accuracy of rare variants increases with higher density of genome-wide genotyping arrays when the size of the reference panel is small.Variants with lower MAF are more difficult to impute.These findings have important implications in the design and replication of large-scale sequencing studies.     

A Genome-Wide Investigation of SNPs and CNVs in Schizophrenia

We report a genome-wide assessment of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) in schizophrenia. We investigated SNPs using 871 patients and 863 controls, following up the top hits in four independent cohorts comprising 1,460 patients and 12,995 controls, all of European origin. We found no genome-wide significant associations, nor could we provide support for any previously reported candidate gene or genome-wide associations. We went on to examine CNVs using a subset of 1,013 cases and 1,084 controls of European ancestry, and a further set of 60 cases and 64 controls of African ancestry. We found that eight cases and zero controls carried deletions greater than 2 Mb, of which two, at 8p22 and 16p13.11-p12.4, are newly reported here. A further evaluation of 1,378 controls identified no deletions greater than 2 Mb, suggesting a high prior probability of disease involvement when such deletions are observed in cases. We also provide further evidence for some smaller, previously reported, schizophrenia-associated CNVs, such as those in NRXN1 and APBA2. We could not provide strong support for the hypothesis that schizophrenia patients have a significantly greater “load” of large (>100 kb), rare CNVs, nor could we find common CNVs that associate with schizophrenia. Finally, we did not provide support for the suggestion that schizophrenia-associated CNVs may preferentially disrupt genes in neurodevelopmental pathways. Collectively, these analyses provide the first integrated study of SNPs and CNVs in schizophrenia and support the emerging view that rare deleterious variants may be more important in schizophrenia predisposition than common polymorphisms. While our analyses do not suggest that implicated CNVs impinge on particular key pathways, we do support the contribution of specific genomic regions in schizophrenia, presumably due to recurrent mutation. On balance, these data suggest that very few schizophrenia patients share identical genomic causation, potentially complicating efforts to personalize treatment regimens.     

Heroin addiction in African Americans: a hypothesis-driven association study

Heroin addiction is a chronic complex disease with a substantial genetic contribution. This study was designed to identify gene variants associated with heroin addiction in African Americans. The emphasis was on genes involved in reward modulation, behavioral control, cognitive function, signal transduction and stress response. We have performed a case–control association analysis by screening with 1350 variants of 130 genes. The sample consisted of 202 former severe heroin addicts in methadone treatment and 167 healthy controls with no history of drug abuse. Single nucleotide polymorphism (SNP), haplotype and multi-SNP genotype pattern analyses were performed. Seventeen SNPs showed point-wise significant association with heroin addiction (nominal P < 0.01). These SNPs are from genes encoding several receptors: adrenergic ( ADRA1A ), arginine vasopressin ( AVPR1A ), cholinergic ( CHRM2 ), dopamine (DRD1 ), GABA-A ( GABRB3 ), glutamate ( GRIN2A ) and serotonin ( HTR3A ) as well as alcohol dehydrogenase ( ADH7 ), glutamic acid decarboxylase ( GAD1 and GAD2 ), the nucleoside transporter ( SLC29A1 ) and diazepam-binding inhibitor ( DBI ). The most significant result of the analyses was obtained for the GRIN2A haplotype G-A-T (rs4587976-rs1071502-rs1366076) with protective effect ( P _uncorrected = 9.6E- 05, P _corrected = 0.058). This study corroborates several reported associations with alcohol and drug addiction as well as other related disorders and extends the list of variants that may affect the development of heroin addiction. Further studies will be necessary to replicate these associations and to elucidate the roles of these variants in drug addiction vulnerability.     

Imputation across genotyping arrays for genome-wide association studies: assessment of bias and a correction strategy

A great promise of publicly sharing genome-wide association data is the potential to create composite sets of controls. However, studies often use different genotyping arrays, and imputation to a common set of SNPs has shown substantial bias: a problem which has no broadly applicable solution. Based on the idea that using differing genotyped SNP sets as inputs creates differential imputation errors and thus bias in the composite set of controls, we examined the degree to which each of the following occurs: (1) imputation based on the union of genotyped SNPs (i.e., SNPs available on one or more arrays) results in bias, as evidenced by spurious associations (type 1 error) between imputed genotypes and arbitrarily assigned case/control status; (2) imputation based on the intersection of genotyped SNPs (i.e., SNPs available on all arrays) does not evidence such bias; and (3) imputation quality varies by the size of the intersection of genotyped SNP sets. Imputations were conducted in European Americans and African Americans with reference to HapMap phase II and III data. Imputation based on the union of genotyped SNPs across the Illumina 1M and 550v3 arrays showed spurious associations for 0.2 % of SNPs: ~2,000 false positives per million SNPs imputed. Biases remained problematic for very similar arrays (550v1 vs. 550v3) and were substantial for dissimilar arrays (Illumina 1M vs. Affymetrix 6.0). In all instances, imputing based on the intersection of genotyped SNPs (as few as 30 % of the total SNPs genotyped) eliminated such bias while still achieving good imputation quality.     

Large Genomic Region Free of GWAS-Based Common Variants Contains Fertility-Related Genes

DNA variants, such as single nucleotide polymorphisms (SNPs) and copy number variants (CNVs), are unevenly distributed across the human genome. Currently, dbSNP contains more than 6 million human SNPs, and whole-genome genotyping arrays can assay more than 4 million of them simultaneously. In our study, we first questioned whether published genome-wide association studies (GWASs) assays cover all regions well in the genome. Using dbSNP build 135 data, we identified 50 genomic regions longer than 100 Kb that do not contain any common SNPs, i.e., those with minor allele frequency (MAF)≥1%. Secondly, because conserved regions are generally of functional importance, we tested genes in those large genomic regions without common SNPs. We found 97 genes and were enriched for reproduction function. In addition, we further filtered out regions with CNVs listed in the Database of Genomic Variants (DGV), segmental duplications from Human Genome Project and common variants identified by personal genome sequencing (UCSC). No region survived after those filtering. Our analysis suggests that, while there may not be many large genomic regions free of common variants, there are still some “holes” in the current human genomic map for common SNPs. Because GWAS only focused on common SNPs, interpretation of GWAS results should take this limitation into account. Particularly, two recent GWAS of fertility may be incomplete due to the map deficit. Additional SNP discovery efforts should pay close attention to these regions.     

Analysis of the 5q31 33 locus shows an association between single nucleotide polymorphism variants in the IL-5 gene and symptomatic infection with the human blood fluke, Schistosoma japonicum

Genetic studies of human susceptibility to Schistosoma (blood fluke) infections have previously identified a genetic locus determining infection intensity with the African species, Schistosoma mansoni, in the 5q31-33 region of the human genome that is known to contain the Th2 immune response cluster, including the genes encoding the IL-4, IL-5, and IL-13 cytokines. These cytokines are key players in inflammatory immune responses and have previously been implicated in human susceptibility to infection with the Asian species, S. japonicum. In a nested case control study, we genotyped 30 HapMap tagging single nucleotide polymorphisms (SNPs) across these three genes in 159 individuals identified as putatively susceptible to reinfection with S. japonicum and in 133 putatively resistant individuals. A third group comprising 113 individuals demonstrating symptomatic infection was also included. The results provided no significant association at a global level between reinfection predisposition and any of the individual SNPs or haplotype blocks. However, two tagging SNPs in IL-5 demonstrated globally significant association with susceptibility to symptomatic infection. They were in strong linkage disequilibrium with each other and were found to belong to the same haplotype block that also provided a significant association after permutation testing. This haplotype was located in the 3'-untranslated region of IL-5, suggesting that variants in this region of IL-5 may modulate the immune response in these individuals with symptomatic infection.     

First Genome-Wide Association Study on Anxiety-Related Behaviours in Childhood

Background

Twin studies have shown that anxiety in a general population sample of children involves both domain-general and trait-specific genetic effects. For this reason, in an attempt to identify genes responsible for these effects, we investigated domain-general and trait-specific genetic associations in the first genome-wide association (GWA) study on anxiety-related behaviours (ARBs) in childhood.

Methods

The sample included 2810 7-year-olds drawn from the Twins Early Development Study (TEDS) with data available for parent-rated anxiety and genome-wide DNA markers. The measure was the Anxiety-Related Behaviours Questionnaire (ARBQ), which assesses four anxiety traits and also yields a general anxiety composite. Affymetrix GeneChip 6.0 DNA arrays were used to genotype nearly 700,000 single-nucleotide polymorphisms (SNPs), and IMPUTE v2 was used to impute more than 1 million SNPs. Several GWA associations from this discovery sample were followed up in another TEDS sample of 4804 children. In addition, Genome-wide Complex Trait Analysis (GCTA) was used on the discovery sample, to estimate the total amount of variance in ARBs that can be accounted for by SNPs on the array.

Results

No SNP associations met the demanding criterion of genome-wide significance that corrects for multiple testing across the genome (p<5×10⁻⁸). Attempts to replicate the top associations did not yield significant results. In contrast to the substantial twin study estimates of heritability which ranged from 0.50 (0.03) to 0.61 (0.01), the GCTA estimates of phenotypic variance accounted for by the SNPs were much lower 0.01 (0.11) to 0.19 (0.12).

Conclusions

Taken together, these GWAS and GCTA results suggest that anxiety – similar to height, weight and intelligence − is affected by many genetic variants of small effect, but unlike these other prototypical polygenic traits, genetic influence on anxiety is not well tagged by common SNPs.