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Glioma is a rare brain tumor with a poor prognosis. Familial glioma is a subset of glioma with a strong genetic predisposition that accounts for approximately 5% of glioma cases. We performed whole-genome sequencing on an exploratory cohort of 203 individuals from 189 families with a history of familial glioma and an additional validation cohort of 122 individuals from 115 families. We found significant enrichment of rare deleterious variants of seven genes in both cohorts, and the most significantly enriched gene was HERC2 ( P  = 0.0006). Furthermore, we identified rare noncoding variants in both cohorts that were predicted to affect transcription factor binding sites or cause cryptic splicing. Last, we selected a subset of discovered genes for validation by CRISPR knockdown screening and found that DMBT1, HP1BP3 , and ZCH7B3 have profound impacts on proliferation. This study performs comprehensive surveillance of the genomic landscape of familial glioma.

Background: Telomere maintenance is increasingly recognized as being fundamental to glioma oncogenesis with longer leukocyte telomere length (LTL) reported to increase risk of glioma. To gain further insight into the relationship between telomere genetics and risk of glioma, we conducted several complementary analyses, using genome-wide association studies data on LTL (78 592 individuals) and glioma (12 488 cases and 18 169 controls)., Methods: We performed both classical and summary Mendelian randomization (SMR), coupled with heterogeneity in dependent instruments tests, at genome-wide significant LTL loci to examine if an association was mediated by the same causal variant in glioma. To prioritize genes underscoring glioma-LTL associations, we analyzed gene expression and DNA methylation data., Results: Genetically increased LTL was significantly associated with increased glioma risk, random-effects inverse variance weighted ORs per 1 SD unit increase in the putative risk factor (odds ratio [OR]SD) 4.79 (95% confidence interval: 2.11-10.85; P = 1.76 × 10-4). SMR confirmed the previously reported LTL associations at 3q26.2 (TERC; PSMR = 1.33 × 10-5), 5p15.33 (TERT; PSMR = 9.80 × 10-27), 10q24.33 (STN1 alias OBFC1; PSMR = 4.31 × 10-5), and 20q13.3 (STMN3/RTEL1; PSMR = 2.47 × 10-4) glioma risk loci. Our analysis implicates variation at 1q42.12 (PSMR = 1.55 × 10-2), 6p21.3 (PSMR = 9.76 × 10-3), 6p22.2 (PSMR = 5.45 × 10-3), 7q31.33 (PSMR = 6.52 × 10-3), and 11q22.3 (PSMR = 8.89 × 10-4) as risk factors for glioma risk. While complicated by patterns of linkage disequilibrium, genetic variation involving PARP1, PRRC2A, CARMIL1, POT1, and ATM-NPAT1 was implicated in the etiology of glioma., Conclusions: These observations extend the role of telomere-related genes in the development of glioma., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Background: Epidemiological studies of adult glioma have identified genetic syndromes and 25 heritable risk loci that modify individual risk for glioma, as well increased risk in association with exposure to ionizing radiation and decreased risk in association with allergies. In this analysis, we assess whether there is a shared genome-wide genetic architecture between glioma and atopic/autoimmune diseases., Methods: Using summary statistics from a glioma genome-wide association studies (GWAS) meta-analysis, we identified significant enrichment for risk variants associated with gene expression changes in immune cell populations. We also estimated genetic correlations between glioma and autoimmune, atopic, and hematologic traits using linkage disequilibrium score regression (LDSC), which leverages genome-wide single-nucleotide polymorphism (SNP) associations and patterns of linkage disequilibrium., Results: Nominally significant negative correlations were observed for glioblastoma (GB) and primary biliary cirrhosis (rg = -0.26, P = .0228), and for non-GB gliomas and celiac disease (rg = -0.32, P = .0109). Our analyses implicate dendritic cells (GB pHM = 0.0306 and non-GB pHM = 0.0186) in mediating both GB and non-GB genetic predisposition, with GB-specific associations identified in natural killer (NK) cells (pHM = 0.0201) and stem cells (pHM = 0.0265)., Conclusions: This analysis identifies putative new associations between glioma and autoimmune conditions with genomic architecture that is inversely correlated with that of glioma and that T cells, NK cells, and myeloid cells are involved in mediating glioma predisposition. This provides further evidence that increased activation of the acquired immune system may modify individual susceptibility to glioma., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: The aetiology of glioma is poorly understood. Summary data from genome-wide association studies (GWAS) can be used in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to search for glioma risk factors., Methods: We performed an MR-PheWAS analysing 316 phenotypes, proxied by 8387 genetic variants, and summary genetic data from a GWAS of 12,488 glioma cases and 18,169 controls. Causal effects were estimated under a random-effects inverse-variance-weighted (IVW-RE) model, with robust adjusted profile score (MR-RAPS), weighted median and mode-based estimates computed to assess the robustness of findings. Odds ratios per one standard deviation increase in each phenotype were calculated for all glioma, glioblastoma (GBM) and non-GBM tumours., Results: No significant associations (P < 1.58 × 10 -4 ) were observed between phenotypes and glioma under the IVW-RE model. Suggestive associations (1.58 × 10 -4  < P < 0.05) were observed between leukocyte telomere length (LTL) with all glioma (OR SD  = 3.91, P = 9.24 × 10 -3 ) and GBM (OR SD  = 4.86, P = 3.23 × 10 -2 ), but the association was primarily driven by the TERT variant rs2736100. Serum low-density lipoprotein cholesterol and plasma HbA1C showed suggestive associations with glioma (OR SD  = 1.11, P = 1.39 × 10 -2 and OR SD  = 1.28, P = 1.73 × 10 -2 , respectively), both associations being reliant on single genetic variants., Conclusions: Our study provides further insight into the aetiological basis of glioma for which published data have been mixed.

Background: The etiological basis of glioma is poorly understood. We have used genetic markers in a Mendelian randomization (MR) framework to examine if lifestyle, cardiometabolic, and inflammatory factors influence the risk of glioma. This methodology reduces bias from confounding and is not affected by reverse causation., Methods: We identified genetic instruments for 37 potentially modifiable risk factors and evaluated their association with glioma risk using data from a genome-wide association study of 12 488 glioma patients and 18 169 controls. We used the estimated odds ratio of glioma associated with each of the genetically defined traits to infer evidence for a causal relationship with the following exposures:Lifestyle and dietary factors-height, plasma insulin-like growth factor 1, blood carnitine, blood methionine, blood selenium, blood zinc, circulating adiponectin, circulating carotenoids, iron status, serum calcium, vitamins (A1, B12, B6, E, and 25-hydroxyvitamin D), fatty acid levels (monounsaturated, omega-3, and omega-6) and circulating fetuin-A;Cardiometabolic factors-birth weight, high density lipoprotein cholesterol, low density lipoprotein cholesterol, total cholesterol, total triglycerides, basal metabolic rate, body fat percentage, body mass index, fasting glucose, fasting proinsulin, glycated hemoglobin levels, diastolic and systolic blood pressure, waist circumference, waist-to-hip ratio; andInflammatory factors- C-reactive protein, plasma interleukin-6 receptor subunit alpha and serum immunoglobulin E., Results: After correction for the testing of multiple potential risk factors and excluding associations driven by one single nucleotide polymorphism, no significant association with glioma risk was observed (ie, PCorrected > 0.05)., Conclusions: This study did not provide evidence supporting any of the 37 factors examined as having a significant influence on glioma risk., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Glioma incidence is highest in non-Hispanic Whites, and to date, glioma genome-wide association studies (GWAS) to date have only included European ancestry (EA) populations. African Americans and Hispanics in the US have varying proportions of EA, African (AA) and Native American ancestries (NAA). It is unknown if identified GWAS loci or increased EA is associated with increased glioma risk. We assessed whether EA was associated with glioma in African Americans and Hispanics. Data were obtained for 832 cases and 675 controls from the Glioma International Case-Control Study and GliomaSE Case-Control Study previously estimated to have <80% EA, or self-identify as non-White. We estimated global and local ancestry using fastStructure and RFMix, respectively, using 1,000 genomes project reference populations. Within groups with ≥40% AA (AFR ≥0.4 ), and ≥15% NAA (AMR ≥0.15 ), genome-wide association between local EA and glioma was evaluated using logistic regression conditioned on global EA for all gliomas. We identified two regions (7q21.11, p = 6.36 × 10 -4 ; 11p11.12, p = 7.0 × 10 -4 ) associated with increased EA, and one associated with decreased EA (20p12.13, p = 0.0026) in AFR ≥0.4 . In addition, we identified a peak at rs1620291 (p = 4.36 × 10 -6 ) in 7q21.3. Among AMR ≥0.15 , we found an association between increased EA in one region (12q24.21, p = 8.38 × 10 -4 ), and decreased EA in two regions (8q24.21, p = 0. 0010; 20q13.33, p = 6.36 × 10 -4 ). No other significant associations were identified. This analysis identified an association between glioma and two regions previously identified in EA populations (8q24.21, 20q13.33) and four novel regions (7q21.11, 11p11.12, 12q24.21 and 20p12.13). The identifications of novel association with EA suggest regions to target for future genetic association studies., (© 2019 UICC.)

Genome-wide association studies (GWAS) have so far identified 25 loci associated with glioma risk, with most showing specificity for either glioblastoma (GBM) or non-GBM tumors. The majority of these GWAS susceptibility variants reside in noncoding regions and the causal genes underlying the associations are largely unknown. Here we performed a transcriptome-wide association study to search for novel risk loci and candidate causal genes at known GWAS loci using Genotype-Tissue Expression Project (GTEx) data to predict cis -predicted gene expression in relation to GBM and non-GBM risk in conjunction with GWAS summary statistics on 12,488 glioma cases (6,183 GBM and 5,820 non-GBM) and 18,169 controls. Imposing a Bonferroni-corrected significance level of P < 5.69 × 10 -6 , we identified 31 genes, including GALNT6 at 12q13.33, as a candidate novel risk locus for GBM (mean Z = 4.43; P = 5.68 × 10 -6 ). GALNT6 resides at least 55 Mb away from any previously identified glioma risk variant, while all other 30 significantly associated genes were located within 1 Mb of known GWAS-identified loci and were not significant after conditioning on the known GWAS-identified variants. These data identify a novel locus ( GALNT6 at 12q13.33) and 30 genes at 12 known glioma risk loci associated with glioma risk, providing further insights into glioma tumorigenesis. SIGNIFICANCE: This study identifies new genes associated with glioma risk, increasing understanding of how these tumors develop., (©2019 American Association for Cancer Research.)

Background: There have been few studies of sufficient size to address the relationship between glioma risk and the use of aspirin or NSAIDs, and results have been conflicting. The purpose of this study was to examine the associations between glioma and aspirin/NSAID use, and to aggregate these findings with prior published studies using meta-analysis., Methods: The Glioma International Case-Control Study (GICC) consists of 4,533 glioma cases and 4,171 controls recruited from 2010 to 2013. Interviews were conducted using a standardized questionnaire to obtain information on aspirin/NSAID use. We examined history of regular use for ≥6 months and duration-response. Restricted maximum likelihood meta-regression models were used to aggregate site-specific estimates, and to combine GICC estimates with previously published studies., Results: A history of daily aspirin use for ≥6 months was associated with a 38% lower glioma risk, compared with not having a history of daily use [adjusted meta-OR = 0.62; 95% confidence interval (CI), 0.54-0.70]. There was a significant duration-response trend ( P = 1.67 × 10 -17 ), with lower ORs for increasing duration of aspirin use. Duration-response trends were not observed for NSAID use. In the meta-analysis aggregating GICC data with five previous studies, there was a marginally significant association between use of aspirin and glioma (mOR = 0.84; 95% CI, 0.70-1.02), but no association for NSAID use., Conclusions: Our study suggests that aspirin may be associated with a reduced risk of glioma., Impact: These results imply that aspirin use may be associated with decreased glioma risk. Further research examining the association between aspirin use and glioma risk is warranted., (©2018 American Association for Cancer Research.)

Background: To date, genome-wide association studies (GWAS) have identified 25 risk variants for glioma, explaining 30% of heritable risk. Most histologies occur with significantly higher incidence in males, and this difference is not explained by currently known risk factors. A previous GWAS identified sex-specific glioma risk variants, and this analysis aims to further elucidate risk variation by sex using gene- and pathway-based approaches., Methods: Results from the Glioma International Case-Control Study were used as a testing set, and results from 3 GWAS were combined via meta-analysis and used as a validation set. Using summary statistics for nominally significant autosomal SNPs (P < 0.01 in a previous meta-analysis) and nominally significant X-chromosome SNPs (P < 0.01), 3 algorithms (Pascal, BimBam, and GATES) were used to generate gene scores, and Pascal was used to generate pathway scores. Results were considered statistically significant in the discovery set when P < 3.3 × 10-6 and in the validation set when P < 0.001 in 2 of 3 algorithms., Results: Twenty-five genes within 5 regions and 19 genes within 6 regions reached statistical significance in at least 2 of 3 algorithms in males and females, respectively. EGFR was significantly associated with all glioma and glioblastoma in males only and a female-specific association in TERT, all of which remained nominally significant after conditioning on known risk loci. There were nominal associations with the BioCarta telomeres pathway in both males and females., Conclusions: These results provide additional evidence that there may be differences by sex in genetic risk for glioma. Additional analyses may further elucidate the biological processes through which this risk is conferred.

Background: The purpose of this study was to evaluate the distribution of glioma-related seizures and seizure control at the time of tumor diagnosis with respect to tumor histologic subtypes, tumor treatment and patient characteristics, and to compare seizure history preceding tumor diagnosis (or study enrollment) between glioma patients and healthy controls., Methods: The Glioma International Case Control study (GICC) risk factor questionnaire collected information on demographics, past medical/medication history, and occupational history. Cases from eight centers were also asked detailed questions on seizures in relation to glioma diagnosis; cases (n = 4533) and controls (n = 4171) were also asked about seizures less than 2 years from diagnosis and previous seizure history more than 2 years prior to tumor diagnosis, including childhood seizures., Results: Low-grade gliomas (LGGs), particularly oligodendrogliomas/oligoastrocytomas, had the highest proportion of glioma-related seizures. Patients with low-grade astrocytoma demonstrated the most medically refractory seizures. A total of 83% of patients were using only one antiepileptic drug (AED), which was levetiracetam in 71% of cases. Gross total resection was strongly associated with reduced seizure frequency (p < 0.009). No significant difference was found between glioma cases and controls in terms of seizure occurring more than 2 years before diagnosis or during childhood., Conclusions: Our study showed that glioma-related seizures were most common in low-grade gliomas. Gross total resection was associated with lower seizure frequency. Additionally, having a history of childhood seizures is not a risk factor ***for developing glioma-related seizures or glioma.

Incidence of glioma is approximately 50% higher in males. Previous analyses have examined exposures related to sex hormones in women as potential protective factors for these tumors, with inconsistent results. Previous glioma genome-wide association studies (GWAS) have not stratified by sex. Potential sex-specific genetic effects were assessed in autosomal SNPs and sex chromosome variants for all glioma, GBM and non-GBM patients using data from four previous glioma GWAS. Datasets were analyzed using sex-stratified logistic regression models and combined using meta-analysis. There were 4,831 male cases, 5,216 male controls, 3,206 female cases and 5,470 female controls. A significant association was detected at rs11979158 (7p11.2) in males only. Association at rs55705857 (8q24.21) was stronger in females than in males. A large region on 3p21.31 was identified with significant association in females only. The identified differences in effect of risk variants do not fully explain the observed incidence difference in glioma by sex.

Recent genome-wide association studies of glioma have led to the discovery of single nucleotide polymorphisms (SNPs) at 25 loci influencing risk. Gliomas are heterogeneous, hence to investigate the relationship between risk SNPs and glioma subtype we analysed 1659 tumours profiled for IDH mutation, TERT promoter mutation and 1p/19q co-deletion. These data allowed definition of five molecular subgroups of glioma: triple-positive (IDH mutated, 1p/19q co-deletion, TERT promoter mutated); TERT-IDH (IDH mutated, TERT promoter mutated, 1p/19q-wild-type); IDH-only (IDH mutated, 1p/19q wild-type, TERT promoter wild-type); triple-negative (IDH wild-type, 1p/19q wild-type, TERT promoter wild-type) and TERT-only (TERT promoter mutated, IDH wild-type, 1p/19q wild-type). Most glioma risk loci showed subtype specificity: (1) the 8q24.21 SNP for triple-positive glioma; (2) 5p15.33, 9p21.3, 17p13.1 and 20q13.33 SNPs for TERT-only glioma; (3) 1q44, 2q33.3, 3p14.1, 11q21, 11q23.3, 14q12, and 15q24.2 SNPs for IDH mutated glioma. To link risk SNPs to target candidate genes we analysed Hi-C and gene expression data, highlighting the potential role of IDH1 at 2q33.3, MYC at 8q24.21 and STMN3 at 20q13.33. Our observations provide further insight into the nature of susceptibility to glioma.

Since the first reports in 2009, genome-wide association studies (GWAS) have been successful in identifying germline variants associated with glioma susceptibility. In this review, we describe a chronological history of glioma GWAS, culminating in the most recent study comprising 12,496 cases and 18,190 controls. We additionally summarize associations at the 27 glioma-risk SNPs that have been reported so far. Future efforts are likely to be principally focused on assessing association of germline-risk SNPs with particular molecular subgroups of glioma, as well as investigating the functional basis of the risk loci in tumor formation. These ongoing studies will be important to maximize the impact of research into glioma susceptibility, both in terms of insight into tumor etiology as well as opportunities for clinical translation. Cancer Epidemiol Biomarkers Prev; 27(4); 418-28. ©2018 AACR See all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer.", (©2018 American Association for Cancer Research.)

Background: Obesity and related factors have been implicated as possible aetiological factors for the development of glioma in epidemiological observation studies. We used genetic markers in a Mendelian randomisation framework to examine whether obesity-related traits influence glioma risk. This methodology reduces bias from confounding and is not affected by reverse causation., Methods: Genetic instruments were identified for 10 key obesity-related risk factors, and their association with glioma risk was evaluated using data from a genome-wide association study of 12,488 glioma patients and 18,169 controls. The estimated odds ratio of glioma associated with each of the genetically defined obesity-related traits was used to infer evidence for a causal relationship., Results: No convincing association with glioma risk was seen for genetic instruments for body mass index, waist-to-hip ratio, lipids, type-2 diabetes, hyperglycaemia or insulin resistance. Similarly, we found no evidence to support a relationship between obesity-related traits with subtypes of glioma-glioblastoma (GBM) or non-GBM tumours., Conclusions: This study provides no evidence to implicate obesity-related factors as causes of glioma.

Background: An inverse relationship between allergies with glioma risk has been reported in several but not all epidemiological observational studies. We performed an analysis of genetic variants associated with atopy to assess the relationship with glioma risk using Mendelian randomisation (MR), an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations., Methods: Two-sample MR was undertaken using genome-wide association study data. We used single nucleotide polymorphisms (SNPs) associated with atopic dermatitis, asthma and hay fever, IgE levels, and self-reported allergy as instrumental variables. We calculated MR estimates for the odds ratio (OR) for each risk factor with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighting (IVW), maximum likelihood estimation (MLE), weighted median estimate (WME) and mode-based estimate (MBE) methods. Violation of MR assumptions due to directional pleiotropy were sought using MR-Egger regression and HEIDI-outlier analysis., Results: Under IVW, MLE, WME and MBE methods, associations between glioma risk with asthma and hay fever, self-reported allergy and IgE levels were non-significant. An inverse relationship between atopic dermatitis and glioma risk was found by IVW (OR 0.96, 95% confidence interval (CI) 0.93-1.00, P = 0.041) and MLE (OR 0.96, 95% CI 0.94-0.99, P = 0.003), but not by WME (OR 0.96, 95% CI 0.91-1.01, P = 0.114) or MBE (OR 0.97, 95% CI 0.92-1.02, P = 0.194)., Conclusions: Our investigation does not provide strong evidence for relationship between atopy and the risk of developing glioma, but findings do not preclude a small effect in relation to atopic dermatitis. Our analysis also serves to illustrate the value of using several MR methods to derive robust conclusions.

To examine for a causal relationship between vitamin D and glioma risk we performed an analysis of genetic variants associated with serum 25-hydroxyvitamin D (25(OH)D) levels using Mendelian randomisation (MR), an approach unaffected by biases from confounding. Two-sample MR was undertaken using genome-wide association study data. Single nucleotide polymorphisms (SNPs) associated with 25(OH)D levels were used as instrumental variables (IVs). We calculated MR estimates for the odds ratio (OR) for 25(OH)D levels with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighted (IVW) and maximum likelihood estimation (MLE) methods. A non-significant association between 25(OH)D levels and glioma risk was shown using both the IVW (OR = 1.21, 95% confidence interval [CI] = 0.90-1.62, P = 0.201) and MLE (OR = 1.20, 95% CI = 0.98-1.48, P = 0.083) methods. In an exploratory analysis of tumour subtype, an inverse relationship between 25(OH)D levels and glioblastoma (GBM) risk was identified using the MLE method (OR = 0.62, 95% CI = 0.43-0.89, P = 0.010), but not the IVW method (OR = 0.62, 95% CI = 0.37-1.04, P = 0.070). No statistically significant association was shown between 25(OH)D levels and non-GBM glioma. Our results do not provide evidence for a causal relationship between 25(OH)D levels and all forms of glioma risk. More evidence is required to explore the relationship between 25(OH)D levels and risk of GBM.

Genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, but individual studies have had limited power to identify risk loci. We performed a meta-analysis of existing GWAS and two new GWAS, which totaled 12,496 cases and 18,190 controls. We identified five new loci for glioblastoma (GBM) at 1p31.3 (rs12752552; P = 2.04 × 10 -9 , odds ratio (OR) = 1.22), 11q14.1 (rs11233250; P = 9.95 × 10 -10 , OR = 1.24), 16p13.3 (rs2562152; P = 1.93 × 10 -8 , OR = 1.21), 16q12.1 (rs10852606; P = 1.29 × 10 -11 , OR = 1.18) and 22q13.1 (rs2235573; P = 1.76 × 10 -10 , OR = 1.15), as well as eight loci for non-GBM tumors at 1q32.1 (rs4252707; P = 3.34 × 10 -9 , OR = 1.19), 1q44 (rs12076373; P = 2.63 × 10 -10 , OR = 1.23), 2q33.3 (rs7572263; P = 2.18 × 10 -10 , OR = 1.20), 3p14.1 (rs11706832; P = 7.66 × 10 -9 , OR = 1.15), 10q24.33 (rs11598018; P = 3.39 × 10 -8 , OR = 1.14), 11q21 (rs7107785; P = 3.87 × 10 -10 , OR = 1.16), 14q12 (rs10131032; P = 5.07 × 10 -11 , OR = 1.33) and 16p13.3 (rs3751667; P = 2.61 × 10 -9 , OR = 1.18). These data substantiate that genetic susceptibility to GBM and non-GBM tumors are highly distinct, which likely reflects different etiology.

To identify protein-altering variants (PAVs) for glioma, we analysed Illumina HumanExome BeadChip exome-array data on 1882 glioma cases and 8079 controls from three independent European populations. In addition to single-variant tests we incorporated information on the predicted functional consequences of PAVs and analysed sets of genes with a higher likelihood of having a role in glioma on the basis of the profile of somatic mutations documented by large-scale sequencing initiatives. Globally there was a strong relationship between effect size and PAVs predicted to be damaging (P=2.29 × 10(-49)); however, these variants which are most likely to impact on risk, are rare (MAF<5%). Although no single variant showed an association which was statistically significant at the genome-wide threshold a number represented promising associations - BRCA2:c.9976A>T, p.(Lys3326Ter), which has been shown to influence breast and lung cancer risk (odds ratio (OR)=2.3, P=4.00 × 10(-4) for glioblastoma (GBM)) and IDH2:c.782G>A, p.(Arg261His) (OR=3.21, P=7.67 × 10(-3), for non-GBM). Additionally, gene burden tests revealed a statistically significant association for HARS2 and risk of GBM (P=2.20 × 10(-6)). Genome scans of low-frequency PAVs represent a complementary strategy to identify disease-causing variants compared with scans based on tagSNPs. Strategies to lessen the multiple testing burden by restricting analysis to PAVs with higher priors affords an opportunity to maximise study power.

Background: Several previous studies have found inverse associations between glioma susceptibility and a history of allergies or other atopic conditions. Some evidence indicates that respiratory allergies are likely to be particularly relevant with regard to glioma risk. Using data from the Glioma International Case-Control Study (GICC), we examined the effects of respiratory allergies and other atopic conditions on glioma risk., Methods: The GICC contains detailed information on history of atopic conditions for 4,533 cases and 4,171 controls, recruited from 14 study sites across five countries. Using two-stage random-effects restricted maximum likelihood modeling to calculate meta-analysis ORs, we examined the associations between glioma and allergy status, respiratory allergy status, asthma, and eczema., Results: Having a history of respiratory allergies was associated with an approximately 30% lower glioma risk, compared with not having respiratory allergies (mOR, 0.72; 95% confidence interval, 0.58-0.90). This association was similar when restricting to high-grade glioma cases. Asthma and eczema were also significantly protective against glioma., Conclusion: A substantial amount of data on the inverse association between atopic conditions and glioma has accumulated, and findings from the GICC study further strengthen the existing evidence that the relationship between atopy and glioma is unlikely to be coincidental., Impact: As the literature approaches a consensus on the impact of allergies in glioma risk, future research can begin to shift focus to what the underlying biologic mechanism behind this association may be, which could, in turn, yield new opportunities for immunotherapy or cancer prevention., (©2016 American Association for Cancer Research.)

Decades of research have established only a few etiological factors for glioma, which is a rare and highly fatal brain cancer. Common methodological challenges among glioma studies include small sample sizes, heterogeneity of tumor subtypes, and retrospective exposure assessment. Here, we briefly describe the Glioma International Case-Control (GICC) Study (recruitment, 2010-2013), a study being conducted by the Genetic Epidemiology of Glioma International Consortium that integrates data from multiple data collection sites, uses a common protocol and questionnaire, and includes biospecimen collection. To our knowledge, the GICC Study is the largest glioma study to date that includes collection of blood samples, which will allow for genetic analysis and interrogation of gene-environment interactions., (© The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Genome-wide association studies (GWAS) have successfully identified a number of common single-nucleotide polymorphisms (SNPs) influencing glioma risk. While these SNPs only explain a small proportion of the genetic risk it is unclear how much is left to be detected by other, yet to be identified, common SNPs. Therefore, we applied Genome-Wide Complex Trait Analysis (GCTA) to three GWAS datasets totalling 3,373 cases and 4,571 controls and performed a meta-analysis to estimate the heritability of glioma. Our results identify heritability estimates of 25% (95% CI: 20-31%, P = 1.15 × 10(-17)) for all forms of glioma - 26% (95% CI: 17-35%, P = 1.05 × 10(-8)) for glioblastoma multiforme (GBM) and 25% (95% CI: 17-32%, P = 1.26 × 10(-10)) for non-GBM tumors. This is a substantial increase from the genetic variance identified by the currently identified GWAS risk loci (~6% of common heritability), indicating that most of the heritable risk attributable to common genetic variants remains to be identified.

Previous genome-wide association studies (GWASs) have shown that common genetic variation contributes to the heritable risk of glioma. To identify new glioma susceptibility loci, we conducted a meta-analysis of four GWAS (totalling 4,147 cases and 7,435 controls), with imputation using 1000 Genomes and UK10K Project data as reference. After genotyping an additional 1,490 cases and 1,723 controls we identify new risk loci for glioblastoma (GBM) at 12q23.33 (rs3851634, near POLR3B, P=3.02 × 10(-9)) and non-GBM at 10q25.2 (rs11196067, near VTI1A, P=4.32 × 10(-8)), 11q23.2 (rs648044, near ZBTB16, P=6.26 × 10(-11)), 12q21.2 (rs12230172, P=7.53 × 10(-11)) and 15q24.2 (rs1801591, near ETFA, P=5.71 × 10(-9)). Our findings provide further insights into the genetic basis of the different glioma subtypes.

Glioma is a rare, but highly fatal, cancer that accounts for the majority of malignant primary brain tumors. Inherited predisposition to glioma has been consistently observed within non-syndromic families. Our previous studies, which involved non-parametric and parametric linkage analyses, both yielded significant linkage peaks on chromosome 17q. Here, we use data from next generation and Sanger sequencing to identify familial glioma candidate genes and variants on chromosome 17q for further investigation. We applied a filtering schema to narrow the original list of 4830 annotated variants down to 21 very rare (<0.1% frequency), non-synonymous variants. Our findings implicate the MYO19 and KIF18B genes and rare variants in SPAG9 and RUNDC1 as candidates worthy of further investigation. Burden testing and functional studies are planned.

Gliomas are the most common brain tumor, with several histological subtypes of various malignancy grade. The genetic contribution to familial glioma is not well understood. Using whole exome sequencing of 90 individuals from 55 families, we identified two families with mutations in POT1 (p.G95C, p.E450X), a member of the telomere shelterin complex, shared by both affected individuals in each family and predicted to impact DNA binding and TPP1 binding, respectively. Validation in a separate cohort of 264 individuals from 246 families identified an additional mutation in POT1 (p.D617Efs), also predicted to disrupt TPP1 binding. All families with POT1 mutations had affected members with oligodendroglioma, a specific subtype of glioma more sensitive to irradiation. These findings are important for understanding the origin of glioma and could have importance for the future diagnostics and treatment of glioma., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Background: The role of telomerase reverse transcriptase (TERT) in gliomagenesis has been recently further strengthened by the frequent occurrence of TERT promoter mutations (TERTp-mut) in gliomas and evidence that the TERT SNP genetic rs2736100 influences glioma risk. TERTp-mut creates a binding site for Ets/TCF transcription factors, whereas the common rs2853669 polymorphism disrupts another Ets/TCF site on TERT promoter., Methods: We sequenced for TERTp-mut in 807 glioma DNAs and in 235 blood DNAs and analysed TERT expression by RT-PCR in 151 samples. TERTp-mut status and TERTp polymorphism rs2853669 were correlated with histology, genomic profile, TERT mRNA expression, clinical outcome and rs2736100 genotype., Results: TERTp-mut identified in 60.8% of gliomas (491 out of 807) was globally associated with poorer outcome (Hazard ratio (HR)=1.50). We defined, based on TERTp-mut and IDH mutation status, four prognostic groups: (1) TERTp-mut and IDH-mut associated with 1p19q codeletion, overall survival (OS)>17 years; (2) TERTp-wt and IDH-mut, associated with TP53 mutation, OS=97.5 months; (3) TERTp-wt and IDH-wt, with no specific association, OS=31.6 months; (4) TERTp-mut and IDH-wt, associated with EGFR amplification, OS=15.4 months. TERTp-mut was associated with higher TERT mRNA expression, whereas the rs2853669 variant was associated with lower TERT mRNA expression. The mutation of CIC (a repressor of ETV1-5 belonging to the Ets/TCF family) was also associated with TERT mRNA upregulation., Conclusions: In addition to IDH mutation status, defining the TERTp-mut status of glial tumours should afford enhanced prognostic stratification of patients with glioma. We also show that TERTp-mut, rs2853669 variant and CIC mutation influence Tert expression. This effect could be mediated by Ets/TCF transcription factors.

Background: Although familial susceptibility to glioma is known, the genetic basis for this susceptibility remains unidentified in the majority of glioma-specific families. An alternative approach to identifying such genes is to examine cancer pedigrees, which include glioma as one of several cancer phenotypes, to determine whether common chromosomal modifications might account for the familial aggregation of glioma and other cancers., Methods: Germline rearrangements in 146 glioma families (from the Gliogene Consortium; http://www.gliogene.org/) were examined using multiplex ligation-dependent probe amplification. These families all had at least 2 verified glioma cases and a third reported or verified glioma case in the same family or 2 glioma cases in the family with at least one family member affected with melanoma, colon, or breast cancer.The genomic areas covering TP53, CDKN2A, MLH1, and MSH2 were selected because these genes have been previously reported to be associated with cancer pedigrees known to include glioma., Results: We detected a single structural rearrangement, a deletion of exons 1-6 in MSH2, in the proband of one family with 3 cases with glioma and one relative with colon cancer., Conclusions: Large deletions and duplications are rare events in familial glioma cases, even in families with a strong family history of cancers that may be involved in known cancer syndromes., (© The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

We have previously identified tagSNPs at 8q24.21 influencing glioma risk. We have sought to fine-map the location of the functional basis of this association using data from four genome-wide association studies, comprising a total of 4147 glioma cases and 7435 controls. To improve marker density across the 700 kb region, we imputed genotypes using 1000 Genomes Project data and high-coverage sequencing data generated on 253 individuals. Analysis revealed an imputed low-frequency SNP rs55705857 (P = 2.24 × 10(-38)) which was sufficient to fully capture the 8q24.21 association. Analysis by glioma subtype showed the association with rs55705857 confined to non-glioblastoma multiforme (non-GBM) tumours (P = 1.07 × 10(-67)). Validation of the non-GBM association was shown in three additional datasets (625 non-GBM cases, 2412 controls; P = 1.41 × 10(-28)). In the pooled analysis, the odds ratio for low-grade glioma associated with rs55705857 was 4.3 (P = 2.31 × 10(-94)). rs55705857 maps to a highly evolutionarily conserved sequence within the long non-coding RNA CCDC26 raising the possibility of direct functionality. These data provide additional insights into the aetiological basis of glioma development.

Background: Most of the heritable risk of glioma is presently unaccounted for by mutations in known genes. In addition to rare inactivating germline mutations in TP53 causing glioma in the context of the Li-Fraumeni syndrome, polymorphic variation in TP53 may also contribute to the risk of developing glioma., Methods: To comprehensively evaluate the impact of variation in TP53 on risk, we analysed 23 tagSNPs and imputed 2377 unobserved genotypes in four series totaling 4147 glioma cases and 7435 controls., Results: The strongest validated association signal was shown by the imputed single-nucleotide polymorphism (SNP) rs78378222 (P=6.86 × 10(-24), minor allele frequency ~0.013). Confirmatory genotyping confirmed the high quality of the imputation. The association between rs78378222 and risk was seen for both glioblastoma multiforme (GBM) and non-GBM tumours. We comprehensively examined the relationship between rs78378222 and overall survival in two of the case series totaling 1699 individuals. Despite employing statistical tests sensitive to the detection of differences in early survival, no association was shown., Conclusion: Our data provided strong validation of rs78378222 as a risk factor for glioma but do not support the tenet that the polymorphism being a clinically useful prognostic marker. Acquired TP53 inactivation is a common feature of glioma. As rs78378222 changes the polyadenylation signal of TP53 leading to impaired 3'-end processing of TP53 mRNA, the SNP has strong plausibility for being directly functional contributing to the aetiological basis of glioma.

Background: Genome-wide association studies have identified single-nucleotide polymorphisms (SNPs) at 7 loci influencing glioma risk: rs2736100 (TERT), rs11979158 and rs2252586 (EGFR), rs4295627 (CCDC26), rs4977756 (CDKN2A/CDKN2B), rs498872 (PHLDB1), and rs6010620 (RTEL1)., Materials and Methods: We studied the relationship among these 7 glioma-risk SNPs and characteristics of tumors from 1374 patients, including grade, IDH (ie IDH1 or IDH2) mutation, EGFR amplification, CDKN2A-p16-INK4a homozygous deletion, 9p and 10q loss, and 1p-19q codeletion., Results: rs2736100 (TERT) and rs6010620 (RTEL1) risk alleles were associated with high-grade disease, EGFR amplification, CDKN2A-p16-INK4a homozygous deletion, and 9p and 10q deletion; rs4295627 (CCDC26) and rs498872 (PHLDB1) were associated with low-grade disease, IDH mutation, and 1p-19q codeletion. In contrast, rs4977756 (CDKN2A/B), rs11979158 (EGFR), and to a lesser extent, rs2252586 (EGFR) risk alleles were independent of tumor grade and genetic profile. Adjusting for tumor grade showed a significant association between rs2736100 and IDH status (P = .01), 10q loss (P = .02); rs4295627 and 1p-19q codeletion (P = .04), rs498872 and IDH (P = .02), 9p loss (P = .04), and 10q loss (P = .02). Case-control analyses stratified into 4 molecular classes (defined by 1p-19q status, IDH mutation, and EGFR amplification) showed an association of rs4295627 and rs498872 with IDH-mutated gliomas (P < 10(-3)) and rs2736100 and rs6010620 with IDH wild-type gliomas (P < 10(-3) and P = .03)., Conclusion: The frequency of EGFR and CDKN2A/B risk alleles were largely independent of tumor genetic profile, whereas TERT, RTEL1, CCDC26, and PHLDB1 variants were associated with different genetic profiles that annotate distinct molecular pathways. Our findings provide further insight into the biological basis of glioma etiology.

Background: While certain inherited syndromes (e.g. Neurofibromatosis or Li-Fraumeni) are associated with an increased risk of glioma, most familial gliomas are non-syndromic. This study describes the demographic and clinical characteristics of the largest series of non-syndromic glioma families ascertained from 14 centres in the United States (US), Europe and Israel as part of the Gliogene Consortium., Methods: Families with 2 or more verified gliomas were recruited between January 2007 and February 2011. Distributions of demographic characteristics and clinical variables of gliomas in the families were described based on information derived from personal questionnaires., Findings: The study population comprised 841 glioma patients identified in 376 families (9797 individuals). There were more cases of glioma among males, with a male to female ratio of 1.25. In most families (83%), 2 gliomas were reported, with 3 and 4 gliomas in 13% and 3% of the families, respectively. For families with 2 gliomas, 57% were among 1st-degree relatives, and 31.5% among 2nd-degree relatives. Overall, the mean (±standard deviation [SD]) diagnosis age was 49.4 (±18.7) years. In 48% of families with 2 gliomas, at least one was diagnosed at <40y, and in 12% both were diagnosed under 40y of age. Most of these families (76%) had at least one grade IV glioblastoma multiforme (GBM), and in 32% both cases were grade IV gliomas. The most common glioma subtype was GBM (55%), followed by anaplastic astrocytoma (10%) and oligodendroglioma (8%). Individuals with grades I-II were on average 17y younger than those with grades III-IV., Interpretation: Familial glioma cases are similar to sporadic cases in terms of gender distribution, age, morphology and grade. Most familial gliomas appear to comprise clusters of two cases suggesting low penetrance, and that the risk of developing additional gliomas is probably low. These results should be useful in the counselling and clinical management of individuals with a family history of glioma., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Background: We propose a 2-step model-based approach, with correction for ascertainment, to linkage analysis of a binary trait with variable age of onset and apply it to a set of multiplex pedigrees segregating for adult glioma., Methods: First, we fit segregation models by formulating the likelihood for a person to have a bivariate phenotype, affection status and age of onset, along with other covariates, and from these we estimate population trait allele frequencies and penetrance parameters as a function of age (N = 281 multiplex glioma pedigrees). Second, the best fitting models are used as trait models in multipoint linkage analysis (N = 74 informative multiplex glioma pedigrees). To correct for ascertainment, a prevalence constraint is used in the likelihood of the segregation models for all 281 pedigrees. Then the trait allele frequencies are reestimated for the pedigree founders of the subset of 74 pedigrees chosen for linkage analysis., Results: Using the best-fitting segregation models in model-based multipoint linkage analysis, we identified 2 separate peaks on chromosome 17; the first agreed with a region identified by Shete and colleagues who used model-free affected-only linkage analysis, but with a narrowed peak: and the second agreed with a second region they found but had a larger maximum log of the odds (LOD)., Conclusions: Our approach was able to narrow the linkage peak previously published for glioma., Impact: We provide a practical solution to model-based linkage analysis for disease affection status with variable age of onset for the kinds of pedigree data often collected for linkage analysis.

The risk of glioma has consistently been shown to be increased twofold in relatives of patients with primary brain tumors (PBT). A recent genome-wide linkage study of glioma families provided evidence for a disease locus on 17q12-21.32, with the possibility of four additional risk loci at 6p22.3, 12p13.33-12.1, 17q22-23.2, and 18q23. To identify the underlying genetic variants responsible for the linkage signals, we compared the genotype frequencies of 5,122 SNPs mapping to these five regions in 88 glioma cases with and 1,100 cases without a family history of PBT (discovery study). An additional series of 84 familial and 903 non-familial cases were used to replicate associations. In the discovery study, 12 SNPs showed significant associations with family history of PBT (P < 0.001). In the replication study, two of the 12 SNPs were confirmed: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.031) and 17q12-21.32 SPOP rs650461 (P = 0.025). In the combined analysis of discovery and replication studies, the strongest associations were attained at four SNPs: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.0001), SOX5 rs7305773 (P = 0.0001) and STKY1 rs2418087 (P = 0.0003), and 17q12-21.32 SPOP rs6504618 (P = 0.0006). Further, a significant gene-dosage effect was found for increased risk of family history of PBT with these four SNPs in the combined data set (P(trend) <1.0 × 10(-8)). The results support the linkage finding that some loci in the 12p13.33-12.1 and 17q12-q21.32 may contribute to gliomagenesis and suggest potential target genes underscoring linkage signals.

Gliomas, which generally have a poor prognosis, are the most common primary malignant brain tumors in adults. Recent genome-wide association studies have shown that inherited susceptibility plays a role in the development of glioma. Although first-degree relatives of patients exhibit a two-fold increased risk of glioma, the search for susceptibility loci in familial forms of the disease has been challenging because the disease is relatively rare, fatal, and heterogeneous, making it difficult to collect sufficient biosamples from families for statistical power. To address this challenge, the Genetic Epidemiology of Glioma International Consortium (Gliogene) was formed to collect DNA samples from families with two or more cases of histologically confirmed glioma. In this study, we present results obtained from 46 U.S. families in which multipoint linkage analyses were undertaken using nonparametric (model-free) methods. After removal of high linkage disequilibrium single-nucleotide polymorphism, we obtained a maximum nonparametric linkage score (NPL) of 3.39 (P = 0.0005) at 17q12-21.32 and the Z-score of 4.20 (P = 0.000007). To replicate our findings, we genotyped 29 independent U.S. families and obtained a maximum NPL score of 1.26 (P = 0.008) and the Z-score of 1.47 (P = 0.035). Accounting for the genetic heterogeneity using the ordered subset analysis approach, the combined analyses of 75 families resulted in a maximum NPL score of 3.81 (P = 0.00001). The genomic regions we have implicated in this study may offer novel insights into glioma susceptibility, focusing future work to identify genes that cause familial glioma.

Background: Despite extensive research on the topic, glioma etiology remains largely unknown. Exploration of potential interactions between single-nucleotide polymorphisms (SNP) of immune genes is a promising new area of glioma research. The case-only study design is a powerful and efficient design for exploring possible multiplicative interactions between factors that are independent of one another. The purpose of our study was to use this exploratory design to identify potential pair wise SNP-SNP interactions from genes involved in several different immune-related pathways for investigation in future studies., Methods: The study population consisted of two case groups: 1,224 histologic confirmed, non-Hispanic white glioma cases from the United States and a validation population of 634 glioma cases from the United Kingdom. Polytomous logistic regression, in which one SNP was coded as the outcome and the other SNP was included as the exposure, was utilized to calculate the ORs of the likelihood of cases simultaneously having the variant alleles of two different SNPs. Potential interactions were examined only between SNPs located in different genes or chromosomes., Results: Using this data mining strategy, we found 396 significant SNP-SNP interactions among polymorphisms of immune-related genes that were present in both the U.S. and U.K. study populations., Conclusion: This exploratory study was conducted for the purpose of hypothesis generation, and thus has provided several new hypotheses that can be tested using traditional case-control study designs to obtain estimates of risk., Impact: This is the first study, to our knowledge, to take this novel approach to identifying SNP-SNP interactions relevant to glioma etiology., (©2011 AACR.)

While gliomas are the most common primary brain tumors, their etiology is largely unknown. To identify novel risk loci for glioma, we conducted genome-wide association (GWA) analysis of two case-control series from France and Germany (2269 cases and 2500 controls). Pooling these data with previously reported UK and US GWA studies provided data on 4147 glioma cases and 7435 controls genotyped for 424 460 common tagging single-nucleotide polymorphisms. Using these data, we demonstrate two statistically independent associations between glioma and rs11979158 and rs2252586, at 7p11.2 which encompasses the EGFR gene (population-corrected statistics, P(c) = 7.72 × 10(-8) and 2.09 × 10(-8), respectively). Both associations were independent of tumor subtype, and were independent of EGFR amplification, p16INK4a deletion and IDH1 mutation status in tumors; compatible with driver effects of the variants on glioma development. These findings show that variation in 7p11.2 is a determinant of inherited glioma risk.

Although epidemiological studies have suggested an association between atopy and glioma risk, these observations have been based on self-reporting of allergic conditions raising the possibility that associations may be noncausal and arise as a consequence of bias, reverse causation or other artifacts. Genetic information provides an alternative approach to investigate the relationship avoiding such biases. We analyzed 1,878 glioma cases and 3,670 controls for variants at 2q12, 5q12.1, 11q13 and 17q21 that are associated with asthma or eczema risk at p < 5.0 × 10(-7) . The SNP rs7216389, which tags the 3' flanking region of ORMDL3 at 17q21 and has been associated with childhood asthma, was correlated with increased glioma risk (OR = 1.10; 95% CI: 1.01-1.19). These data provide evidence for a correlation between asthma susceptibility and glioma risk and illustrate the value of using genetics as an investigative tool for developing etiological hypotheses., (Copyright © 2010 UICC.)

Purpose: Genome-wide association studies have recently identified single-nucleotide polymorphisms (SNP) in five loci at 5p15.33 (rs2736100, TERT), 8q24.21 (rs4295627, CCDC26), 9p21.3 (rs4977756, CDKN2A/CDKN2B), 20q13.33 (rs6010620, RTEL1), and 11q23.3 (rs498872, PHLDB1) to be associated with glioma risk. Because gliomas are heterogeneous in histology, molecular alterations, and clinical behavior, we have investigated these polymorphisms for potential correlations with tumor histology and patient survival., Experimental Design: We studied the relationship between SNPs and glioma subtype in two large patient cohorts from France and Germany, totaling 1,577 patients, as well as the relationship between SNP genotype and overall survival., Results: In both cohorts, the frequencies of rs2736100 and rs6010620 risk genotypes were highly correlated with high-grade disease (P < 0.001), whereas rs4295627 and rs498872 risk genotypes were inversely related to tumor grade (P < 0.001). These data show that genetic variations at these loci have subtype-specific effects on the risk of developing glioma. In contrast, the rs4977756 genotype was not correlated with tumor grade, consistent with the causal variant having a generic influence on glioma development. None of the five SNPs was associated with prognosis independent of tumor grade., Conclusions: Our findings provide novel insight into etiologic pathways in the different glioma subtypes., (©2010 AACR.)

There is increasing recognition of familial propensity to glioma as a distinct clinical entity beyond a few rare syndromes; however its genetic basis is poorly understood. The role of p16(INK4A)/p14(ARF) and p53 mutations in sporadic glioma provides a strong rationale for investigating germline mutations in these genes as a cause of familial glioma. To survey the familial glioma phenotype and examine the contribution of germline mutation in p16(INK4A)/p14(ARF) and p53 to the disease we have analyzed a series of 101 index familial cases collected through the GLIOGENE Consortium (http://braintumor.epigenetic.org/). There was little evidence for within family correlations for tumour histology, suggesting generic susceptibility to glial tumors. We did not detect any functional mutations in p16(INK4A) or p14(ARF). One index case with glioblastoma multiforme (GBM) diagnosed at age 54 and had a family history comprised of a paternal aunt with GBM at age 55, carried the p53 R158H mutation, which is predicted to be functional and has previously been implicated as a cause of Li-Fraumeni syndrome. Our findings provide no evidence that p16(INK4A)/p14(ARF) and p53 mutations contribute significantly to familial glioma.

The etiology of glioma is barely known. Epidemiologic studies have provided evidence for an inverse relation between glioma risk and allergic disease. Genome-wide association data have identified common genetic variants at 5p15.33 (rs2736100, TERT), 8q24.21 (rs4295627, CCDC26), 9p21.3 (rs4977756, CDKN2A-CDKN2B), 11q23.3 (rs498872, PHLDB1), and 20q13.33 (rs6010620, RTEL1) as determinants of glioma risk. The authors investigated whether there is interaction between the effects of allergy and these 5 variants on glioma risk. Data from 5 case-control studies carried out in Denmark, Finland, Sweden, and the United Kingdom (2000-2004) were used, totaling 1,029 cases and 1,668 controls. Risk was inversely associated with asthma, hay fever, eczema, and "any allergy," significantly for each factor except asthma, and was significantly positively associated with number of risk alleles for each of the 5 single nucleotide polymorphisms. There was interaction between asthma and rs498872 (greater protective effect of asthma with increasing number of risk alleles; per-allele interaction odds ratio (OR) = 0.65, P = 0.041), between "any allergy" and rs4977756 (smaller protective effect; interaction OR = 1.27, P = 0.047), and between "any allergy" and rs6010620 (greater protective effect; interaction OR = 0.70, P = 0.017). Case-only analyses provided further support for atopy interactions for rs4977756 and rs498872. This study provides evidence for possible gene-environment interactions in glioma development.

The study of inherited susceptibility to cancer has been one of the most informative areas of research in the past decade. Most of the cancer genetics studies have been focused on the common tumors such as breast and colorectal cancers. As the allelic architecture of these tumors is unraveled, research attention is turning to other rare cancers such as glioma, which are also likely to have a major genetic component as the basis of their development. In this brief review we discuss emerging data on glioma whole genome-association searches to identify risk loci. Two glioma genome-wide association studies have so far been reported. Our group identified 5 risk loci for glioma susceptibility (TERT rs2736100, CCDC26 rs4295627, CDKN2A/CDKN2B rs4977756, RTEL1 rs6010620, and PHLDB1 rs498872). Wrensch and colleagues provided further evidence to 2 risk loci (CDKN2B rs1412829 and RTEL1 rs6010620) for GBM and anaplastic astrocytoma. Although these data provide the strongest evidence to date for the role of common low-risk variants in the etiology of glioma, the single-nucleotide polymorphisms identified alone are unlikely to be candidates for causality. Identifying the causal variant at each specific locus and its biological impact now poses a significant challenge, contingent on a combination of fine mapping and functional analyses. Finally, we hope that a greater understanding of the biological basis of the disease will lead to the development of novel therapeutic interventions.

To identify risk variants for glioma, we conducted a meta-analysis of two genome-wide association studies by genotyping 550K tagging SNPs in a total of 1,878 cases and 3,670 controls, with validation in three additional independent series totaling 2,545 cases and 2,953 controls. We identified five risk loci for glioma at 5p15.33 (rs2736100, TERT; P = 1.50 x 10(-17)), 8q24.21 (rs4295627, CCDC26; P = 2.34 x 10(-18)), 9p21.3 (rs4977756, CDKN2A-CDKN2B; P = 7.24 x 10(-15)), 20q13.33 (rs6010620, RTEL1; P = 2.52 x 10(-12)) and 11q23.3 (rs498872, PHLDB1; P = 1.07 x 10(-8)). These data show that common low-penetrance susceptibility alleles contribute to the risk of developing glioma and provide insight into disease causation of this primary brain tumor.