Purpose

Gliomas are one of the most fatal malignancies, with largely unknown etiology. This study examines a possible connection between glioma and melanoma, which might provide insight into gliomas' etiology.

Methods

Using data provided by the Surveillance, Epidemiology, and End Results program from 1992 to 2009, a cohort was constructed to determine the incidence rates of glioma among those who had a prior diagnosis of invasive melanoma. Glioma rates in those with prior melanoma were compared with those in the general population.

Results

The incidence rate of all gliomas was greater among melanoma cases than in the general population: 10.46 versus 6.13 cases per 100,000 person-years, standardized incidence ratios = 1.42 (1.22-1.62). The female excess rate was slightly greater (42%) than that among males (29%). Sensitivity analyses did not reveal evidence that radiation treatment of melanoma is responsible for the detected gap in the rates of gliomas.

Conclusions

Our analysis documented increased risk of glioma among melanoma patients. Because no common environmental risk factors are identified for glioma and melanoma, it is hypothesized that a common genetic predisposition may be responsible for the detected association.

Purpose

The incidences of atopic conditions (allergies, asthma, or eczema) and glioma vary by ethnicity. Atopic conditions are inversely associated with gliomas. We conducted a pooled multisite study investigating the associations of atopic conditions with glioma in different race/ethnicity groups.

Methods

Using glioma cases and healthy controls, unconditional logistic regression was conducted to assess the associations of atopic conditions with glioma separately in white, black, Asian, and Hispanic subpopulations. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated.

Results

Glioblastoma multiforme cases were less likely than controls to report a history of atopic conditions in whites (OR = 0.46, [95% CI, 0.38-0.54]) and Asians (OR = 0.27, [95% CI, 0.10-0.73]). The same trend was seen when looking at glioma cases of all histologies. An inverse association was not seen in blacks for glioblastoma multiforme or all histologies combined.

Conclusions

The inverse association between glioma and atopic conditions may vary by ethnicity due to a difference in the biology of atopic conditions in different ethnicities but may be due to chance because of the limitations of small nonwhite sample sizes.

Purpose

The association between female reproductive factors and glioma risk is unclear, but most published studies have been limited by small sample size. We conducted a pooled multisite study of pre- and postmenopausal women, investigating the effect of female reproductive factors, including hormonal medications.

Methods

Unconditional logistic regression was used to calculate odds ratios (ORs) and 95 % confidence intervals (95 % CIs) assessing the effects of female reproductive factors and female hormonal medications in glioma cases and unrelated controls.

Results

Menarche over the age of 15 as compared to under 12 was associated with a statistically significant risk for glioma (OR 2.00, 95 % CI 1.47-2.71). Use of oral contraceptive pills (OCP) was inversely associated with risk of glioma (OR 0.61, 95 % CI 0.50-0.74), and there was an inverse trend with longer duration of OCP use (p for trend <0.0001). Use of hormone replacement therapy (HRT) was also inversely associated with risk of glioma (OR 0.55, 95 % CI 0.44-0.68), and there was an inverse trend with longer duration of use (p for trend <0.0001). Compared to those reporting neither OCP use nor HRT use, those who reported using both were less likely to have a diagnosis of glioma (OR 0.34, 95 % CI 0.24-0.48).

Conclusions

Female reproductive hormones may decrease the risk for glioma. The association appears to be strongest with greater length of use and use of both HRT and OCP.

Abstract Background Malignant glioma is a rare cancer with poor survival. The influence of diet and antioxidant intake on glioma survival is not well understood. The current study examines the association between antioxidant intake and survival after glioma diagnosis. Methods Adult patients diagnosed with malignant glioma during 1991-1994 and 1997-2001 were enrolled in a population-based study. Diagnosis was confirmed by review of pathology specimens. A modified food-frequency questionnaire interview was completed by each glioma patient or a designated proxy. Intake of each food item was converted to grams consumed/day. From this nutrient database, 16 antioxidants, calcium, a total antioxidant index and 3 macronutrients were available for survival analysis. Cox regression estimated mortality hazard ratios associated with each nutrient and the antioxidant index adjusting for potential confounders. Nutrient values were categorized into tertiles. Models were stratified by histology (Grades II, III, and IV) and conducted for all (including proxy) subjects and for a subset of self-reported subjects. Results Geometric mean values for 11 fat-soluble and 6 water-soluble individual antioxidants, antioxidant index and 3 macronutrients were virtually the same when comparing all cases (n = 748) to self-reported cases only (n = 450). For patients diagnosed with Grade II and Grade III histology, moderate (915.8-2118.3 mcg) intake of fat-soluble lycopene was associated with poorer survival when compared to low intake (0.0-914.8 mcg), for self-reported cases only. High intake of vitamin E and moderate/high intake of secoisolariciresinol among Grade III patients indicated greater survival for all cases. In Grade IV patients, moderate/high intake of cryptoxanthin and high intake of secoisolariciresinol were associated with poorer survival among all cases. Among Grade II patients, moderate intake of water-soluble folate was associated with greater survival for all cases; high intake of vitamin C and genistein and the highest level of the antioxidant index were associated with poorer survival for all cases. Conclusions The associations observed in our study suggest that the influence of some antioxidants on survival following a diagnosis of malignant glioma are inconsistent and vary by histology group. Further research in a large sample of glioma patients is needed to confirm/refute our results.

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.

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.

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.

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.

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.

Glioblastoma (GBM) is the most common malignant brain tumor in the United States. Incidence of GBM increases with age, and younger age-at-diagnosis is significantly associated with improved prognosis. While the relationship between candidate GBM risk SNPs and age-at-diagnosis has been explored, genome-wide association studies (GWAS) have not previously been stratified by age. Potential age-specific genetic effects were assessed in autosomal SNPs for GBM patients using data from four previous GWAS. Using age distribution tertiles (18-53, 54-64, 65+) datasets were analyzed using age-stratified logistic regression to generate p values, odds ratios (OR), and 95% confidence intervals (95%CI), and then combined using meta-analysis. There were 4,512 total GBM cases, and 10,582 controls used for analysis. Significant associations were detected at two previously identified SNPs in 7p11.2 (rs723527 [p_54-63 = 1.50x10^-9 , OR_54-63 = 1.28, 95%CI_54-63 = 1.18-1.39; p₆₄₊ = 2.14x10^-11 , OR₆₄₊ = 1.32, 95%CI₆₄₊ = 1.21-1.43] and rs11979158 [p_54-63 = 6.13x10^-8 , OR_54-63 = 1.35, 95%CI_54-63 = 1.21-1.50; p₆₄₊ = 2.18x10^-10 , OR₆₄₊ = 1.42, 95%CI₆₄₊ = 1.27-1.58]) but only in persons >54. There was also a significant association at the previously identified lower grade glioma (LGG) risk locus at 8q24.21 (rs55705857) in persons ages 18-53 (p_18-53 = 9.30 × 10^-11 , OR_18-53 = 1.76, 95%CI_18-53 = 1.49-2.10). Within The Cancer Genome Atlas (TCGA) there was higher prevalence of 'LGG'-like tumor characteristics in GBM samples in those 18-53, with IDH1/2 mutation frequency of 15%, as compared to 2.1% [54-63] and 0.8% [64+] (p = 0.0005). Age-specific differences in cancer susceptibility can provide important clues to etiology. The association of a SNP known to confer risk for IDH1/2 mutant glioma and higher prevalence of IDH1/2 mutation within younger individuals 18-53 suggests that more younger individuals may present initially with 'secondary glioblastoma.'