| 1. |
- Antoniou, Antonis C., et al.
(author)
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A locus on 19p13 modifies risk of breast cancer in BRCA1 mutation carriers and is associated with hormone receptor-negative breast cancer in the general population
- 2010
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 42:10, s. 885-892
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Journal article (peer-reviewed)abstract
- Germline BRCA1 mutations predispose to breast cancer. To identify genetic modifiers of this risk, we performed a genome-wide association study in 1,193 individuals with BRCA1 mutations who were diagnosed with invasive breast cancer under age 40 and 1,190 BRCA1 carriers without breast cancer diagnosis over age 35. We took forward 96 SNPs for replication in another 5,986 BRCA1 carriers (2,974 individuals with breast cancer and 3,012 unaffected individuals). Five SNPs on 19p13 were associated with breast cancer risk (P-trend = 2.3 x 10(-9) to Ptrend = 3.9 x 10(-7)), two of which showed independent associations (rs8170, hazard ratio (HR) = 1.26, 95% CI 1.17-1.35; rs2363956 HR = 0.84, 95% CI 0.80-0.89). Genotyping these SNPs in 6,800 population-based breast cancer cases and 6,613 controls identified a similar association with estrogen receptor-negative breast cancer (rs2363956 per-allele odds ratio (OR) = 0.83, 95% CI 0.75-0.92, P-trend = 0.0003) and an association with estrogen receptor-positive disease in the opposite direction (OR = 1.07, 95% CI 1.01-1.14, P-trend = 0.016). The five SNPs were also associated with triple-negative breast cancer in a separate study of 2,301 triple-negative cases and 3,949 controls (Ptrend = 1 x 10(-7) to Ptrend = 8 x 10(-5); rs2363956 per-allele OR = 0.80, 95% CI 0.74-0.87, P-trend = 1.1 x 10(-7)).
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| 2. |
- Atkins, Isabelle, et al.
(author)
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Transcriptome-Wide Association Study Identifies New Candidate Susceptibility Genes for Glioma
- 2019
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In: Cancer Research. - : American Association for Cancer Research. - 0008-5472 .- 1538-7445. ; 79:8, s. 2065-2071
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Journal article (peer-reviewed)abstract
- 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 x 10(-6), candidate novel risk locus for GBM (mean Z = 4.43; P = 5.68 x 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.
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| 3. |
- Disney-Hogg, Linden, et al.
(author)
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Impact of atopy on risk of glioma : a Mendelian randomisation study
- 2018
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In: BMC Medicine. - : BioMed Central. - 1741-7015. ; 16
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Journal article (peer-reviewed)abstract
- 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.
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| 4. |
- Disney-Hogg, Linden, et al.
(author)
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Influence of obesity-related risk factors in the aetiology of glioma
- 2018
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In: British Journal of Cancer. - : Nature Publishing Group. - 0007-0920 .- 1532-1827. ; 118:7, s. 1020-1027
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Journal article (peer-reviewed)abstract
- 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.
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| 5. |
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| 6. |
- Eckel-Passow, Jeanette E., et al.
(author)
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Using germline variants to estimate glioma and subtype risks
- 2019
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In: Neuro-Oncology. - : Oxford University Press. - 1522-8517 .- 1523-5866. ; 21:4, s. 451-461
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Journal article (peer-reviewed)abstract
- Background: Twenty-five single nucleotide polymorphisms (SNPs) are associated with adult diffuse glioma risk. We hypothesized that the inclusion of these 25 SNPs with age at diagnosis and sex could estimate risk of glioma as well as identify glioma subtypes.Methods: Case-control design and multinomial logistic regression were used to develop models to estimate the risk of glioma development while accounting for histologic and molecular subtypes. Case-case design and logistic regression were used to develop models to predict isocitrate dehydrogenase (IDH) mutation status. A total of 1273 glioma cases and 443 controls from Mayo Clinic were used in the discovery set, and 852 glioma cases and 231 controls from UCSF were used in the validation set. All samples were genotyped using a custom Illumina OncoArray.Results: Patients in the highest 5% of the risk score had more than a 14-fold increase in relative risk of developing an IDH mutant glioma. Large differences in lifetime absolute risk were observed at the extremes of the risk score percentile. For both IDH mutant 1p/19q non-codeleted glioma and IDH mutant 1p/19q codeleted glioma, the lifetime risk increased from almost null to 2.3% and almost null to 1.7%, respectively. The SNP-based model that predicted IDH mutation status had a validation concordance index of 0.85.Conclusions: These results suggest that germline genotyping can provide new tools for the initial management of newly discovered brain lesions. Given the low lifetime risk of glioma, risk scores will not be useful for population screening; however, they may be useful in certain clinically defined high-risk groups.
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| 7. |
- Eckel-Passow, Jeanette, et al.
(author)
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USING GERMLINE VARIANTS TO PREDICT GLIOMA RISK AND IDENTIFY GLIOMA SUBTYPE PRE-OPERATIVELY
- 2018
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In: Neuro-Oncology. - : OXFORD UNIV PRESS INC. - 1522-8517 .- 1523-5866. ; 20, s. 82-82
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Journal article (other academic/artistic)abstract
- To date, 25 single nucleotide polymorphisms (SNPs) have been shown to be associated with overall glioma risk or with risk of specific subtypes of glioma. We hypothesized that the inclusion of these 25 SNPs with patient age at diagnosis and sex could predict risk of glioma as well as predict IDH mutation status. Thus, case-control design and multinomial logistic regression were used to develop models to estimate the risk of glioma development while accounting for molecular subtypes. Case-case design and logistic regression were used to develop models to predict IDH mutation status. Each model included all 25 glioma risk SNPs, patient age at diagnosis and sex. A total of 1273 glioma cases and 443 controls from Mayo Clinic were used in the discovery set, and 852 glioma cases and 231 controls from UCSF were used in the validation set. All samples were genotyped using a custom Illumina OncoArray. We observed that patients in the highest 5% of the risk score had more than a 14-fold increased relative risk of developing an IDH-mutant glioma, compared to patients with median risk score. Large differences in lifetime absolute risk were observed at the extremes of the risk score percentile categories. For both IDH-mutated 1p/19q non-codeleted glioma and IDH-mutated 1p/19q-codeleted glioma, the lifetime risk increased from almost null to 2.3% and almost null to 1.7%, respectively. The SNP-based model that predicted IDH mutation status had a validation c-index of 0.85. These results suggest that germline genotyping has the potential to provide a new tool for clinicians for the initial management of newly-discovered brain lesions. Specifically, given the low lifetime risk of glioma, SNP-based risk scores should not be useful for general population screening. However, with further research these risk scores may be useful in certain clinically-defined high-risk groups.
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| 8. |
- Johansson, Mattias, et al.
(author)
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The influence of obesity-related factors in the etiology of renal cell carcinoma—A mendelian randomization study
- 2019
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In: PLoS Medicine. - : Public Library of Science (PLoS). - 1549-1277 .- 1549-1676. ; 16:1
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Journal article (peer-reviewed)abstract
- Background: Several obesity-related factors have been associated with renal cell carcinoma (RCC), but it is unclear which individual factors directly influence risk. We addressed this question using genetic markers as proxies for putative risk factors and evaluated their relation to RCC risk in a mendelian randomization (MR) framework. This methodology limits bias due to confounding and is not affected by reverse causation.Methods and findings: Genetic markers associated with obesity measures, blood pressure, lipids, type 2 diabetes, insulin, and glucose were initially identified as instrumental variables, and their association with RCC risk was subsequently evaluated in a genome-wide association study (GWAS) of 10,784 RCC patients and 20,406 control participants in a 2-sample MR framework. The effect on RCC risk was estimated by calculating odds ratios (ORSD) for a standard deviation (SD) increment in each risk factor. The MR analysis indicated that higher body mass index increases the risk of RCC (ORSD: 1.56, 95% confidence interval [CI] 1.44–1.70), with comparable results for waist-to-hip ratio (ORSD: 1.63, 95% CI 1.40–1.90) and body fat percentage (ORSD: 1.66, 95% CI 1.44–1.90). This analysis further indicated that higher fasting insulin (ORSD: 1.82, 95% CI 1.30–2.55) and diastolic blood pressure (DBP; ORSD: 1.28, 95% CI 1.11–1.47), but not systolic blood pressure (ORSD: 0.98, 95% CI 0.84–1.14), increase the risk for RCC. No association with RCC risk was seen for lipids, overall type 2 diabetes, or fasting glucose.Conclusions: This study provides novel evidence for an etiological role of insulin in RCC, as well as confirmatory evidence that obesity and DBP influence RCC risk.
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| 9. |
- Melin, Beatrice S., et al.
(author)
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Genome-wide association study of glioma subtypes identifies specific differences in genetic susceptibility to glioblastoma and non-glioblastoma tumors
- 2017
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 49:5, s. 789-794
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Journal article (peer-reviewed)abstract
- 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 x 10(-9), odds ratio (OR) = 1.22), 11q14.1 (rs11233250; P = 9.95 x 10(-10), OR = 1.24), 16p13.3 (rs2562152; P = 1.93 x 10-8, OR = 1.21), 16q12.1 (rs10852606; P = 1.29 x 10(-11), OR = 1.18) and 22q13.1 (rs2235573; P = 1.76 x 10(-10), OR = 1.15), as well as eight loci for non-GBM tumors at 1q32.1 (rs4252707; P = 3.34 x 10(-9), OR = 1.19), 1q44 (rs12076373; P = 2.63 x 10(-10), OR = 1.23), 2q33.3 (rs7572263; P = 2.18 x 10(-10), OR = 1.20), 3p14.1 (rs11706832; P = 7.66 x 10(-9), OR = 1.15), 10q24.33 (rs11598018; P = 3.39 x 10-8, OR = 1.14), 11q21 (rs7107785; P = 3.87 x 10(-10), OR = 1.16), 14q12 (rs10131032; P = 5.07 x 10(-11), OR = 1.33) and 16p13.3 (rs3751667; P = 2.61 x 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.
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| 10. |
- Ostrom, Quinn, et al.
(author)
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PREVIOUSLY IDENTIFIED COMMON GLIOMA RISK SNPs ARE ASSOCIATED WITH FAMILIAL GLIOMA
- 2018
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In: Neuro-Oncology. - : OXFORD UNIV PRESS INC. - 1522-8517 .- 1523-5866. ; 20, s. 108-108
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Journal article (other academic/artistic)abstract
- BACKGROUND: Approximately 5% of gliomas occur in individuals with a family history of glioma, and first-degree relatives of brain tumor cases have a two-fold increase in risk of brain tumor. Family-based studies have had little success in identifying high penetrance risk variants. Recent somatic characterization has shown that tumors from familial cases are indistinguishable from sporadic cases, suggesting that familial cases may arise through similar mechanisms of gliomagenesis, and therefore may be associated with common variants as well as rare mutations. In this analysis, we assessed whether previously identified common risk variants are associated with familial glioma. METHODS: Data were obtained from the Glioma International Case Control (GICC) Study for 447 familial cases and 3,286 controls. We assessed 25 risk loci previously identified by glioma GWAS, and odds ratios (OR) and 95% confidence intervals (95%CI) were calculated using an additive genetic logistic regression model adjusted for age, sex, and the first principal component. Results were considered significant at p TERT, EGFR, CCDC26, CDKN2B, TP53, and RTEL1. The strongest association was at rs55705857 (CCDC26, OR=2.5, p=1.14x10-14). These SNPs were further examined using a caseonly approach comparing familial to non-familial cases, and there was no significant difference in allele frequencies by family history status. CONCLUSIONS: In this analysis we identified a significant association between familial glioma and six common risk variants previously identified by glioma GWAS. This provides further evidence of shared pathways of genetic risk and gliomagenesis between familial and non-familial glioma. Further exploration is necessary to determine the overall contribution of common genetic variation to risk of familial glioma.
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