Armstrong, Georgina

Abstract BACKGROUND: Incidence of glioma varies significantly by sex, and most glioma histologies occur with greater incidence in males. Previous analyses have examined the impact of estrogen exposure as a risk factor for these tumors, but have found results of varying significance and low effect size. There may be differences in effect of previously discovered risk alleles that contribute to sex differences. METHODS: Using data collected for three previous glioma GWAS in European-ancestry populations (MD Anderson Cancer Center, the San Francisco Adult Glioma Study, and the Glioma International Case Control Study) we assessed sex-specific effects for 14 previously identified and 13 newly identified glioma risk SNPs (27 total) overall and for glioblastoma (GBM) and non-GBM tumors separately. There were 3,892 male cases (59% GBM), 4,522 male controls, 2,500 female cases (52% GBM) and 4,940 female controls. Sex-specific odds ratios (ORM and ORF), 95% confidence intervals (95% CI) and p values (pM and pF) were generated using stratified logistic regression models. Data from each study were analyzed separately and combined using inverse variance weighted meta-analysis. Results were considered statistically significant at p<6.2x10-4. RESULTS: In GBM, rs11979158 (7p11.2, pM=1.01x10-10, ORM=1.43 [95% CI: 1.28-1.59]; pF=3.43x10-3, ORF=1.22 [95% CI: 1.07-1.39]) and rs2562152 (16p13.3, pM=5.59x10-4, ORM=1.23 [95% CI: 1.09-1.39]; pF=1.22x10-1, ORF=1.12 [95% CI: 0.97-1.29]) had significant effect in males only. In non-GBM gliomas, rs12076373 (1q44, pM=3.56x10-7, ORM=1.41, 95% CI: 1.23-1.61; pF=1.76x10-2, ORF=1.20, 95% CI: 1.03-1.38), rs11979158 (7p11.2, pM=1.77x10-5, ORM=1.32 [95% CI: 1.16-1.49]; pF=2.73x10-1, ORF=1.08 [95% CI: 0.94-1.24]), and rs3751667 (16p13.3, pM=9.44x10-7, ORM=1.30 [95% CI: 1.17-1.44]; pF=5.18x10-2, ORF=1.13 [95% CI: 1.00-1.28]) had significant effect in males only. Effect size for rs55705857 (8q24.21) varied significantly by sex, with ORM=2.63 (95% CI: 2.24-3.09, pM=4.42x10-32), as compared to ORF=3.95 (95% CI: 3.28-4.76, pF=1.82x10-47). A sensitivity analysis was performed due to allele frequency heterogeneity by study and results did not change. CONCLUSIONS: Sex differences and other demographic differences in cancer susceptibility can provide important clues to etiology, and these differences can be leveraged for discovery in genetic association studies. Significant differences in effect size may suggest variation in genetic effect of risk alleles or in unidentified risk factors that vary in prevalence or effect by sex. There may also be differences in the distribution of molecular subtypes within each histology by sex. Further investigation using an agnostic approach may further elucidate the relationship between effect of risk alleles and sex. Citation Format: Quinn T. Ostrom, Ben Kinnersley, Margaret Wrensch, Jeanette E. Eckel-Passow, Georgina Armstrong, Terri Rice, Yanwen Chen, John Wiencke, Lucie McCoy, Helen Hansen, Christopher Amos, Jonine L. Bernstein, Elizabeth B. Claus, Dora Il'yasova, Christoffer Johansen, Daniel Lachance, Rose Lai, Ching C. Lau, Ryan T. Merrell, Sara H. Olson, Siegal Sadetzki, Joellen Schildkraut, Sanjay Shete, Richard S. Houlston, Robert B. Jenkins, Beatrice Melin, Melissa Bondy, Jill S. Barnholtz-Sloan. Estimating sex-specific effects of genetic loci associated with glioma risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1315. doi:10.1158/1538-7445.AM2017-1315

Abstract Background: Numerous epidemiologic studies have examined the association between aspirin (ASA), non-steroid anti-inflammatory drugs (NSAIDs) and the development of glioma, but the results have been inconsistent. The goal of this study was to evaluate the relationship between the intake of these drugs and glioma risk in a large, international case-control study. Methods: Between 2010 and 2015, the Glioma International Case-Control Study (GICC) recruited newly diagnosed glioma cases and matched controls in 14 different sites across five countries. Each subject was interviewed using a standardized questionnaire to obtain NSAIDs and ASA use. We examined the associations between ever use (at least > 6 months), duration of drug use and glioma histology. Ever use data on 4533 glioma cases and 4171 controls was combined using maximum likelihood estimation/restricted maximum likelihood meta-analysis methods. Furthermore, based on a priori hypotheses, we performed subgroup analyses based on gender and glioma histological grades. Results: Use of ASA for > 6 months was associated with a 33% lower glioma risk compared to those who never took it (adjusted Meta-OR 0.67, 95% CI 0.54-0.83). Duration of intake showed a significant trend test (p < 0.0001), with ORs became lower for increasing number of years of ASA use. In subgroup analyses, intake of ASA was significantly associated with glioma risk in both men and women (adjusted Meta-OR = 0.65, 95% CI 0.51-0.84 for men; adjusted Meta-OR = 0.74, 95% CI 0.58-0.93 for women). ASA intake was protective for grade IV glioma (glioblastoma) and grade II/III glioma (adjusted meta-OR 0.63, 95% CI 0.5-0.8 for glioblastoma; adjusted meta-OR 0.67, 95% CI 0.50 - 0.89 for grade II/III glioma). For NSAIDs intake, ever use > 6 months was not associated with glioma risk (adjusted meta-OR 0.87, 95% CI 0.71-1.07). However, NSAIDs use was protective for women (adjusted meta-OR 0.72, 95% CI 0.55-0.93) in subgroup analyses but not for men (adjusted meta-OR 1.03; 95% CI 0.86-1.23). The interaction between gender, NSAIDs and glioma risk was significant (p-value 0.0076).. Sensitivity analyses excluding those who took ASA or NSAIDs within the past 12 months for headache, and the removal of proxy respondents did not change our results. Conclusion: ASA was associated with a significant protective effect for glioma, but NSAIDs were only associated with reduced glioma risk in women. Given the possibility of recall bias in case-control studies of brain tumors, we may verify dosage and duration of drug intake in those countries with electronic pharmacy records within the GICC. Citation Format: Rose K. Lai, Renke Zhou, E. Susan Amirian, Christoffer Johansen, Michael E. Scheurer, Georgina N. Armstrong, Ching C. Lau, Elizabeth B. Claus, Jill S. Barnholtz-Sloan, Dora Il’yasova, Joellen Schildkraut, Francis Ali-Osman, Siegal Sadetzki, Richard Houlston, Robert B. Jenkins, Daniel Lachance, Sara H. Olson, Jonine L. Bernstein, Ryan T. Merrell, Margaret R. Wrensch, Faith G. Davis, Sanjay Shete, Christopher I. Amos, Beatrice S. Melin, Melissa Bondy. Aspirin, non-steroidal anti-inflammatory drugs (NSAIDs) and the risk of glioma: Results from the Glioma International Case Control Study. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3446.

AbstractVaricella zoster virus (VZV) is a neurotropic α‐herpesvirus that causes chickenpox and establishes life‐long latency in the cranial nerve and dorsal root ganglia of the host. To date, VZV is the only virus consistently reported to have an inverse association with glioma. The Glioma International Case‐Control Study (GICC) is a large, multisite consortium with data on 4533 cases and 4171 controls collected across five countries. Here, we utilized the GICC data to confirm the previously reported associations between history of chickenpox and glioma risk in one of the largest studies to date on this topic. Using two‐stage random‐effects restricted maximum likelihood modeling, we found that a positive history of chickenpox was associated with a 21% lower glioma risk, adjusting for age and sex (95% confidence intervals (CI): 0.65–0.96). Furthermore, the protective effect of chickenpox was stronger for high‐grade gliomas. Our study provides additional evidence that the observed protective effect of chickenpox against glioma is unlikely to be coincidental. Future studies, including meta‐analyses of the literature and investigations of the potential biological mechanism, are warranted.

Abstract 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. Cancer Epidemiol Biomarkers Prev; 25(2); 282–90. ©2016 AACR.

Abstract Background: Recent genome-wide association studies (GWAS) have identified 28 susceptibility loci for Lung cancer (LC), 32 loci for smoking behavior, 10 loci for chronic obstructive pulmonary disease (COPD), 63 loci for pulmonary function and related phenotypes, totaling 107 GWAS susceptibility loci (as of November 2014). Given the common variants that have been found to be associated with LC in GWAS, targeted-region exome sequencing provides a cost-effective approach for further investigation of high-priority regions of the genome and has the great potential to identify rare causal variants in GWAS loci. Patients and Methods: Using an extreme phenotype approach, we selected 48 sporadic LC patients reporting heavy smoking histories with the presence of severe COPD in whom environmental factors are considered overwhelming, and 54 familial LC cases from families with at least three first-degree relatives with LC who are likely enriched for genomic signal, to search for the disease-causing rare mutations within the target 107 GWAS loci using exome sequencing data. Results: By focusing on exome profiles of these target 107 loci, we identified two disease-causing rare mutations on 6p21.32 TNXB p. Arg504His and 10q25.1 CCDC147 p.Arg696Cys. The homozygous Arg504His mutation presented in four familial and one sporadic LC cases. Notably, the minor allele frequency (MAF) of this variant in Caucasians from 1000 Genomes is very rare (<0.001). The heterozygous CCDC147 Arg696Cys variant were identified in two familial cases and one sporadic case. The MAF for this variant in the Caucasians from 1000 Genomes is 0.004. Both deleterious changes lead to truncation of the putative proteins, which disrupts the predicted domain and alters the cellular localization. We also observed several other suggestive rare mutations on G7C, TNS1, DBH1, and CHRNA5. Conclusion: Our target exome sequencing results demonstrate novel highly disruptive LC risk-conferring TNXB and CCDC147 mutations. Since the rare variants have appreciable effects on disease risk prediction, families and patients may warrant screening for mutations in TNXB and CCDC147 (if validated) to assess their potential LC risk. Citation Format: Yanhong Liu, Farrah Kheradmand, Michael Scheurer, Caleb Davis, David Wheeler, Edwin Silverman, Shete Sanjay, Spiridon Tsavachidis, Georgina Armstrong, Elena Kupert, Marshall Anderson, Yafang Li, Claudio Pikielny, Joan E. Bailey-Wilson, Ming You, Colette Gaba, Mariza DeAndrade, Diptasri Mandal, Claire Simpson, Susan Pinney, Christopher Amos, Margaret Spitz. Target exome sequencing for disease-causing rare mutations in familial and sporadic lung cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4600. doi:10.1158/1538-7445.AM2015-4600

AbstractEvidence for familial aggregation of glioma has been documented in both case-control and cohort studies and occurs apart from the well-described rare inherited genetic syndromes involving glioma: neurofibromatosis type 1 and 2, tuberous sclerosis, Turcot's syndrome, and Li-Fraumeni syndrome. Nonsyndromic glioma families have been studied but no genes have been identified in the two published linkage studies of familial glioma probably due to the small number of families. Because glioma is a rare but devastating cancer, and a family history of glioma has been observed in ∼5% of the cases, we initiated an international consortium to identify glioma families not affected by syndromes to better understand the inherited factors related to this disease. The international consortium GLIOGENE is an acronym for “glioma gene” and includes 15 research groups in North America, Europe, and Israel to study familial glioma. The overarching goal is to characterize genes in glioma families using a genome-wide single-nucleotide polymorphism approach and conducting linkage analysis to identify new genomic regions or loci that could harbor genes important for gliomagenesis. Here, we review the rationale for studying familial glioma and our proposed strategy for the GLIOGENE study. (Cancer Epidemiol Biomarkers Prev 2007;16(9):1730–4)