Gliomas account for approximately 80% of all primary malignant brain tumors, and despite improvements in clinical care over the last 20 years remain among the most lethal tumors, underscoring the need for gaining new insights that could translate into clinical advances. Recent genome-wide association studies (GWAS) have identified seven new susceptibility regions. We conducted a new independent GWAS of glioma using 1,856 cases and 4,955 controls (from 14 cohort studies, 3 casecontrol studies, and 1 population-based case only study) and found evidence of strong replication for three of the seven previously reported associations at 20q13.33 (RTEL), 5p15.33 (TERT), and 9p21.3 (CDKN2BAS), and consistent association signals for the remaining four at 7p11.2 (EGFR both loci), 8q24.21 (CCDC26) and 11q23.3 (PHLDB1). The direction and magnitude of the signal were consistent for samples from cohort and case-control studies, but the strength of the association was more pronounced for loci rs6010620 (20q,13.33; RTEL) and rs2736100 (5p15.33, TERT) in cohort studies despite the smaller number of cases in this group, likely due to relatively more higher grade tumors being captured in the cohort studies. We further examined the 85 most promising single nucleotide polymorphism (SNP) markers identified in our study in three replication sets (5,015 cases and 11,601 controls), but no new markers reached genome-wide significance. Our findings suggest that larger studies focusing on novel approaches as well as specific tumor subtypes or subgroups will be required to identify additional common susceptibility loci for glioma risk.
To identify predisposition loci for classical Hodgkin Lymphoma (cHL) we conducted a genome-wide association study of 589 cHL cases and 5,199 controls with validation in 4 independent samples totaling 2,057 cases and 3,416 controls. We identified three new susceptibility loci at 2p16.1 (rs1432295, REL; odds ratio [OR]=1.22, Pcombined=1.91×10−8), 8q24.21 (rs2019960, PVT1; OR=1.33, Pcombined=1.26×10−13) and 10p14 (rs501764, GATA3; OR=1.25, Pcombined=7.05×10−8). Furthermore, we confirmed the role of the MHC in disease etiology by revealing a strong HLA association (rs6903608; OR=1.70, Pcombined=2.84×10−50). These data provide new insight into the pathogenesis of cHL.
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.
In addition to HLA, recent genome-wide association studies (GWASs) of Hodgkin's lymphoma (HL) have identified susceptibility loci for HL at 2p16.1, 8q24.21 and 10p14. In this study, we perform a GWAS meta-analysis with published GWAS (totalling 1,465 cases and 6,417 controls of European background), and follow-up the most significant association signals in 2,024 cases and 1,853 controls. A combined analysis identifies new HL susceptibility loci mapping to 3p24.1 (rs3806624; P ¼ 1.14 Â 10 À 12 , odds ratio (OR) ¼ 1.26) and 6q23.3 (rs7745098; P ¼ 3.42 Â 10 À 9 , OR ¼ 1.21). rs3806624 localizes 5 0 to the EOMES (eomesodermin) gene within a p53 response element affecting p53 binding. rs7745098 maps intergenic to HBS1L and MYB, a region previously associated with haematopoiesis. These findings provide further insight into the genetic and biological basis of inherited susceptibility to HL.
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.
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.
Since an association between the human leukocyte antigen (HLA) region and Hodgkin lymphoma (HL) was first reported in 1967, many studies have reported associations between HL risk and both single nucleotide polymorphism (SNP) and classic HLA allele variation in the major histocompatibility complex. However, population stratification and the extent and complexity of linkage disequilibrium within the major histocompatibility complex have hindered efforts to fine-map causal signals. Using SNP data to impute alleles at classic HLA loci, we have conducted an integrated analysis of HL risk within the HLA region in 582 early-onset HL cases and 4736 controls. We confirm that the strongest signal of association comes from an SNP located in the class II region, rs6903608 (odds ratio [OR] ؍ 1.79, P ؍ 6.63 ؋ 10 ؊19 ), which is unlikely to be driven by association to HLA-DRB, DQA, or DQB alleles. In addition, we identify independent signals at rs2281389 (OR ؍ 1.73, P ؍ 6.31 ؋ 10 ؊13 ), a SNP that maps closely to HLA-DPB1, and the class II HLA allele DQA1*02:01 (OR ؍ 0.56, P ؍ 1.51 ؋ 10 ؊7 ). These data suggest that multiple independent loci within the HLA class II region contribute to the risk of developing early-onset HL. (Blood. 2011; 118(3):670-674) IntroductionHodgkin lymphoma (HL) is a common lymph node cancer of germinal center B-cell origin, which is characterized by malignant Hodgkin and Reed-Sternberg (HRS) cells mixed with a dominant background population of reactive lymphocytes and other inflammatory cells. 1 Although Epstein-Barr virus (EBV) infection may be causally related to a number of cases, there is little evidence to support the involvement of other environmental risk factors. 2 Evidence for inherited genetic influence on susceptibility is provided by the increased familial risk and high concordance between monozygotic twins. 3 Since an association between the human leukocyte antigen (HLA) region and HL risk was first reported in 1967, 4 studies have subsequently identified associations between both HLA class I and class II alleles and common HL (cHL) risk. [5][6][7][8][9][10] Studies to date have evaluated only specific HLA alleles and have not taken into account the existence of complex linkage disequilibrium patterns between the multiple risk loci mapping to the major histocompatibility complex (MHC) region, associations between HLA alleles at different resolution, and the need to control rigorously for population stratification. In view of the limitations of these previously published studies, we have conducted a more comprehensive analysis.It has recently been shown that single nucleotide polymorphism (SNP) data within the 6p21 region can be used to impute alleles at key classic class I (HLA-A, HLA-B, and HLA-C) and class II (HLA-DRB1, HLA-DQA1, and HLA-DQB1) loci with accuracy that exceeds 90% at the 4-digit level. 11,12 Using existing genotype data from a previous genome-wide association study of HL, which identified many SNPs within the HLA region that are strongly associated with disea...
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.