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The ATM serine/threonine kinase (ATM) pathway plays important roles in pancreatic cancer (PanC) development and progression, but the roles of genetic variants of the genes in this pathway in the etiology of PanC are unknown. In the present study, we assessed associations between 31,499 single nucleotide polymorphisms (SNPs) in 198 ATM pathway-related genes and PanC risk using genotyping data from two previously published PanC genome-wide association studies (GWASs) of 15,423 subjects of European ancestry. In multivariable logistic regression analysis, we identified three novel independent SNPs to be significantly associated with PanC risk [PIK3C3 rs76692125 G>A: odds ratio (OR)=1.26, 95% confidence interval (CI)=1.12-1.43 and P=2.07×10(-4), INSR rs11668724 G>A: OR=0.89, 95% CI=0.84-0.94 and P=4.21×10(-5) and MAP3K4 rs13207108 C>T: OR=0.83, 95% CI=0.75-0.92, P=2.26×10(-4)]. The combined analysis of these three SNPs exhibited an increased PanC risk in a dose-response manner as the number of unfavorable genotypes increased (P (trend)

High hyperdiploidy (HD) is the most common cytogenetic subtype of childhood acute lymphoblastic leukemia (ALL), and a higher incidence of HD has been reported in ALL patients with congenital cancer syndromes. We assessed the frequency of predisposing germline mutations in 57 HD-ALL patients from the California Childhood Leukemia Study via targeted sequencing of cancer-relevant genes. Three out of 57 patients (5.3%) harbored confirmed germline mutations that were likely causal, in NBN, ETV6, and FLT3, with an additional six patients (10.5%) harboring putative predisposing mutations that were rare in unselected individuals (

Little is known about the causes of meningioma. Obesity and obesity-related traits have been reported in several epidemiological observational studies to be risk factors for meningioma. We performed an analysis of genetic variants associated with obesity-related traits to assess the relationship with meningioma risk using Mendelian randomization (MR), an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations. We considered 11 obesity-related traits, identified genetic instruments for these factors, and assessed their association with meningioma risk using data from a genome-wide association study comprising 1,606 meningioma patients and 9,823 controls. To evaluate the causal relationship between the obesity-related traits and meningioma risk, we consider the estimated odds ratio (OR) of meningioma for each genetic instrument. We identified positive associations between body mass index (odds ratio [ORSD] = 1.27, 95% confidence interval [CI] = 1.03-1.56, P = 0.028) and body fat percentage (ORSD = 1.28, 95% CI = 1.01-1.63, P = 0.042) with meningioma risk, albeit non-significant after correction for multiple testing. Associations for basal metabolic rate, diastolic blood pressure, fasting glucose, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, systolic blood pressure, total cholesterol, triglycerides and waist circumference with risk of meningioma were non-significant. Our analysis provides additional support for obesity being associated with an increased risk of meningioma. CA extern

Background Meningiomas are adult brain tumors originating in the meningeal coverings of the brain and spinal cord, with significant heritable basis. Genome-wide association studies (GWAS) have previously identified only a single risk locus for meningioma, at 10p12.31. Methods To identify a susceptibility locus for meningioma, we conducted a meta-analysis of 2 GWAS, imputed using a merged reference panel from the 1000 Genomes Project and UK10K data, with validation in 2 independent sample series totaling 2138 cases and 12081 controls. Results We identified a new susceptibility locus for meningioma at 11p15.5 (rs2686876, odds ratio = 1.44, P = 9.86 × 10–9). A number of genes localize to the region of linkage disequilibrium encompassing rs2686876, including RIC8A, which plays a central role in the development of neural crest-derived structures, such as the meninges. Conclusions This finding advances our understanding of the genetic basis of meningioma development and provides additional support for a polygenic model of meningioma.

Background: The genetic etiology of osteosarcoma remains poorly understood despite the publication of a genome-wide association study. Association between HLA genetic variants and risk of several cancers has been observed, but HLA variation is not well captured by standard SNP arrays.Methods: We genotyped 207 Californian pediatric osteosarcoma cases and 696 controls of European ancestry using a custom genome-wide array supplemented with approximately 6,000 additional probes across the MHC region. We subsequently imputed 4-digit classical HLA alleles using a reference panel of 5,225 individuals who underwent high-resolution HLA typing via next-generation sequencing. Case-control comparisons were adjusted for ancestry-informative principal components, and top associations from the discovery analysis underwent replication in an independent dataset of 657 cases and 1,183 controls.Results: Three highly correlated HLA class II variants (r 2 = 0.33-0.98) were associated with osteosarcoma risk in discovery analyses, including HLA-DRB1*0301 (OR = 0.52; P = 3.2 × 10-3), HLA-DQA1*0501 (OR = 0.74; P = 0.031), and HLA-DQB1*0201 (OR = 0.51; P = 2.7 × 10-3). Similar associations were observed in the replication data (P range = 0.011-0.037). Meta-analysis of the two datasets identified HLA-DRB1*0301 as the most significantly associated variant (ORmeta = 0.62; P meta = 1.5 × 10-4), reaching Bonferroni-corrected statistical significance. The meta-analysis also revealed a second significant independent signal at HLA-DQA1*01:01 (ORmeta = 1.33, P meta = 1.2 × 10-3), and a third suggestive association at HLA-DQB1*0302 (ORmeta = 0.73, P meta = 6.4 × 10-3).Conclusions: Multiple independent HLA class II alleles may influence osteosarcoma risk.Impact: Additional work is needed to extend our observations to other patient populations and to clarify the potential causal mechanisms underlying these associations. Understanding immunologic contributions to the etiology of osteosarcoma may inform rational therapeutic targets. Cancer Epidemiol Biomarkers Prev; 27(10); 1151-8. ©2018 AACR.

BackgroundAlthough increased height has been associated with osteosarcoma risk in previous epidemiologic studies, to the authors' knowledge the relative contribution of stature during different developmental timepoints remains unclear. Furthermore, the question of how genetic determinants of height impact osteosarcoma etiology remains unexplored. Genetic variants associated with stature in previous genome-wide association studies may be biomarkers of osteosarcoma risk.MethodsThe authors tested the associations between osteosarcoma risk and polygenic scores for adult height (416 variants), childhood height (6 variants), and birth length (5 variants) in 864 osteosarcoma cases and 1879 controls of European ancestry.ResultsEach standard deviation increase in the polygenic score for adult height, corresponding to a 1.7-cm increase in stature, was found to be associated with a 1.10-fold increase in the risk of osteosarcoma (95% confidence interval [95% CI], 1.01-1.19; P =.027). Each standard deviation increase in the polygenic score for childhood height, corresponding to a 0.5-cm increase in stature, was associated with a 1.10-fold increase in the risk of osteosarcoma (95% CI, 1.01-1.20; P =.023). The polygenic score for birth length was not found to be associated with osteosarcoma risk (P =.11). When adult and childhood height scores were modeled together, they were found to be independently associated with osteosarcoma risk (P =.037 and P = .043, respectively). An expression quantitative trait locus for cartilage intermediate layer protein 2 (CILP2), rs8103992, was significantly associated with osteosarcoma risk after adjustment for multiple comparisons (odds ratio, 1.35; 95% CI, 1.16-1.56 [P = 7.93×10-5 and Padjusted =.034]).ConclusionsA genetic propensity for taller adult and childhood height attainments contributed independently to osteosarcoma risk in the current study data. These results suggest that the biological pathways affecting normal bone growth may be involved in osteosarcoma etiology.

Genome-wide association studies of childhood acute lymphoblastic leukemia (ALL) have identified regions of association at PIP4K2A and upstream of BMI1 at chromosome 10p12.31-12.2. The contribution of both loci to ALL risk and underlying functional variants remain to be elucidated. We carried out single nucleotide polymorphism (SNP) imputation across chromosome 10p12.31-12.2 in Latino and non-Latino white ALL cases and controls from two independent California childhood leukemia studies, and additional Genetic Epidemiology Research on Aging study controls. Ethnicity-stratified association analyses were performed using logistic regression, with meta-analysis including 3,133 cases (1,949 Latino, 1,184 non-Latino white) and 12,135 controls (8,584 Latino, 3,551 non-Latino white). SNP associations were identified at both BMI1 and PIP4K2A. After adjusting for the lead PIP4K2A SNP, genome-wide significant associations remained at BMI1, and vice-versa (pmeta < 10-10 ), supporting independent effects. Lead SNPs differed by ethnicity at both peaks. We sought functional variants in tight linkage disequilibrium with both the lead Latino SNP among Admixed Americans and lead non-Latino white SNP among Europeans. This pinpointed rs11591377 (pmeta = 2.1 x 10-10 ) upstream of BMI1, residing within a hematopoietic stem cell enhancer of BMI1, and which showed significant preferential binding of the risk allele to MYBL2 (p = 1.73 x 10-5 ) and p300 (p = 1.55 x 10-3 ) transcription factors using binomial tests on ChIP-Seq data from a SNP heterozygote. At PIP4K2A, we identified rs4748812 (pmeta = 1.3 x 10-15 ), which alters a RUNX1 binding motif and demonstrated chromosomal looping to the PIP4K2A promoter. Fine-mapping chromosome 10p12 in a multi-ethnic ALL GWAS confirmed independent associations and identified putative functional variants upstream of BMI1 and at PIP4K2A.

Approximately 8% of the human genome is comprised of endogenous retroviral insertions (ERVs) originating from historic retroviral integration into germ cells. The function of ERVs as regulators of gene expression is well established. Less well studied are insertional polymorphisms of ERVs and their contribution to the heritability of complex phenotypes. The most recent integration of ERV, HERV-K, is expressed in a range of complex human conditions from cancer to neurologic diseases. Using an in-house computational pipeline and whole-genome sequencing data from the diverse 1,000 Genomes Phase 3 population (n = 2,504), we identified 46 polymorphic HERV-K insertions that are tagged by adjacent single nucleotide polymorphisms (SNPs). To test the potential role of polymorphic HERV-K in the heritability of complex diseases, existing databases were queried for enrichment of established relationships between the HERV-K insertion-associated SNPs (hiSNPs), and tissue specific gene expression and disease phenotypes. Overall, hiSNPs for the 46 polymorphic HERV-K sites were statistically enriched (p < 1.0E-16) for eQTLs across 44 human tissues. Fifteen of the 46 HERV-K insertions had hiSNPs annotated in the EMBL-EBI GWAS Catalog and cumulatively associated with >100 phenotypes. Experimental factor ontology enrichment analysis suggests that polymorphic HERV-K specifically contribute to neurologic and immunologic disease phenotypes, including traits related to intra cranial volume (FDR 2.00E-09), Parkinson's disease (FDR 1.80E-09), and autoimmune diseases (FDR 1.80E-09). These results provide strong candidates for context-specific study of polymorphic HERV-K insertions in disease-related traits, serving as a roadmap for future studies of the heritability of complex disease.

Although genome-wide association studies have identified several susceptibility loci for adult glioma, little is known regarding the potential contribution of genetic variation in the human leukocyte antigen (HLA) region to glioma risk. HLA associations have been reported for various malignancies, with many studies investigating selected candidate HLA polymorphisms. However, no systematic analysis has been conducted in glioma patients, and no investigation into potential non-additive effects has been described. We conducted comprehensive genetic analyses of HLA variants among 1746 adult glioma patients and 2312 controls of European-ancestry from the GliomaScan Consortium. Genotype data were generated with the Illumina 660-Quad array, and we imputed HLA alleles using a reference panel of 5225 individuals in the Type 1 Diabetes Genetics Consortium who underwent high-resolution HLA typing via next-generation sequencing. Case-control comparisons were adjusted for population stratification using ancestry-informative principal components. Because alleles in different loci across the HLA region are linked, we created multigene haplotypes consisting of the genes DRB1, DQA1, and DQB1. Although none of the haplotypes were associated with glioma in additive models, inclusion of a dominance term significantly improved the model for multigene haplotype HLA-DRB1*1501-DQA1*0102-DQB1*0602 (P = 0.002). Heterozygous carriers of the haplotype had an increased risk of glioma [odds ratio (OR) 1.23; 95% confidence interval (CI) 1.01-1.49], while homozygous carriers were at decreased risk compared with non-carriers (OR 0.64; 95% CI 0.40-1.01). Our results suggest that the DRB1*1501-DQA1*0102-DQB1*0602 haplotype may contribute to the risk of glioma in a non-additive manner, with the positive dominance effect partly explained by an epistatic interaction with HLA-DRB1*0401-DQA1*0301-DQB1*0301.