Genetic predisposition to longer telomere length and risk of childhood, adolescent and adult-onset ependymoma

Ependymoma is the third most common brain tumor in children, with well-described molecular characterization but poorly understood underlying germline risk factors. To investigate whether genetic predisposition to longer telomere length influences ependymoma risk, we utilized case–control data from three studies: a population-based pediatric and adolescent ependymoma case–control sample from California (153 cases, 696 controls), a hospital-based pediatric posterior fossa type A (EPN-PF-A) ependymoma case–control study from Toronto’s Hospital for Sick Children and the Children’s Hospital of Philadelphia (83 cases, 332 controls), and a multicenter adult-onset ependymoma case–control dataset nested within the Glioma International Case-Control Consortium (GICC) (103 cases, 3287 controls). In the California case–control sample, a polygenic score for longer telomere length was significantly associated with increased risk of ependymoma diagnosed at ages 12–19 (P = 4.0 × 10 −3 ), but not with ependymoma in children under 12 years of age (P = 0.94). Mendelian randomization supported this observation, identifying a significant association between genetic predisposition to longer telomere length and increased risk of adolescent-onset ependymoma (OR PRS  = 1.67; 95% CI 1.18–2.37; P = 3.97 × 10 −3 ) and adult-onset ependymoma (P MR-Egger  = 0.042), but not with risk of ependymoma diagnosed before age 12 (OR = 1.12; 95% CI 0.94–1.34; P = 0.21), nor with EPN-PF-A (P MR-Egger  = 0.59). These findings complement emerging literature suggesting that augmented telomere maintenance is important in ependymoma pathogenesis and progression, and that longer telomere length is a risk factor for diverse nervous system malignancies.

[1]  J. Shay,et al.  Human Telomerase and Its Regulation , 2002, Microbiology and Molecular Biology Reviews.

[2]  Hilde van der Togt,et al.  Publisher's Note , 2003, J. Netw. Comput. Appl..

[3]  N. Carter,et al.  A DNA damage checkpoint response in telomere-initiated senescence , 2003, Nature.

[4]  J. Rutka,et al.  Human telomere reverse transcriptase expression predicts progression and survival in pediatric intracranial ependymoma. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[5]  P. Donnelly,et al.  A new multipoint method for genome-wide association studies by imputation of genotypes , 2007, Nature Genetics.

[6]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[7]  M. Shago,et al.  Telomere maintenance and dysfunction predict recurrence in paediatric ependymoma , 2008, British Journal of Cancer.

[8]  J. Lowe,et al.  Multifactorial analysis of predictors of outcome in pediatric intracranial ependymoma. , 2008, Neuro-oncology.

[9]  J. Lowe,et al.  Pediatric Ependymoma: Biological Perspectives , 2009, Molecular Cancer Research.

[10]  R. O'Sullivan,et al.  Telomeres: protecting chromosomes against genome instability , 2010, Nature Reviews Molecular Cell Biology.

[11]  C. Hawkins,et al.  Telomerase Inhibition as a Novel Therapy for Pediatric Ependymoma , 2010, Brain pathology.

[12]  D. Hanahan,et al.  Hallmarks of Cancer: The Next Generation , 2011, Cell.

[13]  T. VanderWeele,et al.  Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. , 2011, International journal of epidemiology.

[14]  R. Kronmal,et al.  Leukocyte telomere length and mortality in the Cardiovascular Health Study. , 2011, The journals of gerontology. Series A, Biological sciences and medical sciences.

[15]  H. Hakonarson,et al.  Common variation at 6q16 within HACE1 and LIN28B influences susceptibility to neuroblastoma , 2012, Nature Genetics.

[16]  George Davey Smith,et al.  Using multiple genetic variants as instrumental variables for modifiable risk factors , 2012, Statistical methods in medical research.

[17]  J. Marchini,et al.  Fast and accurate genotype imputation in genome-wide association studies through pre-phasing , 2012, Nature Genetics.

[18]  O. Delaneau,et al.  A linear complexity phasing method for thousands of genomes , 2011, Nature Methods.

[19]  David T. W. Jones,et al.  Methylation of the TERT promoter and risk stratification of childhood brain tumours: an integrative genomic and molecular study. , 2013, The Lancet. Oncology.

[20]  Susan M. Chang,et al.  Genetic variants in telomerase-related genes are associated with an older age at diagnosis in glioma patients: evidence for distinct pathways of gliomagenesis. , 2013, Neuro-oncology.

[21]  David T. W. Jones,et al.  Distribution of TERT promoter mutations in pediatric and adult tumors of the nervous system , 2013, Acta Neuropathologica.

[22]  S. Thompson,et al.  Use of allele scores as instrumental variables for Mendelian randomization , 2013, International journal of epidemiology.

[23]  S. A. Au Yeung,et al.  Mendelian randomization estimates may be inflated. , 2013, Journal of the American College of Cardiology.

[24]  P. O’Reilly,et al.  Identification of seven loci affecting mean telomere length and their association with disease , 2013, Nature Genetics.

[25]  J. Barnholtz-Sloan,et al.  CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2007-2011. , 2012, Neuro-oncology.

[26]  J. Rutka,et al.  Telomerase inhibition abolishes the tumorigenicity of pediatric ependymoma tumor-initiating cells , 2014, Acta Neuropathologica.

[27]  J. Barnholtz-Sloan,et al.  The epidemiology of glioma in adults: a "state of the science" review. , 2014, Neuro-oncology.

[28]  L. Morgan,et al.  The epidemiology of glioma in adults: a "state of the science" review. , 2015, Neuro-oncology.

[29]  P. Froguel,et al.  Genetic determinants of leucocyte telomere length in children: a neglected and challenging field. , 2015, Paediatric and perinatal epidemiology.

[30]  N. Timpson,et al.  Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors , 2015, European Journal of Epidemiology.

[31]  Gabor T. Marth,et al.  A global reference for human genetic variation , 2015, Nature.

[32]  G. Davey Smith,et al.  Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression , 2015, International journal of epidemiology.

[33]  J. Eckel-Passow,et al.  Telomere maintenance and the etiology of adult glioma. , 2015, Neuro-oncology.

[34]  Gary D Bader,et al.  Molecular Classification of Ependymal Tumors across All CNS Compartments, Histopathological Grades, and Age Groups. , 2015, Cancer cell.

[35]  Alexander R. Pico,et al.  Longer genotypically-estimated leukocyte telomere length is associated with increased adult glioma risk , 2015, Oncotarget.

[36]  E. Epel,et al.  Human telomere biology: A contributory and interactive factor in aging, disease risks, and protection , 2015, Science.

[37]  Alan M. Kwong,et al.  Next-generation genotype imputation service and methods , 2016, Nature Genetics.

[38]  K. Aldape,et al.  The Glioma International Case-Control Study: A Report From the Genetic Epidemiology of Glioma International Consortium. , 2015, American journal of epidemiology.

[39]  David T. W. Jones,et al.  Telomere dysfunction and chromothripsis , 2016, International journal of cancer.

[40]  N. Samani,et al.  Common genetic variants associated with telomere length confer risk for neuroblastoma and other childhood cancers. , 2016, Carcinogenesis.

[41]  N. Samani,et al.  Genetic Variation Associated with Longer Telomere Length Increases Risk of Chronic Lymphocytic Leukemia , 2016, Cancer Epidemiology, Biomarkers & Prevention.

[42]  G. Davey Smith,et al.  Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator , 2016, Genetic epidemiology.

[43]  J. Mao,et al.  Missing heritability of complex diseases: Enlightenment by genetic variants from intermediate phenotypes , 2016, BioEssays : news and reviews in molecular, cellular and developmental biology.

[44]  Alan M. Kwong,et al.  A reference panel of 64,976 haplotypes for genotype imputation , 2015, Nature Genetics.

[45]  Fernando Pires Hartwig,et al.  Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption , 2017, bioRxiv.

[46]  E. Hewer,et al.  TERT Promoter Mutations but not the Alternative Lengthening of Telomeres Phenotype Are Present in a Subset of Ependymomas and Are Associated With Adult Onset and Progression to Ependymosarcoma , 2016, Journal of neuropathology and experimental neurology.

[47]  S. Spiegl-Kreinecker,et al.  Telomerase activation in posterior fossa group A ependymomas is associated with dismal prognosis and chromosome 1q gain , 2017, Neuro-oncology.

[48]  Christopher R. Gignoux,et al.  Human demographic history impacts genetic risk prediction across diverse populations , 2016, bioRxiv.

[49]  I. Smirnov,et al.  GWAS in childhood acute lymphoblastic leukemia reveals novel genetic associations at chromosomes 17q12 and 8q24.21 , 2018, Nature Communications.

[50]  Tom R. Gaunt,et al.  Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study , 2017 .

[51]  A. Aviv,et al.  Mutations, Cancer and the Telomere Length Paradox. , 2017, Trends in cancer.

[52]  Olena O Yavorska,et al.  MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data , 2017, International journal of epidemiology.

[53]  J. Jonkers,et al.  The CST Complex Mediates End Protection at Double-Strand Breaks and Promotes PARP Inhibitor Sensitivity in BRCA1-Deficient Cells , 2018, Cell reports.

[54]  Michael C. Heinold,et al.  The landscape of genomic alterations across childhood cancers , 2018, Nature.

[55]  E. Semmes,et al.  Intermediate phenotypes underlying osteosarcoma risk , 2018, Oncotarget.

[56]  G. Davey Smith,et al.  Evaluating the potential role of pleiotropy in Mendelian randomization studies , 2018, Human molecular genetics.

[57]  I. Smirnov,et al.  Genetic determinants of childhood and adult height associated with osteosarcoma risk , 2018, Cancer.

[58]  I. Smirnov,et al.  Longer genotypically-estimated leukocyte telomere length is associated with increased meningioma risk , 2019, Journal of Neuro-Oncology.

[59]  J. Barnholtz-Sloan,et al.  CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2012-2016. , 2019, Neuro-oncology.

[60]  G. Davey Smith,et al.  An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome , 2018, bioRxiv.

[61]  Kelsey E. Grinde,et al.  Generalizing polygenic risk scores from Europeans to Hispanics/Latinos , 2018, Genetic epidemiology.

[62]  Q. Wei,et al.  Common genetic variation and risk of osteosarcoma in a multi-ethnic pediatric and adolescent population. , 2020, Bone.

[63]  Helen E. Parkinson,et al.  The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019 , 2018, Nucleic Acids Res..

[64]  H. Hakonarson,et al.  European genetic ancestry associated with risk of childhood ependymoma. , 2020, Neuro-oncology.

[65]  Lincoln D. Stein,et al.  Metabolic Regulation of the Epigenome Drives Lethal Infantile Ependymoma , 2020, Cell.