Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Genetics and Genomics

Predicted leukocyte telomere length and risk of germ cell tumours

British Journal of Cancer volume 127, pages 301–312 (2022)Cite this article

Subjects

Abstract

Background

Genetically predicted leukocyte telomere length (LTL) has been evaluated in several studies of childhood and adult cancer. We test whether genetically predicted longer LTL is associated with germ cell tumours (GCT) in children and adults.

Methods

Paediatric GCT samples were obtained from a Children’s Oncology Group study and state biobank programs in California and Michigan (N = 1413 cases, 1220 biological parents and 1022 unrelated controls). Replication analysis included 396 adult testicular GCTs (TGCT) and 1589 matched controls from the UK Biobank. Mendelian randomisation was used to look at the association between genetically predicted LTL and GCTs and TERT variants were evaluated within GCT subgroups.

Results

We identified significant associations between TERT variants reported in previous adult TGCT GWAS in paediatric GCT: TERT/rs2736100-C (OR = 0.82; P = 0.0003), TERT/rs2853677-G (OR = 0.80; P = 0.001), and TERT/rs7705526-A (OR = 0.81; P = 0.003). We also extended these findings to females and tumours outside the testes. In contrast, we did not observe strong evidence for an association between genetically predicted LTL by other variants and GCT risk in children or adults.

Conclusion

While TERT is a known susceptibility locus for GCT, our results suggest that LTL predicted by other variants is not strongly associated with risk in either children or adults.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Association between individual single nucleotide polymorphisms (SNPs) that genetically predict leukocyte telomere length (LTL) and paediatric germ cell tumour (GCT) risk: results from the Mendelian Randomization (MR) analysis.
Fig. 2: Sub-group specific association between genetically predicted leukocyte telomere length (LTL) and paediatric germ cell tumour (GCT) risk: results from the Mendelian Randomization (MR) analysis.
Fig. 3: Association between individual single nucleotide polymorphisms (SNPs) that genetically predict leukocyte telomere length (LTL) and UKB testicular germ cell tumour (TGCT) risk: results from the Mendelian Randomization analysis.
Fig. 4: Meta-analysis results for subgroup-specific associations between TERT single nucelotide polymorphisms (SNPs) and germ cell tumor (GCT) risk.

Similar content being viewed by others

Data availability

The paediatric and adolescent datasets generated from the Children’s Oncology Group (COG) and used for analyses in the current study will be shared publicly on dbGaP. Data generated from the California and Michigan Biobank samples cannot be shared due to state-specific restrictions regarding the use of the data. The UK Biobank data is publicly available and can be accessed on the UK Biobank website (https://www.ukbiobank.ac.uk/).

Code availability

Representative code used to analyse the data in this study is provided in Supplemental Materials.

References

  1. Hug N, Lingner J. Telomere length homeostasis. Chromosoma. 2006;115:413–25.

    Article  CAS  PubMed  Google Scholar 

  2. Needham BL, Adler N, Gregorich S, Rehkopf D, Lin J, Blackburn EH, et al. Socioeconomic status, health behavior, and leukocyte telomere length in the National Health and Nutrition Examination Survey, 1999–2002. Soc Sci Med. 2013;85:1–8.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Brown L, Needham B, Ailshire J. Telomere length among older U.S. adults: differences by race/ethnicity, gender, and age. J Aging Health. 2017;29:1350–66.

    Article  PubMed  Google Scholar 

  4. Vaziri H, Dragowska W, Allsopp RC, Thomas TE, Harley CB, Lansdorp PM. Evidence for a mitotic clock in human hematopoietic stem cells: loss of telomeric DNA with age. Proc Natl Acad Sci USA. 1994;91:9857–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Smith EM, Pendlebury DF, Nandakumar J. Structural biology of telomeres and telomerase. Cell Mol Life Sci. 2020;77:61–79.

    Article  CAS  PubMed  Google Scholar 

  6. Shay JW. Role of telomeres and telomerase in aging and cancer. Cancer Discov. 2016;6:584–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Wentzensen IM, Mirabello L, Pfeiffer RM, Savage SA. The association of telomere length and cancer: a meta-analysis. Cancer Epidemiol Biomark Prev. 2011;20:1238–50.

    Article  CAS  Google Scholar 

  8. Okamoto K, Seimiya H. Revisiting telomere shortening in cancer. Cells. 2019;8:107.

    Article  CAS  PubMed Central  Google Scholar 

  9. Ma H, Zhou Z, Wei S, Liu Z, Pooley KA, Dunning AM, et al. Shortened telomere length is associated with increased risk of cancer: a meta-analysis. PLoS ONE. 2011;6:e20466.

  10. Pooley KA, Sandhu MS, Tyrer J, Shah M, Driver KE, Luben RN, et al. Telomere length in prospective and retrospective cancer case-control studies. Cancer Res. 2010;70:3170–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Steenstrup T, Hjelmborg JVB, Kark JD, Christensen K, Aviv A. The telomere lengthening conundrum - Artifact or biology? Nucleic Acids Res. 2013;41:1–7.

    Article  CAS  Google Scholar 

  12. Baird DM. Mechanisms of telomeric instability. Cytogenetic Genome Res. 2009;122:308–14.

    Article  CAS  Google Scholar 

  13. Kawanishi S, Oikawa S. Mechanism of telomere shortening by oxidative stress. Ann N. Y Acad Sci. 2004;1019:278–84.

    Article  CAS  PubMed  Google Scholar 

  14. Valdes AM, Andrew T, Gardner JP, Kimura M, Oelsner E, Cherkas LF, et al. Obesity, cigarette smoking, and telomere length in women. Lancet-. 2005;366:662–4.

    Article  CAS  PubMed  Google Scholar 

  15. Turner KJ. Telomere biology and human phenotype. Cells. 2019;8:73.

  16. Factor-Litvak P, Susser E, Kezios K, McKeague I, Kark JD, Hoffman M, et al. Leukocyte telomere length in newborns: implications for the role of telomeres in human disease. Pediatrics. 2016;137:e20153927.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Oosterhuis JW, Looijenga LHJ. Human germ cell tumours from a developmental perspective. Nat Rev Cancer. 2019;19:522–37.

    Article  CAS  PubMed  Google Scholar 

  18. Poynter JN, Amatruda JF, Ross JA. Trends in incidence and survival of pediatric and adolescent patients with germ cell tumors in the United States, 1975 to 2006. Cancer. 2010;116:4882–91.

    Article  PubMed  Google Scholar 

  19. Rajpert-De Meyts E, McGlynn KA, Okamoto K, Jewett MAS, Bokemeyer C. Testicular germ cell tumours. Lancet. 2016;387:1762–74.

    Article  PubMed  Google Scholar 

  20. Litchfield K, Thomsen H, Mitchell JS, Sundquist J, Houlston RS, Hemminki K, et al. Quantifying the heritability of testicular germ cell tumour using both population-based and genomic approaches. Sci Rep. 2015;5:1–7.

    Article  Google Scholar 

  21. Sampson JN, Wheeler WA, Yeager M, Panagiotou O, Wang Z, Berndt SI, et al. Analysis of heritability and shared heritability based on genome-wide association studies for thirteen cancer types. J Natl Cancer Inst. 2015;107:djv279.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Turnbull C, Rapley EA, Seal S, Pernet D, Renwick A, Hughes D, et al. Variants near DMRT1, TERT and ATF7IP are associated with testicular germ cell cancer. Nat Genet. 2010;42:604–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Litchfield K, Levy M, Orlando G, Loveday C, Law PJ, Migliorini G, et al. Identification of 19 new risk loci and potential regulatory mechanisms influencing susceptibility to testicular germ cell tumor. Nat Genet. 2017;49:1133–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Wang Z, McGlynn KA, Rajpert-De Meyts E, Bishop DT, Chung CC, Dalgaard MD, et al. Meta-analysis of five genome-wide association studies identifies multiple new loci associated with testicular germ cell tumor. Nat Genet. 2017;49:1141–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Ruark E, Seal S, McDonald H, Zhang F, Elliot A, Lau K, et al. Identification of nine new susceptibility loci for testicular cancer, including variants near DAZL and PRDM14. Nat Genet. 2013;45:686–9.

    Article  CAS  PubMed  Google Scholar 

  26. Pooley KA, Bojesen SE, Weischer M, Nielsen SF, Thompson D, Amin Al Olama A, et al. A genome-wide association scan (GWAS) for mean telomere length within the COGS project: identified loci show little association with hormone-related cancer risk. Hum Mol Genet. 2013;22:5056–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Codd V, Nelson CP, Albrecht E, Mangino M, Deelen J, Buxton JL, et al. Identification of seven loci affecting mean telomere length and their association with disease. Nat Genet. 2013;45:422–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Mangino M, Hwang SJ, Spector TD, Hunt SC, Kimura M, Fitzpatrick AL, et al. Genome-wide meta-analysis points to CTC1 and ZNF676 as genes regulating telomere homeostasis in humans. Hum Mol Genet. 2012;21:5385–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Codd V, Mangino M, van der Harst P, Braund PS, Beveridge AJ, Rafelt S, et al. Variants near TERC are associated with mean telomere length. Nat Genet. 2010;42:197–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Walsh KM, Whitehead TP, de Smith AJ, Smirnov IV, Park M, Endicott AA, et al. Common genetic variants associated with telomere length confer risk for neuroblastoma and other childhood cancers. Carcinogenesis. 2016;37:576–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Levy D, Neuhausen SL, Hunt SC, Kimura M, Hwang SJ, Chen W, et al. Genome-wide association identifies OBFC1 as a locus involved in human leukocyte telomere biology. Proc Natl Acad Sci USA. 2010;107:9293–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Li C, Stoma S, Lotta LA, Warner S, Albrecht E, Allione A, et al. Genome-wide association analysis in humans links nucleotide metabolism to leukocyte telomere length. Am J Hum Genet. 2020;106:389–404.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Wang Z, Rice SV, Chang TC, Liu Y, Liu Q, Qin N, et al. Molecular mechanism of telomere length dynamics and its prognostic value in pediatric cancers. Intergovernmental Panel on Climate Change, editor. JNCI: J Natl Cancer Inst. 2019;112:756–64.

    Article  PubMed Central  CAS  Google Scholar 

  34. Gao Y, Wei Y, Zhou X, Huang S, Zhao H, Zeng P. Assessing the relationship between leukocyte telomere length and cancer risk/mortality in UK biobank and TCGA datasets with the genetic risk score and Mendelian randomization approaches. Front Genet. 2020;11:1270.

  35. Pierce BL, Kraft P, Zhang C. Mendelian randomization studies of cancer risk: a literature review. Curr Epidemiol Rep. 2018;5:184–96.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Zhang C, Ostrom QT, Semmes EC, Ramaswamy V, Hansen HM, Morimoto L, et al. Genetic predisposition to longer telomere length and risk of childhood, adolescent and adult-onset ependymoma. Acta Neuropathologica Commun. 2020;8:173.

    Article  CAS  Google Scholar 

  37. Ojha J, Codd V, Nelson CP, Samani NJ, Smirnov IV, Madsen NR, et al. Genetic variation associated with longer telomere length increases risk of chronic lymphocytic leukemia. Cancer Epidemiol Biomark Prev. 2016;25:1043–9.

    Article  CAS  Google Scholar 

  38. Walsh KM, Codd V, Rice T, Nelson CP, Smirnov IV, Mccoy LS, et al. Longer genotypically-estimated leukocyte telomere length is associated with increased adult glioma risk. Oncotarget. 2015;6:42468.

  39. Haycock PC, Burgess S, Nounu A, Zheng J, Okoli GN, Bowden J, et al. Association between telomere length and risk of cancer and non-neoplastic diseases a Mendelian randomization study. JAMA Oncol. 2017;3:636–51.

    Article  PubMed  Google Scholar 

  40. Brown DW, Lan Q, Rothman N, Pluta J, Almstrup K, Dalgaard MD, et al. Genetically inferred telomere length and testicular germ cell tumor risk. Cancer Epidemiol Biomark Prevention. 2021;30:1275–8.

  41. Musselman JRB, Spector LG, Krailo MD, Reaman GH, Linabery AM, Poynter JN, et al. The Children’s Oncology Group Childhood Cancer Research Network (CCRN): case catchment in the United States. Cancer. 2014;120:3007–15.

    Article  PubMed  Google Scholar 

  42. Poynter JN, Richardson M, Roesler M, Krailo M, Amatruda JF, Frazier AL. Family history of cancer in children and adolescents with germ cell tumours: a report from the Children’s Oncology Group. Br J Cancer. 2018;118:121–6.

    Article  PubMed  Google Scholar 

  43. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904–9.

    Article  CAS  PubMed  Google Scholar 

  44. Patterson N, Price AL, Reich D. Population structure and eigenanalysis. PLoS Genet. 2006;2:e190.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. Das S, Forer L, Schönherr S, Sidore C, Locke AE, Kwong A, et al. Next-generation genotype imputation service and methods. Nat Genet. 2016;48:1284–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Taliun D, Harris DN, Kessler MD, Carlson J, Szpiech ZA, Torres R, et al. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature. 2021;590:290–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Fuchsberger C, Abecasis GR, Hinds DA. Minimac2: faster genotype imputation. Bioinformatics. 2015;31:782–4.

    Article  CAS  PubMed  Google Scholar 

  48. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira M, Bender D, et al. PLINK: whole genome data analysis toolset. Am J Hum Genet. 2007;81:559–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Spielman RS, Mcginnis RE, Ewenst WJ. Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). Am J Hum Genet. 1993;52:506.

  50. Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics Appl Note. 2010;26:2190–1.

    Article  CAS  Google Scholar 

  51. Cochran WG. The combination of estimates from different experiments. Biometrics. 1954;10:101–29.

    Article  Google Scholar 

  52. Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, et al. The MR-base platform supports systematic causal inference across the human phenome. eLife. 2018;7:e34408.

  53. Didelez V, Sheehan N. Mendelian randomization as an instrumental variable approach to causal inference. Stat Methods Med Res. 2007;16:309–30.

    Article  PubMed  Google Scholar 

  54. Smith GD, Ebrahim S. “Mendelian randomization”: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32:1–22.

    Article  PubMed  Google Scholar 

  55. Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017;32:377–89.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Bowden J, Davey, Smith G, Haycock PC, Burgess S. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016;40:304–14.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Bowden J, Spiller W, Del Greco FM, Sheehan N, Thompson J, Minelli C, et al. Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the Radial plot and Radial regression. Int J Epidemiol. 2018;47:1264–78.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12:e1001779.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. UK Biobank. UKB: Data-Field 22009 Genetic principal components [Internet]. [cited 2021 May 6]. Available from: https://biobank.ctsu.ox.ac.uk/crystal/field.cgi?id=22009.

  61. Brion MJA, Shakhbazov K, Visscher PM. Calculating statistical power in Mendelian randomization studies. Int J Epidemiol. 2013;42:1497–501.

    Article  PubMed  Google Scholar 

  62. Bentley JL. Multidimensional binary search trees used for associative searching. Commun ACM. 1975;18:509–17.

    Article  Google Scholar 

  63. Kuhn HW. The Hungarian method for the assignment problem. Nav Res Logist Q. 1955;2:83–97.

    Article  Google Scholar 

  64. Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44:512–25.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Oosterhuis JW, Looijenga LHJ. Testicular germ-cell tumours in a broader perspective. Nat Rev Cancer. 2005;5:210–22.

    Article  CAS  PubMed  Google Scholar 

  66. Lonsdale J, Thomas J, Salvatore M, Phillips R, Lo E, Shad S, et al. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013;45:580–5.

    Article  CAS  Google Scholar 

  67. Eisenberg DTA, Kuzawa CW. The paternal age at conception effect on offspring telomere length: mechanistic, comparative and adaptive perspectives. Philos Trans R Soc B: Biol Sci. 2018;373:20160442.

    Article  CAS  Google Scholar 

  68. Wright WE, Piatyszek MA, Rainey WE, Byrd W, Shay JW. Telomerase activity in human germline and embryonic tissues and cells. Developmental Genet. 1996;18:173–9.

    Article  CAS  Google Scholar 

  69. Schrader M, Burger AM, Müller M, Krause H, Straub B, Schostak M, et al. The differentiation status of primary gonadal germ cell tumors correlates inversely with telomerase activity and the expression level of the gene encoding the catalytic subunit of telomerase. BMC Cancer. 2002;2:32.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Johnston HE, Mann JR, Williams J, Waterhouse JAH, Birch JM, Cartwright RA, et al. The Inter-Regional, Epidemiological Study of Childhood Cancer (IRESCC): case-control study in children with germ cell tumours. Carcinogenesis. 1986;7:717–22.

    Article  CAS  PubMed  Google Scholar 

  71. Chen Z, Robison L, Giller R, Krailo M, Davis M, Gardner K, et al. Risk of childhood germ cell tumors in association with parental smoking and drinking. Cancer. 2005;103:1064–71.

    Article  PubMed  Google Scholar 

  72. Johnson KJ, Carozza SE, Chow EJ, Fox EE, Horel S, McLaughlin CC, et al. Parental age and risk of childhood cancer: a pooled analysis. Epidemiology. 2009;20:475–83.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Shu XO, Nesbit ME, Buckley JD, Krailo MD, Robison LL. An exploratory analysis of risk factors for childhood malignant germ-cell tumors: report from the Childrens Cancer Group (Canada, United States). Cancer Causes Control. 1995;6:187–98.

    Article  CAS  PubMed  Google Scholar 

  74. Stephansson O, Wahnström C, Pettersson A, Sørensen HT, Tretli S, Gissler M, et al. Perinatal risk factors for childhood testicular germ-cell cancer: a Nordic population-based study. Cancer Epidemiol. 2011;35:e100–4.

    Article  PubMed  Google Scholar 

  75. Wanderas EH, Grotmol T, Fossa SD, Tretli S. Maternal health and pre- and perinatal characteristics in the etiology of testicular cancer: a prospective population- and register-based study on Norwegian males born between 1967 and 1995. Cancer Causes Control: CCC. 1998;9:475–86.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge the University of Minnesota Genomics Center for performing the genotyping assays and the University of Minnesota Supercomputing Institute for providing hardware and support for the statistical analyses.

Funding

This work was supported by the National Institutes of Health (grant R01 CA151284 to Jenny N. Poynter, National Clinical Trials Network Operations Center grant U10CA180886, and National Clinical Trials Network Statistics and Data Management Center grant U10CA180899), and Epidemiology Award from Alex’s Lemonade Stand Foundation (Wynnewood, Pennsylvania), and the Children’s Cancer Research Fund (Minneapolis, Minnesota).

Author information

Authors and Affiliations

  1. Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, MN, 55455, USA

    Shannon S. Cigan, Erica K. Langer, Anthony J. Hooten & Jenny N. Poynter

  2. Division of Computational Biology, Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, 55455, USA

    John J. Meredith, Ava C. Kelley, John A. Lane, Benjamin R. Cole & Nathan Pankratz

  3. Department of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, 55455, USA

    Tianzhong Yang

  4. Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA

    Mark Krailo

  5. Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Boston, MA, 02215, USA

    A. Lindsay Frazier

  6. Masonic Cancer Center, University of Minnesota, Minneapolis, MN, 55455, USA

    Jenny N. Poynter

Authors
  1. Shannon S. Cigan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. John J. Meredith
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ava C. Kelley
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tianzhong Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Erica K. Langer
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Anthony J. Hooten
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. John A. Lane
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Benjamin R. Cole
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Mark Krailo
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. A. Lindsay Frazier
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Nathan Pankratz
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Jenny N. Poynter
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

SSC analysed and interpreted the data, conducted the literature review, and drafted the article. TY assisted with the interpretation of the data and power calculations. NP, JJM, ACK, JAL and BRC conceptualised the study design, processed the genetic data and assisted with data analysis. EKL and AJH conducted laboratory work and supervised the data collection. MK and ALF contributed to the study design. JNP designed the study, conceptualised the analysis and interpreted the data. All authors contributed to the drafting, review and approval of the final article.

Corresponding author

Correspondence to Shannon S. Cigan.

Ethics declarations

Competing interests

ALF has acted as a paid consultant for Decibel Therapeutics for work performed outside of the current study. The remaining authors declare no competing interests.

Ethics approval and consent to participate

All study procedures were approved by the University of Minnesota Institutional Review Board. The California Committee for the Protection of Human Subjects and the Michigan Department of Health and Human Services Institutional Review Board approved the use of the biobank samples.

Consent to publish

This manuscript does not contain any individual person’s data in any form.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

41416_2022_1798_MOESM1_ESM.pdf

Supplemental Table S1. Individual effect of leukocyte telomere length (LTL) related variants on germ cell tumor risk (GCT)

41416_2022_1798_MOESM2_ESM.pdf

Supplemental Table S2. Sensitivity analysis for the MR analyses of genetically predicted telomere length on pediatric germ cell tumor

Supplemental Table S3 - Linkage relationship of TERT variants in previously reported loci.

41416_2022_1798_MOESM4_ESM.pdf

Supplemental Figure S1. Mendelian Randomization (MR) analysis results for the association between individual SNPs that genetically predict leukocyte telomere length (LTL) and pediatric germ cell tumor

41416_2022_1798_MOESM5_ESM.pdf

Supplemental Figure S2. Mendelian Randomization (MR) analysis results for the association between individual SNPs that genetically predict leukocyte telomere length (LTL) and pediatric germ cell tumor

Code availability

Nature Portfolio Reporting Summary

Nature Portfolio Policy Checklist

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cigan, S.S., Meredith, J.J., Kelley, A.C. et al. Predicted leukocyte telomere length and risk of germ cell tumours. Br J Cancer 127, 301–312 (2022). https://doi.org/10.1038/s41416-022-01798-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41416-022-01798-3

Search

Advanced search

Quick links