Genetically predicted telomere length is associated with clonal somatic copy number alterations in peripheral leukocytes
Autoři:
Derek W. Brown aff001; Shu-Hong Lin aff001; Po-Ru Loh aff003; Stephen J. Chanock aff001; Sharon A. Savage aff001; Mitchell J. Machiela aff001
Působiště autorů:
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, United States of America
aff001; Cancer Prevention Fellowship Program, Division of Cancer Prevention, National Cancer Institute, Rockville, MD, United States of America
aff002; Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States of America
aff003; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
aff004
Vyšlo v časopise:
Genetically predicted telomere length is associated with clonal somatic copy number alterations in peripheral leukocytes. PLoS Genet 16(10): e32767. doi:10.1371/journal.pgen.1009078
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1009078
Souhrn
Telomeres are DNA-protein structures at the ends of chromosomes essential in maintaining chromosomal stability. Observational studies have identified associations between telomeres and elevated cancer risk, including hematologic malignancies; but biologic mechanisms relating telomere length to cancer etiology remain unclear. Our study sought to better understand the relationship between telomere length and cancer risk by evaluating genetically-predicted telomere length (gTL) in relation to the presence of clonal somatic copy number alterations (SCNAs) in peripheral blood leukocytes. Genotyping array data were acquired from 431,507 participants in the UK Biobank and used to detect SCNAs from intensity information and infer telomere length using a polygenic risk score (PRS) of variants previously associated with leukocyte telomere length. In total, 15,236 (3.5%) of individuals had a detectable clonal SCNA on an autosomal chromosome. Overall, higher gTL value was positively associated with the presence of an autosomal SCNA (OR = 1.07, 95% CI = 1.05–1.09, P = 1.61×10−15). There was high consistency in effect estimates across strata of chromosomal event location (e.g., telomeric ends, interstitial or whole chromosome event; Phet = 0.37) and strata of copy number state (e.g., gain, loss, or neutral events; Phet = 0.05). Higher gTL value was associated with a greater cellular fraction of clones carrying autosomal SCNAs (β = 0.004, 95% CI = 0.002–0.007, P = 6.61×10−4). Our population-based examination of gTL and SCNAs suggests inherited components of telomere length do not preferentially impact autosomal SCNA event location or copy number status, but rather likely influence cellular replicative potential.
Zdroje
1. Blackburn EH, Epel ES, Lin J. Human telomere biology: A contributory and interactive factor in aging, disease risks, and protection. Science. 2015;350: 1193–1198. doi: 10.1126/science.aab3389 26785477
2. 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: 636–651. doi: 10.1001/jamaoncol.2016.5945 28241208
3. López-Otín C, Blasco MA, Partridge L, Serrano M, Kroemer G. The hallmarks of aging. Cell. 2013;153: 1194–1217. doi: 10.1016/j.cell.2013.05.039 23746838
4. Samani NJ, van der Harst P. Biological ageing and cardiovascular disease. Heart Br Card Soc. 2008;94: 537–539. doi: 10.1136/hrt.2007.136010 18411343
5. Artandi SE, DePinho RA. Telomeres and telomerase in cancer. Carcinogenesis. 2009;31: 9–18. doi: 10.1093/carcin/bgp268 19887512
6. Kyo S, Inoue M. Complex regulatory mechanisms of telomerase activity in normal and cancer cells: how can we apply them for cancer therapy? Oncogene. 2002;21: 688–697. doi: 10.1038/sj.onc.1205163 11850797
7. Shay JW, Wright WE. Telomeres and telomerase: three decades of progress. Nat Rev Genet. 2019;20: 299–309. doi: 10.1038/s41576-019-0099-1 30760854
8. Aviv A, Anderson JJ, Shay JW. Mutations, cancer and the telomere length paradox. Trends Cancer. 2017;3: 253–258. doi: 10.1016/j.trecan.2017.02.005 28718437
9. Aviv A, Shay JW. Reflections on telomere dynamics and ageing-related diseases in humans. Philos Trans R Soc B Biol Sci. 2018;373: 20160436.
10. Machiela MJ, Lan Q, Slager SL, Vermeulen RCH, Teras LR, Camp NJ, et al. Genetically predicted longer telomere length is associated with increased risk of B-cell lymphoma subtypes. Hum Mol Genet. 2016;25: 1663–1676. doi: 10.1093/hmg/ddw027 27008888
11. Machiela MJ, Hofmann JN, Carreras-Torres R, Brown KM, Johansson M, Wang Z, et al. Genetic Variants Related to Longer Telomere Length are Associated with Increased Risk of Renal Cell Carcinoma. Eur Urol. 2017;72: 747–754. doi: 10.1016/j.eururo.2017.07.015 28797570
12. Iles MM, Bishop DT, Taylor JC, Hayward NK, Brossard M, Cust AE, et al. The effect on melanoma risk of genes previously associated with telomere length. J Natl Cancer Inst. 2014;106. doi: 10.1093/jnci/dju267 25231748
13. Machiela MJ, Hsiung CA, Shu X-O, Seow WJ, Wang Z, Matsuo K, et al. Genetic variants associated with longer telomere length are associated with increased lung cancer risk among never-smoking women in Asia: a report from the female lung cancer consortium in Asia. Int J Cancer. 2015;137: 311–319. doi: 10.1002/ijc.29393 25516442
14. Machiela MJ, Chanock SJ. Detectable clonal mosaicism in the human genome. Semin Hematol. 2013;50: 348–359. doi: 10.1053/j.seminhematol.2013.09.001 24246702
15. Machiela MJ. Mosaicism, aging and cancer. Curr Opin Oncol. 2019;31: 108–113. doi: 10.1097/CCO.0000000000000500 30585859
16. Terao C, Suzuki A, Momozawa Y, Akiyama M, Ishigaki K, Yamamoto K, et al. The genomic landscape of clonal hematopoiesis in Japan. bioRxiv. 2019; 653733. doi: 10.1101/653733
17. Loh P-R, Genovese G, Handsaker RE, Finucane HK, Reshef YA, Palamara PF, et al. Insights into clonal haematopoiesis from 8,342 mosaic chromosomal alterations. Nature. 2018;559: 350–355. doi: 10.1038/s41586-018-0321-x 29995854
18. Jacobs KB, Yeager M, Zhou W, Wacholder S, Wang Z, Rodriguez-Santiago B, et al. Detectable clonal mosaicism and its relationship to aging and cancer. Nat Genet. 2012;44: 651–658. doi: 10.1038/ng.2270 22561519
19. Zhou W, Machiela MJ, Freedman ND, Rothman N, Malats N, Dagnall C, et al. Mosaic loss of chromosome Y is associated with common variation near TCL1A. Nat Genet. 2016;48: 563–568. doi: 10.1038/ng.3545 27064253
20. Xie M, Lu C, Wang J, McLellan MD, Johnson KJ, Wendl MC, et al. Age-related mutations associated with clonal hematopoietic expansion and malignancies. Nat Med. 2014;20: 1472–1478. doi: 10.1038/nm.3733 25326804
21. Hinds DA, Barnholt KE, Mesa RA, Kiefer AK, Do CB, Eriksson N, et al. Germ line variants predispose to both JAK2 V617F clonal hematopoiesis and myeloproliferative neoplasms. Blood. 2016;128: 1121–1128. doi: 10.1182/blood-2015-06-652941 27365426
22. Zink F, Stacey SN, Norddahl GL, Frigge ML, Magnusson OT, Jonsdottir I, et al. Clonal hematopoiesis, with and without candidate driver mutations, is common in the elderly. Blood. 2017;130: 742–752. doi: 10.1182/blood-2017-02-769869 28483762
23. Taub MA, Weinstock JS, Iyer KR, Yanek LR, Conomos MP, Brody JA, et al. Novel genetic determinants of telomere length from a multi-ethnic analysis of 75,000 whole genome sequences in TOPMed. bioRxiv. 2019; 749010. doi: 10.1101/749010
24. Dagnall CL, Hicks B, Teshome K, Hutchinson AA, Gadalla SM, Khincha PP, et al. Effect of pre-analytic variables on the reproducibility of qPCR relative telomere length measurement. PloS One. 2017;12: e0184098. doi: 10.1371/journal.pone.0184098 28886139
25. 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: 422–427, 427e1-2. doi: 10.1038/ng.2528 23535734
26. Chang S-C, Prescott J, De Vivo I, Kraft P, Okereke OI. Polygenic risk score of shorter telomere length and risk of depression and anxiety in women. J Psychiatr Res. 2018;103: 182–188. doi: 10.1016/j.jpsychires.2018.05.021 29883926
27. Machiela MJ, Zhou W, Karlins E, Sampson JN, Freedman ND, Yang Q, et al. Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome. Nat Commun. 2016;7: 11843. doi: 10.1038/ncomms11843 27291797
28. Forsberg LA, Rasi C, Malmqvist N, Davies H, Pasupulati S, Pakalapati G, et al. Mosaic loss of chromosome Y in peripheral blood is associated with shorter survival and higher risk of cancer. Nat Genet. 2014;46: 624–628. doi: 10.1038/ng.2966 24777449
29. Loftfield E, Zhou W, Graubard BI, Yeager M, Chanock SJ, Freedman ND, et al. Predictors of mosaic chromosome Y loss and associations with mortality in the UK Biobank. Sci Rep. 2018;8: 12316–12316. doi: 10.1038/s41598-018-30759-1 30120341
30. Thompson DJ, Genovese G, Halvardson J, Ulirsch JC, Wright DJ, Terao C, et al. Genetic predisposition to mosaic Y chromosome loss in blood. Nature. 2019;575: 652–657. doi: 10.1038/s41586-019-1765-3 31748747
31. Wright DJ, Day FR, Kerrison ND, Zink F, Cardona A, Sulem P, et al. Genetic variants associated with mosaic Y chromosome loss highlight cell cycle genes and overlap with cancer susceptibility. Nat Genet. 2017;49: 674–679. doi: 10.1038/ng.3821 28346444
32. Zhou W, Machiela MJ, Freedman ND, Rothman N, Malats N, Dagnall C, et al. Mosaic loss of chromosome Y is associated with common variation near TCL1A. Nat Genet. 2016;48: 563. doi: 10.1038/ng.3545 27064253
33. Machiela MJ, Chanock SJ. LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants. Bioinforma Oxf Engl. 2015;31: 3555–3557. doi: 10.1093/bioinformatics/btv402 26139635
34. 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.
35. 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–e1001779. doi: 10.1371/journal.pmed.1001779 25826379
36. Chen C-Y, Pollack S, Hunter DJ, Hirschhorn JN, Kraft P, Price AL. Improved ancestry inference using weights from external reference panels. Bioinforma Oxf Engl. 2013;29: 1399–1406. doi: 10.1093/bioinformatics/btt144 23539302
37. Price AL, Zaitlen NA, Reich D, Patterson N. New approaches to population stratification in genome-wide association studies. Nat Rev Genet. 2010;11: 459–463. doi: 10.1038/nrg2813 20548291
38. 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: 904–909. doi: 10.1038/ng1847 16862161
39. Patterson N, Price AL, Reich D. Population structure and eigenanalysis. PLoS Genet. 2006;2: e190. doi: 10.1371/journal.pgen.0020190 17194218
40. Yu K, Wang Z, Li Q, Wacholder S, Hunter DJ, Hoover RN, et al. Population Substructure and Control Selection in Genome-Wide Association Studies. PLOS ONE. 2008;3: e2551. doi: 10.1371/journal.pone.0002551 18596976
41. Loh P-R, Genovese G, McCarroll SA. Monogenic and polygenic inheritance become instruments for clonal selection. bioRxiv. 2019; 653691. doi: 10.1101/653691
42. Machiela MJ, Zhou W, Sampson JN, Dean MC, Jacobs KB, Black A, et al. Characterization of large structural genetic mosaicism in human autosomes. Am J Hum Genet. 2015;96: 487–497. doi: 10.1016/j.ajhg.2015.01.011 25748358
43. Loh P-R, Danecek P, Palamara PF, Fuchsberger C, A Reshef Y, K Finucane H, et al. Reference-based phasing using the Haplotype Reference Consortium panel. Nat Genet. 2016;48: 1443–1448. doi: 10.1038/ng.3679 27694958
44. Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, et al. The human genome browser at UCSC. Genome Res. 2002;12: 996–1006. doi: 10.1101/gr.229102 12045153
45. 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: 512–525. doi: 10.1093/ije/dyv080 26050253
46. 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: 304–314. doi: 10.1002/gepi.21965 27061298
47. Burgess S, Scott RA, Timpson NJ, Smith GD, Thompson SG, EPIC-InterAct Consortium. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. Eur J Epidemiol. 2015;30: 543–552. doi: 10.1007/s10654-015-0011-z 25773750
48. Dai JY, Peters U, Wang X, Kocarnik J, Chang-Claude J, Slattery ML, et al. Diagnostics for pleiotropy in Mendelian randomization studies: global and individual tests for direct effects. Am J Epidemiol. 2018;187: 2672–2680. doi: 10.1093/aje/kwy177 30188971
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