Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed

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Citações na Scopus
24
Tipo de produção
article
Data de publicação
2022
Título da Revista
ISSN da Revista
Título do Volume
Editora
CELL PRESS
Autores
TAUB, M. A.
CONOMOS, M. P.
KEENER, R.
IYER, K. R.
WEINSTOCK, J. S.
YANEK, L. R.
LANE, J.
MILLER-FLEMING, T. W.
BRODY, J. A.
RAFFIELD, L. M.
Citação
CELL GENOMICS, v.2, n.1, article ID 100084, p, 2022
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Genetic studies on telomere length are important for understanding age-related diseases. Prior GWASs for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally diverse individuals (European, African, Asian, and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole-genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n = 109,122 individuals. We identified 59 sentinel variants (p < 5 × 10−9) in 36 loci associated with telomere length, including 20 newly associated loci (13 were replicated in external datasets). There was little evidence of effect size heterogeneity across populations. Fine-mapping at OBFC1 indicated that the independent signals colocalized with cell-type-specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated that our TL polygenic trait scores (PTSs) were associated with an increased risk of cancer-related phenotypes. © 2021
Palavras-chave
telomere length genetics, telomeres, trans-population genome-wide association study
Referências
  1. Aviv A., Shay J.W., Reflections on telomere dynamics and ageing-related diseases in humans, Philos. Trans. R. Soc. Lond. B Biol. Sci., 373, (2018)
  2. McNally E.J., Luncsford P.J., Armanios M., Long telomeres and cancer risk: the price of cellular immortality, J. Clin. Invest., 129, pp. 3474-3481, (2019)
  3. Codd V., Nelson C.P., Albrecht E., Mangino M., Deelen J., Buxton J.L., Hottenga J.J., Fischer K., Esko T., Surakka I., Et al., Identification of seven loci affecting mean telomere length and their association with disease, Nat. Genet., 45, pp. 422-427, (2013)
  4. Codd V., Mangino M., van der Harst P., Braund P.S., Kaiser M., Beveridge A.J., Rafelt S., Moore J., Nelson C., Soranzo N., Et al., Common variants near TERC are associated with mean telomere length, Nat. Genet., 42, pp. 197-199, (2010)
  5. Delgado D.A., Zhang C., Chen L.S., Gao J., Roy S., Shinkle J., Sabarinathan M., Argos M., Tong L., Ahmed A., Et al., Genome-wide association study of telomere length among South Asians identifies a second RTEL1 association signal, J. Med. Genet., 55, pp. 64-71, (2018)
  6. Gu J., Chen M., Shete S., Amos C.I., Kamat A., Ye Y., Lin J., Dinney C.P., Wu X., A genome-wide association study identifies a locus on chromosome 14q21 as a predictor of leukocyte telomere length and as a marker of susceptibility for bladder cancer, Cancer Prev. Res. (Phila.), 4, pp. 514-521, (2011)
  7. Lee J.H., Cheng R., Honig L.S., Feitosa M., Kammerer C.M., Kang M.S., Schupf N., Lin S.J., Sanders J.L., Bae H., Et al., Genome wide association and linkage analyses identified three loci-4q25, 17q23.2, and 10q11.21-associated with variation in leukocyte telomere length: the Long Life Family Study, Front. Genet., 4, (2014)
  8. Levy D., Neuhausen S.L., Hunt S.C., Kimura M., Hwang S.J., Chen W., Bis J.C., Fitzpatrick A.L., Smith E., Johnson A.D., Et al., Genome-wide association identifies OBFC1 as a locus involved in human leukocyte telomere biology, Proc. Natl. Acad. Sci. USA, 107, pp. 9293-9298, (2010)
  9. Liu Y., Cao L., Li Z., Zhou D., Liu W., Shen Q., Wu Y., Zhang D., Hu X., Wang T., Et al., A genome-wide association study identifies a locus on TERT for mean telomere length in Han Chinese, PLoS ONE, 9, (2014)
  10. Mangino M., Christiansen L., Stone R., Hunt S.C., Horvath K., Eisenberg D.T., Kimura M., Petersen I., Kark J.D., Herbig U., Et al., DCAF4, a novel gene associated with leucocyte telomere length, J. Med. Genet., 52, pp. 157-162, (2015)
  11. Mangino M., Hwang S.J., Spector T.D., Hunt S.C., Kimura M., Fitzpatrick A.L., Christiansen L., Petersen I., Elbers C.C., Harris T., Et al., Genome-wide meta-analysis points to CTC1 and ZNF676 as genes regulating telomere homeostasis in humans, Hum. Mol. Genet., 21, pp. 5385-5394, (2012)
  12. Mangino M., Richards J.B., Soranzo N., Zhai G., Aviv A., Valdes A.M., Samani N.J., Deloukas P., Spector T.D., A genome-wide association study identifies a novel locus on chromosome 18q12.2 influencing white cell telomere length, J. Med. Genet., 46, pp. 451-454, (2009)
  13. Pooley K.A., Bojesen S.E., Weischer M., Nielsen S.F., Thompson D., Amin Al Olama A., Michailidou K., Tyrer J.P., Benlloch S., Brown J., 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., 22, pp. 5056-5064, (2013)
  14. Prescott J., Kraft P., Chasman D.I., Savage S.A., Mirabello L., Berndt S.I., Weissfeld J.L., Han J., Hayes R.B., Chanock S.J., Et al., Genome-wide association study of relative telomere length, PLoS ONE, 6, (2011)
  15. Saxena R., Bjonnes A., Prescott J., Dib P., Natt P., Lane J., Lerner M., Cooper J.A., Ye Y., Li K.W., Et al., Genome-wide association study identifies variants in casein kinase II (CSNK2A2) to be associated with leukocyte telomere length in a Punjabi Sikh diabetic cohort, Circ. Cardiovasc. Genet., 7, pp. 287-295, (2014)
  16. Walsh K.M., Codd V., Smirnov I.V., Rice T., Decker P.A., Hansen H.M., Kollmeyer T., Kosel M.L., Molinaro A.M., McCoy L.S., Et al., Variants near TERT and TERC influencing telomere length are associated with high-grade glioma risk, Nat. Genet., 46, pp. 731-735, (2014)
  17. Zeiger A.M., White M.J., Eng C., Oh S.S., Witonsky J., Goddard P.C., Contreras M.G., Elhawary J.R., Hu D., Mak A.C.Y., Et al., Genetic Determinants of Telomere Length in African American Youth, Sci. Rep., 8, (2018)
  18. Dorajoo R., Chang X., Gurung R.L., Li Z., Wang L., Wang R., Beckman K.B., Adams-Haduch J., M Y., Liu S., Et al., Loci for human leukocyte telomere length in the Singaporean Chinese population and trans-ethnic genetic studies, Nat. Commun., 10, (2019)
  19. Li C., Stoma S., Lotta L.A., Warner S., Albrecht E., Allione A., Arp P.P., Broer L., Buxton J.L., Da Silva Couto Alves A., Et al., Genome-wide Association Analysis in Humans Links Nucleotide Metabolism to Leukocyte Telomere Length, Am. J. Hum. Genet., 106, pp. 389-404, (2020)
  20. Ding Z., Mangino M., Aviv A., Spector T., Durbin R., Estimating telomere length from whole genome sequence data, Nucleic Acids Res., 42, (2014)
  21. Kimura M., Stone R.C., Hunt S.C., Skurnick J., Lu X., Cao X., Harley C.B., Aviv A., Measurement of telomere length by the Southern blot analysis of terminal restriction fragment lengths, Nat. Protoc., 5, pp. 1596-1607, (2010)
  22. Alder J.K., Hanumanthu V.S., Strong M.A., DeZern A.E., Stanley S.E., Takemoto C.M., Danilova L., Applegate C.D., Bolton S.G., Mohr D.W., Et al., Diagnostic utility of telomere length testing in a hospital-based setting, Proc. Natl. Acad. Sci. USA, 115, pp. E2358-E2365, (2018)
  23. Almasy L., Blangero J., Multipoint quantitative-trait linkage analysis in general pedigrees, Am. J. Hum. Genet., 62, pp. 1198-1211, (1998)
  24. Fang H., Hui Q., Lynch J., Honerlaw J., Assimes T.L., Huang J., Vujkovic M., Damrauer S.M., Pyarajan S., Gaziano J.M., Et al., Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies, Am. J. Hum. Genet., 105, pp. 763-772, (2019)
  25. Zhang M., Wang R., Wang Y., Diao F., Lu F., Gao D., Chen D., Zhai Z., Shu H., The CXXC finger 5 protein is required for DNA damage-induced p53 activation, Sci. China C Life Sci., 52, pp. 528-538, (2009)
  26. Kaul R., Mukherjee S., Ahmed F., Bhat M.K., Chhipa R., Galande S., Chattopadhyay S., Direct interaction with and activation of p53 by SMAR1 retards cell-cycle progression at G2/M phase and delays tumor growth in mice, Int. J. Cancer, 103, pp. 606-615, (2003)
  27. Bulik-Sullivan B.K., Loh P.R., Finucane H.K., Ripke S., Yang J., Patterson N., Daly M.J., Price A.L., Neale B.M., LD Score regression distinguishes confounding from polygenicity in genome-wide association studies, Nat. Genet., 47, pp. 291-295, (2015)
  28. Bulik-Sullivan B., Finucane H.K., Anttila V., Gusev A., Day F.R., Loh P.R., Duncan L., Perry J.R., Patterson N., Robinson E.B., Et al., An atlas of genetic correlations across human diseases and traits, Nat. Genet., 47, pp. 1236-1241, (2015)
  29. Cochran W.G., The combination of estimates from different experiments, Biometrics, 10, pp. 101-129, (1954)
  30. Stuart B.D., Choi J., Zaidi S., Xing C., Holohan B., Chen R., Choi M., Dharwadkar P., Torres F., Girod C.E., Et al., Exome sequencing links mutations in PARN and RTEL1 with familial pulmonary fibrosis and telomere shortening, Nat. Genet., 47, pp. 512-517, (2015)
  31. Tummala H., Walne A., Collopy L., Cardoso S., de la Fuente J., Lawson S., Powell J., Cooper N., Foster A., Mohammed S., Et al., Poly(A)-specific ribonuclease deficiency impacts telomere biology and causes dyskeratosis congenita, J. Clin. Invest., 125, pp. 2151-2160, (2015)
  32. Touzot F., Callebaut I., Soulier J., Gaillard L., Azerrad C., Durandy A., Fischer A., de Villartay J.P., Revy P., Function of Apollo (SNM1B) at telomere highlighted by a splice variant identified in a patient with Hoyeraal-Hreidarsson syndrome, Proc. Natl. Acad. Sci. USA, 107, pp. 10097-10102, (2010)
  33. van Overbeek M., de Lange T., Apollo, an Artemis-related nuclease, interacts with TRF2 and protects human telomeres in S phase, Curr. Biol., 16, pp. 1295-1302, (2006)
  34. Lenain C., Bauwens S., Amiard S., Brunori M., Giraud-Panis M.J., Gilson E., The Apollo 5′ exonuclease functions together with TRF2 to protect telomeres from DNA repair, Curr. Biol., 16, pp. 1303-1310, (2006)
  35. Wu M., Reuter M., Lilie H., Liu Y., Wahle E., Song H., Structural insight into poly(A) binding and catalytic mechanism of human PARN, EMBO J., 24, pp. 4082-4093, (2005)
  36. Stewart J.A., Wang Y., Ackerson S.M., Schuck P.L., Emerging roles of CST in maintaining genome stability and human disease, Front. Biosci., 23, pp. 1564-1586, (2018)
  37. Battle A., Brown C.D., Engelhardt B.E., Montgomery S.B., Genetic effects on gene expression across human tissues, Nature, 550, pp. 204-213, (2017)
  38. Vosa U., Claringbould A., Westra H.-J., Bonder M.J., Deelen P., Zeng B., Kirsten H., Saha A., Kreuzhuber R., Yazar S., Et al., Unraveling the polygenic architecture of complex traits using blood eQTL metaanalysis, Nat. Genet., 53, pp. 1300-1310, (2021)
  39. Kundaje A., Meuleman W., Ernst J., Bilenky M., Yen A., Heravi-Moussavi A., Kheradpour P., Zhang Z., Wang J., Ziller M.J., Et al., Integrative analysis of 111 reference human epigenomes, Nature, 518, pp. 317-330, (2015)
  40. Januszewski A.S., Sutanto S.S., McLennan S., O'Neal D.N., Keech A.C., Twigg S.M., Jenkins A.J., Shorter telomeres in adults with type 1 diabetes correlate with diabetes duration, but only weakly with vascular function and risk factors, Diabetes Res. Clin. Pract., 117, pp. 4-11, (2016)
  41. Oglesbee M.J., Herdman A.V., Passmore G.G., Hoffman W.H., Diabetic ketoacidosis increases extracellular levels of the major inducible 70-kDa heat shock protein, Clin. Biochem., 38, pp. 900-904, (2005)
  42. Nussey D.H., Baird D., Barrett E., Boner W., Fairlie J., Gemmell N., Hartmann N., Horn T., Haussmann M., Olsson M., Et al., Measuring telomere length and telomere dynamics in evolutionary biology and ecology, Methods Ecol. Evol., 5, pp. 299-310, (2014)
  43. Aubert G., Hills M., Lansdorp P.M., Telomere length measurement-caveats and a critical assessment of the available technologies and tools, Mutat. Res., 730, pp. 59-67, (2012)
  44. Lee M., Napier C.E., Yang S.F., Arthur J.W., Reddel R.R., Pickett H.A., Comparative analysis of whole genome sequencing-based telomere length measurement techniques, Methods, 114, pp. 4-15, (2017)
  45. Demanelis K., Jasmine F., Chen L.S., Chernoff M., Tong L., Delgado D., Zhang C., Shinkle J., Sabarinathan M., Lin H., Et al., Determinants of telomere length across human tissues, Science, 369, (2020)
  46. Taliun D., Harris D.N., Kessler M.D., Carlson J., Szpiech Z.A., Torres R., Taliun S.A.G., Corvelo A., Gogarten S.M., Kang H.M., Et al., Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program, Nature, 590, pp. 290-299, (2021)
  47. Gogarten S.M., Sofer T., Chen H., Yu C., Brody J.A., Thornton T.A., Rice K.M., Conomos M.P., Genetic association testing using the GENESIS R/Bioconductor package, Bioinformatics, 35, pp. 5346-5348, (2019)
  48. Hormozdiari F., Kostem E., Kang E.Y., Pasaniuc B., Eskin E., Identifying causal variants at loci with multiple signals of association, Genetics, 198, pp. 497-508, (2014)
  49. Giambartolomei C., Vukcevic D., Schadt E.E., Franke L., Hingorani A.D., Wallace C., Plagnol V., Bayesian test for colocalisation between pairs of genetic association studies using summary statistics, PLoS Genet., 10, (2014)
  50. Carroll R.J., Bastarache L., Denny J.C., R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment, Bioinformatics, 30, pp. 2375-2376, (2014)
  51. TOPMed Projects and Their Parent Studies, (2021)
  52. Jun G., Wing M.K., Abecasis G.R., Kang H.M., An efficient and scalable analysis framework for variant extraction and refinement from population-scale DNA sequence data, Genome Res., 25, pp. 918-925, (2015)
  53. Nersisyan L., Arakelyan A., Computel: computation of mean telomere length from whole-genome next-generation sequencing data, PLoS ONE, 10, (2015)
  54. Aviv A., Hunt S.C., Lin J., Cao X., Kimura M., Blackburn E., Impartial comparative analysis of measurement of leukocyte telomere length/DNA content by Southern blots and qPCR, Nucleic Acids Res., 39, (2011)
  55. O'Callaghan N.J., Fenech M., A quantitative PCR method for measuring absolute telomere length, Biol. Proced. Online, 13, (2011)
  56. Mwasongwe S., Gao Y., Griswold M., Wilson J.G., Aviv A., Reiner A.P., Raffield L.M., Leukocyte telomere length and cardiovascular disease in African Americans: the Jackson Heart Study, Atherosclerosis, 266, pp. 41-47, (2017)
  57. Leek J.T., Storey J.D., Capturing heterogeneity in gene expression studies by surrogate variable analysis, PLoS Genet., 3, pp. 1724-1735, (2007)
  58. Stegle O., Parts L., Piipari M., Winn J., Durbin R., Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses, Nat. Protoc., 7, pp. 500-507, (2012)
  59. Pedersen B.S., Quinlan A.R., Mosdepth: quick coverage calculation for genomes and exomes, Bioinformatics, 34, pp. 867-868, (2018)
  60. Derrien T., Estelle J., Marco Sola S., Knowles D.G., Raineri E., Guigo R., Ribeca P., Fast computation and applications of genome mappability, PLoS ONE, 7, (2012)
  61. Halko N., Martinsson P.G., Tropp J.A., Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions, SIAM Rev., 2, pp. 217-288, (2011)
  62. Conomos M.P., Miller M.B., Thornton T.A., Robust inference of population structure for ancestry prediction and correction of stratification in the presence of relatedness, Genet. Epidemiol., 39, pp. 276-293, (2015)
  63. Sofer T., Zheng X., Gogarten S.M., Laurie C.A., Grinde K., Shaffer J.R., Shungin D., O'Connell J.R., Durazo-Arvizo R.A., Raffield L., Et al., A fully adjusted two-stage procedure for rank-normalization in genetic association studies, Genet. Epidemiol., 43, pp. 263-275, (2019)
  64. Conomos M.P., Reiner A.P., Weir B.S., Thornton T.A., Model-free Estimation of Recent Genetic Relatedness, Am. J. Hum. Genet., 98, pp. 127-148, (2016)
  65. Tang Z.Z., Lin D.Y., Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs, Am. J. Hum. Genet., 97, pp. 35-53, (2015)
  66. Zhou B., Shi J., Whittemore A.S., Optimal methods for meta-analysis of genome-wide association studies, Genet. Epidemiol., 35, pp. 581-591, (2011)
  67. BRAVO variant browser: University of Michigan and NHLBI, (2018)
  68. Cochran W.G., The Combination of Estimates from Different Experiments, Biometrics, 10, pp. 101-129, (1954)
  69. Wilson J.G., Rotimi C.N., Ekunwe L., Royal C.D., Crump M.E., Wyatt S.B., Steffes M.W., Adeyemo A., Zhou J., Taylor H.A., Et al., Study design for genetic analysis in the Jackson Heart Study, Ethn. Dis., 15, (2005)
  70. Frankish A., Diekhans M., Ferreira A.M., Johnson R., Jungreis I., Loveland J., Mudge J.M., Sisu C., Wright J., Armstrong J., Et al., GENCODE reference annotation for the human and mouse genomes, Nucleic Acids Res., 47, D1, pp. D766-D773, (2019)
  71. Liu X., White S., Peng B., Johnson A.D., Brody J.A., Li A.H., Huang Z., Carroll A., Wei P., Gibbs R., Et al., WGSA: an annotation pipeline for human genome sequencing studies, J. Med. Genet., 53, pp. 111-112, (2016)
  72. Ahn D.H., Ozer H.G., Hancioglu B., Lesinski G.B., Timmers C., Bekaii-Saab T., Whole-exome tumor sequencing study in biliary cancer patients with a response to MEK inhibitors, Oncotarget, 7, pp. 5306-5312, (2016)
  73. Ioannidis N.M., Rothstein J.H., Pejaver V., Middha S., McDonnell S.K., Baheti S., Musolf A., Li Q., Holzinger E., Karyadi D., Et al., REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants, Am. J. Hum. Genet., 99, pp. 877-885, (2016)
  74. Jagadeesh K.A., Wenger A.M., Berger M.J., Guturu H., Stenson P.D., Cooper D.N., Bernstein J.A., Bejerano G., M-CAP eliminates a majority of variants of uncertain significance in clinical exomes at high sensitivity, Nat. Genet., 48, pp. 1581-1586, (2016)
  75. Kircher M., Witten D.M., Jain P., O'Roak B.J., Cooper G.M., Shendure J., A general framework for estimating the relative pathogenicity of human genetic variants, Nat. Genet., 46, pp. 310-315, (2014)
  76. Graham G., Disparities in cardiovascular disease risk in the United States, Curr. Cardiol. Rev., 11, pp. 238-245, (2015)
  77. Chen H., Huffman J.E., Brody J.A., Wang C., Lee S., Li Z., Gogarten S.M., Sofer T., Bielak L.F., Bis J.C., Et al., Efficient Variant Set Mixed Model Association Tests for Continuous and Binary Traits in Large-Scale Whole-Genome Sequencing Studies, Am. J. Hum. Genet., 104, pp. 260-274, (2019)
  78. Brody J.A., Morrison A.C., Bis J.C., O'Connell J.R., Brown M.R., Huffman J.E., Ames D.C., Carroll A., Conomos M.P., Gabriel S., Et al., Analysis commons, a team approach to discovery in a big-data environment for genetic epidemiology, Nat. Genet., 49, pp. 1560-1563, (2017)
  79. Wu M.C., Lee S., Cai T., Li Y., Boehnke M., Lin X., Rare-variant association testing for sequencing data with the sequence kernel association test, Am. J. Hum. Genet., 89, pp. 82-93, (2011)
  80. Keramati A.R., Yanek L.R., Iyer K., Taub M.A., Ruczinski I., Becker D.M., Becker L.C., Faraday N., Mathias R.A., Targeted deep sequencing of the PEAR1 locus for platelet aggregation in European and African American families, Platelets, 30, pp. 380-386, (2019)
  81. The GTEx Consortium atlas of genetic regulatory effects across human tissues, Science, 369, pp. 1318-1330, (2020)
  82. Kent W.J., Sugnet C.W., Furey T.S., Roskin K.M., Pringle T.H., Zahler A.M., Haussler D., The human genome browser at UCSC, Genome Res., 12, pp. 996-1006, (2002)
  83. Li D., Hsu S., Purushotham D., Sears R.L., Wang T., WashU Epigenome Browser update 2019, Nucleic Acids Res., 47, W1, pp. W158-W165, (2019)
  84. Raney B.J., Dreszer T.R., Barber G.P., Clawson H., Fujita P.A., Wang T., Nguyen N., Paten B., Zweig A.S., Karolchik D., Kent W.J., Track data hubs enable visualization of user-defined genome-wide annotations on the UCSC Genome Browser, Bioinformatics, 30, pp. 1003-1005, (2014)
  85. Denny J.C., Ritchie M.D., Basford M.A., Pulley J.M., Bastarache L., Brown-Gentry K., Wang D., Masys D.R., Roden D.M., Crawford D.C., PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations, Bioinformatics, 26, pp. 1205-1210, (2010)
  86. McCarthy S., Das S., Kretzschmar W., Delaneau O., Wood A.R., Teumer A., Kang H.M., Fuchsberger C., Danecek P., Sharp K., Et al., A reference panel of 64,976 haplotypes for genotype imputation, Nat. Genet., 48, pp. 1279-1283, (2016)
  87. Dey R., Schmidt E.M., Abecasis G.R., Lee S., A Fast and Accurate Algorithm to Test for Binary Phenotypes and Its Application to PheWAS, Am. J. Hum. Genet., 101, pp. 37-49, (2017)