Abstract
Genome-wide association studies (GWASs) have identified several single-nucleotide polymorphisms (SNPs) influencing the risk of Hodgkin’s lymphoma (HL) and demonstrated the association of common genetic variation for this type of cancer. Such evidence for inherited genetic risk is also provided by the family history and the very high concordance between monozygotic twins. However, little is known about the genetic and environmental contributions. A common measure for describing the phenotypic variation due to genetics is the heritability. Using GWAS data on 906 HL cases by considering all typed SNPs simultaneously, we have calculated that the common variance explained by SNPs accounts for >35% of the total variation on the liability scale in HL (95% confidence interval 6–62%). These findings are consistent with similar heritability estimates of ∼0.40 (95% confidence interval 0.17–0.58) based on Swedish population data. Our estimates support the underlying polygenic basis for susceptibility to HL, and show that heritability based on the population data is somehow larger than heritability based on the genomic data because of the possibility of some missing heritability in the GWAS data. Besides that there is still major evidence for multiple loci causing HL on chromosomes other than chromosome 6 that need to be detected. Because of limited findings in prior GWASs, it seems worth checking for more loci causing susceptibility to HL.
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References
Bose S, Ganesan C, Pant M, Lai C, Tabbara IA : Lymphocyte-predominant Hodgkin disease: a comprehensive overview. Am J Clin Oncol 2013; 36: 91–96.
Engert A, Horning SJ : Hodgkin Lymphoma. A Comprehensive Update on Diagnostics and Clinics: Hematologic malignancies. Heidelberg; New York: Springer-Verlag, 2011, pp 1, online resource (ix, 381 p).
Parkin DM : 11. Cancers attributable to infection in the UK in 2010. Br J Cancer 2011; 105 (Suppl 2): S49–S56.
Anderson LA, Gadalla S, Morton LM et alPopulation-based study of autoimmune conditions and the risk of specific lymphoid malignancies. Int J Cancer 2009; 125: 398–405.
Hemminki K, Czene K : Attributable risks of familial cancer from the Family-Cancer Database. Cancer Epidemiol Biomarkers Prev 2002; 11: 1638–1644.
Frampton M, da Silva Filho MI, Broderick P et alVariation at 3p24.1 and 6q23.3 influences the risk of Hodgkin’s lymphoma. Nat Commun 2013; 4: 2549.
Urayama KY, Jarrett RF, Hjalgrim H et alGenome-wide association study of classical Hodgkin lymphoma and Epstein-Barr virus status-defined subgroups. J Natl Cancer Inst 2012; 104: 240–253.
Shugart YY, Hemminki K, Vaittinen P, Kingman A, Dong C : A genetic study of Hodgkin’s lymphoma: an estimate of heritability and anticipation based on the familial cancer database in Sweden. Hum Genet 2000; 106: 553–556.
Eichler EE, Flint J, Gibson G et alMissing heritability and strategies for finding the underlying causes of complex disease. Nat Rev Genet 2010; 11: 446–450.
Wray NR, Yang J, Hayes BJ, Price AL, Goddard ME, Visscher PM : Pitfalls of predicting complex traits from SNPs. Nat Rev Genet 2013; 14: 507–515.
Bloom JS, Ehrenreich IM, Loo WT, Lite TL, Kruglyak L : Finding the sources of missing heritability in a yeast cross. Nature 2013; 494: 234–237.
Wilson AJ : Why h2 does not always equal VA/VP? J Evol Biol 2008; 21: 647–650.
Hill WG : Understanding and using quantitative genetic variation. Philos Trans R Soc Lond B Biol Sci 2010; 365: 73–85.
Vinkhuyzen AA, Wray NR, Yang J, Goddard ME, Visscher PM : Estimation and partition of heritability in human populations using whole-genome analysis methods. Annu Rev Genet 2013; 47: 75–95.
Falconer DS : Introduction to Quantitative Genetics, 3rd edn. Burnt Mill, Harlow, Essex, England New York: Longman, Wiley, 1989.
Lee SH, Wray NR, Goddard ME, Visscher PM : Estimating missing heritability for disease from genome-wide association studies. Am J Hum Genet 2011; 88: 294–305.
Schmermund A, Mohlenkamp S, Stang A et alAssessment of clinically silent atherosclerotic disease and established and novel risk factors for predicting myocardial infarction and cardiac death in healthy middle-aged subjects: rationale and design of the Heinz Nixdorf RECALL Study. Risk Factors, Evaluation of Coronary Calcium and Lifestyle. Am Heart J 2002; 144: 212–218.
Purcell S, Neale B, Todd-Brown K et alPLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007; 81: 559–575.
Yang J, Benyamin B, McEvoy BP et alCommon SNPs explain a large proportion of the heritability for human height. Nat Genet 2010; 42: 565–569.
Speed D, Hemani G, Johnson Michael R, Balding David J : Improved Heritability Estimation from Genome-wide SNPs. Am J Hum Genet 2012; 91: 1011–1021.
Dempster ER, Lerner IM : Heritability of threshold characters. Genetics 1950; 35: 212–236.
Yang J, Lee SH, Goddard ME, Visscher PM : GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet 2011; 88: 76–82.
Guan Y, Stephens M : Bayesian variable selection regression for genome-wide association studies and other large-scale problems. Ann Appl Stat 2011; 5: 1780–1815.
Hemminki K, Ji J, Brandt A, Mousavi SM, Sundquist J : The Swedish Family-Cancer Database 2009: prospects for histology-specific and immigrant studies. Int J Cancer 2010; 126: 2259–2267.
R Core Team: R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing, 2013, ISBN 3-900051-07-0. http://www.R-project.org/.
Madsen P : User’s Guide to DmuTrace: A Package for Preparing Data Sets, Version 2. Aarhus, UK: University of Aarhus, Faculty of Agricultural Sciences, Department of Animal Breeding and Genetics, 2012.
Sorensen D, Gianola D : Likelihood, Bayesian and MCMC Methods in Quantitative Genetics. New York: Springer-Verlag, 2002.
Odegard J, Meuwissen TH, Heringstad B, Madsen P : A simple algorithm to estimate genetic variance in an animal threshold model using Bayesian inference. Genet Sel Evol 2010; 42: 29.
Lynch M, Walsh B : Genetics and Analysis of Quantitative Traits. Sunderland, MA: Sinauer, 1998.
Madsen P, Jensen J : DMU: A User's Guide. A Package for Analyzing Multivariate Mixed Models, Version 6, release 4.7. Aarhus, UK: University of Aarhus, Faculty of Agricultural Sciences, Department of Animal Breeding and Genetics, 2007.
Hadfield JD : MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R Package. J Stat Softw 2010; 33: 1–22.
Yang J, Manolio TA, Pasquale LR et alGenome partitioning of genetic variation for complex traits using common SNPs. Nat Genet 2011; 43: 519–525.
Wray NR, Yang J, Goddard ME, Visscher PM : The genetic interpretation of area under the ROC curve in genomic profiling. PLoS Genet 2010; 6: e1000864.
Gelman A : Bayesian Data Analysis, 2nd edn. Boca Raton, FL: Chapman & Hall/CRC, 2004.
Stephens M, Balding DJ : Bayesian statistical methods for genetic association studies. Nat Rev Genet 2009; 10: 681–690.
Ovaskainen O, Cano JM, Merila J : A Bayesian framework for comparative quantitative genetics. Proc Biol Sci R Soc 2008; 275: 669–678.
Enciso-Mora V, Hosking FJ, Sheridan E et alCommon genetic variation contributes significantly to the risk of childhood B-cell precursor acute lymphoblastic leukemia. Leukemia 2012; 26: 2212–2215.
Lee SH, DeCandia TR, Ripke S et alEstimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs. Nat Genet 2012; 44: 247–250.
Enciso-Mora V, Broderick P, Ma Y et alA genome-wide association study of Hodgkin's lymphoma identifies new susceptibility loci at 2p16.1 (REL), 8q24.21 and 10p14 (GATA3). Nat Genet 2010; 42: 1126–1130.
Gianola D, Foulley J : Sire evaluation for ordered categorical data with a threshold model. Genet Sel Evol 1983; 15: 201–224.
Tenesa A, Haley CS : The heritability of human disease: estimation, uses and abuses. Nat Rev Genet 2013; 14: 139–149.
Benchek P, Morris NJ : How meaningful are heritability estimates of liability? Hum Genet 2013; 132: 1351–1360.
Goldin LR, Pfeiffer RM, Gridley G et alFamilial aggregation of Hodgkin lymphoma and related tumors. Cancer 2004; 100: 1902–1908.
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We are grateful for the technical support on the program package DMU by Per Madsen and Guosheng Su.
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Thomsen, H., da Silva Filho, M., Försti, A. et al. Heritability estimates on Hodgkin’s lymphoma: a genomic- versus population-based approach. Eur J Hum Genet 23, 824–830 (2015). https://doi.org/10.1038/ejhg.2014.184
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DOI: https://doi.org/10.1038/ejhg.2014.184
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